﻿PT	AU	BA	BE	GP	AF	BF	CA	TI	SO	SE	BS	LA	DT	CT	CY	CL	SP	HO	DE	ID	AB	C1	RP	EM	RI	OI	FU	FX	CR	NR	TC	Z9	U1	U2	PU	PI	PA	SN	EI	BN	J9	JI	PD	PY	VL	IS	PN	SU	SI	MA	BP	EP	AR	DI	D2	PG	WC	SC	GA	UT	PM	OA	HC	HP	DA
J	Sun, YC; Wang, B				Sun, Yuchen; Wang, Bang			Indoor corner recognition from crowdsourced trajectories using smartphone sensors	EXPERT SYSTEMS WITH APPLICATIONS			English	Article						Indoor corner recognition; Fake corner problem; Pose diversity problem; Indoor positioning system; Machine learning	RECEIVED SIGNAL STRENGTH; POSITIONING SYSTEMS; LOCALIZATION; ENVIRONMENTS; CLASSIFIERS; NETWORKS; WIFI	Recently, fingerprint crowdsourcing from pedestrian movement trajectories has been promoted to alleviate the site survey burden for radio map construction in fingerprinting-based indoor localization. Indoor corners, as one of the most common indoor landmarks, play an important role in movement trajectory analysis. This paper studies the problem of indoor corner recognition in crowdsourced movement trajectories. In a movement trajectory, smartphone internal sensor measurements experience some signal changes when passing by a corner. However, the state-of-the-art Solutions based on signal change detection cannot well deal with the fake corner problem and pose diversity problem in most practical movement trajectories. In this paper, we study the corner recognition problem from an expert system viewpoint by applying machine learning techniques. In particular, we extract recognition features from both the time and frequency domain and propose a hierarchical corner recognition scheme consisting of three classifiers. The first pose classifier is to classify various poses into only two groups according to whether or not a smartphone is kept in a fixed position relative to a user upper body when collecting sensor measurements. Feature selection is then applied to train two corner classifiers each for one pose group. Field experiments are conducted to compare our proposed scheme with three state-of-the-art algorithms. In all cases, our scheme outperforms the best of these algorithms in terms of much higher Fl-measure and precision for corner recognition. The results also provide insights on the potentials of using more advanced techniques from expert systems in indoor localization. (C) 2017 Elsevier Ltd. All rights reserved.	[Sun, Yuchen; Wang, Bang] HUST, Sch Elect Informat & Commun, Luoyu Lu 1037, Wuhan 430074, Hubei, Peoples R China	Wang, B (reprint author), HUST, Sch Elect Informat & Commun, Luoyu Lu 1037, Wuhan 430074, Hubei, Peoples R China.	396630446@qq.com; wangbang@hust.edu.cn			National Natural Science Foundation of China [61371141]; Fundamental Research Funds for the Central Universities [HUST2015QN081]	This work is partly supported by the National Natural Science Foundation of China (Grant No. 61371141) and the Fundamental Research Funds for the Central Universities (No. HUST2015QN081).	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Appl.	OCT 1	2017	82						266	277		10.1016/j.eswa.2017.04.024		12	Computer Science, Artificial Intelligence; Engineering, Electrical & Electronic; Operations Research & Management Science	Computer Science; Engineering; Operations Research & Management Science	EW0XF	WOS:000402213800019		No			2017-07-02	
J	Guo, KH; Tang, YY; Zhang, PY				Guo, Kehua; Tang, Yayuan; Zhang, Peiyun			CSF: Crowdsourcing semantic fusion for heterogeneous media big data in the internet of things	INFORMATION FUSION			English	Article						Crowdsourcing computing; Semantic fusion; Social media; Big data; Internet of things	INFORMATION FUSION; RETRIEVAL; CLASSIFICATION; MULTIMEDIA; MACHINE; SYSTEM	With the rising popularity of social media in the context of environments based on the Internet of things (loT), semantic information has emerged as an important bridge to connect human intelligence with heterogeneous media big data. As a critical tool to improve media big data retrieval, semantic fusion encounters a number of challenges: the manual method is inefficient, and the automatic approach is inaccurate. To address these challenges, this paper proposes a solution called CSF (Crowdsourcing Semantic Fusion) that makes full use of the collective wisdom of social users and introduces crowdsourcing computing to semantic fusion. First, the correlation of cross-modal semantics is mined and the semantic objects are normalized for fusion. Second, we employ the dimension reduction and relevance feedback approaches to reduce non-principal components and noise. Finally, we research the storage and distribution mechanism. Experiment results highlight the efficiency and accuracy of the proposed approach. The proposed method is an effective and practical cross-modal semantic fusion and distribution mechanism for heterogeneous social media, provides a novel idea for social media semantic processing, and uses an interactive visualization framework for social media knowledge mining and retrieval to improve semantic knowledge and the effect of representation. (C) 2017 Elsevier B.V. All rights reserved.	[Guo, Kehua; Tang, Yayuan] Cent S Univ, Sch Informat Sci & Engn, Changsha, Hunan, Peoples R China; [Guo, Kehua] Minjiang Univ, Key Lab Informat Proc & Intelligent Control Fujia, Fuzhou, Peoples R China; [Zhang, Peiyun] Anhui Normal Univ, Sch Math & Comp Sci, Wuhu, Peoples R China	Guo, KH (reprint author), Cent S Univ, Sch Informat Sci & Engn, Changsha, Hunan, Peoples R China.; Guo, KH (reprint author), Minjiang Univ, Key Lab Informat Proc & Intelligent Control Fujia, Fuzhou, Peoples R China.	guokehua@csu.edu.cn			Hunan Science and Technology Plan [2012RS4054]; Natural Science Foundation of China [61672535, 61472005]; Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education Innovation Fund [JYB201502]; Key Laboratory of Information Processing and Intelligent Control of Fujian Innovation Fund [MJUKF201735]	This work is supported by the Hunan Science and Technology Plan (2012RS4054), Natural Science Foundation of China (61672535, 61472005), Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education Innovation Fund (JYB201502), Key Laboratory of Information Processing and Intelligent Control of Fujian Innovation Fund (MJUKF201735). The authors declare that they have no conflict of interests.	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Fusion	SEP	2017	37						77	85		10.1016/j.inffus.2017.01.008		9	Computer Science, Artificial Intelligence; Computer Science, Theory & Methods	Computer Science	ES4PV	WOS:000399518100007		No			2017-07-02	
J	Sachdeva, S; McCaffrey, S; Locke, D				Sachdeva, Sonya; McCaffrey, Sarah; Locke, Dexter			Social media approaches to modeling wildfire smoke dispersion: spatiotemporal and social scientific investigations	INFORMATION COMMUNICATION & SOCIETY			English	Article						Crowdsourcing; air quality; wildfire; smoke; risk perception	PARTICULATE AIR-POLLUTION; BIG DATA; HEALTH; CALIFORNIA; FIRES; MORTALITY; EXPOSURE; CLIMATE; VISITS; ASTHMA	Wildfires have significant effects on human populations, economically, environmentally, and in terms of their general well-being. Smoke pollution, in particular, from either prescribed burns or uncontrolled wildfires, can have significant health impacts. Some estimates suggest that smoke dispersion from fire events may affect the health of one in three residents in the United States, leading to an increased incidence of respiratory illnesses such as asthma and pulmonary disease. Scarcity in the measurements of particulate matter responsible for these public health issues makes addressing the problem of smoke dispersion challenging, especially when fires occur in remote regions. Crowdsourced data have become an essential component in addressing other societal problems (e.g., disaster relief, traffic congestion) but its utility in monitoring air quality impacts of wildfire events is unexplored. In this study, we assessed if user-generated social media content can be used as a complementary source of data in measuring particulate pollution from wildfire smoke. We found that the frequency of daily tweets within a 40,000km(2) area was a significant predictor of PM2.5 levels, beyond daily and geographic variation. These results suggest that social media can be a valuable tool for the measurement of air quality impacts of wildfire events, particularly in the absence of data from physical monitoring stations. Also, an analysis of the semantic content in people's tweets provided insight into the socio-psychological dimensions of fire and smoke and their impact on people residing in, working in, or otherwise engaging with affected areas.	[Sachdeva, Sonya; McCaffrey, Sarah] US Forest Serv, 1033 Univ Pl,Ste 360, Evanston, IL 60201 USA; [Locke, Dexter] Clark Univ, Grad Sch Geog, Worcester, MA 01610 USA	Sachdeva, S (reprint author), US Forest Serv, 1033 Univ Pl,Ste 360, Evanston, IL 60201 USA.	sonyasachdeva@fs.fed.us; smccaffrey@fs.fed.us; dexter.locke@gmail.com					Barrington L, 2011, ANN GEOPHYS-ITALY, V54, P680, DOI 10.4401/ag-5324; Blei DM, 2003, J MACH LEARN RES, V3, P993, DOI 10.1162/jmlr.2003.3.4-5.993; Bowman David M. J. S., 2005, EcoHealth, V2, P76, DOI 10.1007/s10393-004-0149-8; Calkin David E., 2015, Forest Ecosystems, V2, P9, DOI 10.1186/s40663-015-0033-8; Cassa C. 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Commun. Soc.	AUG	2017	20	8					1146	1161		10.1080/1369118X.2016.1218528		16	Communication; Sociology	Communication; Sociology	ET4RD	WOS:000400271600003		No			2017-07-02	
J	Aitamurto, T; Landemore, H; Galli, JS				Aitamurto, Tanja; Landemore, Helene; Galli, Jorge Saldivar			Unmasking the crowd: participants' motivation factors, expectations, and profile in a crowdsourced law reform	INFORMATION COMMUNICATION & SOCIETY			English	Article						Crowdsourcing; crowdlaw; democratic innovations; digital democracy; participatory democracy; motivation factors	WIKIPEDIA; DEMOCRACY	This article examines the demographic characteristics, motivations, and expectations of participants in a crowdsourced off-road traffic law reform in Finland. We found that the participants were mainly educated, full-time working professional males with a strong interest in off-road traffic. Though a minority, the women participating in the process produced more ideas than the men. The crowd was motivated by a mix of intrinsic and extrinsic factors. Intrinsic motivations included fulfilling civic duty, affecting the law for sociotropic reasons, to deliberate with and learn from peers. Extrinsic motivations included changing the law for financial gain or other benefits. Participation in crowdsourced policy-making was an act of grassroots advocacy, whether to pursue one's own interest or more altruistic goals, such as protecting nature. The motivations driving the participation were in part similar to those observed in traditional democratic processes, such as elections as well as other online collaborations such as crowdsourced journalism and citizen science. The crowds' behavior was, however, paradoxical. They participated despite the fact that they did not expect that their contributions would affect the law.	[Aitamurto, Tanja] Stanford Univ, Sch Engn, Brown Inst Media Innovat, Stanford, CA 94305 USA; [Landemore, Helene] Yale Univ, Polit Sci, New Haven, CT USA; [Galli, Jorge Saldivar] Univ Trento, Dept Informat Engn & Comp Sci, Trento, Italy	Aitamurto, T (reprint author), Stanford Univ, Sch Engn, Brown Inst Media Innovat, Stanford, CA 94305 USA.	tanja.aitamurto@gmail.com; helene.landemore@yale.edu; jorge.saldivargalli@unitn.it					Aitamurto T., 2012, PUBLICATIONS COMMITT; Aitamurto T., 2015, INT J COMMUNICATION, V9, P1; Aitamurto T., 2015, J SOCIAL MEDIA ORG, V2, P1; Aitamurto T., 2014, PUBLICATIONS COMMITT; Albrecht S., 2006, INFORM COMMUNICATION, V9, P62, DOI DOI 10.1080/13691180500519548; Benkler Y, 2002, YALE LAW J, V112, P369, DOI 10.2307/1562247; Blais A, 1999, PUBLIC CHOICE, V99, P39, DOI 10.1023/A:1018341418956; Brabham DC, 2012, J APPL COMMUN RES, V40, P307, DOI 10.1080/00909882.2012.693940; Brabham DC, 2013, MIT PRESS ESSENT, P1; Brabham D. 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Commun. Soc.	AUG	2017	20	8					1239	1260		10.1080/1369118X.2016.1228993		22	Communication; Sociology	Communication; Sociology	ET4RD	WOS:000400271600008		No			2017-07-02	
J	Lee, J; Lee, D; Hwang, SW				Lee, Jongwuk; Lee, Dongwon; Hwang, Seung-won			CrowdK: Answering top-k queries with crowdsourcing	INFORMATION SCIENCES			English	Article						Crowdsourcing; Top-k queries; Parameterized framework; Dynamic programming	ALGORITHMS	In recent years, crowdsourcing has emerged as a new computing paradigm for bridging the gap between human- and machine-based computation. As one of the core operations in data retrieval, we study top-k queries with crowdsourcing, namely crowd-enabled top-queries. This problem is formulated with three key factors, latency, monetary cost, and quality of answers. We first aim to design a novel framework that minimizes monetary cost when latency is constrained. Toward this goal, we employ a two-phase parameterized framework with two parameters, called buckets and ranges. On top of this framework, we develop three methods: greedy, equi-sized, and dynamic programming, to determine the buckets and ranges. By combining the three methods at each phase, we propose four algorithms: GdyBucket, EquiBucket, EquiRange, and CrowdK. When the crowd answers are imprecise, we also address improving the accuracy of the top-k answers. Lastly, using both simulated crowds and real crowds at Amazon Mechanical Turk, we evaluate the trade-off between our proposals with respect to monetary cost, accuracy of answers, and running time. Compared to other competitive algorithms, it is found that CrowdK reduces monetary cost up to 20 times, without sacrificing the accuracy of the top-k answers. (C) 2017 Elsevier Inc. All rights reserved.	[Lee, Jongwuk] Sungkyunkwan Univ, Dept Software, Seoul, South Korea; [Lee, Dongwon] Penn State Univ, Coll Informat Sci & Technol, University Pk, PA 16802 USA; [Hwang, Seung-won] Yonsei Univ, Dept Comp Sci, Seoul, South Korea	Lee, J (reprint author), Sungkyunkwan Univ, Dept Software, Seoul, South Korea.	jongwuklee@skku.edu; dongwon@psu.edu; seungwonh@yonsei.ac.kr			National Research Foundation of Korea (NRF) grant - Korea government (MSIP) [2015R1C1A1A01055442]	This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (No. 2015R1C1A1A01055442).	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J	Chatterjee, S; Mukhopadhyay, A; Bhattacharyya, M				Chatterjee, Sujoy; Mukhopadhyay, Anirban; Bhattacharyya, Malay			Dependent judgment analysis: A Markov chain based approach for aggregating crowdsourced opinions	INFORMATION SCIENCES			English	Article						Dependent judgment analysis; Crowdsourcing; Majority voting; Markov chain		Annotation of large-scale datasets can promisingly be done by crowd workers in a time and cost effective way. A major challenge in this area is how we aggregate the opinions received from multiple workers to derive the final judgment. Most of the crowd opinion aggregation models known so far deal with independent opinions, where the crowd workers provide their opinions unanimously and these are not visible to everyone. In real life, there are applications where an annotator can see others' opinions. This incurs a higher chance of getting biased by the other opinions. This paper addresses a new problem, hereafter termed as dependent judgment analysis, and proposes a method to derive the final judgment from a given set of independent and dependent opinions. Here, a Markov chain based aggregation method is used to handle the opinions of the crowd workers for finding a consensus. We study the performance of the proposed method on a synthetic dataset and another real-life dataset published in recent times. The proposed method is applied on these two datasets to find out the aggregated judgment. The efficacy of our proposed method is shown by comparing it with majority voting. (C) 2017 Elsevier Inc. All rights reserved.	[Chatterjee, Sujoy; Mukhopadhyay, Anirban] Univ Kalyani, Dept Comp Sci & Engn, Kalyani 741235, W Bengal, India; [Bhattacharyya, Malay] Indian Inst Engn Sci & Technol Shibpur, Dept Informat Technol, Howrah, India	Chatterjee, S (reprint author), Univ Kalyani, Dept Comp Sci & Engn, Kalyani 741235, W Bengal, India.	sujoy@klyuniv.ac.in; anirban@klyuniv.ac.in; malaybhattacharyya@it.iiests.ac.in			Visvesvaraya Young Faculty Research Fellowship of DeitY, Government of India; DST-PURSE grant of University of Kalyani	The authors would like to thank the anonymous reviewers for their valuable comments that greatly helped to improve the quality of the paper. The work of Malay Bhattacharyya is supported by the Visvesvaraya Young Faculty Research Fellowship 2015-16 of DeitY, Government of India. Anirban Mukhopadhyay acknowledges the support received from DST-PURSE grant of University of Kalyani.	Alarifi A, 2016, INFORM SCIENCES, V372, P332, DOI 10.1016/j.ins.2016.08.036; Ayala R.J.D., 2010, PSYCHOMETRIKA, V75, P778; Bhattacharyya M., 2014, P AAAI C HUM COMP CR; Bordogna G, 2014, INFORM SCIENCES, V258, P312, DOI 10.1016/j.ins.2013.07.013; Chatterjee S., 2016, P 4 AAAI C HUM COMP; Costa-Jussa MR, 2014, INFORM SCIENCES, V275, P400, DOI 10.1016/j.ins.2014.01.043; Dawid A P, 1979, APPL STAT, V28, P20, DOI DOI 10.2307/2346806; Demartini G., 2012, P 21 INT C WORLD WID, P469, DOI DOI 10.1145/2187836.2187900; Ferschl F., 1981, METRIKA, V28, P137, DOI 10.1007/BF01902886; Hovy D., 2013, P NAACL HLT, P1120; Jung J.H., 2012, P 4 HUM COMP WORKSH; Karger D. R., 2011, P ADV NEUR INF PROC, P1953; Kumar A., 2011, P WORKSH CROWDS SEAR, P19; Lease M., 2011, P 3 HUM COMP WORKSH, P97; Papoulis A., 1984, PROBABILITY RANDOM V; Raykar VC, 2012, J MACH LEARN RES, V13, P491; Ross J., 2010, P 28 INT C HUM FACT, P2863, DOI DOI 10.1145/1753846.1753873.ACCESSED; Ross S.M., 2010, INTRO PROBABILITY MO, P191, DOI 10.1016/B978-0-12-375686-2.00009-1; Sheshadri A., 2013, P 1 AAAI C HUM COMP, P2035; Smyth P., 1994, P ADV NEUR INF PROC, P1085; Snow R., 2008, P C EMP METH NAT LAN, P254, DOI 10.3115/1613715.1613751; Sorokin A., 2008, P 1 IEEE WORKSH INT, P1; Welinder P., 2010, P ADV NEUR INF PROC, P2424; Whitehill J, 2009, P ADV NEUR INF PROC, P2035	24	0	0	8	8	ELSEVIER SCIENCE INC	NEW YORK	360 PARK AVE SOUTH, NEW YORK, NY 10010-1710 USA	0020-0255	1872-6291		INFORM SCIENCES	Inf. Sci.	AUG	2017	396						83	96		10.1016/j.ins.2017.01.036		14	Computer Science, Information Systems	Computer Science	EP4VW	WOS:000397379000007		No			2017-07-02	
J	O'Leary, DE				O'Leary, Daniel E.			Crowd performance in prediction of the World Cup 2014	EUROPEAN JOURNAL OF OPERATIONAL RESEARCH			English	Article						OR in sports; Crowdsourcing E; xpertise; Brier score; FIFA World Cup	ASSOCIATION FOOTBALL; INDEPENDENT TRIALS; ENGLISH FOOTBALL; MARKETS; SIMULATION; SUCCESSES; MATCHES; NUMBER; SPORT; GOALS	This paper investigates the performance of the Yahoo crowd and experts in predicting the outcomes of matches in the World Cup in 2014. The analysis finds that the Yahoo crowd was statistically significantly better at predicting outcomes of matches than experts and very similar in performance to established betting odds. In addition, this paper finds that there was a statistically significant difference between the Yahoo crowd and a different crowd's performances, for the same task, suggesting that characteristics of the "crowd matter."Finally, this paper finds that different crowdsourcing approaches apparently provide different results. Accordingly, it is important to specify the particular crowdsourcing approach, rather than simply "crowdsource. (C) 2017 Elsevier B.V. All rights reserved.	[O'Leary, Daniel E.] Univ Southern Calif, Los Angeles, CA 90089 USA	O'Leary, DE (reprint author), Univ Southern Calif, Los Angeles, CA 90089 USA.	oleary@usc.edu					Bothos E, 2010, IEEE INTELL SYST, V25, P50, DOI 10.1109/MIS.2010.152; Brennan C., 2014, US TODAY        0702; Brier GW, 1950, MONTHLY WEATHER REVI, V78, P1, DOI [DOI 10.1175/1520-0493(1950)078<0001:VOFEIT>2.0.CO;2, 10.1175/1520-0493(1950)078<0001:VOFEIT&>2.0.CO;2]; Budescu DV, 2015, MANAGE SCI, V61, P267, DOI 10.1287/mnsc.2014.1909; Caffo B., 2007, METHODS BIOSTATISTIC; Crowder M, 2002, J ROY STAT SOC D-STA, V51, P157, DOI 10.1111/1467-9884.00308; De Veaux R. D., 2008, INTRO STAT; Dixon MJ, 2004, INT J FORECASTING, V20, P697, DOI 10.1016/j.ijforecast.2003.12.007; DIXON MJ, 1997, J ROY STAT SOC C-APP, V46, P265, DOI 10.1111/1467-9876.00065; Dobson S., 2000, STOCHASTIC MODELING, DOI 10.1.1.27.816&rep=repl&type-pdf; Dobson S., 2001, EC FOOTBALL; Dyte D, 2000, J OPER RES SOC, V51, P993, DOI 10.1057/palgrave.jors.2600997; FAMA EF, 1970, J FINANC, V25, P383, DOI 10.2307/2325486; Feller W., 1950, INTRO PROBABILITY TH; Fernandez M, 2010, IEEE T AERO ELEC SYS, V46, P803, DOI 10.1109/TAES.2010.5461658; Forrest D, 2000, INT J FORECASTING, V16, P317, DOI 10.1016/S0169-2070(00)00050-9; Forrest D, 2005, INT J FORECASTING, V21, P551, DOI 10.1016/j.ijforecast.2005.03.003; Forrest D., 2009, APPL ECON, V40, P317; Gneiting T, 2007, J AM STAT ASSOC, V102, P359, DOI 10.1198/016214506000001437; Goddard J, 2005, INT J FORECASTING, V21, P331, DOI 10.1016/j.ijforecast.2004.08.002; Godin F., 2014, KDD WORKSH LARG SCAL; Goldman Sachs, 2014, WORLD CUP EC 2014; GROFMAN B, 1983, THEOR DECIS, V15, P261, DOI 10.1007/BF00125672; Hayek FA, 1945, AM ECON REV, V35, P519; Herzog SM, 2011, JUDGM DECIS MAK, V6, P58; Hirth M, 2013, MATH COMPUT MODEL, V57, P2918, DOI 10.1016/j.mcm.2012.01.006; HOEFFDING W, 1956, ANN MATH STAT, V27, P713, DOI 10.1214/aoms/1177728178; Howe J., 2006, WIRED; Jenkins M., 2006, BLOOMBERG SPORTS HAS; Koning RH, 2003, EUR J OPER RES, V148, P268, DOI 10.1016/S0377-2217(02)00683-5; Makradakis S., 1998, FORECASTING METHODS; MARGOLIS H, 1976, PUBLIC CHOICE, V26, P119, DOI 10.1007/BF01725800; McCullough BD, 2010, J APPL STAT, V37, P881, DOI 10.1080/02664760902889965; McGwire D., 2014, 2014 WORLD CUP ROUND; McHale I, 2011, STAT MODEL, V11, P219, DOI 10.1177/1471082X1001100303; Moore D. S., 2004, BASIC PRACTICE STAT; PWC, 2014, PWC WORLD CUP IND WH; Radosavljevic V., 2014, KDD WORKSH LARG SCAL; Riccobono A., 2014, WORLD CUP 2014 EARLY; Roulston MS, 2002, MON WEATHER REV, V130, P1653, DOI 10.1175/1520-0493(2002)130<1653:EPFUIT>2.0.CO;2; Schlaefl S., 2014, PREDICTING WORLD CUP; Schumaker RP, 2016, DECIS SUPPORT SYST, V88, P76, DOI 10.1016/j.dss.2016.05.010; Sklar A., 1996, IMS LECT NOTES MONOG, V28; Surowiecki J., 2004, WISDOM CROWDS; THALER RH, 1988, J ECON PERSPECT, V2, P161; Troubadour, 2014, PRED WORLDCUP2014; WANG YH, 1993, STAT SINICA, V3, P295	47	0	0	22	22	ELSEVIER SCIENCE BV	AMSTERDAM	PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS	0377-2217	1872-6860		EUR J OPER RES	Eur. J. Oper. Res.	JUL 16	2017	260	2					715	724		10.1016/j.ejor.2016.12.043		10	Management; Operations Research & Management Science	Business & Economics; Operations Research & Management Science	EO8PS	WOS:000396952700027		No			2017-07-02	
J	Korpusik, M; Glass, J				Korpusik, Mandy; Glass, James			Spoken Language Understanding for a Nutrition Dialogue System	IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING			English	Article						Conditional random field; crowdsourcing; neural networks; semantic tagging; word vectors		Food logging is recommended by dieticians for prevention and treatment of obesity, but currently available mobile applications for diet tracking are often too difficult and timeconsuming for patients to use regularly. For this reason, we propose a novel approach to food journaling that uses speech and language understanding technology in order to enable efficient self-assessment of energy and nutrient consumption. This paper presents ongoing language understanding experiments conducted as part of a larger effort to create a nutrition dialogue system that automatically extracts food concepts from a user's spoken meal description. We first summarize the data collection and annotation of food descriptions performed via Amazon Mechanical Turk (AMT), for both a written corpus and spoken data from an in-domain speech recognizer. We show that the addition of word vector features improves conditional random field (CRF) performance for semantic tagging of food concepts, achieving an average F1 test score of 92.4 on written data; we also demonstrate that a convolutional neural network (CNN) with no hand-crafted features outperforms the best CRF on spoken data, achieving an F1 test score of 91.3. We illustrate two methods for associating foods with properties: segmenting meal descriptions with a CRF, and a complementary method that directly predicts associations with a feed-forward neural network. Finally, we conduct an end-to-end system evaluation through an AMTuser study with worker ratings of 83% semantic tagging accuracy.	[Korpusik, Mandy; Glass, James] MIT, Comp Sci & Artificial Intelligence Lab, Cambridge, MA 02139 USA	Korpusik, M (reprint author), MIT, Comp Sci & Artificial Intelligence Lab, Cambridge, MA 02139 USA.	korpusik@mit.edu; glass@mit.edu			Quanta Computing, Inc.; NIH; Department of Defense (DoD) through the National Defense Science and Engineering Graduate Fellowship (NDSEG) Program	This work was supported in part by a grant from Quanta Computing, Inc., in part by the NIH, and in part by the Department of Defense (DoD) through the National Defense Science and Engineering Graduate Fellowship (NDSEG) Program. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Ani Nenkova. (Corresponding author: Mandy Korpusik.)	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H. Organization, 2000, OB PREV MAN GLOB EP; Yao K., 2013, P 14 ANN C INT SPEEC, P2524; Yao KS, 2014, 2014 IEEE WORKSHOP ON SPOKEN LANGUAGE TECHNOLOGY SLT 2014, P189, DOI 10.1109/SLT.2014.7078572; Yin W., 2016, ARXIV160204341; Yin W., 2016, T ASS COMPUT LINGUIS, V4, P259; Young S, 2010, COMPUT SPEECH LANG, V24, P150, DOI 10.1016/j.csl.2009.04.001; Zhang X., 2015, P ADV NEUR INF PROC, P649	76	0	0	0	0	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC	PISCATAWAY	445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA	2329-9290			IEEE-ACM T AUDIO SPE	IEEE-ACM Trans. Audio Speech Lang.	JUL	2017	25	7					1450	1461		10.1109/TASLP.2017.2694699		12	Acoustics; Engineering, Electrical & Electronic	Acoustics; Engineering	EX5VP	WOS:000403311100004		No			2017-07-02	
J	Alacovska, A				Alacovska, Ana			The history of participatory practices: rethinking media genres in the history of user-generated content in 19th-century travel guidebooks	MEDIA CULTURE & SOCIETY			English	Article						crowdsourcing practices; genre; genre affordances; history of digital technologies; history of participation; new media history; participatory practices; travel guidebooks; user-generated content	WEB; BBC	This article charts the historical stability and continuity of participatory and crowdsourcing practices. Theoretically, it suggests that the blurring of the boundaries between audiences and producers, with the ensuing result of user-generated content, is by no means solely the upshot of new media technological affordances but largely a function of relatively stabilized, genre-specific formal and functional properties, or genre affordances'. Certain referential and performative genres enable interaction between audiences, texts and producers independently of new media technologies because these genres constitute what matters for both producers and audiences in specific historical circumstances. Genres make available shared cultural, social and pragmatic resources for appropriate and desirable being, doing, feeling and thinking. Empirically, this article builds upon an archival study of co-production related to the specific genre of travel guidebooks. It investigates (a) audience feedback in the form of handwritten letters sent to John Murray, a venerable 19th-century British publishing house, and (b) the ways in which John Murray's yesteryear guidebook producers actively solicited and implemented reader-authored content in professional production practice.	[Alacovska, Ana] Copenhagen Business Sch, Porcelaenshaven 18A, DK-2000 Frederiksberg, Denmark	Alacovska, A (reprint author), Copenhagen Business Sch, Porcelaenshaven 18A, DK-2000 Frederiksberg, Denmark.	aa.ikl@cbs.dk			Doctoral School for Organisation and Management Studies at the Copenhagen Business School	The Doctoral School for Organisation and Management Studies at the Copenhagen Business School.	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Soc.	JUL	2017	39	5					661	679		10.1177/0163443716663642		19	Communication; Sociology	Communication; Sociology	EX3SQ	WOS:000403153100004		No			2017-07-02	
J	Willis, CG; Law, E; Williams, AC; Franzone, BF; Bernardos, R; Bruno, L; Hopkins, C; Schorn, C; Weber, E; Park, DS; Davis, CC				Willis, Charles G.; Law, Edith; Williams, Alex C.; Franzone, Brian F.; Bernardos, Rebecca; Bruno, Lian; Hopkins, Claire; Schorn, Christian; Weber, Ella; Park, Daniel S.; Davis, Charles C.			CrowdCurio: an online crowdsourcing platform to facilitate climate change studies using herbarium specimens	NEW PHYTOLOGIST			English	Article						citizen science; flowering; fruiting; phenological sensitivity; phenology; phenophase	PLANT PHENOLOGY; CITIZEN-SCIENCE; FLOWERING TIMES; THOREAUS WOODS; RECORDS; PHOTOGRAPHS; REVEAL; DRIVEN; COMMON; SHOW	Phenology is a key aspect of plant success. Recent research has demonstrated that herbarium specimens can provide important information on plant phenology. Massive digitization efforts have the potential to greatly expand herbarium-based phenological research, but also pose a serious challenge regarding efficient data collection. Here, we introduce CrowdCurio, a crowdsourcing tool for the collection of phenological data from herbarium specimens. We test its utility by having workers collect phenological data (number of flower buds, open flowers and fruits) from specimens of two common New England (USA) species: Chelidonium majus and Vaccinium angustifolium. We assess the reliability of using nonexpert workers (i.e. Amazon Mechanical Turk) against expert workers. We also use these data to estimate the phenological sensitivity to temperature for both species across multiple phenophases. We found no difference in the data quality of nonexperts and experts. Nonexperts, however, were a more efficient way of collecting more data at lower cost. We also found that phenological sensitivity varied across both species and phenophases. Our study demonstrates the utility of CrowdCurio as a crowdsourcing tool for the collection of phenological data from herbarium specimens. Furthermore, our results highlight the insight gained from collecting large amounts of phenological data to estimate multiple phenophases.	[Willis, Charles G.; Franzone, Brian F.; Bernardos, Rebecca; Bruno, Lian; Hopkins, Claire; Schorn, Christian; Weber, Ella; Park, Daniel S.; Davis, Charles C.] Harvard Univ, Dept Organism & Evolutionary Biol, Cambridge, MA 20138 USA; [Willis, Charles G.; Franzone, Brian F.; Bernardos, Rebecca; Bruno, Lian; Hopkins, Claire; Schorn, Christian; Weber, Ella; Park, Daniel S.; Davis, Charles C.] Harvard Univ, Harvard Univ Herbaria, Cambridge, MA 20138 USA; [Law, Edith; Williams, Alex C.] Univ Waterloo, David R Cheriton Sch Comp Sci, Waterloo, ON N2L 3G1, Canada	Willis, CG; Davis, CC (reprint author), Harvard Univ, Dept Organism & Evolutionary Biol, Cambridge, MA 20138 USA.; Willis, CG; Davis, CC (reprint author), Harvard Univ, Harvard Univ Herbaria, Cambridge, MA 20138 USA.	charleswillis@fas.harvard.edu; cdavis@oeb.harvard.edu			New England Vascular Plant Project [NSF-DBI:EF1208835]; NSERC [RGPIN-2015-04543]	We would like to thank Anne Marie Countie and Michaela Schmull for their help on the project. This study was funded as part of the New England Vascular Plant Project (NSF-DBI:EF1208835) and part of a NSERC Discovery Grant (RGPIN-2015-04543).	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N., 2002, MODERN APPL STAT S; Walther GR, 2004, PERSPECT PLANT ECOL, V6, P169; Williams AC, 2014, BIG DAT BIG DAT 2014, P100; Willis CG, TRENDS ECOL IN PRESS; Willis CG, 2008, P NATL ACAD SCI USA, V105, P17029, DOI 10.1073/pnas.0806446105; Willis CG, 2010, PLOS ONE, V5, DOI 10.1371/journal.pone.0008878; Wolkovich EM, 2014, NEW PHYTOL, V201, P1156, DOI 10.1111/nph.12599; Zohner CM, 2014, ECOL LETT, V17, P1016, DOI 10.1111/ele.12308	46	0	0	2	2	WILEY	HOBOKEN	111 RIVER ST, HOBOKEN 07030-5774, NJ USA	0028-646X	1469-8137		NEW PHYTOL	New Phytol.	JUL	2017	215	1					479	488		10.1111/nph.14535		10	Plant Sciences	Plant Sciences	EW3PQ	WOS:000402413100040	28394023	No			2017-07-02	
J	Ma, Q; Gao, L; Liu, YF; Huang, JW				Ma, Qian; Gao, Lin; Liu, Ya-Feng; Huang, Jianwei			Economic Analysis of Crowdsourced Wireless Community Networks	IEEE TRANSACTIONS ON MOBILE COMPUTING			English	Article						Mobile crowdsourcing; wireless community network; economic analysis; price differentiation	OPTIMIZATION	Crowdsourced wireless community networks can effectively alleviate the limited coverage issue of Wi-Fi access points (APs), by encouraging individuals (users) to share their private residential Wi-Fi APs with others. In this paper, we provide a comprehensive economic analysis for such a crowdsourced network, with the particular focus on the users' behavior analysis and the community network operator's pricing design. Specifically, we formulate the interactions between the network operator and users as a two-layer Stackelberg model, where the operator determining the pricing scheme in Layer I, and then users determining their Wi-Fi sharing schemes in Layer II. First, we analyze the user behavior in Layer II via a two-stage membership selection and network access game, for both small-scale networks and large-scale networks. Then, we design a partial price differentiation scheme for the operator in Layer I, which generalizes both the complete price differentiation scheme and the single pricing scheme (i.e., no price differentiation). We show that the proposed partial pricing scheme can achieve a good trade off between the revenue and the implementation complexity. Numerical results demonstrate that when using the partial pricing scheme with only two prices, we can increase the operator's revenue up to 124.44 percent comparing with the single pricing scheme, and can achieve an average of 80 percent of the maximum operator revenue under the complete price differentiation scheme.	[Ma, Qian; Huang, Jianwei] Chinese Univ Hong Kong, Dept Informat Engn, Shatin, Hong Kong, Peoples R China; [Gao, Lin] Harbin Inst Technol, Sch Elect & Informat Engn, Shenzhen 518055, Peoples R China; [Liu, Ya-Feng] Chinese Acad Sci, Acad Math & Syst Sci, Inst Computat Math & Sci Engn Comp, State Key Lab Sci & Engn Comp, Beijing 100190, Peoples R China	Ma, Q (reprint author), Chinese Univ Hong Kong, Dept Informat Engn, Shatin, Hong Kong, Peoples R China.	mq012@ie.cuhk.edu.hk; gaolin@hitsz.edu.cn; yafliu@lsec.cc.ac.cn; jwhuang@ie.cuhk.edu.hk			General Research Funds under the University Grant Committee of the Hong Kong Special Administrative Region, China [CUHK 14202814]; National Natural Science Foundation of China [11301516, 11331012]	This work is partially supported by the General Research Funds (Project No.: CUHK 14202814) established under the University Grant Committee of the Hong Kong Special Administrative Region, China, and the National Natural Science Foundation of China under Grants 11301516 and 11331012. Lin Gao is the corresponding author.	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H., 2008, P IEEE INFOCOM, P1552; Mas-Colell A., 1995, MICROECONOMIC THEORY; Mazloumian A., 2008, P INT WORKSH EC NETW, P103, DOI 10.1145/1403027.1403050; Queipo NV, 2005, PROG AEROSP SCI, V41, P1, DOI 10.1016/j.paerosci.2005.02.001; Regis RG, 2013, ENG OPTIMIZ, V45, P529, DOI 10.1080/0305215X.2012.687731; Rios LM, 2013, J GLOBAL OPTIM, V56, P1247, DOI 10.1007/s10898-012-9951-y; Simon HA, 1991, ORGAN SCI, V2, P125, DOI 10.1287/orsc.2.1.125; Schmalensee R., 1989, HDB IND ORG, V1, P597, DOI 10.1016/S1573-448X(89)01013-7	29	0	0	0	0	IEEE COMPUTER SOC	LOS ALAMITOS	10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1314 USA	1536-1233	1558-0660		IEEE T MOBILE COMPUT	IEEE. Trans. Mob. Comput.	JUL 1	2017	16	7					1856	1869		10.1109/TMC.2016.2606390		14	Computer Science, Information Systems; Telecommunications	Computer Science; Telecommunications	EX0IG	WOS:000402902900006		No			2017-07-02	
J	Zhao, C; Yang, SS; Yang, XY; McCann, JA				Zhao, Cong; Yang, Shusen; Yang, Xinyu; McCann, Julie A.			Rapid, User-Transparent, and Trustworthy Device Pairing for D2D-Enabled Mobile Crowdsourcing	IEEE TRANSACTIONS ON MOBILE COMPUTING			English	Article						Mobile crowdsourcing; D2D communications; user-transparent pairing; trustworthiness	TRUST MANAGEMENT; REPUTATION; NETWORKS; AUTHENTICATION	Mobile Crowdsourcing is a promising service paradigm utilizing ubiquitous mobile devices to facilitate large-scale crowdsourcing tasks (e.g., urban sensing and collaborative computing). Many applications in this domain require Device-to-Device (D2D) communications between participating devices for interactive operations such as task collaborations and file transmissions. Considering the private participating devices and their opportunistic encountering behaviors, it is highly desired to establish secure and trustworthy D2D connections in a fast and autonomous way, which is vital for implementing practical Mobile Crowdsourcing Systems (MCSs). In this paper, we develop an efficient scheme, Trustworthy Device Pairing (TDP), which achieves user-transparent secure D2D connections and reliable peer device selections for trustworthy D2D communications. Through rigorous analysis, we demonstrate the effectiveness and security intensity of TDP in theory. The performance of TDP is evaluated based on both real-world prototype experiments and extensive trace-driven simulations. Evaluation results verify our theoretical analysis and show that TDP significantly outperforms existing approaches in terms of pairing speed, stability, and security.	[Zhao, Cong; Yang, Shusen; Yang, Xinyu] Xi An Jiao Tong Univ, Xian 710049, Shaanxi, Peoples R China; [McCann, Julie A.] Imperial Coll London, Dept Comp, London SW7 2AZ, England	Zhao, C (reprint author), Xi An Jiao Tong Univ, Xian 710049, Shaanxi, Peoples R China.	zhaocong@stu.xjtu.edu.cn; shusenyang@mail.xjtu.edu.cn; yxyphd@mail.xjtu.edu.cn; j.mccann@imperial.ac.uk			Intel Corporation; China 1000 Young Talents Program; Young Talent Support Plan of Xi'an Jiaotong University; NSF China (NSFC) [61572398]	This work is sponsored by Intel Corporation, China 1000 Young Talents Program, Young Talent Support Plan of Xi'an Jiaotong University, and NSF China (NSFC) under Grant 61572398. The authors thank the anonymous reviewers for their helpful and insightful comments and suggestions, which significantly contribute to improving the quality of the paper. Shusen Yang is the corresponding author.	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Trans. Mob. Comput.	JUL 1	2017	16	7					2008	2022		10.1109/TMC.2016.2611575		15	Computer Science, Information Systems; Telecommunications	Computer Science; Telecommunications	EX0IG	WOS:000402902900017		No			2017-07-02	
J	Meadows, A; Nolan, LJ; Higgs, S				Meadows, Angela; Nolan, Laurence J.; Higgs, Suzanne			Self-perceived food addiction: Prevalence, predictors, and prognosis	APPETITE			English	Article						Food addiction; Food use disorder; Disordered eating; Eating self-efficacy; Body image	BARRATT IMPULSIVENESS SCALE; BINGE-EATING DISORDER; SEEKING WEIGHT-LOSS; BODY-MASS INDEX; OBESE-PATIENTS; PSYCHOMETRIC EVALUATION; BARIATRIC SURGERY; BRITISH WOMEN; RISK-FACTORS; OVERWEIGHT	Food addiction is controversial within the scientific community. However many lay people consider themselves addicted to certain foods. We assessed the prevalence and characteristics of self-perceived "food addiction" and its relationship to a diagnostic measure of "clinical food addiction" in two samples: (1) 658 university students, and (2) 614 adults from an international online crowdsourcing platform. Participants indicated whether they considered themselves to be addicted to food, and then completed the Yale Food Addiction Scale, measures of eating behavior, body image, and explicit and internalized weight stigma. Participants in the community sample additionally completed measures of impulsivity, food cravings, binge eating, and depressive symptomatology. Follow-up data were collected from a subset of 305 students (mean follow-up 280 +/- 30 days). Self-perceived "food addiction" was prevalent, and was associated with elevated levels of problematic eating behavior, body image concerns, and psychopathology compared with "non-addicts", although individuals who also received a positive "diagnosis" on the Yale Food Addiction Scale experienced the most severe symptoms. A clear continuum was evident for all measures despite no differences in body mass index between the three groups. Multinomial logistic regression analyses indicated that perceived lack of self-control around food was the main factor distinguishing between those who did and did not consider themselves addicted to food, whereas severity of food cravings and depressive symptoms were the main discriminating variables between self-classifiers and those receiving a positive "diagnosis" on the Yale Food Addiction Scale. Self perceived "food addiction" was moderately stable across time, but did not appear predictive of worsening eating pathology. Self-classification as a "food addict" may be of use in identifying individuals in need of assistance with food misuse, loss-of-control eating, and body image issues. (C) 2017 Elsevier Ltd. All rights reserved.	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J	Carton, L; Ache, P				Carton, Linda; Ache, Peter			Citizen-sensor-networks to confront government decision-makers: Two lessons from the Netherlands	JOURNAL OF ENVIRONMENTAL MANAGEMENT			English	Article						Citizen-sensor-networks; Participatory sensing; Voluntary environmental monitoring; Airport noise; Human induced earthquakes; Citizen empowerment	INFORMATION; HEALTH; WORLD	This paper presents one emerging social-technical innovation: The evolution of citizen-sensor-networks where citizens organize themselves from the 'bottom up', for the sake of confronting governance officials with measured information about environmental qualities. We have observed how citizen-sensor networks have been initiated in the Netherlands in cases where official government monitoring and business organizations leave gaps. The formed citizen-sensor-networks collect information about issues that affect the local community in their quality-of-living. In particular, two community initiatives are described where the sensed environmental information, on noise pollution and gas-extraction induced earthquakes respectively, is published through networked geographic information methods. Both community initiatives pioneered in developing an approach that comprises the combined setting-up of sensor data flows, real-time map portals and community organization. Two particular cases are analyzed to trace the emergence and network operation of such 'networked geo-information tools' in practice: (1) The Groningen earthquake monitor, and (2) The Airplane Monitor Schiphol. In both cases, environmental 'externalities' of spatial-economic activities play an important role, having economic dimensions of national importance (e.g. gas extraction and national airport development) while simultaneously affecting the regional community with environmental consequences. The monitoring systems analyzed in this paper are established bottom-up, by citizens for citizens, to serve as 'information power' in dialogue with government institutions. The goal of this paper is to gain insight in how these citizen-sensor-networks come about: how the idea for establishing a sensor network originated, how their value gets recognized and adopted in the overall 'system of governance'; to what extent they bring countervailing power against vested interests and established discourses to the table and influence power-laden conflicts over environmental pressures; and whether or not they achieve (some form of) institutionalization and, ultimately, policy change. We find that the studied-citizen-sensor networks gain strength by uniting efforts and activities in crowdsourcing data, providing factual, 'objectivized data' or 'evidence' of the situation 'on the ground' on a matter of local community-wide concern. By filling an information need of the local community, a process of 'collective sense-making' combined with citizen empowerment could grow, which influenced societal discourse and challenged prevailing truth-claims of public institutions. In both cases similar, 'competing' web-portals were developed in response, both by the gas-extraction company and the airport. But with the citizen-sensor-networks alongside, we conclude there is a shift in power balance involved between government and affected communities, as the government no longer has information monopoly on environmental measurements. (C) 2017 Elsevier Ltd. All rights reserved.	[Carton, Linda; Ache, Peter] Radboud Univ Nijmegen, Inst Management Res, Dept Geog Planning & Environm, Spatial Planning Grp, Thomas van Aquinostr 3, NL-6525 GD Nijmegen, Netherlands	Carton, L (reprint author), Radboud Univ Nijmegen, Inst Management Res, Dept Geog Planning & Environm, Thomas van Aquinostr 3, NL-6525 GD Nijmegen, Netherlands.	l.carton@fm.ru.nl; p.ache@fm.ru.n					Adams MD, 2016, J ENVIRON MANAGE, V168, P133, DOI 10.1016/j.jenvman.2015.12.012; Bodansky D, 1999, AM J INT LAW, V93, P596, DOI 10.2307/2555262; Boulos Kamel, 2011, INT J HEALTH GEOGR, V2011, P67; Burke J.A., 2006, WORLD SENS WEB WORKS; Carton L. 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R., 2014, GRONINGER BODEM BEWE	39	0	0	6	6	ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD	LONDON	24-28 OVAL RD, LONDON NW1 7DX, ENGLAND	0301-4797	1095-8630		J ENVIRON MANAGE	J. Environ. Manage.	JUL 1	2017	196						234	251		10.1016/j.jenvman.2017.02.044		18	Environmental Sciences	Environmental Sciences & Ecology	EV6OI	WOS:000401888300025	28284944	No			2017-07-02	
J	Boothby, CA; Kim, HS; Romanow, NK; Hodgins, DC; McGrath, DS				Boothby, Celina A.; Kim, Hyoun S.; Romanow, Nicole K.; Hodgins, David C.; McGrath, Daniel S.			Assessing the role of impulsivity in smoking & non-smoking disordered gamblers	ADDICTIVE BEHAVIORS			English	Article						Smoking; Disordered gambling; Co-morbid addictions; Trait impulsivity; Urgency	SEEKING PATHOLOGICAL GAMBLERS; GAMBLING SEVERITY INDEX; CIGARETTE-SMOKING; TOBACCO USE; PSYCHIATRIC-DISORDERS; NICOTINE DEPENDENCE; SUBSTANCE USE; YOUNG-ADULTS; ALCOHOL; URGENCY	Background: Co-morbidity with other addictive behaviors is common in disordered gambling (DG). In particular, tobacco dependence has been found to be among the most prevalent disorders co-morbid with DG. While the extant literature has firmly established the co-occurrence of DG and smoking, there is a paucity of research examining factors that differentiate DGs who smoke from those who do not. Objectives: To address this empirical gap, the current study tested whether dimensions of trait impulsivity as measured by the UPPS-P Impulsive Behavior Scale (positive urgency, negative urgency, lack of premeditation, lack of perseverance, and sensation seeking), discriminated between non-DGs and DGs based on their present smoking status: non-smoker, occasional smoker, and daily smoker. Methods: To this end, 564 community gamblers were recruited through a crowdsourcing platform (Amazon's Mechanical Turk) and completed an online survey, assessing problem gambling severity, tobacco use, and trait impulsivity. Results: MANOVA analyses revealed significant main effects for both gambling severity and smoking status groups. Importantly, a significant gambling by smoking interaction was also found. Pairwise comparisons revealed that DGs who were daily smokers scored higher on negative urgency than those who smoked occasionally or not all. Furthermore, among non-DGs, smoking status failed to discriminate between mean scores on negative urgency. No other significant interaction effects were found for the remaining UPPS-P impulsivity facets. Conclusions: Results suggest that individual components of trait impulsivity, and more specifically negative urgency, successfully differentiate DGs who do not smoke, or just smoke occasionally, from DGs who smoke daily. These findings suggest that the degree of trait impulsivity may potentially distinguish between DGs and DGs who are dually addicted to other substances such as tobacco.(C) 2017 Elsevier Ltd. All rights reserved.	[Boothby, Celina A.; Kim, Hyoun S.; Romanow, Nicole K.; Hodgins, David C.; McGrath, Daniel S.] Univ Calgary, Dept Psychol, Adm Bldg AD 216,2500 Univ Dr NW, Calgary, AB T2N 1N4, Canada	McGrath, DS (reprint author), Univ Calgary, Dept Psychol, Adm Bldg AD 216,2500 Univ Dr NW, Calgary, AB T2N 1N4, Canada.	celina.boothby@ucalgary.ca; hyoun.kim@ucalgary.ca; nromanow@ucalgary.ca; dhodgins@ucalgary.ca; daniel.mcgrath@ucalgary.ca			Alberta Gambling Research Institute (AGRI); AGRI; Alberta Innovates: Health Solutions (AIHS); Social Sciences and Humanities Research Council (SSHRC)	This research was not directly grant funded. During the preparation of this manuscript, Daniel S. McGrath received partial financial salary support from the Alberta Gambling Research Institute (AGRI). Hyoun S. Kim received doctoral awards from AGRI, Alberta Innovates: Health Solutions (AIHS), and the Social Sciences and Humanities Research Council (SSHRC). David C. Hodgins is a coordinator of AGRI, which provides partial financial salary support. AGRI had no direct role in this study.	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E., 2008, INT GAMBL STUD, V8, P281, DOI DOI 10.1080/14459790802405905; Verdejo-Garcia A, 2007, DRUG ALCOHOL DEPEN, V91, P213, DOI 10.1016/j.drugalcdep.2007.05.025; Whiteside SP, 2001, PERS INDIV DIFFER, V30, P669, DOI 10.1016/S0191-8869(00)00064-7; Yan WS, 2016, SCI REP-UK, V6, DOI 10.1038/srep39233	53	0	0	18	18	PERGAMON-ELSEVIER SCIENCE LTD	OXFORD	THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND	0306-4603	1873-6327		ADDICT BEHAV	Addict. Behav.	JUL	2017	70						35	41		10.1016/j.addbeh.2017.02.002		7	Psychology, Clinical; Substance Abuse	Psychology; Substance Abuse	ER5XI	WOS:000398877200007	28189937	No			2017-07-02	
J	Livan, G; Caccioli, F; Aste, T				Livan, Giacomo; Caccioli, Fabio; Aste, Tomaso			Excess reciprocity distorts reputation in online social networks	SCIENTIFIC REPORTS			English	Article							COMPLEX NETWORKS; FEEDBACK; SYSTEMS; ORGANIZATION; WORLD; MODEL; EBAY; BIAS	The peer-to-peer (P2P) economy relies on establishing trust in distributed networked systems, where the reliability of a user is assessed through digital peer-review processes that aggregate ratings into reputation scores. Here we present evidence of a network effect which biases digital reputation, revealing that P2P networks display exceedingly high levels of reciprocity. In fact, these are much higher than those compatible with a null assumption that preserves the empirically observed level of agreement between all pairs of nodes, and rather close to the highest levels structurally compatible with the networks' reputation landscape. This indicates that the crowdsourcing process underpinning digital reputation can be significantly distorted by the attempt of users to mutually boost reputation, or to retaliate, through the exchange of ratings. We uncover that the least active users are predominantly responsible for such reciprocity-induced bias, and that this fact can be exploited to obtain more reliable reputation estimates. Our findings are robust across different P2P platforms, including both cases where ratings are used to vote on the content produced by users and to vote on user profiles.	[Livan, Giacomo; Caccioli, Fabio; Aste, Tomaso] UCL, Dept Comp Sci, 66-72 Gower St, London WC1E 6EA, England; [Livan, Giacomo; Caccioli, Fabio; Aste, Tomaso] London Sch Econ & Polit Sci, System Risk Ctr, Houghton St, London WC2A 2AE, England	Livan, G (reprint author), UCL, Dept Comp Sci, 66-72 Gower St, London WC1E 6EA, England.; Livan, G (reprint author), London Sch Econ & Polit Sci, System Risk Ctr, Houghton St, London WC2A 2AE, England.	g.livan@ucl.ac.uk			Economic and Social Research Council (ESRC) [ES/K002309/1]; EPSRC Early Career Fellowship in Digital Economy [EP/N006062/1]	We acknowledge support from the Economic and Social Research Council (ESRC) in funding the Systemic Risk Centre (Grant No. ES/K002309/1). Giacomo Livan acknowledges support from an EPSRC Early Career Fellowship in Digital Economy (Grant No. EP/N006062/1).	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N., 2012, ANTIFRAGILE THINGS G; Van Dijck J., 2015, SOCIAL MEDIA SOC, V1; Vavilis S, 2014, DECIS SUPPORT SYST, V61, P147, DOI 10.1016/j.dss.2014.02.002; Wasserman S, 1994, SOCIAL NETWORK ANAL; Zervas G., 2016, RISE SHARING EC ESTI; Zervas G., 2015, 1 LOOK ONLINE REPUTA	42	0	0	0	0	NATURE PUBLISHING GROUP	LONDON	MACMILLAN BUILDING, 4 CRINAN ST, LONDON N1 9XW, ENGLAND	2045-2322			SCI REP-UK	Sci Rep	JUN 14	2017	7								3551	10.1038/s41598-017-03481-7		11	Multidisciplinary Sciences	Science & Technology - Other Topics	EX5YG	WOS:000403318400105		gold			2017-07-02	
J	Mejri, O; Menoni, S; Matias, K; Aminoltaheri, N				Mejri, Ouejdane; Menoni, Scira; Matias, Kyla; Aminoltaheri, Negar			Crisis information to support spatial planning in post disaster recovery	INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION			English	Article						Crisis information; Spatial planning; Resilience; Knowledge management; Ontologies; Crowdsourcing	DAMAGE ASSESSMENT; RISK	In this paper we propose to explore the complex node of post disaster reconstruction, knowledge and data necessary to support spatial planning, and new information technologies. The methodology that is illustrated assumes that post-event damage assessments are useful to verify to what extent hazard and risk assessments that were available to planners to make decisions before the disaster were correct and if they were actually used as a basis for locational and zoning choices. Our contribution is aimed at the creation and design of knowledge bases accounting for the dynamic evolution of disasters. New web based technologies provide the opportunity to collect and analyse dynamic territorial crisis data using crowdsourcing and crowdmapping platforms. The proposed methodology permits to sort and classify a very large set of different types of data generated through the web. Semantic conceptualization using ontologies is performed to identify and select the information produced during the emergency that can support spatial planning in the post disaster reconstruction. The city of Tacloban in the Philippines, affected by the Super Typhoon Haiyan in November 2013 constitutes the test case for applying the methodology that has been developed.	[Mejri, Ouejdane; Menoni, Scira] Politecn Milan, Dipartimento Architettura & Studi Urbani DASTU, Dept Architecture & Urban Studies, Via Bonardi 3, I-20133 Milan, Italy; [Matias, Kyla] Univ Tokyo, Dept Urban Engn, Tokyo, Japan; [Aminoltaheri, Negar] Politecn Milan, Sci Civil Engn Risk Mitigat CERM, Milan, Italy	Menoni, S (reprint author), Politecn Milan, Dipartimento Architettura & Studi Urbani DASTU, Dept Architecture & Urban Studies, Via Bonardi 3, I-20133 Milan, Italy.	scira.menoni@polimi.it			European Commission under the VII Framework Programme; DG-ECHO [G.A.N. ECHO/SUB/2014/694469]	The research that is reported in the article has been developed within the Know-4-drr (Enabling knowledge for disaster risk reduction in integration to climate change adaptation) - C.N. 603807) project funded by the European Commission under the VII Framework Programme and the Idea project (Improving Damage assessments to Enhance cost-benefit Analyses) EU prevention and preparedness project in civil protection and marine pollution funded by DG-ECHO, G.A.N. ECHO/SUB/2014/694469).	Abecker A., 2009, HDB ONTOLOGIES, P713, DOI 10.1007/978-3-540-92673-3_32; Ackoff R. 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J. Disaster Risk Reduct.	JUN	2017	22						46	61		10.1016/j.ijdrr.2017.02.007		16	Geosciences, Multidisciplinary; Meteorology & Atmospheric Sciences; Water Resources	Geology; Meteorology & Atmospheric Sciences; Water Resources	EX8XL	WOS:000403533400005		No			2017-07-02	
J	Malhotra, A; Majchrzak, A; Niemiec, RM				Malhotra, Arvind; Majchrzak, Ann; Niemiec, Rebecca M.			Using Public Crowds for Open Strategy Formulation: Mitigating the Risks of Knowledge Gaps	LONG RANGE PLANNING			English	Article							COMPUTER-MEDIATED COMMUNICATION; INFORMATION-SYSTEMS STRATEGY; OPEN INNOVATION; PERSPECTIVE-TAKING; SOCIAL SOFTWARE; RESEARCH AGENDA; PRODUCT IDEAS; CO-CREATION; PARTICIPATION; COMMUNITIES	Online platforms allow for the possibility of including an ad hoc crowd of interested internal and external stakeholders drawn from the general public for open strategy formulation (OSF). However, sharing and integration of knowledge in ad hoc crowds are often impeded by knowledge gaps because of the wide diversity in these crowds. Two risks arise particularly for open strategy formulation when knowledge gaps are present: contentious conflict risk and self-promotion risk. Using action research, we examine the actions that mitigated these risk-inducing knowledge gaps. In particular, we found that four mitigation actions were taken: appropriately framing the strategic challenge question posed to the crowds, implementing a 2-phased guided crowdsourcing process to promote collaboration over contention, instructions explicitly discouraging self-promotion, and having the crowd post anonymously. Implications for future research and management implications on the use of online platforms for OSF are discussed. (C) 2016 Elsevier Ltd. All rights reserved.	[Malhotra, Arvind] Univ North Carolina Chapel Hill, Kenan Flagler Business Sch, Entrepreneurial Educ, Chapel Hill, NC 27599 USA; [Malhotra, Arvind] Univ North Carolina Chapel Hill, Kenan Flagler Business Sch, Strategy & Entrepreneurship, Chapel Hill, NC 27599 USA; [Majchrzak, Ann] Univ Southern Calif, Marshall Sch Business, Business Adm, Los Angeles, CA 90089 USA; [Majchrzak, Ann] Marshall, Dept Data Sci & Operat, Digital Innovat, Los Angeles, CA USA; [Majchrzak, Ann] Ramon Llull Univ, Esade Business Sch, Barcelona, Spain; [Majchrzak, Ann] LUISS, Rome Sch Business & Management areas Innovat & Or, Rome, Italy; [Majchrzak, Ann] London Sch Econ, Dept Management, Informat Syst & Innovat Grp, London, England; [Niemiec, Rebecca M.] Stanford Sch Earth Sci, Environm & Resources, Stanford, CA USA	Malhotra, A (reprint author), Univ North Carolina Chapel Hill, Kenan Flagler Business Sch, Entrepreneurial Educ, Chapel Hill, NC 27599 USA.; Malhotra, A (reprint author), Univ North Carolina Chapel Hill, Kenan Flagler Business Sch, Strategy & Entrepreneurship, Chapel Hill, NC 27599 USA.				National Science Foundation (NSF) [121983]	The authors would like to thank National Science Foundation for their generous funding of this research (NSF #121983).	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JUN	2017	50	3			SI		397	410		10.1016/j.lrp.2016.06.004		14	Business; Management; Planning & Development	Business & Economics; Public Administration	EX3IX	WOS:000403126900008		No			2017-07-02	
J	Baldassano, SN; Brinkmann, BH; Ung, H; Blevins, T; Conrad, EC; Leyde, K; Cook, MJ; Khambhati, AN; Wagenaar, JB; Worrell, GA; Litt, B				Baldassano, Steven N.; Brinkmann, Benjamin H.; Ung, Hoameng; Blevins, Tyler; Conrad, Erin C.; Leyde, Kent; Cook, Mark J.; Khambhati, Ankit N.; Wagenaar, Joost B.; Worrell, Gregory A.; Litt, Brian			Crowdsourcing seizure detection: algorithm development and validation on human implanted device recordings	BRAIN			English	Article						crowdsourcing; epilepsy; seizure detection; intracranial EEG; experimental models	RESPONSIVE CORTICAL STIMULATION; ARTIFICIAL NEURAL-NETWORK; INTRACRANIAL EEG; INTRACTABLE EPILEPSY; CANINE EPILEPSY; ONSET DETECTION; LONG-TERM; PREDICTION; IDENTIFICATION; PERFORMANCE	There exist significant clinical and basic research needs for accurate, automated seizure detection algorithms. These algorithms have translational potential in responsive neurostimulation devices and in automatic parsing of continuous intracranial electroencephalography data. An important barrier to developing accurate, validated algorithms for seizure detection is limited access to high-quality, expertly annotated seizure data from prolonged recordings. To overcome this, we hosted a kaggle.com competition to crowdsource the development of seizure detection algorithms using intracranial electroencephalography from canines and humans with epilepsy. The top three performing algorithms from the contest were then validated on out-of-sample patient data including standard clinical data and continuous ambulatory human data obtained over several years using the implantable NeuroVista seizure advisory system. Two hundred teams of data scientists from all over the world participated in the kaggle.com competition. The top performing teams submitted highly accurate algorithms with consistent performance in the out-of-sample validation study. The performance of these seizure detection algorithms, achieved using freely available code and data, sets a new reproducible benchmark for personalized seizure detection. We have also shared a 'plug and play' pipeline to allow other researchers to easily use these algorithms on their own datasets. The success of this competition demonstrates how sharing code and high quality data results in the creation of powerful translational tools with significant potential to impact patient care.	[Baldassano, Steven N.; Ung, Hoameng; Blevins, Tyler; Khambhati, Ankit N.; Litt, Brian] Univ Penn, Dept Bioengn, Philadelphia, PA 19104 USA; [Baldassano, Steven N.; Ung, Hoameng; Blevins, Tyler; Khambhati, Ankit N.; Wagenaar, Joost B.; Litt, Brian] Univ Penn, Ctr Neuroengn & Therapeut, Philadelphia, PA 19104 USA; [Brinkmann, Benjamin H.; Worrell, Gregory A.] Mayo Clin, Dept Neurol, Mayo Syst Electrophysiol Lab, Rochester, MN 55905 USA; [Brinkmann, Benjamin H.; Worrell, Gregory A.] Mayo Clin, Dept Biomed Engn, Rochester, MN 55905 USA; [Brinkmann, Benjamin H.; Worrell, Gregory A.] Mayo Clin & Mayo Fdn, Dept Neurol, 200 1st St SW, Rochester, MN 55905 USA; [Conrad, Erin C.; Wagenaar, Joost B.; Litt, Brian] Univ Penn, Dept Neurol, Philadelphia, PA 19104 USA; [Leyde, Kent] NeuroVista, Seattle, WA USA; [Cook, Mark J.] St Vincents Hosp, Melbourne, Vic, Australia; [Cook, Mark J.] Univ Melbourne, Dept Med, Melbourne, Vic, Australia	Baldassano, SN (reprint author), Univ Penn, 301 Hayden Hall,3320 Smith Walk, Philadelphia, PA 19104 USA.	stevennb@mail.med.upenn.edu			National Institutes of Health (NIH) [UH2-NS095495-01, R01NS092882, 1K01ES025436-01]; Mirowski Family Foundation; Ashton Fellowship at the University of Pennsylvania; NIH [5-U24-NS-063930-05]	This research was supported by the National Institutes of Health (NIH) (UH2-NS095495-01, R01NS092882, 1K01ES025436-01), the Mirowski Family Foundation, the Ashton Fellowship at the University of Pennsylvania, and contributions from Neil and Barbara Smit. The International Epilepsy Electrophysiology (IEEG) Portal is funded by the NIH (5-U24-NS-063930-05).	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J	Wang, XY; Mudie, LI; Baskaran, M; Cheng, CY; Alward, WL; Friedman, DS; Brady, CJ				Wang, Xueyang; Mudie, Lucy I.; Baskaran, Mani; Cheng, Ching-Yu; Alward, Wallace L.; Friedman, David S.; Brady, Christopher J.			Crowdsourcing to Evaluate Fundus Photographs for the Presence of Glaucoma	JOURNAL OF GLAUCOMA			English	Article						teleglaucoma; crowdsourcing; image analysis	OPEN-ANGLE GLAUCOMA; DIABETIC-RETINOPATHY; UNITED-STATES; OPTIC DISC; PREVALENCE; EYE; POPULATION; AGREEMENT; RETINA	Purpose: To assess the accuracy of crowdsourcing for grading optic nerve images for glaucoma using Amazon Mechanical Turk before and after training modules. Materials and Methods: Images (n=60) from 2 large population studies were graded for glaucoma status and vertical cup-to-disc ratio (VCDR). In the baseline trial, users on Amazon Mechanical Turk (Turkers) graded fundus photos for glaucoma and VCDR after reviewing annotated example images. In 2 additional trials, Turkers viewed a 26-slide PowerPoint training or a 10-minute video training and passed a quiz before being permitted to grade the same 60 images. Each image was graded by 10 unique Turkers in all trials. The mode of Turker grades for each image was compared with an adjudicated expert grade to determine accuracy as well as the sensitivity and specificity of Turker grading. Results: In the baseline study, 50% of the images were graded correctly for glaucoma status and the area under the receiver operating characteristic (AUROC) was 0.75 [95% confidence interval (CI), 0.64-0.87]. Post-PowerPoint training, 66.7% of the images were graded correctly with AUROC of 0.86 (95% CI, 0.780.95). Finally, Turker grading accuracy was 63.3% with AUROC of 0.89 (95% CI, 0.83-0.96) after video training. Overall, Turker VCDR grades for each image correlated with expert VCDR grades (Bland-Altman plot mean difference = -0.02). Conclusions: Turkers graded 60 fundus images quickly and at low cost, with grading accuracy, sensitivity, and specificity, all improving with brief training. With effective education, crowdsourcing may be an efficient tool to aid in the identification of glaucomatous changes in retinal images.	[Wang, Xueyang; Mudie, Lucy I.; Friedman, David S.; Brady, Christopher J.] Johns Hopkins Sch Med, Wilmer Eye Inst, 600 North Wolfe St, Baltimore, MD 21287 USA; [Alward, Wallace L.] Univ Iowa, Carver Coll Med, Dept Ophthalmol & Visual Sci, Iowa City, IA USA; [Baskaran, Mani; Cheng, Ching-Yu] Natl Univ Singapore, Singapore Natl Eye Ctr, Singapore Eye Res Inst, Singapore, Singapore; [Baskaran, Mani; Cheng, Ching-Yu] Natl Univ Singapore, Duke NUS Med Sch, Singapore, Singapore; [Cheng, Ching-Yu] Natl Univ Singapore, Yong Loo Lin Sch Med, Dept Ophthalmol, Singapore, Singapore	Brady, CJ (reprint author), Johns Hopkins Sch Med, Wilmer Eye Inst, 600 North Wolfe St, Baltimore, MD 21287 USA.	cbrady5@jhmi.edu			National Center for Advancing Translational Sciences (NCATS) a component of the National Institutes of Health (NIH) [KL2TR001077]; NIH Roadmap for Medical Research	This publication was made possible by the Johns Hopkins Institute for Clinical and Translational Research (ICTR) which is funded in part by Grant Number KL2TR001077 from the National Center for Advancing Translational Sciences (NCATS) a component of the National Institutes of Health (NIH), and NIH Roadmap for Medical Research. Its contents are solely the responsibility of the authors and do not necessarily represent the official view of the Johns Hopkins ICTR, NCATS, or NIH.	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Glaucoma	JUN	2017	26	6					505	510		10.1097/IJG.0000000000000660		6	Ophthalmology	Ophthalmology	EW5CY	WOS:000402524000013	28319525	No			2017-07-02	
J	Ravazzani, G; Corbari, C; Ceppi, A; Feki, M; Mancini, M; Ferrari, F; Gianfreda, R; Colombo, R; Ginocchi, M; Meucci, S; De Vecchi, D; Dell'Acqua, F; Ober, G				Ravazzani, Giovanni; Corbari, Chiara; Ceppi, Alessandro; Feki, Mouna; Mancini, Marco; Ferrari, Fabrizio; Gianfreda, Roberta; Colombo, Roberto; Ginocchi, Mirko; Meucci, Stefania; De Vecchi, Daniele; Dell'Acqua, Fabio; Ober, Giovanna			From (cyber)space to ground: new technologies for smart farming	HYDROLOGY RESEARCH			English	Article; Proceedings Paper	5th Hydrology Days of the Italian-Hydrological-Society	OCT 06-08, 2015	Perugia, ITALY	Italian Hydrol Soc		crowdsourcing; hydrological model; irrigation management; satellite observations; soil moisture; weather forecast	DISTRIBUTED HYDROLOGICAL MODEL; LAND-SURFACE TEMPERATURE; DATA ASSIMILATION SYSTEM; SATELLITE DATA; RIVER-BASINS; REFERENCE EVAPOTRANSPIRATION; DISCHARGE MEASUREMENTS; CLIMATE; BALANCE; CALIBRATION	Increased water demand and climate change impacts have recently enhanced the need to improve water resources management, even in those areas which traditionally have an abundant supply of water, such as the Po Valley in northern Italy. The highest consumption of water is devoted to irrigation for agricultural production, and so it is in this area that efforts have to be focused to study possible interventions. Meeting and optimizing the consumption of water for irrigation also means making more resources available for drinking water and industrial use, and maintaining an optimal state of the environment. In this study we show the effectiveness of the combined use of numerical weather predictions and hydrological modelling to forecast soil moisture and crop water requirement in order to optimize irrigation scheduling. This system combines state of the art mathematical models and new technologies for environmental monitoring, merging ground observed data with Earth observations from space and unconventional information from the cyberspace through crowdsourcing.	[Ravazzani, Giovanni; Corbari, Chiara; Ceppi, Alessandro; Feki, Mouna; Mancini, Marco] Politecn Milan, Dept Civil & Environm Engn, Piazza Leonardo da Vinci 32, I-20133 Milan, Italy; [Ferrari, Fabrizio; Gianfreda, Roberta] Terraria Srl, Via Melchiorre Gioia 132, I-20125 Milan, Italy; [Colombo, Roberto; Ginocchi, Mirko] Univ Milano Bicocca, DISAT, Remote Sensing Environm Dynam Lab, Piazza Sci 1, I-20126 Milan, Italy; [Meucci, Stefania] MMI Srl, Via Daniele Crespi 7, I-20133 Milan, Italy; [De Vecchi, Daniele; Dell'Acqua, Fabio] Univ Pavia, Dept Ind & Informat Engn, Via Ferrata 5, I-27100 Pavia, Italy; [Ober, Giovanna] CGS SpA, Via Gallarate 150, I-20151 Milan, Italy	Ravazzani, G (reprint author), Politecn Milan, Dept Civil & Environm Engn, Piazza Leonardo da Vinci 32, I-20133 Milan, Italy.	giovanni.ravazzani@polimi.it			Lombardy region	This work was sponsored by the Lombardy region in the framework of the SEGUICI project. We thank ARPA Lombardia (http://www.arpalombardia.it) and the Meteonetwork Association (http://www.meteonetwork.it) for providing meteorological observations from automatic stations. The editor, Prof. Attilio Castellarin, and three anonymous reviewers are gratefully acknowledged for their efforts to improve the quality and contents of this manuscript.	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J	Feller, J; Gleasure, R; Treacy, S				Feller, Joseph; Gleasure, Rob; Treacy, Stephen			Information sharing and user behavior in internet-enabled peer-to-peer lending systems: an empirical study	JOURNAL OF INFORMATION TECHNOLOGY			English	Article						Internet-enabled Peer-to-Peer Lending Systems (IP2PLS); crowdfunding; collective action; information sharing; personal transparency; Social Identity Theory	SOCIAL IDENTITY THEORY; SALIENCE; TRUST; MICROFINANCE; PERFORMANCE; COMMITMENT; IDENTIFICATION; MARKETPLACES; ORGANIZATION; DIMENSIONS	Internet-based information systems (IS) have enabled various forms of collective intelligence, action, and resources (e.g. open source software, innovation marketplaces, crowdsourcing, and crowdfunding). Within the domain of crowdfunding, Internet-enabled Peer-to-Peer Lending Systems (IP2PLS) have emerged as a disruptive technology, with implications for the financial services sector, business capitalization strategies, and personal and community development. IS research investigating user behavior in IP2PLS has revealed the saliency of social identity and personal transparency (as expressed through information sharing) in such systems. Prior research has largely focused on a small number of IP2PLS providers, thus this study examines a very large but under-researched platform. The study tests a theoretical model based on Social Identity Theory and prior IP2PLS studies, through an analysis of 116,667 loan records, and a subsequent analysis of 1000 manually coded records, to investigate the impact of information sharing on user (lenders and borrowers) behavior. The study reveals the importance of social (vs financial) data, and further reveals relationships that frequently contradict prior findings from other IP2PLS. The study thus implies the need for a more heterogeneous view of the IP2PLS domain, and the need to more fully understand as systems that support user behavior by enabling social information exchanges.	[Feller, Joseph; Gleasure, Rob; Treacy, Stephen] Univ Coll Cork, Dept Accounting Finance & Informat Syst, ORahilly Bldg 2-130,Coll Rd, Cork, Ireland	Feller, J (reprint author), Univ Coll Cork, Dept Accounting Finance & Informat Syst, ORahilly Bldg 2-130,Coll Rd, Cork, Ireland.	jfeller@afis.ucc.ie			Lewis Charitable Foundation (USA) through the Technology-Enabled Organizational Openness and Transparency (TOTO) at University College Cork, Ireland	This paper reports on research funded by the Lewis Charitable Foundation (USA) through the Technology-Enabled Organizational Openness and Transparency (TOTO) project hosted at University College Cork, Ireland.	Alvesson M, 2010, HUM RELAT, V63, P193, DOI 10.1177/0018726709350372; ANSOFF HI, 1975, CALIF MANAGE REV, V18, P21; Arnett DB, 2003, J MARKETING, V67, P89, DOI 10.1509/jmkg.67.2.89.18614; ASHFORTH BE, 1989, ACAD MANAGE REV, V14, P20, DOI 10.2307/258189; Ashmore RD, 2004, PSYCHOL BULL, V130, P80, DOI 10.1037/0033-2909.130.1.80; Atkinson S. 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C., 1979, SOCIAL PSYCHOL INTER, P33, DOI DOI 10.1016/S0065-2601(05)37005-5; Uzzi B, 1996, AM SOCIOL REV, V61, P674, DOI 10.2307/2096399; Wang H., 2010, ICIS 2010 P; Wang H., 2011, COMMUNICATIONS ASS I, V29, P243; Wang H, 2009, LECT NOTES BUS INF P, V36, P182; Yum H, 2012, ELECTRON COMMER R A, V11, P469, DOI 10.1016/j.elerap.2012.05.003; Zhang JJ, 2012, MANAGE SCI, V58, P892, DOI 10.1287/mnsc.1110.1459	82	0	0	8	8	PALGRAVE MACMILLAN LTD	BASINGSTOKE	BRUNEL RD BLDG, HOUNDMILLS, BASINGSTOKE RG21 6XS, HANTS, ENGLAND	0268-3962	1466-4437		J INF TECHNOL	J. Inf. Technol.	JUN	2017	32	2					127	146		10.1057/jit.2016.1		20	Computer Science, Information Systems; Information Science & Library Science; Management	Computer Science; Information Science & Library Science; Business & Economics	EW5WD	WOS:000402576300002		No			2017-07-02	
J	Ramsdale, JD; Balme, MR; Conway, SJ; Gallagher, C; van Gasselt, SA; Hauber, E; Orgel, C; Sejourne, A; Skinner, JA; Costard, F; Johnsson, A; Losiak, A; Reiss, D; Swirad, ZM; Kereszturi, A; Smith, IB; Platz, T				Ramsdale, Jason D.; Balme, Matthew R.; Conway, Susan J.; Gallagher, Colman; van Gasselt, Stephan A.; Hauber, Ernst; Orgel, Csilla; Sejourne, Antoine; Skinner, James A.; Costard, Francois; Johnsson, Andreas; Losiak, Anna; Reiss, Dennis; Swirad, Zuzanna M.; Kereszturi, Akos; Smith, Isaac B.; Platz, Thomas			Grid-based mapping: A method for rapidly determining the spatial distributions of small features over very large areas	PLANETARY AND SPACE SCIENCE			English	Article							TRANSVERSE AEOLIAN RIDGES; NORTHERN PLAINS; ISIDIS PLANITIA; MARS; LATITUDE; GLACIATION; ORIGIN; CONES; AGES; SITE	The increased volume, spatial resolution, and areal coverage of high-resolution images of Mars over the past 15 years have led to an increased quantity and variety of small-scale landform identifications. Though many such landforms are too small to represent individually on regional-scale maps, determining their presence or absence across large areas helps form the observational basis for developing hypotheses on the geological nature and environmental history of a study area. The combination of improved spatial resolution and near-continuous coverage significantly increases the time required to analyse the data. This becomes problematic when attempting regional or global-scale studies of metre and decametre-scale landforms. Here, we describe an approach for mapping small features (from decimetre to kilometre scale) across large areas, formulated for a project to study the northern plains of Mars, and provide context on how this method was developed and how it can be implemented. Rather than. "mapping" with points and polygons, grid-based mapping uses a "tick box" approach to efficiently record the locations of specific landforms (we use an example suite of glacial landforms; including viscous flow features, the latitude dependant mantle and polygonised ground). A grid of squares (e.g. 20 km by 20 km) is created over the mapping area. Then the basemap data are systematically examined, grid-square by grid-square at full resolution, in order to identify the landforms while recording the presence or absence of selected landforms in each grid-square to determine spatial distributions. The result is a series of grids recording the distribution of all the mapped landforms across the study area. In some ways, these are equivalent to raster images, as they show a continuous distribution-field of the various landforms across a defined (rectangular, in most cases) area. When overlain on context maps, these form a coarse, digital landform map. We find that grid-based mapping provides an efficient solution to the problems of mapping small landforms over large areas, by providing a consistent and standardised approach to spatial data collection. The simplicity of the grid-based mapping approach makes it extremely scalable and workable for group efforts, requiring minimal user experience and producing consistent and repeatable results. The discrete nature of the datasets, simplicity of approach, and divisibility of tasks, open up the possibility for citizen science in which crowdsourcing large grid based mapping areas could be applied.	[Ramsdale, Jason D.; Balme, Matthew R.; Conway, Susan J.] Open Univ, Dept Phys Sci, Walton Hall, Milton Keynes MK7 6AA, Bucks, England; [Balme, Matthew R.; Platz, Thomas] Planetary Sci Inst, Suite 106,1700 East Ft Lowell, Tucson, AZ USA; [Conway, Susan J.] CNRS, UMR 6112, Lab Planetol & Geodynam, 2 Rue Houssiniere,BP 92208, F-44322 Nantes 3, France; [Gallagher, Colman] Univ Coll, UCD Sch Geog, Dublin 4, Ireland; [Gallagher, Colman] Univ Coll, UCD Earth Inst, Dublin 4, Ireland; [van Gasselt, Stephan A.; Orgel, Csilla] Free Univ Berlin, Inst Geol Sci Planetary Sci & Remote Sensing, D-12249 Berlin, Germany; [Hauber, Ernst; Orgel, Csilla] DLR Inst Planetenforsch, Rutherfordstr 2, D-12489 Berlin, Adlershof, Germany; [Sejourne, Antoine; Costard, Francois] Univ Paris 11, Univ Paris Saclay, CNRS, GEOPS Geosci Paris Sud, Bat 509, F-91405 Orsay, France; [Skinner, James A.] US Geol Survey, Flagstaff, AZ 86001 USA; [Johnsson, Andreas] Univ Gothenburg, Dept Earth Sci, Box 460, SE-40530 Gothenburg, Sweden; [Losiak, Anna] Polish Acad Sci, Inst Geol Sci, Podwale 75, PL-50449 Wroclaw, Poland; [Losiak, Anna] Univ Vienna, Dept Lithospher Res, Althanstr 14, A-1090 Vienna, Austria; [Reiss, Dennis] Westfallische Wilheims Univ, Inst Planetol, Wilhelm Klemm Str 10, D-48149 Munster, Germany; [Swirad, Zuzanna M.] Univ Durham, Dept Geog, Durham DH1 3LE, England; [Kereszturi, Akos] Res Ctr Astron & Earth Sci, Csatkai U 6-8, H-9400 Sopron, Hungary; [Smith, Isaac B.] Univ Texas Austin, Inst Geophys, JJ Pickle Res Campus,Bldg 196, Austin, TX 78758 USA; [Platz, Thomas] Max Planck Inst Sonnensyst Forsch, Justus von Liebig Weg 3, D-37077 Gottingen, Germany	Ramsdale, JD (reprint author), Open Univ, Dept Phys Sci, Walton Hall, Milton Keynes MK7 6AA, Bucks, England.	jason.ramsdale@open.ac.uk			STFC [ST/L000776/1, ST/K502212/1]; UK Leverhulme Trust [RPG-397]; French Space Agency CNES; NCN [UMO-2013/08/S/ST10/00586]; ERASMUS program; BMWi [50QM1301]	JR was supported by STFC (ST/L000776/1 and ST/K502212/1). MB was supported by grants from STFC (ST/L000776/1) and the UK Leverhulme Trust (RPG-397). SC was supported by the Leverhulme Trust (RPG-397) and the French Space Agency CNES. M.R.P. AL was supported by grant NCN (UMO-2013/08/S/ST10/00586). CO was supported by the ERASMUS program and BMWi grant 50QM1301.	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JUN	2017	140						49	61		10.1016/j.pss.2017.04.002		13	Astronomy & Astrophysics	Astronomy & Astrophysics	EW2UG	WOS:000402350900007		No			2017-07-02	
J	Chatterjee, A; Seo, DW; Varshney, LR				Chatterjee, Avhishek; Seo, Daewon; Varshney, Lav R.			Capacity of Systems with Queue-Length Dependent Service Quality	IEEE TRANSACTIONS ON INFORMATION THEORY			English	Article						Channel capacity; quality of service; queuing	SERVER TIMING CHANNEL; INFORMATION-THEORY; TIME; BITS	We study the information-theoretic limit of reliable information processing by a server with queue-length dependent quality of service. We define the capacity for such a system as the number of bits reliably processed per unit time, and characterize it in terms of queuing system parameters. We also characterize the distributions of the arrival and service processes that maximize and minimize the capacity of such systems in a discretetime setting. For arrival processes with at most one arrival per time slot, we observed a minimum around the memoryless distribution. We also studied the case of multiple arrivals per time slot, and observed that burstiness in arrival has adverse effects on the system. The problem is theoretically motivated by an effort to incorporate the notion of reliability in queuing systems, and is applicable in the contexts of crowdsourcing, multimedia communication, and stream computing.	[Chatterjee, Avhishek; Seo, Daewon; Varshney, Lav R.] Univ Illinois, Coordinated Sci Lab, Urbana, IL 61801 USA	Chatterjee, A (reprint author), Univ Illinois, Coordinated Sci Lab, Urbana, IL 61801 USA.	avhishek@illinois.edu; dseo9@illinois.edu; varshney@illinois.edu			National Science Foundation [CCF-1623821]	This work was supported by the National Science Foundation under Grant CCF-1623821. This paper was presented in part at the 2016 International Symposium on Information Theory and Its Applications [1].	Anantharam V, 1996, IEEE T INFORM THEORY, V42, P4, DOI 10.1109/18.481773; Bedekar AS, 1998, IEEE T INFORM THEORY, V44, P446, DOI 10.1109/18.661496; Borokhovich M., 2015, P DAT GOOD EXCH D4GX; Branson S, 2014, INT J COMPUT VISION, V108, P3, DOI 10.1007/s11263-014-0698-4; Caire G, 1999, IEEE T INFORM THEORY, V45, P2007, DOI 10.1109/18.782125; Chatterjee A., 2015, P 2015 IEEE INFOCOM, P1769; Chatterjee A., 2016, P INT S INF THEOR AP, P583; Costa M, 2016, IEEE T INFORM THEORY, V62, P1897, DOI 10.1109/TIT.2016.2533395; Cover T. M., 1991, ELEMENTS INFORM THEO; Derlet RW, 2000, ANN EMERG MED, V35, P63, DOI 10.1016/S0196-0644(00)70105-3; Draper SC, 2005, IEEE T AUTOMAT CONTR, V50, P532, DOI 10.1109/TAC.2005.844911; Dugdale DC, 1999, J GEN INTERN MED, V14, pS34; Ephremides A, 1998, IEEE T INFORM THEORY, V44, P2416, DOI 10.1109/18.720543; Giles J, 2002, IEEE T INFORM THEORY, V48, P2455, DOI 10.1109/TIT.2002.801405; Gong X, 2011, 2011 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY PROCEEDINGS (ISIT), P1255, DOI 10.1109/ISIT.2011.6033737; Gorantla SK, 2012, IEEE T INF FOREN SEC, V7, P64, DOI 10.1109/TIFS.2011.2163398; Goyal VK, 2001, IEEE SIGNAL PROC MAG, V18, P74, DOI 10.1109/79.952806; Han T. S., 2003, INFORM SPECTRUM METH; HARRIS CM, 1967, OPER RES, V15, P117, DOI 10.1287/opre.15.1.117; Jamal M., 2007, INT J STRESS MANAGE, V14, P175, DOI DOI 10.1037/1072-5245.14.2.175; Kleinrock L., 1975, QUEUING SYSTEMS THEO, V1; Michelusi N, 2016, IEEE J SEL AREA COMM, V34, P584, DOI 10.1109/JSAC.2016.2525558; Musy S, 2006, 2006 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY, VOLS 1-6, PROCEEDINGS, P2899, DOI 10.1109/ISIT.2006.261670; Pinsker M. S., 1964, INFORM INFORM STABIL; Prabhakar B, 2003, IEEE T INFORM THEORY, V49, P357, DOI 10.1109/TIT.2002.807287; Raj S., 2004, ADV NETWORK INFORM T, P127; SCHWARTZ B, 1978, SOC PSYCHOL, V41, P3, DOI 10.2307/3033592; SRIRAM K, 1989, IEEE T COMMUN, V37, P703, DOI 10.1109/26.31162; Sundaresan R, 2000, IEEE T INFORM THEORY, V46, P705, DOI 10.1109/18.825847; Tavan M, 2013, ANN ALLERTON CONF, P755, DOI 10.1109/Allerton.2013.6736600; TELATAR IE, 1995, IEEE J SEL AREA COMM, V13, P963, DOI 10.1109/49.400652; Telatar I E., 1992, THESIS; Vempaty A, 2014, IEEE J-STSP, V8, P667, DOI 10.1109/JSTSP.2014.2316116; VERDU S, 1994, IEEE T INFORM THEORY, V40, P1147, DOI 10.1109/18.335960; Wagner AB, 2005, IEEE T INFORM THEORY, V51, P447, DOI 10.1109/TIT.2004.840876	35	0	0	1	1	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC	PISCATAWAY	445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA	0018-9448	1557-9654		IEEE T INFORM THEORY	IEEE Trans. Inf. Theory	JUN	2017	63	6					3950	3963		10.1109/TIT.2017.2681682		14	Computer Science, Information Systems; Engineering, Electrical & Electronic	Computer Science; Engineering	EV8UF	WOS:000402058900035		No			2017-07-02	
J	Strickland, JC; Stoops, WW				Strickland, Justin C.; Stoops, William W.			Stimulus Selectivity of Drug Purchase Tasks: A Preliminary Study Evaluating Alcohol and Cigarette Demand	EXPERIMENTAL AND CLINICAL PSYCHOPHARMACOLOGY			English	Article						behavioral economics; demand; chocolate; mTurk; soda	BEHAVIORAL ECONOMIC-ANALYSIS; RELATIVE REINFORCING EFFICACY; USE DISORDERS; INTERVENTION OUTCOMES; NICOTINE DEPENDENCE; COCAINE USERS; STRESS; SMOKING; SMOKERS; CURVE	The use of drug purchase tasks to measure drug demand in human behavioral pharmacology and addiction research has proliferated in recent years. Few studies have systematically evaluated the stimulus selectivity of drug purchase tasks to demonstrate that demand metrics are specific to valuation of or demand for the commodity under study. Stimulus selectivity is broadly defined for this purpose as a condition under which a specific stimulus input or target (e.g., alcohol, cigarettes) is the primary determinant of behavior (e.g., demand). The overall goal of the present study was to evaluate the stimulus selectivity of drug purchase tasks. Participants were sampled from the Amazon. com's crowdsourcing platform Mechanical Turk. Participants completed either alcohol and soda purchase tasks (Experiment 1; N = 139) or cigarette and chocolate purchase tasks (Experiment 2; N = 46), and demand metrics were compared to self-reported use behaviors. Demand metrics for alcohol and soda were closely associated with commodity-similar (e.g., alcohol demand and weekly alcohol use) but not commodity-different (e.g., alcohol demand and weekly soda use) variables. A similar pattern was observed for cigarette and chocolate demand, but selectivity was not as consistent as for alcohol and soda. Collectively, we observed robust selectivity for alcohol and soda purchase tasks and modest selectivity for cigarette and chocolate purchase tasks. These preliminary outcomes suggest that demand metrics adequately reflect the specific commodity under study and support the continued use of purchase tasks in substance use research.	[Strickland, Justin C.; Stoops, William W.] Univ Kentucky, Coll Arts & Sci, Dept Psychol, 171 Funkhouser Dr, Lexington, KY 40506 USA; [Stoops, William W.] Univ Kentucky, Coll Med, Dept Behav Sci, Lexington, KY 40536 USA; [Stoops, William W.] Univ Kentucky, Coll Med, Dept Psychiat, Lexington, KY USA	Strickland, JC (reprint author), Univ Kentucky, Coll Arts & Sci, Dept Psychol, 171 Funkhouser Dr, Lexington, KY 40506 USA.	justrickland@uky.edu			Psi Chi Psychology Honor Society; National Science Foundation [1247392]	This work was supported by the Psi Chi Psychology Honor Society and National Science Foundation Grant 1247392. These funding sources had no role in study design, data collection or analysis, or preparation or submission of the article.	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A., 2013, INTRO LEARNING BEHAV; Roma PG, 2016, MANAG DECIS ECON, V37, P306, DOI 10.1002/mde.2718; Schlienz NJ, 2014, ADDICT BEHAV, V39, P1484, DOI 10.1016/j.addbeh.2014.05.008; Sinha R, 2008, ANN NY ACAD SCI, V1141, P105, DOI 10.1196/annals.1441.030; SPILLMAN D, 1990, PSYCHOL REP, V66, P499, DOI 10.2466/PR0.66.2.499-502; Stein JS, 2015, EXP CLIN PSYCHOPHARM, V23, P377, DOI 10.1037/pha0000020; Strickland JC, 2016, EXP CLIN PSYCHOPHARM, V24, P447, DOI 10.1037/pha0000096; Strickland JC, 2016, DRUG ALCOHOL DEPEN, V166, P61, DOI 10.1016/j.drugalcdep.2016.06.022; Wilson AG, 2016, NICOTINE TOB RES, V18, P524, DOI 10.1093/ntr/ntv154	43	0	0	1	1	AMER PSYCHOLOGICAL ASSOC	WASHINGTON	750 FIRST ST NE, WASHINGTON, DC 20002-4242 USA	1064-1297	1936-2293		EXP CLIN PSYCHOPHARM	Exp. Clin. Psychopharmacol.	JUN	2017	25	3					198	207		10.1037/pha0000123		10	Psychology, Biological; Psychology, Clinical; Pharmacology & Pharmacy; Psychiatry	Psychology; Pharmacology & Pharmacy; Psychiatry	EU5QP	WOS:000401088100007	28493743	No			2017-07-02	
J	Peters, EN; Rosenberry, ZR; Schauer, GL; O'Grady, KE; Johnson, PS				Peters, Erica N.; Rosenberry, Zachary R.; Schauer, Gillian L.; O'Grady, Kevin E.; Johnson, Patrick S.			Marijuana and Tobacco Cigarettes: Estimating Their Behavioral Economic Relationship Using Purchasing Tasks	EXPERIMENTAL AND CLINICAL PSYCHOPHARMACOLOGY			English	Article						marijuana; cannabis; tobacco; cigarette; behavioral economics	CO-USE; POLYDRUG ABUSE; SUBSTANCE USE; CANNABIS USE; ALCOHOL-USE; DEMAND; DRUG; REINFORCERS; ABSTINENCE; CONCURRENT	Although marijuana and tobacco are commonly coused, the nature of their relationship has not been fully elucidated. Behavioral economics has characterized the relationship between concurrently available commodities but has not been applied to marijuana and tobacco couse. U.S. adults >= 18 years who coused marijuana and tobacco cigarettes were recruited via Mechanical Turk, a crowdsourcing service by Amazon. Participants (N = 82) completed online purchasing tasks assessing hypothetical marijuana or tobacco cigarette puff consumption across a range of per-puff prices; 2 single-commodity tasks assessed these when only 1 commodity was available, and 2 cross-commodity tasks assessed these in the presence of a concurrently available fixed-price commodity. Purchasing tasks generated measures of demand elasticity, that is, sensitivity of consumption to prices. In single-commodity tasks, consumption of tobacco cigarette puffs (elasticity of demand: alpha = 0.0075; 95% confidence interval [0.0066, 0.0085], R-2 = 0.72) and of marijuana puffs (alpha = .0044; 95% confidence interval [0.0038, 0.0049], R-2 = 0.71) declined significantly with increases in price per puff. In cross-commodity tasks when both tobacco cigarette puffs and marijuana puffs were available, demand for 1 commodity was independent of price increases in the other commodity (ps > .05). Results revealed that, in this small sample, marijuana and tobacco cigarettes did not substitute for each other and did not complement each other; instead, they were independent of each other. These preliminary results can inform future studies assessing the economic relationship between tobacco and marijuana in the quickly changing policy climate in the United States.	[Peters, Erica N.; Rosenberry, Zachary R.] Battelle Publ Hlth Ctr Tobacco Res, 6115 Falls Rd,Suite 200, Baltimore, MD 21209 USA; [Schauer, Gillian L.] Univ Washington, Sch Publ Hlth, Dept Hlth Serv, Seattle, WA 98195 USA; [O'Grady, Kevin E.] Univ Maryland, Dept Psychol, College Pk, MD 20742 USA; [Johnson, Patrick S.] Calif State Univ Chico, Dept Psychol, Chico, CA 95929 USA	Peters, EN (reprint author), Battelle Publ Hlth Ctr Tobacco Res, 6115 Falls Rd,Suite 200, Baltimore, MD 21209 USA.	finan@battelle.org			Battelle Memorial Institute	We gratefully acknowledge Meridith Thanner, Kelly Ward, and Michael Daley for their contributions to the current research. All authors contributed in a significant way to the manuscript and have read and approved the final manuscript. This work was supported by internal funds from Battelle Memorial Institute. The funding source had no role other than financial support.	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S. Department of Health and Human Services, 2015, NAT SURV DRUG US HLT; Vandrey RG, 2008, DRUG ALCOHOL DEPEN, V92, P48, DOI 10.1016/j.drugalcdep.2007.06.010; VUCHINICH RE, 1988, J ABNORM PSYCHOL, V97, P181, DOI 10.1037//0021-843X.97.2.181; PETERS EN, 2010, Patent No. 106111; LEVIN KH, 2010, Patent No. 111120	48	0	0	3	3	AMER PSYCHOLOGICAL ASSOC	WASHINGTON	750 FIRST ST NE, WASHINGTON, DC 20002-4242 USA	1064-1297	1936-2293		EXP CLIN PSYCHOPHARM	Exp. Clin. Psychopharmacol.	JUN	2017	25	3					208	215		10.1037/pha0000122		8	Psychology, Biological; Psychology, Clinical; Pharmacology & Pharmacy; Psychiatry	Psychology; Pharmacology & Pharmacy; Psychiatry	EU5QP	WOS:000401088100008	28437124	No			2017-07-02	
J	Lu, YD; Singh, PV; Sun, BH				Lu, Yingda; Singh, Param Vir; Sun, Baohong			IS A CORE-PERIPHERY NETWORK GOOD FOR KNOWLEDGE SHARING? A STRUCTURAL MODEL OF ENDOGENOUS NETWORK FORMATION ON A CROWDSOURCED CUSTOMER SUPPORT FORUM	MIS QUARTERLY			English	Article						Structural modeling; social networks; Web 2.0; learning by sharing; social media; discussion forums; social CRM	PERFECT INDUSTRY DYNAMICS; SOCIAL CONTAGION; DECISION-MAKING; BRAND CHOICE; HETEROGENEITY; COMMUNICATION; DEMAND; FAMILY	Many companies have adopted technology driven social learning platforms such as social customer relationship management (crowdsourcing customer support) to support knowledge sharing among customers. A number of these self-evolving, online customer support communities have reported the emergence of a coreperiphery knowledge sharing network structure. In this study, we investigate why such a structure emerges and its implications for knowledge sharing within the community. We propose a dynamic structural model with endogenized knowledge-sharing and network formation. Our model recognizes the dynamic and interdependent nature of knowledge seeking and sharing decisions and allows them to be driven by knowledge increments and social status building in anticipation of future reciprocal rewards from peers. Applying this model to a fine grained panel dataset from a social customer support forum for a telecom firm, we illustrate that a user in this community gains value from being linked to other individuals with higher social status. As a result, a user is more inclined to answer the questions of those who are in the core (well connected) than questions from those who are in the periphery (not well connected). We find that users are taking into account the expected likelihood of their questions receiving a solution before asking a question. With the emergence of a core-periphery network structure, peripheral individuals are discouraged from asking questions as their expectation of receiving a solution to their question is very low. Thus, the core-periphery structure has created a barrier to knowledge flow to new customers who need the knowledge the most. Our counterfactuals show that hiding the identity of the knowledge seeker or making the individual contributions obsolete faster helps break the core-periphery structure and improves knowledge sharing in the community.	[Lu, Yingda] Rensselaer Polytech Inst, Lally Sch Management, Troy, NY 12180 USA; [Singh, Param Vir] Carnegie Mellon Univ, David A Tepper Sch Business, Pittsburgh, PA 15213 USA; [Sun, Baohong] Cheung Kong Grad Sch Business, 1 E Changan Ave, Dongcheng Qu, Beijing Shi, Peoples R China	Lu, YD (reprint author), Rensselaer Polytech Inst, Lally Sch Management, Troy, NY 12180 USA.	luy6@rpi.edu; psidhu@cmu.edu; bhsun@ckgsb.edu.cn					Adamic L. 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T., 2007, J SOCIAL STRUCTURE, V8, P564; Zhang J., 2007, P 16 INT C WORLD WID, P221, DOI DOI 10.1145/1242572.1242603; Zhang JJ, 2010, MARKET SCI, V29, P315, DOI 10.1287/mksc.1090.0500	52	0	0	8	8	SOC INFORM MANAGE-MIS RES CENT	MINNEAPOLIS	UNIV MINNESOTA-SCH MANAGEMENT 271 19TH AVE SOUTH, MINNEAPOLIS, MN 55455 USA	0276-7783			MIS QUART	MIS Q.	JUN	2017	41	2					607	+				27	Computer Science, Information Systems; Information Science & Library Science; Management	Computer Science; Information Science & Library Science; Business & Economics	EU8WY	WOS:000401320400013		No			2017-07-02	
J	Micallef, L; Palmas, G; Oulasvirta, A; Weinkauf, T				Micallef, Luana; Palmas, Gregorio; Oulasvirta, Antti; Weinkauf, Tino			Towards Perceptual Optimization of the Visual Design of Scatterplots	IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS			English	Article; Proceedings Paper	IEEE Pacific Visualization Symposium (IEEE PacificVis)	APR 18-21, 2017	Seoul Natl Univ, Seoul, SOUTH KOREA	IEEE, IEEE Tech Comm Visualizat & Comp Graph	Seoul Natl Univ	Scatterplot; optimization; perception; crowdsourcing	MULTICLASS SCATTERPLOTS; RANKING VISUALIZATIONS; QUALITY METRICS; WEBERS LAW; REDUCTION; GRAPHICS; PLOTS	Designing a good scatterplot can be difficult for non-experts in visualization, because they need to decide on many parameters, such as marker size and opacity, aspect ratio, color, and rendering order. This paper contributes to research exploring the use of perceptual models and quality metrics to set such parameters automatically for enhanced visual quality of a scatterplot. A key consideration in this paper is the construction of a cost function to capture several relevant aspects of the human visual system, examining a scatterplot design for some data analysis task. We show how the cost function can be used in an optimizer to search for the optimal visual design for a user's dataset and task objectives (e.g., "reliable linear correlation estimation is more important than class separation"). The approach is extensible to different analysis tasks. To test its performance in a realistic setting, we pre-calibrated it for correlation estimation, class separation, and outlier detection. The optimizer was able to produce designs that achieved a level of speed and success comparable to that of those using human-designed presets (e.g., in R or MATLAB). Case studies demonstrate that the approach can adapt a design to the data, to reveal patterns without user intervention.	[Micallef, Luana] Aalto Univ, Dept Comp Sci, Helsinki Inst Informat Technol, Espoo 02150, Finland; [Palmas, Gregorio; Weinkauf, Tino] KTH Royal Inst Technol, Dept Computat Sci & Technol, Sch Comp Sci & Commun, S-11428 Stockholm, Sweden; [Oulasvirta, Antti] Aalto Univ, Dept Commun & Networking, Espoo 02150, Finland	Micallef, L (reprint author), Aalto Univ, Dept Comp Sci, Helsinki Inst Informat Technol, Espoo 02150, Finland.	luana.micallef@hiit.fi; gpalmas@kth.se; antti.oulasvirta@aalto.fi; weinkauf@kth.se			Academy of Finland; Centre of Excellence in Computational Inference Research (COIN); SkAT-VG project - EC [618067]; European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme [637991];  [305780]	Luana Micallef was funded by the Academy of Finland, Centre of Excellence in Computational Inference Research (COIN), and grant agreement 305780. Gregorio Palmas and Tino Weinkauf received partial funding through the SkAT-VG project, funded by the EC under FP7-ICT-2013-C, Future Emerging Technologies, grant agreement 618067. Antti Oulasvirta was funded by the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement 637991).	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J	Dumas, TM; Maxwell-Smith, M; Davis, JP; Giulietti, PA				Dumas, Tara M.; Maxwell-Smith, Matthew; Davis, Jordan P.; Giulietti, Paul A.			Lying or longing for likes? Narcissism, peer belonging, loneliness and normative versus deceptive like-seeking on Instagram in emerging adulthood	COMPUTERS IN HUMAN BEHAVIOR			English	Article						Instagram; Narcissism; Peer belonging; Loneliness; Deception; Social networks	SELF-PRESENTATION; BEHAVIOR; FACEBOOK; ESTEEM; SENSE	We examined the extent to which emerging adults engage in different behaviors on Instagram, a popular social networking site, to gain attention and validation from others via "likes." We also examined individual differences in the frequency of like-seeking behavior and motives for Instagram use as mediators of these relationships. Participants (N = 198 and 265 (replication study)) were recruited via an online crowdsourcing portal to complete a survey. Results demonstrated that, as predicted, participants engaged in an assortment of different like-seeking behaviors. Further, a two-factor solution emerged, with like-seeking behavior separated by whether they were normative (i.e., common or accepted, e.g., using filters or hashtags) or deceptive (e.g., buying likes or changing one's appearance in photos using software). Deceptive like-seeking was predicted by stronger narcissism and a weaker sense of peer belonging, whereas normative like-seeking was predicted by stronger narcissism and a stronger sense of peer belonging. Further, consistent with hypotheses, significant mediators of the relation between narcissism and deceptive like-seeking included motives to use Instagram to increase popularity and showcase creativity. Results help to identify young people who are more susceptible to engaging in deceptive, potentially harmful acts to gain attention and validation on Instagram. (C) 2017 Elsevier Ltd. All rights reserved.	[Dumas, Tara M.; Giulietti, Paul A.] Western Univ, Huron Univ Coll, London, ON, Canada; [Maxwell-Smith, Matthew] Western Univ, London, ON, Canada; [Davis, Jordan P.] Univ Illinois, Champaign, IL USA	Dumas, TM (reprint author), Huron Univ Coll, 1349 Western Rd, London, ON N6G 1H3, Canada.	tdumas2@uwo.ca					Arnett JJ, 2000, AM PSYCHOL, V55, P469, DOI 10.1037//0003-066X.55.5.469; Barry C. M., 2016, OXFORD HDB EMERGING; Berinsky AJ, 2012, POLIT ANAL, V20, P351, DOI 10.1093/pan/mpr057; Campbell WK, 2002, PERS SOC PSYCHOL B, V28, P358, DOI 10.1177/0146167202286007; Campbell WK, 1999, J PERS SOC PSYCHOL, V77, P1254, DOI 10.1037/0022-3514.77.6.1254; Carpenter CJ, 2012, PERS INDIV DIFFER, V52, P482, DOI 10.1016/j.paid.2011.11.011; DePaulo BM, 1998, J PERS SOC PSYCHOL, V74, P63, DOI 10.1037/0022-3514.74.1.63; DePaulo BM, 1996, J PERS SOC PSYCHOL, V70, P979, DOI 10.1037/0022-3514.70.5.979; Diener E, 1999, PSYCHOL BULL, V125, P276, DOI 10.1037/0033-2909.125.2.276; Duggan M., 2014, SOCIAL MEDIA UPDATE; EMMONS RA, 1984, J PERS ASSESS, V48, P291, DOI 10.1207/s15327752jpa4803_11; Gentile B, 2013, PSYCHOL ASSESSMENT, V25, P1120, DOI 10.1037/a0033192; Hayes A. F., 2013, INTRO MEDIATION MODE; HAYS RD, 1987, J PERS ASSESS, V51, P69, DOI 10.1207/s15327752jpa5101_6; Hu Y., 2014, WHAT WE INSTAGRAM 1; Instagram, 2016, STATS; Jonason PK, 2014, PERS INDIV DIFFER, V70, P117, DOI 10.1016/j.paid.2014.06.038; Kim J, 2011, CYBERPSYCH BEH SOC N, V14, P359, DOI 10.1089/cyber.2010.0374; Lee JA, 2016, CYBERPSYCH BEH SOC N, V19, P347, DOI 10.1089/cyber.2015.0486; Mehdizadeh S, 2010, CYBERPSYCH BEH SOC N, V13, P357, DOI 10.1089/cyber.2009.0257; Moon JH, 2016, PERS INDIV DIFFER, V101, P22, DOI 10.1016/j.paid.2016.05.042; Morf CC, 2001, PSYCHOL INQ, V12, P177, DOI 10.1207/S15327965PLI1204_1; Muthen L. K., 2010, US STAT ANAL LATENT; Newman BM, 2007, ADOLESCENCE, V42, P241; Ong EYL, 2011, PERS INDIV DIFFER, V50, P180, DOI 10.1016/j.paid.2010.09.022; Pittman M., 2015, J SOCIAL MEDIA SOC, V4; Rimal RN, 2005, COMMUN RES, V32, P389, DOI 10.1177/0093650205275385; Sheldon P, 2016, COMPUT HUM BEHAV, V58, P89, DOI 10.1016/j.chb.2015.12.059; Stanton K, 2016, PERS INDIV DIFFER, V88, P187, DOI 10.1016/j.paid.2015.09.015; Strayhorn TL, 2012, J COLL STUDENT DEV, V53, P783; Tajfel H., 2010, SOCIAL IDENTITY INTE; Tarrant M, 2002, SOC DEV, V11, P110, DOI 10.1111/1467-9507.00189; VELICER WF, 1976, PSYCHOMETRIKA, V41, P321, DOI 10.1007/BF02293557; Weiss R. S., 1973, LONELINESS EXPERIENC	34	0	0	27	27	PERGAMON-ELSEVIER SCIENCE LTD	OXFORD	THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND	0747-5632	1873-7692		COMPUT HUM BEHAV	Comput. Hum. Behav.	JUN	2017	71						1	10		10.1016/j.chb.2017.01.037		10	Psychology, Multidisciplinary; Psychology, Experimental	Psychology	ES4NC	WOS:000399511000001		No			2017-07-02	
J	Micholia, P; Karaliopoulos, M; Koutsopoulos, I; Aiello, LM; Morales, GDF; Quercia, D				Micholia, Panagiota; Karaliopoulos, Merkouris; Koutsopoulos, Iordanis; Aiello, Luca Maria; Morales, Gianmarco De Francisci; Quercia, Daniele			Incentivizing social media users for mobile crowdsourcing	INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES			English	Article						Mobile crowdsourcing; Flickr; Incentives	TASKS	We focus on the problem of contributor-task matching in mobile crowd-sourcing. The idea is to identify existing social media users who possess domain expertise (e.g., photography) and incentivize them to perform some tasks (e.g., take quality pictures). To this end, we propose a framework that extracts the potential contributors' expertise based on their social media activity and determines incentives for them within the constraint of a budget. This framework does so by preferentially targeting contributors who are likely to offer quality content. We evaluate our framework on Flickr data for the entire city of Barcelona and show that it ensures high levels of task quality and wide geographic coverage, all without compromising fairness.	[Micholia, Panagiota; Karaliopoulos, Merkouris; Koutsopoulos, Iordanis] Univ Econ & Business, 76 Patiss Str, GR-10434 Athens, Greece; [Morales, Gianmarco De Francisci] Qatar Comp Res Inst, Tornado Tower,18th Floor, Doha, Qatar; [Aiello, Luca Maria; Quercia, Daniele] Nokia Bell Labs, Broers Bldg,21 JJ Thomson Ave, Cambridge CB30FA, England	Micholia, P (reprint author), Univ Econ & Business, 76 Patiss Str, GR-10434 Athens, Greece.	panamixo@aueb.gr; mkaralio@aueb.gr; jordan@aueb.gr; luca.aiello@nokia.com; gdfm@acm.org; quercia@cantab.net			European Commission [688768]	P. Micholia, M. Karaliopoulos and I. Koutsopoulos acknowledge the support of the European Commission through the Horizon 2020 project netCommons (Contract number 688768, duration 2016-2018).	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JUN	2017	102						4	13		10.1016/j.ijhcs.2016.09.007		10	Computer Science, Cybernetics; Ergonomics; Psychology, Multidisciplinary	Computer Science; Engineering; Psychology	ES4PU	WOS:000399518000002		No			2017-07-02	
J	Huang, Y; White, C; Xia, H; Wang, Y				Huang, Yun; White, Corey; Xia, Huichuan; Wang, Yang			A computational cognitive modeling approach to understand and design mobile crowdsourcing for campus safety reporting	INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES			English	Article						Mobile crowdsourcing; Cognitive computational method; Public safety; User contribution; Drift-diffusion decision model; Nudge mechanism	DIFFUSION-MODEL; CRIME; BYSTANDER; DECISIONS; SEX	The under-reporting of public safety incidents is a long-standing issue. In this paper, we propose a computational cognitive modeling approach to understand and design a mobile crowdsourcing system for improving campus safety reporting. In particular, we adopt drift-diffusion models (DDMs) from cognitive psychology to investigate the effect of various factors on users' reporting tendency for public safety. Our lab experiment and online study show consistent results on how location context impacts people's reporting decisions. This finding informs the design of a novel location-based nudge mechanism, which is tested in another lab experiment with 84 participants and proved to be effective in changing users' reporting decisions. Our follow-up interview study further suggests that the influence of people's mobility patterns (e.g., expected walking distance) could explain why the nudge design is effective. Our work not only informs the design of mobile crowdsourcing for public safety reporting but also demonstrates the value of applying a computational cognitive modeling approach to address HCI research questions more broadly.	[Huang, Yun; Xia, Huichuan; Wang, Yang] Syracuse Univ, Sch Informat Studies, Syracuse, NY 13244 USA; [White, Corey] Syracuse Univ, Dept Psychol, Syracuse, NY 13244 USA	Huang, Y (reprint author), Syracuse Univ, Sch Informat Studies, Syracuse, NY 13244 USA.	yhuang@syr.edu; cnwhite@syr.edu; hxia@syr.edu; ywang@syr.edu			National Science Foundation [1464312]	We thank our participants for sharing their insights. This material is based upon work supported by the National Science Foundation under Grant no. 1464312. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.	Ackerman M. 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Sahami, 2014, P SIGCHI C HUM FACT, P3055; Singer S., 1998, J QUANT CRIMINAL; SKOGAN WG, 1984, J RES CRIME DELINQ, V21, P113, DOI 10.1177/0022427884021002003; Sun R, 2008, CAMB HANDB PSYCHOL, P3; Tan E., 2015, ICONFERENCE MAR; Thaler R. H., 2008, NUDGE IMPROVING DECI; Thompson D., 2007, J AM COLL HLTH; Tilak S., 2013, ISRN SENS NETW; Tompson L, 2015, CARTOGR GEOGR INF SC, V42, P97, DOI 10.1080/15230406.2014.972456; U.S. Department of Education, 1992, J CLER DISCL CAMP SE; Wang Y., 2016, P PRIV ENHANC TECHNO, V2016, P172; White CN, 2014, J EXP PSYCHOL LEARN, V40, P385, DOI 10.1037/a0034851; Wilcox P., 2007, CRIME DELINQ; Woolnough AD, 2009, SECUR J, V22, P40, DOI 10.1057/sj.2008.11; Xie M, 2012, J QUANT CRIMINOL, V28, P265, DOI 10.1007/s10940-011-9140-z; Zimmerman J., 2011, P 2011 ANN C HUM FAC, P1677	80	0	0	6	6	ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD	LONDON	24-28 OVAL RD, LONDON NW1 7DX, ENGLAND	1071-5819	1095-9300		INT J HUM-COMPUT ST	Int. J. Hum.-Comput. Stud.	JUN	2017	102						27	40		10.1016/j.ijhcs.2016.11.003		14	Computer Science, Cybernetics; Ergonomics; Psychology, Multidisciplinary	Computer Science; Engineering; Psychology	ES4PU	WOS:000399518000004		No			2017-07-02	
J	Sasao, T; Konomi, S; Kostakos, V; Kuribayashi, K; Goncalves, J				Sasao, Tomoyo; Konomi, Shin'ichi; Kostakos, Vassilis; Kuribayashi, Keisuke; Goncalves, Jorge			Community Reminder: Participatory contextual reminder environments for local communities	INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES			English	Article						Mobile crowdsourcing; Community; Context awareness; Reminder; Participation	DESIGN	Many projects have looked at how communities can co-design shared online repositories, such as Wikimapia and Wikipedia. However, little work has examined how local communities can give advice and support to their members by creating context-aware reminders that may include advice, tips and small requests. We developed the Community Reminder environment, a smartphone-based platform that supports community members to design and use context-aware reminders. We have conducted a one month field study of Community Reminder to crowdsource and deliver safety-relevant information in a local community. The results show the benefits of involving community members in reminder design and connecting different perspectives. We also show that the proposed approach can broaden participation in local communities. (C) 2017 Elsevier Ltd. All rights reserved.	[Sasao, Tomoyo; Kuribayashi, Keisuke] Univ Tokyo, Grad Sch Frontier Sci, Tokyo, Japan; [Konomi, Shin'ichi] Univ Tokyo, Ctr Spatial Informat Sci, Tokyo, Japan; [Kostakos, Vassilis; Goncalves, Jorge] Univ Oulu, Ctr Ubiquitous Comp, Oulu, Finland	Sasao, T (reprint author), Univ Tokyo, Grad Sch Frontier Sci, Tokyo, Japan.				MEXT; JSPS KAKENHI [15J08542]; SS Avenue, Inc.; Academy of Finland [276786-AWARE, 285062-iCYCLE, 286386-CPDSS, 285459-iSCIENCE]; European Commission [PCIG11-GA-2012-322138, 645706-GRAGE, 6AIKA-A71143-AKAI]	We thank all the participants who contributed to the study. This work is partially supported by MEXT under the Green Network of Excellence (GRENE) program, JSPS KAKENHI Grant No. 15J08542, and SS Avenue, Inc. under the joint research program on crowdsourcing tools for coping with crimes and disasters using spatial information. This work is also partially funded by the Academy of Finland (Grants 276786-AWARE, 285062-iCYCLE, 286386-CPDSS, 285459-iSCIENCE), and the European Commission (Grants PCIG11-GA-2012-322138, 645706-GRAGE, and 6AIKA-A71143-AKAI). The work only reflects the authors' views.	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JUN	2017	102						41	53		10.1016/j.ijhcs.2016.09.001		13	Computer Science, Cybernetics; Ergonomics; Psychology, Multidisciplinary	Computer Science; Engineering; Psychology	ES4PU	WOS:000399518000005		No			2017-07-02	
J	Niforatos, E; Vourvopoulos, A; Langheinrich, M				Niforatos, Evangelos; Vourvopoulos, Athanasios; Langheinrich, Marc			Understanding the potential of human-machine crowdsourcing for weather data	INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES			English	Article						Sensor networks; Smart cities; Crowdsourcing; Mobile sensing		Reliable weather estimation traditionally requires a dense network of meteorological measurement stations. The concept of participatory sensing promises to alleviate this requirement by crowdsourcing weather data from an ideally very large set of participating users instead. Participation may involve nothing more than downloading a corresponding app to enable the collection of such data, given that modern smartphones contain a plethora of weather-related sensors. To understand the potential of participatory sensing for weather estimation, and how humans can be put "in the loop" to further improve such sensing, we created Atmos - a crowdsourcing weather app that not only periodically samples smartphones' sensors for weather measurements, but also allows users to enter their own estimates of both current and future weather conditions. We present the results of a 32-month public deployment of Atmos on the Google Play Store, showing that a combination of both types of "sensing" results in accurate temperature estimates, featuring an average error rate of 2.7 degrees C, whereas when using only user inputs, the average error rate drops to 1.86 degrees C.	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Proceedings: LNCS 9671, P567, DOI 10.1007/978-3-319-38791-8_50; Niforatos Evangelos, 2012, Journal of Location Based Services, V6, P234, DOI 10.1080/17489725.2012.691671; Niforatos E., 2014, UBICOMP 14 ADJUNCT, P135; Niforatos E., 2015, P 4 ACM INT S PERV D; Niforatos E., 2015, P 14 INT C MOB UB MU, P152; Niforatos E., 2015, P 2015 ACM INT S WEA, P775; Overeem A, 2013, GEOPHYS RES LETT, V40, P4081, DOI 10.1002/grl.50786; Rachuri KK, 2013, INT CONF PERVAS COMP, P85, DOI 10.1109/PerCom.2013.6526718; Schweizer I., 2011, P 2 INT WORKSH SENS, P1; Shoemaker G., 2007, P 20 ANN ACM S US IN, P53, DOI DOI 10.1145/1294211.1294221; Whittle J, 2010, UBICOMP 2010: PROCEEDINGS OF THE 2010 ACM CONFERENCE ON UBIQUITOUS COMPUTING, P41; Zarko I. Podnar, 2013, P 2013 ACM C PERV UB, P1099, DOI DOI 10.1145/2494091.2499577	53	0	0	4	4	ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD	LONDON	24-28 OVAL RD, LONDON NW1 7DX, ENGLAND	1071-5819	1095-9300		INT J HUM-COMPUT ST	Int. J. Hum.-Comput. Stud.	JUN	2017	102						54	68		10.1016/j.ijhcs.2016.10.002		15	Computer Science, Cybernetics; Ergonomics; Psychology, Multidisciplinary	Computer Science; Engineering; Psychology	ES4PU	WOS:000399518000006		No			2017-07-02	
J	Huang, Y; Shema, A; Xia, HC				Huang, Yun; Shema, Alain; Xia, Huichuan			A proposed genome of mobile and situated crowdsourcing and its design implications for encouraging contributions	INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES			English	Article						Survey; Mobile crowdsourcing; Situated crowdsourcing; Genome; Design suggestions		A number of papers have surveyed mobile crowdsourcing systems and, to a lesser extent, situated crowdsourcing systems. These surveys have either contributed a comprehensive taxonomy of the diverse application domains where the systems have tapped into or have characterized different components of the system platforms. In this paper, we present a survey of mobile and situated crowdsourcing systems by addressing fundamental questions about user contributions that system designers pose when building new systems or evaluating existing ones. We select and analyze 40 mobile and situated crowdsourcing systems for which prototypes were deployed and studied in the real world. Inspired by the MIT's genetic model of collective intelligence, we propose our genetic model and new genes for mobile and situated crowdsourcing systems by examining user contributions to the selected systems. We present the observed patterns of different genes and discuss how the model can be used to create new applications and design ideas. By reviewing the existing design principles of online communities, we also provide examples to illustrate how unique genes inspire new design suggestions for encouraging user contributions in the context of mobile and situated crowdsourcing.	[Huang, Yun; Shema, Alain; Xia, Huichuan] Syracuse Univ, Sch Informat Studies, Syracuse, NY 13244 USA	Huang, Y (reprint author), Syracuse Univ, Sch Informat Studies, Syracuse, NY 13244 USA.	yhuang@syr.edu; sralain@syr.edu; hxia@syr.edu			National Science Foundation [1464312]; Google Faculty Research Award	This material is based upon work supported by the National Science Foundation under Grant No.#1464312. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. We also thank the support from a Google Faculty Research Award.	Airbnb, 2015, VAC RENT HOM AP ROOM; AMABILE TM, 1976, J PERS SOC PSYCHOL, V34, P92, DOI 10.1037//0022-3514.34.1.92; Arvedson L.A., 1975, THESIS; BANERJEE AV, 1992, Q J ECON, V107, P797, DOI 10.2307/2118364; Beach Aaron, 2008, NETWORK IEEE, V22, P50; Bigham J. 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JUN	2017	102						69	80		10.1016/j.ijhcs.2016.08.004		12	Computer Science, Cybernetics; Ergonomics; Psychology, Multidisciplinary	Computer Science; Engineering; Psychology	ES4PU	WOS:000399518000007		No			2017-07-02	
J	Chang, YJ; Paruthi, G; Wu, HY; Lin, HY; Newman, MW				Chang, Yung-Ju; Paruthi, Gaurav; Wu, Hsin-Ying; Lin, Hsin-Yu; Newman, Mark W.			An investigation of using mobile and situated crowdsourcing to collect annotated travel activity data in real-word settings	INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES			English	Article						Mobile crowdsourcing; Crowdsensing; Wearable camera; Annotated activity data collection; Travel activity	DAY RECONSTRUCTION METHOD; WEARABLE CAMERAS; TIME-USE; PHONE; EXPERIENCE; GPS; VALIDITY	Collecting annotated activity data is vital to many forms of context-aware system development. Leveraging a crowd of smartphone users to collect annotated activity data in the wild is a promising direction because the data being collected are realistic and diverse. However, current research lacks a systematic analysis comparing different approaches for collecting such data and investigating how users use these approaches to collect activity data in real world settings. In this paper, we report results from a field study investigating the use of mobile crowdsourcing to collect annotated travel activity data through three approaches: Participatory, Context Triggered In Situ, and Context-Triggered Post Hoc. In particular, we conducted two phases of analysis. In Phase One, we analyzed and compared the resulting data collected via the three approaches and user experience. In Phase Two, we analyzed users' recording and annotation behavior as well as the annotation content in using each approach in the field. Our results suggested that although Context-Triggered approaches produced a larger number of recordings, they did not necessarily lead to a larger quantity of data than the Participatory approach. It was because many of the recordings were either not labeled, incomplete, and/or fragmented due to the imperfect context detection. In addition, recordings collected by the Participatory approach tended to be more complete and contain less noise. In terms of user experience, while users appreciated automated recording and reminders because of their convenience, they highly valued having the control over what and when to record and annotate that the Participatory approach provided. Finally, we showed that activity type (Driver, Riding as Passenger, Walking) influenced users' behaviors in recording and annotating their activity data. It influenced the timing of recording and annotating using the Participatory approach, users' receptivity using the Context-Triggered In Situ approach, and the characteristics of the content of annotations. Based on these findings, we provide design and methodological recommendations for future work that aims to leverage mobile crowdsourcing to collect annotated activity data.	[Chang, Yung-Ju; Paruthi, Gaurav; Wu, Hsin-Ying; Lin, Hsin-Yu; Newman, Mark W.] Univ Michigan, Sch Informat, Ann Arbor, MI 48109 USA; [Chang, Yung-Ju] Natl Chiao Tung Univ, Dept Comp Sci, Hsingchu City, Taiwan	Chang, YJ (reprint author), Natl Chiao Tung Univ, Dept Comp Sci, Hsingchu City, Taiwan.	armuro@cs.nctu.edu.tw; gparuthi@umich.edu; hsinying@umich.edu; hyclin@umich.edu; mwnewman@umich.edu			NSF award [IIS-1149601]; University of Michigan M-Cubed program [349]	This work was funded in part by NSF award IIS-1149601 and the University of Michigan M-Cubed program, Project ID: 349.	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Sahami, 2014, P SIGCHI C HUM FACT, P3055; Silvertown J, 2009, TRENDS ECOL EVOL, V24, P467, DOI 10.1016/j.tree.2009.03.017; Sonnenberg B, 2012, SOC SCI RES, V41, P1037, DOI 10.1016/j.ssresearch.2012.03.013; Turner L.D., 2015, INTERRUPTIBILITY PRE; Vondrick C, 2013, INT J COMPUT VISION, V101, P184, DOI 10.1007/s11263-012-0564-1	69	0	0	3	3	ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD	LONDON	24-28 OVAL RD, LONDON NW1 7DX, ENGLAND	1071-5819	1095-9300		INT J HUM-COMPUT ST	Int. J. Hum.-Comput. Stud.	JUN	2017	102						81	102		10.1016/j.ijhcs.2016.11.001		22	Computer Science, Cybernetics; Ergonomics; Psychology, Multidisciplinary	Computer Science; Engineering; Psychology	ES4PU	WOS:000399518000008		No			2017-07-02	
J	Ludwig, T; Kotthaus, C; Reuter, C; van Dongen, S; Pipek, V				Ludwig, Thomas; Kotthaus, Christoph; Reuter, Christian; van Dongen, Soren; Pipek, Volkmar			Situated crowdsourcing during disasters: Managing the tasks of spontaneous volunteers through public displays	INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES			English	Article						Crisis management; Situated crowdsourcing; Spontaneous volunteers; Disasters; Design case study	RESILIENCE; MEDIA	Although emergency services have already recognized the importance of citizen-initiated activities during disasters, still questions with regard to the coordination of spontaneous volunteers and their activities arise. Within our article, we will present a technological approach based on public displays which aims to foster situated crowdsourcing between affected citizens, spontaneous volunteers as well as official emergency services. We will address the research question: How can the situated tasks performed by spontaneous volunteers be supported by the use of public displays during disasters? First we will present the current state of the art with regard to the coordination practices of spontaneous volunteers and emergency services within disaster situations as well as related problems, potentials and specifics of situated crowdsourcing and public displays. To gain insight into actual coordination practices, we conducted an empirical study with 18 different stakeholders involved in disaster management. Based on the literature review and our empirical study, we have derived a technical concept that supports the task and activity management of spontaneous volunteers as well as the coordination both of the demands of affected people and the offers from spontaneous volunteers. We have implemented our concept as the public display application 'City-Share', which provides a robust communication infrastructure and encompasses situated crowdsourcing mechanisms for managing offers and demands of activities on the -ground. Based on its evaluation with several users, we will discuss our findings with regard to the assignment of tasks on-the-ground and situated crowdsourcing during emergencies. We outline that City-Share can improve a community's disaster resilience, especially when focusing on the kind of collaborative resilience emerging between official stakeholders and spontaneous volunteers or affected citizens at a local level. (C) 2017 Elsevier Ltd. All rights reserved.	[Ludwig, Thomas; Kotthaus, Christoph; Reuter, Christian; van Dongen, Soren; Pipek, Volkmar] Univ Siegen, Inst Informat Syst, Siegen, Germany	Ludwig, T (reprint author), Univ Siegen, Inst Informat Syst, Siegen, Germany.	thomas.ludwig@uni-siegen.de			German Federal Ministry for Education and Research [13N13559]	The research project 'KOKOS' is funded by the German Federal Ministry for Education and Research (No. 13N13559).	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J	Deng, WH; Hu, JN; Zhang, NH; Chen, BH; Guo, J				Deng, Weihong; Hu, Jiani; Zhang, Nanhai; Chen, Binghui; Guo, Jun			Fine-grained face verification: FGLFW database, baselines, and human-DCMN partnership	PATTERN RECOGNITION			English	Article						Fine-grained visual recognition; Face verification; Labeled face in the wild; Deep learning	RECOGNITION	As performance on some aspects of the Labeled Faces in the Wild (LFW) benchmark approaches 100% accuracy, there is an intense debate on whether unconstrained face verification problem has already been solved. In this paper, we study a new face verification problem that assumes the imposter would deliberately seek a people with similarly-looking face to invade the biometric system. To simulate this deliberate imposture attack, we first construct a Fine-Grained LFW (FGLFW) database, which deliberately selects 3000 similarly-looking face pairs within original image folders by human crowdsourcing to replace the negative pairs of LFW. Our controlled human survey reports 99.85% accuracy on LFW, but only 92.03% accuracy on FGLFW. As the algorithm baselines, we evaluate several state-of-the-art metric learning, face descriptors, and deep learning methods on the new FGLFW database, and their accuracy drops about 10-20% compared to the corresponding LFW performance. To address this challenge, we develop a Deep Convolutional Maxout Network (DCMN) which aim to tolerate the multi-modal intra-personal variations and distinguish fine-grained localized inter-personal facial details. The experimental results suggest that the proposed DCMN method significantly outperforms current techniques such as Deepface, DeepID2, and VGG-Face. Fusion of the scores of our proposed DCMN to that of human operators notably boost the verification accuracy from 92-96%, suggesting that human algorithm partnerships are promising to detect the similarly-looking deliberate impostors.	[Deng, Weihong; Hu, Jiani; Zhang, Nanhai; Chen, Binghui; Guo, Jun] Beijing Univ Posts & Telecommun, Sch Informat & Commun Engn, Beijing 100876, Peoples R China	Deng, WH (reprint author), Beijing Univ Posts & Telecommun, Sch Informat & Commun Engn, Beijing 100876, Peoples R China.	whdeng@bupt.edu.cn			NSFC (National Natural Science Foundation of China) [61375031, 61573068, 61471048, 61273217]; Fundamental Research Funds for the Central Universities [2014ZD03-01]; Program for New Century Excellent Talents in University; Beijing Nova Program [Z161100004916088]	This work was partially sponsored by supported by the NSFC (National Natural Science Foundation of China) under Grant nos. 61375031, 61573068, 61471048, and 61273217, the Fundamental Research Funds for the Central Universities under Grant no. 2014ZD03-01, This work was also supported by the Program for New Century Excellent Talents in University, Beijing Nova Program under Grant no. Z161100004916088.	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JUN	2017	66				SI		63	73		10.1016/j.patcog.2016.11.023		11	Computer Science, Artificial Intelligence; Engineering, Electrical & Electronic	Computer Science; Engineering	EP4TC	WOS:000397371800008		No			2017-07-02	
J	Lu, JF; Tang, CB; Li, X; Wu, Q				Lu, Jianfeng; Tang, Changbing; Li, Xiang; Wu, Qian			Designing Socially-Optimal Rating Protocols for Crowdsourcing Contest Dilemma	IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY			English	Article						Crowdsourcing contest dilemma; incentive mechanism; rating protocol; social optimum; game theory	INDIRECT RECIPROCITY; COOPERATION; NETWORKS; ENFORCEMENT; MANETS; GAME	Despite the increasing popularity and the perceived promise of crowdsourcing, its openness presents individuals with an opportunity to exhibit antisocial behavior, such as free-ride and attack to decrease the social welfare, which is considered as a crowdsourcing contest dilemma. Hence, incentive mechanisms are needed to compel rational and selfish individuals to contribute well behavior in tasks. In this paper, we integrate the pricing and reputation schemes to design a novel socially optimal rating protocol based on game theory, in which each player is tagged with a rating to represent its social status, and players are encouraged to contribute good behaviors to increase their ratings, thus receive higher rewards. In particular, we analyze how the players' behaviors are influenced by the incurred costs and the designed payment, as well as their long-term utilities. By quantifying the sufficient and necessary conditions under which all players comply with the social norm in their self-interests, we formulate the rating protocol design problem, and analyze the impacts of the design parameters in order to characterize the optimal design, that maximizes the social welfare to achieve the social optimum. Finally, illustrative results show the validity and effectiveness of our proposed protocol design for crowdsourcing contest dilemma.	[Lu, Jianfeng; Tang, Changbing; Wu, Qian] Zhejiang Normal Univ, Dept Comp Sci & Engn, Jinhua 321004, Peoples R China; [Li, Xiang] Fudan Univ, Dept Elect Engn, Adapt Networks & Control Lab, Shanghai 200433, Peoples R China; [Li, Xiang] Fudan Univ, Sch Informat Sci & Engn, Ctr Smart Networks & Syst, Shanghai 200433, Peoples R China	Lu, JF (reprint author), Zhejiang Normal Univ, Dept Comp Sci & Engn, Jinhua 321004, Peoples R China.	lujianfeng@zjnu.edu.cn; tangcb@zjnu.edu.cn; lix@fudan.edu.cn; wxq_TS@163.com			National Natural Science Foundation of China [61402418, 61503342, 61401399, 61672468, 61602418]; National Science Fund for Distinguished Young Scholar of China [614250192]; Social Development Project of Zhejiang provincial public Technology Research [2017C33054]; Ministry of Education in China Project of Humanity and Social Science [12YJCZH142]; Zhejiang Provincial Natural Science Foundation of China [LY16F030002]	This work was supported in part by the National Natural Science Foundation of China under Grant 61402418, Grant 61503342, Grant 61401399, Grant 61672468, and Grant 61602418, in part by the National Science Fund for Distinguished Young Scholar of China under Grant 614250192, in part by the Social Development Project of Zhejiang provincial public Technology Research under Grant 2017C33054, in part by the Ministry of Education in China Project of Humanity and Social Science under Grant 12YJCZH142, and in part by the Zhejiang Provincial Natural Science Foundation of China under Grant LY16F030002. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Walid Saad.	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Inf. Forensic Secur.	JUN	2017	12	6					1330	1344		10.1109/TIFS.2017.2656468		15	Computer Science, Theory & Methods; Engineering, Electrical & Electronic	Computer Science; Engineering	EN5YH	WOS:000396081200007		No			2017-07-02	
J	Bremner, PA; Celiktutan, O; Gunes, H				Bremner, Paul Adam; Celiktutan, Oya; Gunes, Hatice			Personality Perception of robot avatar Teleoperators in solo and Dyadic Tasks	FRONTIERS IN ROBOTICS AND AI			English	Article						telepresence; Big Five personality traits; personality perception	ACCURACY; BIG-5; ACQUAINTANCE; IMPRESSIONS; APPEARANCE; JUDGMENTS; BEHAVIOR; TRAITS	Humanoid robot avatars are a potential new telecommunication tool, whereby a user is remotely represented by a robot that replicates their arm, head, and possible face movements. They have been shown to have a number of benefits over more traditional media such as phones or video calls. However, using a teleoperated humanoid as a communication medium inherently changes the appearance of the operator, and appearance-based stereotypes are used in interpersonal judgments (whether consciously or unconsciously). One such judgment that plays a key role in how people interact is personality. Hence, we have been motivated to investigate if and how using a robot avatar alters the perceived personality of teleoperators. To do so, we carried out two studies where participants performed 3 communication tasks, solo in study one and dyadic in study two, and were recorded on video both with and without robot mediation. Judges recruited using online crowdsourcing services then made personality judgments of the participants in the video clips. We observed that judges were able to make internally consistent trait judgments in both communication conditions. However, judge agreement was affected by robot mediation, although which traits were affected was highly task dependent. Our most important finding was that in dyadic tasks personality trait perception was shifted to incorporate cues relating to the robot's appearance when it was used to communicate. Our findings have important implications for telepresence robot design and personality expression in autonomous robots.	[Bremner, Paul Adam] Univ West England, Bristol Robot Lab, Bristol, England; [Celiktutan, Oya; Gunes, Hatice] Univ Cambridge, Comp Lab, Cambridge, England	Bremner, PA (reprint author), Univ West England, Bristol Robot Lab, Bristol, England.	paul.bremner@brl.ac.uk			EPSRC under IDEAS Factory Sandpits [EP/L00416X/1]	This work was funded by the EPSRC under its IDEAS Factory Sandpits call on Digital Personhood (Grant Ref: EP/L00416X/1).	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Robot. AI	MAY 23	2017	4								16	10.3389/frobt.2017.00016		16	Robotics	Robotics	EW7IQ	WOS:000402683400001		gold			2017-07-02	
J	Zhao, R; Sun, JB; Zhang, XX; Wu, HJ; Liu, P; Yang, XJ; Qin, W				Zhao, Rui; Sun, Jinbo; Zhang, Xinxin; Wu, Huanju; Liu, Peng; Yang, Xuejuan; Qin, Wei			Sleep spindle detection based on non-experts: A validation study	PLOS ONE			English	Article							ARTIFICIAL NEURAL-NETWORKS; PARKINSONS-DISEASE; HEALTHY-SUBJECTS; EEG; DENSITY; MEMORY; FINGERPRINT; PERFORMANCE; INCREASES; DISORDER	Accurate and efficient detection of sleep spindles is a methodological challenge. The present study describes a method of using non-experts for manual detection of sleep spindles. We recruited five experts and 168 non-experts to manually identify spindles in stage N2 and stage N3 sleep data using a MATLAB interface. Scorers classified each spindle into definite and indefinite spindle (with weights of 1 and 0.5, respectively). First, a method of optimizing the thresholds of the expert/non-expert group consensus according to the results of experts and non-experts themselves is described. Using this method, we established expert and non-expert group standards from expert and non-expert scorers, respectively, and evaluated the performance of the non-expert group standards by compared with the expert group standard (termed EGS). The results indicated that the highest performance was the nonexpert group standard when definite spindles were only considered (termed nEGS-1; F1 score = 0.78 for N2; 0.68 for N3). Second, four automatic spindle detection methods were compared with the EGS. We found that the performance of nEGS-1 versus EGS was higher than that of the four automated methods. Our results also showed positive correlation between the mean F1 score of individual expert in EGS and the F1 score of nEGS-1 versus EGS across 30 segments of stage N2 data (r = 0.61, P < 0.001). Further, we found that six and nine non-experts were needed to manually identify spindles in stages N2 and N3, respectively, while maintaining acceptable performance of nEGS-1 versus EGS (F1 score = 0.79 for N2; 0.64 for N3). In conclusion, this study establishes a detailed process for detection of sleep spindles by non-experts in a crowdsourcing scheme.	[Zhao, Rui; Sun, Jinbo; Zhang, Xinxin; Wu, Huanju; Liu, Peng; Yang, Xuejuan; Qin, Wei] Xidian Univ, Sch Life Sci & Technol, Sleep & Neuroimage Grp, Xian, Shaanxi, Peoples R China	Qin, W (reprint author), Xidian Univ, Sch Life Sci & Technol, Sleep & Neuroimage Grp, Xian, Shaanxi, Peoples R China.	wqin@xidian.edu.cn			National Basic Research Program of China [2015CB856403, 2014CB543203, 2012CB518501]; National Natural Science Foundation of China [81271644, 81471811, 81471738, 61401346]; Fundamental Research Funds for the Central Universities	This study was financially supported by National Basic Research Program of China under Grant Nos. 2015CB856403, 2014CB543203 and 2012CB518501; the National Natural Science Foundation of China under Grant Nos. 81271644, 81471811, 81471738 and 61401346; and the Fundamental Research Funds for the Central Universities. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.	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J	Laaksonen, M; Sajanti, E; Sormunen, JJ; Penttinen, R; Hanninen, J; Ruohomaki, K; Saaksjarvi, I; Vesterinen, EJ; Vuorinen, I; Hytonen, J; Klemola, T				Laaksonen, Maija; Sajanti, Eeva; Sormunen, Jani J.; Penttinen, Ritva; Hanninen, Jari; Ruohomaki, Kai; Saaksjarvi, Ilari; Vesterinen, Eero J.; Vuorinen, Ilppo; Hytonen, Jukka; Klemola, Tero			Crowdsourcing-based nationwide tick collection reveals the distribution of Ixodes ricinus and I. persulcatus and associated pathogens in Finland	EMERGING MICROBES & INFECTIONS			English	Article						Borrelia burgdorferi; Borrelia miyamotoi; crowdsourcing; distribution; Ixodes persulcatus; Ixodes ricinus; tick-borne encephalitis virus; tick-borne pathogens	BORNE ENCEPHALITIS-VIRUS; BURGDORFERI SENSU-LATO; GEOGRAPHICAL-DISTRIBUTION; LYME BORRELIOSIS; CLIMATE-CHANGE; PREVALENCE; RUSSIA; EUROPE; SWEDEN; POPULATION	A national crowdsourcing-based tick collection campaign was organized in 2015 with the objective of producing novel data on tick distribution and tick-borne pathogens in Finland. Nearly 20 000 Ixodes ticks were collected. The collected material revealed the nationwide distribution of I. persulcatus for the first time and a shift northwards in the distribution of I. ricinus in Finland. A subset of 2038 tick samples containing both species was screened for Borrelia burgdorferi sensu lato (the prevalence was 14.2% for I. ricinus and 19.8% for I. persulcatus), B. miyamotoi (0.2% and 0.4%, respectively) and tick-borne encephalitis virus (TBEV; 0.2% and 3.0%, respectively). We also report new risk areas for TBEV in Finland and, for the first time, the presence of B. miyamotoi in ticks from mainland Finland. Most importantly, our study demonstrates the overwhelming power of citizen science in accomplishing a collection effort that would have been impossible with the scientific community alone.	[Laaksonen, Maija; Sormunen, Jani J.; Ruohomaki, Kai; Klemola, Tero] Univ Turku, Dept Biol, FI-20014 Turku, Finland; [Sajanti, Eeva; Hytonen, Jukka] Univ Turku, Dept Med Microbiol & Immunol, FI-20520 Turku, Finland; [Sormunen, Jani J.; Hanninen, Jari; Vuorinen, Ilppo] Univ Turku, Archipelago Res Inst, Biodivers Unit, FI-20014 Turku, Finland; [Penttinen, Ritva; Saaksjarvi, Ilari] Univ Turku, Biodivers Unit, Zool Museum, FI-20014 Turku, Finland; [Vesterinen, Eero J.] Univ Helsinki, Dept Agr Sci, FI-00014 Helsinki, Finland	Laaksonen, M (reprint author), Univ Turku, Dept Biol, FI-20014 Turku, Finland.	maija.k.laaksonen@utu.fi	Klemola, Tero/B-9235-2014	Klemola, Tero/0000-0002-8510-329X	University of Turku; Maj and Tor Nessling Foundation; Jane and Aatos Erkko Foundation; Varsinais-Suomi Regional Fund of the Finnish Cultural Foundation; Academy of Finland; Pfizer Inc. (Finland)	We thank Jorma Nurmi (Department of Biology, University of Turku) for providing coordinates for tick distribution maps, Heidi Isokaanta (Department of Medical Microbiology and Immunology, University of Turku) for technical assistance with DNA/RNA extractions, Otto Glader (Department of Medical Microbiology and Immunology, University of Turku) for helping with the pathogen PCR runs, Julia Geller (Department of Virology, National Institute of Health Development, Tallinn, Estonia) for providing us with a positive B. miyamotoi control, and Elina Tonteri (Department of Virology, University of Helsinki, Helsinki, Finland) and Anu Jaaskelainen (Department of Virology, University of Helsinki, Helsinki, Finland) for providing TBEV strains for positive controls. This work was supported by the University of Turku, Sakari Alhopuro, Pfizer Inc. (Finland), Maj and Tor Nessling Foundation, Jane and Aatos Erkko Foundation, The Varsinais-Suomi Regional Fund of the Finnish Cultural Foundation, and the Academy of Finland.	Alekseev AN, 1998, J MED ENTOMOL, V35, P136; Balashov Yu S., 1998, Entomologicheskoe Obozrenie, V77, P713; Borgoyakov V. Yu., 2010, Parazitologiya (St. Petersburg), V44, P543; Bormane A, 2004, INT J MED MICROBIOL, V293, P36, DOI 10.1016/S1433-1128(04)80007-X; Bugmyrin SV, 2013, TICKS TICK-BORNE DIS, V4, P57, DOI 10.1016/j.ttbdis.2012.07.004; Burbaite Lina, 2009, Estonian Journal of Ecology, V58, P169, DOI 10.3176/eco.2009.3.02; Dobson ADM, 2011, J APPL ECOL, V48, P1029, DOI 10.1111/j.1365-2664.2011.02004.x; Geller J, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0051914; Gray J. 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Microbes Infect.	MAY 10	2017	6								e31	10.1038/emi.2017.17		7	Immunology; Microbiology	Immunology; Microbiology	EW1ZY	WOS:000402297000003	28487561	gold			2017-07-02	
J	Goncalves, J; Hosio, S; Kostakos, V				Goncalves, Jorge; Hosio, Simo; Kostakos, Vassilis			Eliciting Structured Knowledge from Situated Crowd Markets	ACM TRANSACTIONS ON INTERNET TECHNOLOGY			English	Article						Crowdsourcing; structured knowledge; situated; questions; options; criteria; performance; accuracy; quality; local crowds	SIMILARITY; FEATURES	We present a crowdsourcing methodology to elicit highly structured knowledge for arbitrary questions. The method elicits potential answers ("options"), criteria against which those options should be evaluated, and a ranking of the top "options." Our study shows that situated crowdsourcing markets can reliably elicit/moderate knowledge to generate a ranking of options based on different criteria that correlate with established online platforms. Our evaluation also shows that local crowds can generate knowledge that is missing from online platforms and on how a local crowd perceives a certain issue. Finally, we discuss the benefits and challenges of eliciting structured knowledge from local crowds.	[Goncalves, Jorge; Hosio, Simo; Kostakos, Vassilis] Univ Oulu, Ctr Ubiquitous Comp, Oulu, Finland; [Goncalves, Jorge; Kostakos, Vassilis] Univ Melbourne, Dept Comp & Informat Syst, Melbourne, Vic, Australia; [Goncalves, Jorge; Hosio, Simo; Kostakos, Vassilis] Erkki Koiso Kanttilan Katu 3,Door E,POB 4500, FI-90014 Oulu, Finland	Goncalves, J (reprint author), Univ Oulu, Ctr Ubiquitous Comp, Oulu, Finland.; Goncalves, J (reprint author), Univ Melbourne, Dept Comp & Informat Syst, Melbourne, Vic, Australia.; Goncalves, J (reprint author), Erkki Koiso Kanttilan Katu 3,Door E,POB 4500, FI-90014 Oulu, Finland.	jorge.goncalves@oulu.fi; simo.hosio@oulu.fi; vassilis.kostakos@oulu.fi			Academy of Finland [276786-AWARE, 285062-iCYCLE, 286386-CPDSS, 285459-iSCIENCE]; European Commission [PCIG11-GA-2012-322138, 645706-GRAGE, 6AIKA-A71143-AKAI]	This work is partially funded by the Academy of Finland (Grants 276786-AWARE, 285062-iCYCLE, 286386-CPDSS, and 285459-iSCIENCE) and the European Commission (Grants PCIG11-GA-2012-322138, 645706-GRAGE, and 6AIKA-A71143-AKAI).	American Movie Awards, 2017, JUDG CRIT; Bangor A, 2008, INT J HUM-COMPUT INT, V24, P574, DOI 10.1080/10447310802205776; Bernstein Michael S., 2010, P 23 ANN ACM S US IN, P313, DOI DOI 10.1145/1866029.1866078; Bin Guo ZhuWang, 2016, ACM COMPUT SURV, V48, P1; Brignull Harry, 2003, P INTERACT 2003, P17; Callison-Burch C., 2009, P 2009 C EMP METH NA, V1, P286, DOI 10.3115/1699510.1699548; Chen Li, 2011, USER MODEL USER-ADAP, V22, P1; Chen L, 2012, USER MODEL USER-ADAP, V22, P125, DOI 10.1007/s11257-011-9108-6; Cheng J, 2015, PROCEEDINGS OF THE 2015 ACM INTERNATIONAL CONFERENCE ON COMPUTER-SUPPORTED COOPERATIVE WORK AND SOCIAL COMPUTING (CSCW'15), P600, DOI 10.1145/2675133.2675214; Downs JS, 2010, CHI2010: PROCEEDINGS OF THE 28TH ANNUAL CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS, VOLS 1-4, P2399; Goncalves Jorge, 2016, P 19 ACM C COMP SUPP, P1040; Goncalves Jorge, 2013, P 2013 ACM INT JOINT, P753; Goncalves Jorge, 2014, P 2014 C DES INT SYS, P705; Goncalves Jorge, 2014, P 2014 ACM INT JOINT, P487; Goncalves J, 2015, COMPUT NETW, V90, P34, DOI 10.1016/j.comnet.2015.07.002; Heimerl Kurtis, 2012, P SIGCHI C HUM FACT, P1539, DOI DOI 10.1145/2207676.2208619; Horton JJ, 2011, EXP ECON, V14, P399, DOI 10.1007/s10683-011-9273-9; Hosio Simo, 2015, POLICY INTERNET, V7, P203, DOI DOI 10.1002/P0I3.90; Hosio Simo, 2016, P 2016 BRIT HCI C BR; Hosio Simo, 2014, P 27 ANN ACM S US IN, P55; Hosio S, 2014, PUB ADMIN INF TECH, V9, P91, DOI 10.1007/978-3-319-05963-1_7; Huang Yi-Ching, 2015, P 18 ACM C COMP COMP, P73; Ipeirotis Panagiotis, 2010, P ACM SIGKDD WORKSH, P64, DOI DOI 10.1145/1837885.1837906; Kittur Aniket, 2011, P 24 ANN ACM S US IN, P43; Kukka Hannu, 2013, P CHI 13, P1699; Lakhani KR, 2003, RES POLICY, V32, P923, DOI 10.1016/S0048-7333(02)00095-1; Lampe C, 2014, GOV INFORM Q, V31, P317, DOI 10.1016/j.giq.2013.11.005; Lee M. D., 2005, COGSCI2005, P1254; Trope J., 2007, SOCIAL PSYCHOL HDB B, V2, P353; Muller Jorg, 2010, P INT C MULT MM 10, P1285, DOI DOI 10.1145/1873951.1874203; Navarro DJ, 2004, PSYCHON B REV, V11, P961, DOI 10.3758/BF03196728; Navarro G, 2001, ACM COMPUT SURV, V33, P31, DOI 10.1145/375360.375365; Noronha Jon, 2011, P 24 ANN ACM S US IN, P1, DOI 10.1145/2047196.2047198; Rogers Yvonne, 2011, INTERACTION DESIGN H; Shirky Clay, 2010, PENGUIN; SWELLER J, 1988, COGNITIVE SCI, V12, P257, DOI 10.1207/s15516709cog1202_4; TVERSKY A, 1977, PSYCHOL REV, V84, P327, DOI 10.1037/0033-295X.84.4.327; von Ahn L., 2004, CHI, P319; Wu Shaomei, 2011, P 27 IEEE INT C DAT, P151	39	0	0	0	0	ASSOC COMPUTING MACHINERY	NEW YORK	2 PENN PLAZA, STE 701, NEW YORK, NY 10121-0701 USA	1533-5399	1557-6051		ACM T INTERNET TECHN	ACM Trans. Internet. Technol.	MAY	2017	17	2			SI				14	10.1145/3007900		21	Computer Science, Information Systems; Computer Science, Software Engineering	Computer Science	EX6HJ	WOS:000403343100004		No			2017-07-02	
J	He, YA; Liang, JQ; Liu, YH				He, Yuan; Liang, Jiaqi; Liu, Yunhao			Pervasive Floorplan Generation Based on Only Inertial Sensing: Feasibility, Design, and Implementation	IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS			English	Article						Mobile crowdsourcing; floorplan generation; inertial sensing		Mobile crowdsourcing is deemed as a powerful technique to solve traditional problems. But the crowdsourced data from smartphones are generally low quality, which can induce crucial challenges and hurt the applicability of crowdsourcing applications. This paper presents our study to address such challenges in a concrete application, namely, floorplan generation. Existing proposals mostly rely on infrastructural references or accurate data sources, which are restricted in terms of applicability and pervasiveness. Our proposal called SenseWit is motivated by the observation that people's behavior offers meaningful clues for location inference. The noise, ambiguity, and behavior diversity contained in the crowdsourced data, however, mean non-trivial challenges in generating high-quality floorplans. We propose: 1) a novel concept called Nail to identify featured locations in indoor space and 2) a heuristic pathlet bundling algorithm to progressively discover the internal layouts of a floorplan. We implement SenseWit and conduct real-world experiments in different spaces to demonstrate its efficacy. This paper offers an efficient technique to obtain high-quality structures (either logical or physical) from low-quality data. We believe it can be generalized to other crowdsourcing applications.	[He, Yuan; Liu, Yunhao] Tsinghua Univ, Sch Software, Beijing 100084, Peoples R China; [He, Yuan; Liu, Yunhao] Tsinghua Univ, Tsinghua Natl Lab Informat Sci & Technol, Beijing 100084, Peoples R China; [Liang, Jiaqi] China Merchants Bank, IT Dept, Shanghai 201201, Peoples R China	He, YA (reprint author), Tsinghua Univ, Sch Software, Beijing 100084, Peoples R China.; He, YA (reprint author), Tsinghua Univ, Tsinghua Natl Lab Informat Sci & Technol, Beijing 100084, Peoples R China.	heyuan@tsinghua.edu.cn; lmumu77@163.com; yunhao@tsinghua.edu.cn			National Natural Science Fund [61422207]; National Natural Science Foundation of China [61373146]	This work was supported in part by the National Natural Science Fund for Excellent Young Scientists under Grant 61422207 and in part by the National Natural Science Foundation of China under Grant 61373146.	Alzantot M, 2012, IEEE WCNC, P3204, DOI 10.1109/WCNC.2012.6214359; Anshul R., 2012, P ACM MOBICOM, P293; Azizyan M, 2009, FIFTEENTH ACM INTERNATIONAL CONFERENCE ON MOBILE COMPUTING AND NETWORKING (MOBICOM 2009), P261; Beauregard S., 2006, P 3 WORKSH POS NAV C, P27; Chen S, 2015, INT CON DISTR COMP S, P1, DOI 10.1109/ICDCS.2015.9; Chen X, 2014, IEEE INFOCOM SER, P2310, DOI 10.1109/INFOCOM.2014.6848175; Chintalapudi K, 2010, MOBICOM 10 & MOBIHOC 10: PROCEEDINGS OF THE 16TH ANNUAL INTERNATIONAL CONFERENCE ON MOBILE COMPUTING AND NETWORKING AND THE 11TH ACM INTERNATIONAL SYMPOSIUM ON MOBILE AD HOC NETWORKING AND COMPUTING, P173; de Magalhaes S. V. G., 2014, P ACM SIGSPATIAL, P613; Gao R., 2014, P 20 ANN INT C MOB C, P249; Jiang Y., 2013, P 2013 ACM INT JOINT, P315; Jiaqi L., 2016, P IEEE DCOSS MAY, P1; Li F., 2012, P 14 INT C UB COMP U, P421, DOI DOI 10.1145/2370216.2370280; Liu SY, 2013, IEEE T VEH TECHNOL, V62, P1527, DOI 10.1109/TVT.2012.2231973; Luo CW, 2014, PROCEEDINGS OF THE 13TH INTERNATIONAL SYMPOSIUM ON INFORMATION PROCESSING IN SENSOR NETWORKS (IPSN' 14), P143, DOI 10.1109/IPSN.2014.6846748; Moustafa A., 2012, P ACM SIGSPATIAL, P99; Rana R., 2010, P 9 ACM IEEE INT C I, P105, DOI 10.1145/1791212.1791226; Roy N, 2014, MOBISYS'14: PROCEEDINGS OF THE 12TH ANNUAL INTERNATIONAL CONFERENCE ON MOBILE SYSTEMS, APPLICATIONS, AND SERVICES, P329, DOI 10.1145/2594368.2594392; Santos M., 2012, P IEEE 7 COL COMP C, P1; Shen G., 2013, P 10 USENIX C NETW S, P85; Shin H, 2012, IEEE T SYST MAN CY C, V42, P889, DOI 10.1109/TSMCC.2011.2169403; Shu Y., 2015, P ACM MOBICOM, P512; Sun W, 2013, INT CON DISTR COMP S, P226, DOI 10.1109/ICDCS.2013.41; Susi M, 2013, SENSORS-BASEL, V13, P1539, DOI 10.3390/s130201539; Thrun S, 2003, AUTON ROBOT, V15, P111, DOI 10.1023/A:1025584807625; Wang H., 2012, P 10 INT C MOB SYST, P197, DOI DOI 10.1145/2307636.2307655; Yang Z, 2012, MOBICOM 12: PROCEEDINGS OF THE 18TH ANNUAL INTERNATIONAL CONFERENCE ON MOBILE COMPUTING AND NETWORKING, P269; Zhang L, 2014, IEEE INFOCOM SER, P799, DOI 10.1109/INFOCOM.2014.6848007; Zhou P., 2012, P 10 INT C MOB SYST, P379	28	0	0	0	0	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC	PISCATAWAY	445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA	0733-8716	1558-0008		IEEE J SEL AREA COMM	IEEE J. Sel. Areas Commun.	MAY	2017	35	5					1132	1140		10.1109/JSAC.2017.2679659		9	Engineering, Electrical & Electronic; Telecommunications	Engineering; Telecommunications	EW0BG	WOS:000402152400009		No			2017-07-02	
J	Sakamoto, M; Nakajima, T; Akioka, S				Sakamoto, Mizuki; Nakajima, Tatsuo; Akioka, Sayaka			Gamifying collective human behavior with gameful digital rhetoric	MULTIMEDIA TOOLS AND APPLICATIONS			English	Article						Digital rhetoric; Design framework; Social infrastructure; Collective human behavior; Social influence; Sustainable society; Gamification; Crowdsourcing	DESIGN	This paper presents a design framework called Gameful Digital Rhetoric that offers a set of design frames for designing meaningful digital rhetoric that guides collective human behavior in ubiquitous social digital services, such as crowdsourcing. The framework is extracted from our experiences with building and developing crowdsourcing case studies. From a video game perspective, the paper has categorized our experiences into seven design frames to encourage collective human activity. This approach is different from traditional gamification, as it focuses more on the semiotic aspect of virtuality in the video games, not game mechanics; it helps to enhance the current meaning of the real world for changing human attitude and behavior through various socio-cultural and psychological techniques. Therefore, it is possible to discuss respective design frames for enhancing crowdsourcing by incrementally adding new digital rhetoric. The paper also presents how Gameful Digital Rhetoric allows us to guide collective human behavior in Collectivist Crowdsourcing; the design is explained through a scenario-based and experiment-based analyses. The paper then discusses how to design collective human behavior with Gameful Digital Rhetoric and how to identify the design's potential pitfalls. Our approach offers useful insights into the design of future social digital services that influence collective human behavior.	[Sakamoto, Mizuki; Nakajima, Tatsuo] Waseda Univ, Dept Comp Sci & Engn, Shinjuku Ku, Tokyo, Japan; [Akioka, Sayaka] Meiji Univ, Dept Network Design, Tokyo, Japan	Nakajima, T (reprint author), Waseda Univ, Dept Comp Sci & Engn, Shinjuku Ku, Tokyo, Japan.	tatsuo@dcl.cs.waseda.ac.jp					Akerlof G, 1970, Q J ECON, V84, P988; Antikainen Maria J, 2010, International Journal of Entrepreneurship and Innovation Management, V11, P440, DOI 10.1504/IJEIM.2010.032267; Asif M. M., 2011, INT J HUMANITIES SOC, V1, P196; Azuma H, 2007, POSTMODERN 2 BORN AN; Bardzell J, 2013, P SIGCHI C HUM FACT; Blythe B, 2014, P INT C HUM FACT COM; Bogost Ian, 2007, PERSUASIVE GAMES EXP; Chandler D, 2013, J ECON BEHAV ORGAN, V90, P123, DOI 10.1016/j.jebo.2013.03.003; Cialdini RB, 2006, INFLUENCE PSYCHOL PE; Conrad CC, 2011, ENVIRON MONIT ASSESS, V176, P273, DOI 10.1007/s10661-010-1582-5; Csikszentmihalyi M., 2008, FLOW PSYCHOL OPTIMAL; Deci E. 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Tools Appl.	MAY	2017	76	10					12539	12581		10.1007/s11042-016-3665-y		43	Computer Science, Information Systems; Computer Science, Software Engineering; Computer Science, Theory & Methods; Engineering, Electrical & Electronic	Computer Science; Engineering	EV7DS	WOS:000401935200017		No			2017-07-02	
J	Dainty, KN; Vaid, H; Brooks, SC				Dainty, Katie N.; Vaid, Haris; Brooks, Steven C.			North American Public Opinion Survey on the Acceptability of Crowdsourcing Basic Life Support for Out-of-Hospital Cardiac Arrest With the PulsePoint Mobile Phone App	JMIR MHEALTH AND UHEALTH			English	Article						sudden cardiac death; surveys and questionnaires; cardiopulmonary resuscitation; PulsePoint; North America	AUTOMATED EXTERNAL DEFIBRILLATORS; TECHNOLOGIES; BYSTANDER; ATTITUDES; SURVIVAL; RISK	Background: The PulsePoint Respond app is a novel system that can be implemented in emergency dispatch centers to crowdsource basic life support (BLS) for patients with cardiac arrest and facilitate bystander cardiopulmonary resuscitation (CPR) and automated external defibrillator use while first responders are en route. Objective: The aim of this study was to conduct a North American survey to evaluate the public perception of the above-mentioned strategy, including acceptability and willingness to respond to alerts. Methods: We designed a Web-based survey administered by IPSOS Reid, an established external polling vendor. Sampling was designed to ensure broad representation using recent census statistics. Results: A total of 2415 survey responses were analyzed (1106 from Canada and 1309 from the United States). It was found that 98.37% (1088/1106) of Canadians and 96% (1259/1309) of Americans had no objections to PulsePoint being implemented in their community; 84.27% (932/1106) of Canadians and 55.61% (728/1309) of Americans said they would download the app to become a potential responder to cardiac arrest, respectively. Among Canadians, those who said they were likely to download PulsePoint were also more likely to have ever had CPR training (OR 1.7, 95% CI 1.2-2.4; P=.002); however, this was not true of American respondents (OR 1.0, 95% CI 0.79-1.3; P=.88). When asked to imagine themselves as a cardiac arrest victim, 95.39% (1055/1106) of Canadians and 92.44% (1210/1309) of Americans had no objections to receiving crowdsourced help in a public setting; 88.79% (982/1106) of Canadians and 84.87% (1111/1309) of Americans also had no objections to receiving help in a private setting, respectively. The most common concern identified with respect to PulsePoint implementation was a responder's lack of ability, training, or access to proper equipment in a public setting. Conclusions: The North American public finds the concept of crowdsourcing BLS for out-of-hospital cardiac arrest to be acceptable. It demonstrates willingness to respond to PulsePoint CPR notifications and to accept help from others alerted by the app if they themselves suffered a cardiac arrest.	[Dainty, Katie N.] St Michaels Hosp, Li Ka Shing Knowledge Inst, Rescu, 30 Bond St, Toronto, ON M5B 1W8, Canada; [Dainty, Katie N.] Univ Toronto, Inst Hlth Policy Management & Evaluat, Toronto, ON, Canada; [Vaid, Haris] Queens Univ, Sch Med, Kingston, ON, Canada; [Brooks, Steven C.] Queens Univ, Dept Emergency Med, Kingston, ON, Canada	Dainty, KN (reprint author), St Michaels Hosp, Li Ka Shing Knowledge Inst, Rescu, 30 Bond St, Toronto, ON M5B 1W8, Canada.	daintyk@smh.ca			Laerdal Foundation for Acute Medicine	This research was funded through a grant from the Laerdal Foundation for Acute Medicine.	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J	Juengst, ET				Juengst, Eric T.			Crowdsourcing the Moral Limits of Human Gene Editing?	HASTINGS CENTER REPORT			English	Article								In 2015, a flourish of alarums and excursions by the scientific community propelled CRISPR/Cas9 and other new gene-editing techniques into public attention. At issue were two kinds of potential gene-editing experiments in humans: those making inheritable germ-line modifications and those designed to enhance human traits beyond what is necessary for health and healing. The scientific consensus seemed to be that while research to develop safe and effective human gene editing should continue, society's moral uncertainties about these two kinds of experiments needed to be better resolved before clinical trials of either type should be attempted.In the United States, the National Academies of Science, Engineering and Medicine (NASEM) convened the Committee on Human Gene Editing: Scientific, Medical and Ethical Considerations to pursue that resolution. The committee's 2017 consensus report has been widely interpreted as opening the door to inheritable human genetic modification and holding a line against enhancement interventions. But on a close reading it does neither. There are two reasons for this eccentric conclusion, both of which depend upon the strength of the committee's commitment to engaging diverse public voices in the gene-editing policy-making process.	[Juengst, Eric T.] Univ N Carolina, Ctr Bioeth, Chapel Hill, NC 27515 USA	Juengst, ET (reprint author), Univ N Carolina, Ctr Bioeth, Chapel Hill, NC 27515 USA.						Anderson F. W., 1972, EW GENETICS FUTURE M, P110; Dresser R, 2004, MILBANK Q, V82, P195, DOI 10.1111/j.0887-378X.2004.00306.x; Dresser Rebecca, 2004, IRB, V26, P1, DOI 10.2307/3563945; Evans C., 2004, DESIGNING OUR DESCEN, P93; HOTCHKISS RD, 1965, J HERED, V56, P197; Isgrig K, 2017, MOL THER, V25, P780, DOI 10.1016/j.ymthe.2017.01.007; Juengst E., 1998, DEMOCRACY SOCIAL VAL, P163; Juengst ET, 2003, HASTINGS CENT REP, V33, P21, DOI 10.2307/3528377; Juengst E., 2009, HUMAN ENHANCEMENT, P43; Kaebnick G. E., 2017, BIOETHICS FORUM; Kaiser J., 2017, SCIENCE; Kimmelman J., 2010, GENE TRANSFER ETHICS; Kozubek J., 2017, SCI AM BLOG     0217; Lanphier E, 2015, NATURE, V519, P410, DOI 10.1038/519410a; Lenoir N, 1999, Columbia Human Rights Law Rev, V30, P537; Mehlman M J, 1999, Wake Forest Law Rev, V34, P671; Mehlman M. J., 2009, PRICE PERFECTION IND; National Academies of Science Engineering and Medicine Committee on Human Gene Editing: Scientific Medical and Ethical Considerations, 2017, HUM GEN ED SCI MED E, P13; Niler E., 2017, WIRED MAGAZINE; Rasko J., 2006, ETHICS INHERITABLE G; Silvers, HUM RIGHTS; Silvers A, 2003, J LAW MED ETHICS, V31, P377, DOI 10.1111/j.1748-720X.2003.tb00101.x; Terry S., 2012, HLTH AFFAIRS BLOG; White G., 1994, KENNEDY INST ETHIC J, V3, P401; Whitehouse PJ, 2005, J AM GERIATR SOC, V53, P1417, DOI 10.1111/j.1532-5415.2005.53411.x; World Anti-Doping Association, 2007, WORLD ANT ASS COD 20	26	0	0	2	2	WILEY	HOBOKEN	111 RIVER ST, HOBOKEN 07030-5774, NJ USA	0093-0334	1552-146X		HASTINGS CENT REP	Hastings Cent. Rep.	MAY-JUN	2017	47	3					15	23		10.1002/hast.701		9	Ethics; Health Care Sciences & Services; Medical Ethics; Social Sciences, Biomedical	Social Sciences - Other Topics; Health Care Sciences & Services; Medical Ethics; Biomedical Social Sciences	EV8KD	WOS:000402028200006	28543411	No			2017-07-02	
J	Love, J; Hirschheim, R				Love, James; Hirschheim, Rudy			Crowdsourcing of information systems research	EUROPEAN JOURNAL OF INFORMATION SYSTEMS			English	Article						crowdsourcing; research agenda; research framework; alternative genre; information systems discipline; IS research	OPEN SOURCE SOFTWARE; KNOWLEDGE; HISTORY; SCIENCE; FIELD	This paper addresses how technology-mediated mass collaboration offers a dramatically innovative alternative for producing IS research. We refer to this emerging genre as the crowdsourced research genre and develop a framework to structure discourse on how it may affect the production of IS research. After systematically traversing the alternative genre's landscape using the framework, we propose a research agenda of the most substantial and imminent issues for the successful development of the genre, including contributor incentives, scholarly contribution assessment, anonymity, governance, intellectual property ownership, and value propositions. In addressing this research agenda, we reflect on what might be learned from other areas in which crowdsourcing has been established with success.	[Love, James] Franciscan Missionaries Our Lady Univ, Dept Healthcare Adm, 5345 Brittany Dr, Baton Rouge, LA 70808 USA; [Hirschheim, Rudy] Louisiana State Univ, Dept Informat Syst & Decis Sci, Business Educ Complex,Room 2221, Baton Rouge, LA 70803 USA	Love, J (reprint author), Franciscan Missionaries Our Lady Univ, Dept Healthcare Adm, 5345 Brittany Dr, Baton Rouge, LA 70808 USA.	James.Love@ololcollege.edu					Beath C, 2013, J ASSOC INF SYST, V14, pI; Behrend TS, 2011, BEHAV RES METHODS, V43, P800, DOI 10.3758/s13428-011-0081-0; Bhattacherjee A, 2012, SOCIAL SCI RES PRINC; Brabham DC, 2008, CONVERGENCE-US, V14, P75, DOI DOI 10.1177/1354856507084420; Brooks F.P., 1995, MYTHICAL MAN MONTH E; Bukvova H, 2009, SPROUTS WORKING PAPE, V9; Carillo K, 2008, J COMPUT INFORM SYST, V49, P1; Chen WS, 2004, INFORM SYST J, V14, P197, DOI 10.1111/j.1365-2575.2004.00173.x; Dennis A., 2001, COMMUNICATIONS, V7, P1; DENNIS AR, 1988, MIS QUART, V12, P591, DOI 10.2307/249135; Elsevier, 2015, OPEN ACCESS OPTIONS; Estelles-Arolas E, 2012, J INF SCI, V38, P189, DOI 10.1177/0165551512437638; Feller J, 2000, P 21 ANN INT C INF S; Fletcher D, 2009, TIME; GasBuddy, 2015, IT WORKS GASB GAS PR; Geiger D, 2011, AMCIS 2011 P ALL SUB; Geiger D, 2011, ACIS 2011 P; Giles J, 2005, NATURE, V438, P900, DOI 10.1038/438900a; Goes P, 2014, MIS Q, V38, piii; Hardaway DE, 2005, COMMUN ACM, V48, P125, DOI 10.1145/1076211.1076216; Hardaway DE, 2012, MIS QUART, V36, P339; Hetmank L, 2013, WIRTSCH P, V2013, P4; Hirschheim R, 2003, J ASSOC INF SYST, V4, P237; Hirschheim R, 2012, J ASSOC INF SYST, V13, P188; Hojat M, 2003, ADV HEALTH SCI EDUC, V8, P75, DOI 10.1023/A:1022670432373; Hovorka D, 2012, ICIS 2012 P; Howe J., 2009, CROWDSOURCING WHY PO; Howe J., 2006, WIRED, V14, P176; Iivari J, 2004, INFORM SYST J, V14, P313, DOI 10.1111/j.1365-2575.2004.00177.x; Iivari J, 2008, EUR J INFORM SYST, V17, P169, DOI 10.1057/ejis.2008.10; The iSchool AT Illinois, 2015, SPEC DAT CUR; Jessup L, 1988, P 1988 ANN M AC MAN; Kaganer E, 2013, SLOAN MANAGE REV, P23; Ke WL, 2010, J ASSOC INF SYST, V11, P784; Keen P. 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J. Inform. Syst.	MAY	2017	26	3					315	332		10.1057/s41303-017-0036-3		18	Computer Science, Information Systems; Information Science & Library Science	Computer Science; Information Science & Library Science	EV6HQ	WOS:000401870900008		No			2017-07-02	
J	Wang, TY; Wang, G; Wang, B; Sambasivan, D; Zhang, ZB; Li, X; Zheng, HT; Zhao, BY				Wang, Tianyi; Wang, Gang; Wang, Bolun; Sambasivan, Divya; Zhang, Zengbin; Li, Xing; Zheng, Haitao; Zhao, Ben Y.			Value and Misinformation in Collaborative Investing Platforms	ACM TRANSACTIONS ON THE WEB			English	Article						Measurement; Management; Design; Crowdsourcing; stock market; sentiment analysis		It is often difficult to separate the highly capable "experts" from the average worker in crowdsourced systems. This is especially true for challenge application domains that require extensive domain knowledge. The problem of stock analysis is one such domain, where even the highly paid, well-educated domain experts are prone to make mistakes. As an extremely challenging problem space, the "wisdom of the crowds" property that many crowdsourced applications rely on may not hold. In this article, we study the problem of evaluating and identifying experts in the context of SeekingAlpha and StockTwits, two crowdsourced investment services that have recently begun to encroach on a space dominated for decades by large investment banks. We seek to understand the quality and impact of content on collaborative investment platforms, by empirically analyzing complete datasets of SeekingAlpha articles (9 years) and StockTwits messages (4 years). We develop sentiment analysis tools and correlate contributed content to the historical performance of relevant stocks. While SeekingAlpha articles and StockTwits messages provide minimal correlation to stock performance in aggregate, a subset of experts contribute more valuable (predictive) content. We show that these authors can be easily identified by user interactions, and investments based on their analysis significantly outperform broader markets. This effectively shows that even in challenging application domains, there is a secondary or indirect wisdom of the crowds. Finally, we conduct a user survey that sheds light on users' views of SeekingAlpha content and stock manipulation. We also devote efforts to identify potential manipulation of stocks by detecting authors controlling multiple identities.	[Wang, Tianyi; Li, Xing] Tsinghua Univ, Elect Engn, Beijing, Peoples R China; [Wang, Tianyi; Wang, Gang; Wang, Bolun; Sambasivan, Divya; Zhang, Zengbin; Zheng, Haitao; Zhao, Ben Y.] Univ Calif Santa Barbara, Dept Comp Sci, Santa Barbara, CA 93106 USA; [Wang, Gang] Virginia Tech, Blacksburg, VA USA	Wang, TY (reprint author), Tsinghua Univ, Elect Engn, Beijing, Peoples R China.; Wang, TY (reprint author), Univ Calif Santa Barbara, Dept Comp Sci, Santa Barbara, CA 93106 USA.	tsinghuawty@gmail.com; gangw@cs.ucsb.edu; bolunwang@cs.ucsb.edu; divya_sambasivan@cs.ucsb.edu; zengbin@cs.ucsb.edu; xing@cernet.edu.cn; htzheng@cs.ucsb.edu; ravenben@cs.ucsb.edu			National Science Foundation [IIS-1321083, CNS-1224100]; DARPA GRAPHS program [BAA-12-01]; Department of State	This work is supported in part by the National Science Foundation under grants IIS-1321083 and CNS-1224100, by the DARPA GRAPHS program (BAA-12-01), and by the Department of State. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of any funding agencies.	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J	Xu, HT; Liu, DP; Wang, HN; Stavrou, A				Xu, Haitao; Liu, Daiping; Wang, Haining; Stavrou, Angelos			An Empirical Investigation of Ecommerce-Reputation-Escalation-as-a-Service	ACM TRANSACTIONS ON THE WEB			English	Article						Security; Measurement; Economics; Human Factors; E-commerce; reputation manipulation; fake transaction		In online markets, a store's reputation is closely tied to its profitability. Sellers' desire to quickly achieve a high reputation has fueled a profitable underground business that operates as a specialized crowdsourcing marketplace and accumulates wealth by allowing online sellers to harness human laborers to conduct fake transactions to improve their stores' reputations. We term such an underground market a seller-reputation-escalation (SRE) market. In this article, we investigate the impact of the SRE service on reputation escalation by performing in-depth measurements of the prevalence of the SRE service, the business model and market size of SRE markets, and the characteristics of sellers and offered laborers. To this end, we have infiltrated five SRE markets and studied their operations using daily data collection over a continuous period of 2 months. We identified more than 11,000 online sellers posting at least 219,165 fake-purchase tasks on the five SRE markets. These transactions earned at least $46,438 in revenue for the five SRE markets, and the total value of merchandise involved exceeded $3,452,530. Our study demonstrates that online sellers using the SRE service can increase their stores' reputations at least 10 times faster than legitimate ones while about 25% of them were visibly penalized. Even worse, we found a much stealthier and more hazardous service that can, within a single day, boost a seller's reputation by such a degree that would require a legitimate seller at least a year to accomplish. Armed with our analysis of the operational characteristics of the underground economy, we offer some insights into potential mitigation strategies. Finally, we revisit the SRE ecosystem 1 year later to evaluate the latest dynamism of the SRE markets, especially the statuses of the online stores once identified to launch fake-transaction campaigns on the SRE markets. We observe that the SRE markets are not as active as they were 1 year ago and about 17% of the involved online stores become inaccessible likely because they have been forcibly shut down by the corresponding E-commerce marketplace for conducting fake transactions.	[Xu, Haitao] Northwestern Univ, Evanston, IL 60208 USA; [Liu, Daiping; Wang, Haining] Univ Delaware, Newark, DE USA; [Stavrou, Angelos] George Mason Univ, Fairfax, VA 22030 USA	Xu, HT (reprint author), Northwestern Univ, Evanston, IL 60208 USA.	hxu@northwestern.edu; dpliu@udel.edu; hnw@udel.edu; astavrou@gmu.edu			NSF [CNS-1618117]	This work was partially supported by NSF grant CNS-1618117. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the funding agency.	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Web	MAY	2017	11	2							13	10.1145/2983646		35	Computer Science, Information Systems; Computer Science, Software Engineering	Computer Science	EV1VP	WOS:000401538100006		No			2017-07-02	
J	Ryvkin, D; Serra, D; Tremewanc, J				Ryvkin, Dmitry; Serra, Danila; Tremewan, James			I paid a bribe: An experiment on information sharing and extortionary corruption	EUROPEAN ECONOMIC REVIEW			English	Article						Information sharing; Extortionary corruption; Experiment; Crowdsourcing	PRICE DISPERSION; FIELD EXPERIMENT; CONSUMER SEARCH; REPUTATION; INDONESIA; COSTS; EBAY; AVERSION; REVIEWS; PEOPLE	Theoretical and empirical research on corruption has flourished in the last three decades; however, identifying successful anti-corruption policies remains a challenge. In this paper we ask whether bottom-up institutions that rely on voluntary and anonymous reports of bribe demands, such as the I paid a bribe website first launched in India in 2010, could act as effective anti-corruption tools, and, if this is the case, whether and how their effectiveness could be improved. We overcome measurement and identification problems by addressing our research questions in the laboratory. Our results show that the presence of a reporting platform like the I paid a bribe website may be insufficient to systematically lower bribery. A more effective platform is one where posts disclose specific information about the size of the bribes and the location of their requestors, i.e., a platform that could serve as a search engine for the least corrupt officials, especially if posting is restricted to service recipients. Our results also show that while citizens rarely post false information, lying by officials, when allowed to post on the platform, is widespread. (C) 2017 Elsevier B.V. All rights reserved.	[Ryvkin, Dmitry] Florida State Univ, Dept Econ, 113 Collegiate Loop, Tallahassee, FL 32306 USA; [Serra, Danila] Southern Methodist Univ, Dept Econ, Umphrey Lee Ctr, 3300 Dyer St,Suite 301C, Dallas, TX 75275 USA; [Tremewan, James] Univ Vienna, Dept Econ, Oskar Morgenstern Pl 1, A-1090 Vienna, Austria	Ryvkin, D (reprint author), Florida State Univ, Dept Econ, 113 Collegiate Loop, Tallahassee, FL 32306 USA.	dyvkin@fsu.edu; dserra@smu.edu; james.tremewan@univie.ac.at					Abbink K, 2002, J LAW ECON ORGAN, V18, P428, DOI 10.1093/jleo/18.2.428; Abbink K, 2014, J PUBLIC ECON, V111, P17, DOI 10.1016/j.jpubeco.2013.12.012; Anderson ET, 2013, J MARKETING RES, V50, P489; Anderson M, 2012, ECON J, V122, P957, DOI 10.1111/j.1468-0297.2012.02512.x; Armantier O, 2013, ECON J, V123, P1168, DOI 10.1111/ecoj.12019; Banerjee AV, 2010, AM ECON J-ECON POLIC, V2, P1, DOI 10.1257/pol.2.1.1; Banuri S, 2015, SOC CHOICE WELFARE, V45, P579, DOI 10.1007/s00355-015-0883-6; Bardhan P, 1997, J ECON LIT, V35, P1320; Barr A, 2010, J PUBLIC ECON, V94, P862, DOI 10.1016/j.jpubeco.2010.07.006; Bikhchandani S, 1996, J ECON DYN CONTROL, V20, P333, DOI 10.1016/0165-1889(94)00854-7; Bjorkman M, 2010, J EUR ECON ASSOC, V8, P571, DOI 10.1111/j.1542-4774.2010.tb00527.x; Bolton G, 2013, MANAGE SCI, V59, P265, DOI 10.1287/mnsc.1120.1609; BURDETT K, 1983, ECONOMETRICA, V51, P955, DOI 10.2307/1912045; Cabral L, 2010, J IND ECON, V58, P54; Camerer C., 2011, WORKING PAPER; Cameron L, 2009, J PUBLIC ECON, V93, P843, DOI 10.1016/j.jpubeco.2009.03.004; Cason TN, 2003, J ECON THEORY, V112, P232, DOI 10.1016/S0022-0531(03)00127-3; Chaudhury N, 2006, J ECON PERSPECT, V20, P91, DOI 10.1257/089533006776526058; Chevalier JA, 2006, J MARKETING RES, V43, P345, DOI 10.1509/jmkr.43.3.345; Davis DD, 1996, ECON INQ, V34, P133; DIAMOND PA, 1971, J ECON THEORY, V3, P156, DOI 10.1016/0022-0531(71)90013-5; Duflo E, 2015, J PUBLIC ECON, V123, P92, DOI 10.1016/j.jpubeco.2014.11.008; Fischbacher U, 2007, EXP ECON, V10, P171, DOI 10.1007/s10683-006-9159-4; Gneezy U, 2013, J ECON BEHAV ORGAN, V93, P293, DOI 10.1016/j.jebo.2013.03.025; Greiner B., 2015, J EC SCI ASS, V1, P114, DOI DOI 10.1007/S40881-015-0004-4; Gupta S., 1998, DOES CORRUPTION AFFE; Holt CA, 2002, AM ECON REV, V92, P1644, DOI 10.1257/000282802762024700; Houser D, 2006, J ECON MANAGE STRAT, V15, P353, DOI 10.1111/j.1530-9134.2006.00103.x; Hunt J, 2007, J DEV ECON, V84, P574, DOI 10.1016/j.jdeveco.2007.02.003; Kessler J., 2011, EXTERNAL VALIDITY LA; Lafky J, 2014, GAME ECON BEHAV, V87, P554, DOI 10.1016/j.geb.2014.02.008; Luca M., 2013, 14006 HARV BUS SCH N; Masclet D, 2012, APPL ECON, V44, P4553, DOI 10.1080/00036846.2011.591740; MAURO P, 1995, Q J ECON, V110, P681, DOI 10.2307/2946696; Mayzlin D., 2012, TECHNICAL REPORT; Meon PG, 2005, PUBLIC CHOICE, V122, P69, DOI 10.1007/s11127-005-3988-0; Morgan J, 2006, GAME ECON BEHAV, V54, P134, DOI 10.1016/j.geb.2004.07.005; Olken BA, 2006, J PUBLIC ECON, V90, P853, DOI 10.1016/j.jpubeco.2005.05.004; Olken BA, 2007, J POLIT ECON, V115, P200, DOI 10.1086/517935; Pradhan M, 2014, AM ECON J-APPL ECON, V6, P105, DOI 10.1257/app.6.2.105; Reinikka R, 2004, Q J ECON, V119, P679, DOI 10.1162/0033553041382120; Resnick P, 2006, EXP ECON, V9, P79, DOI 10.1007/s10683-006-4309-2; Rockenbach B, 2012, J ECON BEHAV ORGAN, V81, P689, DOI 10.1016/j.jebo.2011.10.009; Ryvkin D., 2016, IND ORG CORRUP UNPUB; Ryvkin D., 2015, IS MORE COMPETITION; Ryvkin D, 2012, J ECON BEHAV ORGAN, V81, P466, DOI 10.1016/j.jebo.2011.07.004; Salmon T., 2016, WORKING PAPER; Sequeira S., 2012, ADV MEASURING CORRUP, P145; Sequeira S., 2013, WORKING PAPER; Serra D, 2006, PUBLIC CHOICE, V126, P225, DOI 10.1007/s11127-006-0286-4; Serra D, 2012, RES EXP ECON, V15, P1; Serra D, 2012, J LAW ECON ORGAN, V28, P569, DOI 10.1093/jleo/ewr010; STAHL DO, 1989, AM ECON REV, V79, P700; Tanzi V., 1998, CORRUPTION PUBLIC IN; Treisman D, 2000, J PUBLIC ECON, V76, P399, DOI 10.1016/S0047-2727(99)00092-4; World Bank, 2004, MAK SERV WORK POOR P; Ye Q, 2009, INT J HOSP MANAG, V28, P180, DOI 10.1016/j.ijhm.2008.06.011	57	0	0	1	1	ELSEVIER SCIENCE BV	AMSTERDAM	PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS	0014-2921	1873-572X		EUR ECON REV	Eur. Econ. Rev.	MAY	2017	94						1	22		10.1016/j.euroecorev.2017.02.003		22	Economics	Business & Economics	EU7IC	WOS:000401207500001		No			2017-07-02	
J	Ali, AL; Falomir, Z; Schmid, F; Freksa, C				Ali, Ahmed Loai; Falomir, Zoe; Schmid, Falko; Freksa, Christian			Rule-guided human classification of Volunteered Geographic Information	ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING			English	Article						Volunteered Geographic Information (VGI); Spatial data quality; Spatial data mining; Classification; Topology; Qualitative spatial reasoning	QUALITATIVE REPRESENTATIONS; IMAGE-ANALYSIS; OPENSTREETMAP; MAPS; SCIENCE; REGION	During the last decade, web technologies and location sensing devices have evolved generating a form of crowdsourcing known as Volunteered Geographic Information (VGI). VGI acted as a platform of spatial data collection, in particular, when a group of public participants are involved in collaborative mapping activities: they work together to collect, share, and use information about geographic features. VGI exploits participants' local knowledge to produce rich data sources. However, the resulting data inherits problematic data classification. In VGI projects, the challenges of data classification are due to the following: (i) data is likely prone to subjective classification, (ii) remote contributions and flexible contribution mechanisms in most projects, and (iii) the uncertainty of spatial data and non-strict definitions of geographic features. These factors lead to various forms of problematic classification: inconsistent, incomplete, and imprecise data classification. This research addresses classification appropriateness. Whether the classification of an entity is appropriate or inappropriate is related to quantitative and/or qualitative observations. Small differences between observations may be not recognizable particularly for non-expert participants. Hence, in this paper, the problem is tackled by developing a rule-guided classification approach. This approach exploits data mining techniques of Association Classification (AC) to extract descriptive (qualitative) rules of specific geographic features. The rules are extracted based on the investigation of qualitative topological relations between target features and their context. Afterwards, the extracted rules are used to develop a recommendation system able to guide participants to the most appropriate classification. The approach proposes two scenarios to guide participants towards enhancing the quality of data classification. An empirical study is conducted to investigate the classification of grass-related features like forest, garden, park, and meadow. The findings of this study indicate the feasibility of the proposed approach. (C) 2016 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved.	[Ali, Ahmed Loai; Falomir, Zoe; Schmid, Falko; Freksa, Christian] Univ Bremen, Bremen Spatial Cognit Ctr, Enrique Schmidt Str 5, D-28359 Bremen, Germany; [Ali, Ahmed Loai] Assiut Univ, Fac Comp & Informat, Dept Informat Syst, Assiut, Egypt	Ali, AL (reprint author), Univ Bremen, Bremen Spatial Cognit Ctr, Enrique Schmidt Str 5, D-28359 Bremen, Germany.	loai@informatik.uni-bremen.de; zfalomir@informatik.uni-bremen.de; schmid@informatik.uni-bremen.de; freksa@uni-bremen.de			German Academic Exchange Service (DAAD); Bremen Spatial Cognition Center (BSCC); European Marie Curie project COGNITIVE-AMI; University of Bremen (project Cognitive Qualitative Descriptions and Applications - CogQDA)	This work is partially funded by the German Academic Exchange Service (DAAD), the Bremen Spatial Cognition Center (BSCC), the European Marie Curie project COGNITIVE-AMI and the University of Bremen (project Cognitive Qualitative Descriptions and Applications - CogQDA).	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Photogramm. Remote Sens.	MAY	2017	127						3	15		10.1016/j.isprsjprs.2016.06.003		13	Geography, Physical; Geosciences, Multidisciplinary; Remote Sensing; Imaging Science & Photographic Technology	Physical Geography; Geology; Remote Sensing; Imaging Science & Photographic Technology	EU7MB	WOS:000401217800002		No			2017-07-02	
J	Aramaki, E; Shikata, S; Ayaya, S; Kumagaya, SI				Aramaki, Eiji; Shikata, Shuko; Ayaya, Satsuki; Kumagaya, Shin-Ichiro			Crowdsourced Identification of Possible Allergy-Associated Factors: Automated Hypothesis Generation and Validation Using Crowdsourcing Services	JMIR RESEARCH PROTOCOLS			English	Article						allergy; crowdsourcing; disease risk; automatic abduction; Tohjisha-Kenkyu; self-support study	EARLY-CHILDHOOD; PUBLIC-HEALTH; FOOD ALLERGY; ASTHMA; DISORDER; RHINITIS; DISEASES; HYGIENE; UPDATE; RISK	Background: Hypothesis generation is an essential task for clinical research, and it can require years of research experience to formulate a meaningful hypothesis. Recent studies have endeavored to apply crowdsourcing to generate novel hypotheses for research. In this study, we apply crowdsourcing to explore previously unknown allergy-associated factors. Objective: In this study, we aimed to collect and test hypotheses of unknown allergy-associated factors using a crowdsourcing service. Methods: Using a series of questionnaires, we asked crowdsourcing participants to provide hypotheses on associated factors for seven different allergies, and validated the candidate hypotheses with odds ratios calculated for each associated factor. We repeated this abductive validation process to identify a set of reliable hypotheses. Results: We obtained two primary findings: (1) crowdsourcing showed that 8 of the 13 known hypothesized allergy risks were statically significant; and (2) among the total of 157 hypotheses generated by the crowdsourcing service, 75 hypotheses were statistically significant allergy-associated factors, comprising the 8 known risks and 53 previously unknown allergy-associated factors. These findings suggest that there are still many topics to be examined in future allergy studies. Conclusions: Crowdsourcing generated new hypotheses on allergy-associated factors. In the near future, clinical trials should be conducted to validate the hypotheses generated in this study.	[Aramaki, Eiji; Shikata, Shuko] Nara Inst Sci & Technol, Grad Sch Informat Sci, Social Comp Lab, Takayama Cho,BLD 405, Ikoma 6300192, Japan; [Ayaya, Satsuki; Kumagaya, Shin-Ichiro] Univ Tokyo, Res Ctr Adv Sci & Technol, Tokyo, Japan	Aramaki, E (reprint author), Nara Inst Sci & Technol, Grad Sch Informat Sci, Social Comp Lab, Takayama Cho,BLD 405, Ikoma 6300192, Japan.	aramaki@is.naist.jp			JSPS KAKENHI [JP16H06395, 16H06399, 16K21720]	This study was supported (in part) by JSPS KAKENHI Grant Numbers JP16H06395, 16H06399, and 16K21720.	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Protoc.	MAY	2017	6	5							e83	10.2196/resprot.5851		12	Health Care Sciences & Services	Health Care Sciences & Services	EV0OI	WOS:000401440100014	28512079	gold			2017-07-02	
J	Xu, Z; Liu, YH; Xuan, JY; Chen, HY; Mei, L				Xu, Zheng; Liu, Yunhuai; Xuan, Junyu; Chen, Haiyan; Mei, Lin			Crowdsourcing based social media data analysis of urban emergency events	MULTIMEDIA TOOLS AND APPLICATIONS			English	Article						Crowdsourcing; Socialmedia analysis; Urban emergency events	WEB; TIME	An urban emergency event requires an immediate reaction or assistance for an emergency situation. With the popularity of the World Wide Web, the internet is becoming a major information provider and disseminator of emergency events and this is due to its real-time, open, and dynamic features. However, faced with the huge, disordered and continuous nature of web resources, it is impossible for people to efficiently recognize, collect and organize these events. In this paper, a crowdsourcing based burst computation algorithm of an urban emergency event is developed in order to convey information about the event clearly and to help particular social groups or governments to process events effectively. A definition of an urban emergency event is firstly introduced. This serves as the foundation for using web resources to compute the burst power of events on the web. Secondly, the different temporal features of web events are developed to provide the basic information for the proposed computation algorithm. Moreover, the burst power is presented to integrate the above temporal features of an event. Empirical experiments on real datasets show that the burst power can be used to analyze events.	[Xu, Zheng; Liu, Yunhuai; Mei, Lin] Minist Publ Secur, Res Inst 3, Shanghai, Peoples R China; [Xu, Zheng] Tsinghua Univ, Beijing, Peoples R China; [Xuan, Junyu] Shanghai Univ, Shanghai, Peoples R China; [Chen, Haiyan] East China Univ Polit Sci & Law, Shanghai, Peoples R China	Xu, Z (reprint author), Minist Publ Secur, Res Inst 3, Shanghai, Peoples R China.	xuzheng@shu.edu.cn			National Science and Technology Major Project [2013ZX01033002-003]; National High Technology Research and Development Program of China (863 Program) [2013AA014601, 2013AA014603]; National Key Technology Support Program [2012BAH07B01]; National Science Foundation of China [61300202, 61300028]; Ministry of Public Security [2014JSYJB009]; China Postdoctoral Science Foundation [2014 M560085]; Shanghai Municipal Commission of Economy and Information [12GA-19]; Science Foundation of Shanghai [13ZR1452900]	This work was supported in part by the National Science and Technology Major Project under Grant 2013ZX01033002-003, in part by the National High Technology Research and Development Program of China (863 Program) under Grant 2013AA014601, 2013AA014603, in part by National Key Technology Support Program under Grant 2012BAH07B01, in part by the National Science Foundation of China under Grant 61300202, 61300028, in part by the Project of the Ministry of Public Security under Grant 2014JSYJB009, in part by the China Postdoctoral Science Foundation under Grant 2014 M560085, the project of Shanghai Municipal Commission of Economy and Information under Grant 12GA-19, and in part by the Science Foundation of Shanghai under Grant 13ZR1452900.	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Tools Appl.	MAY	2017	76	9					11567	11584		10.1007/s11042-015-2731-1		18	Computer Science, Information Systems; Computer Science, Software Engineering; Computer Science, Theory & Methods; Engineering, Electrical & Electronic	Computer Science; Engineering	EU2GE	WOS:000400845000026		No			2017-07-02	
J	Seidel, VP; Langner, B; Sims, J				Seidel, Victor P.; Langner, Benedikt; Sims, Jonathan			Dominant communities and dominant designs: Community-based innovation in the context of the technology life cycle	STRATEGIC ORGANIZATION			English	Article						innovation management; organization design; technological change; online communities; crowdsourcing	OPEN-SOURCE SOFTWARE; LINUX KERNEL; FIRM; GOVERNANCE; MOTIVATION; EVOLUTION; INDUSTRY; CREATION; USERS; ORGANIZATION	Online community-based innovationwhether through self-organized communities, firm-community collaborations, or innovation contests and crowdsourcingis increasingly used as a source of technological advances, yet studies in this domain are often detached from considering the dynamics of technological evolution itself. Where technological advances reside (knowledge distribution), the degree to which innovation tasks can be specified (task decomposition) and the rate of technological progress (performance trajectory) all vary dramatically over the technology life cycle. These factors have implications for what forms of online crowds and communities are most likely to contribute technological advances. We provide a dynamic model of the expected dominant communities for technological advances at each phase of the life cycle, and we draw on examples from open-source software and consumer three-dimensional printing to illustrate the model. Our objectives are to determine how different forms of community-based innovation dominate at different times, to ground innovation models more firmly in material technological advances, and to provide focus for future research in this domain.	[Seidel, Victor P.] Babson Coll, FW Olin Grad Sch Business, Babson Pk, MA 02157 USA; [Langner, Benedikt] Bain & Co, Munich, Germany; [Sims, Jonathan] Babson Coll, Strategy, Babson Pk, MA 02157 USA	Seidel, VP (reprint author), Babson Coll, FW Olin Grad Sch Business, Babson Pk, MA 02157 USA.	vseidel@babson.edu			Green Templeton Doctoral Scholarship Fund; Said Foundation of Said Business School, University of Oxford; Babson Faculty Research Fund	The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: B.L. is supported by the Green Templeton Doctoral Scholarship Fund and the Said Foundation of Said Business School, University of Oxford. V.P.S. and J.S. are supported by the Babson Faculty Research Fund.	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Organ.	MAY	2017	15	2					220	241		10.1177/1476127016653726		22	Business; Management	Business & Economics	EU7TT	WOS:000401238300005		No			2017-07-02	
J	Nickerson, JA; Wuebker, R; Zenger, T				Nickerson, Jackson A.; Wuebker, Robert; Zenger, Todd			Problems, theories, and governing the crowd	STRATEGIC ORGANIZATION			English	Article						crowdsourcing; governance; knowledge creation; managerial cognition; value creation; vertical integration	RESEARCH-AND-DEVELOPMENT; KNOWLEDGE-BASED EXAMINATION; TECHNOLOGICAL-DEVELOPMENT; INNOVATION CONTESTS; FUTURE-DIRECTIONS; FIRM; PERFORMANCE; GOVERNANCE; BOUNDARIES; COLLABORATION	Research and recommendations on innovation through crowdsourcing are diverse and often contradictory, providing little guidance on when, where, and under what conditions to use various forms of crowdsourcing. This article responds by arguing that focal economic actors, as organization designers, catalyze innovation when they efficiently match attributes of the problem or attributes of a domain of problems to modes of organizing problem finding and solution search. Four basic insights drive this approach. First, sourcing from the crowd is, fundamentally, a governance choice. Second, crowdsourcing is an amalgam of both problem finding and problem solving through the crowd. Third, the attributes of focal actors, including the theories of value creation they possess, shape problem formulation, solution-search, and the governance of these processes. Fourth, the act of defining problems reveals, and often generates, a vast residual domain of problemsoften unseen by the focal economic actorthat is implicitly deferred to the crowd to find and potentially solve.	[Nickerson, Jackson A.] Washington Univ, Olin Business Sch, Campus Box 1133,1 Brookings Dr, St Louis, MO 63130 USA; [Wuebker, Robert; Zenger, Todd] Univ Utah, David Eccles Sch Business, Salt Lake City, UT 84112 USA	Zenger, T (reprint author), Univ Utah, David Eccles Sch Business, Salt Lake City, UT 84112 USA.	nickerson@wustl.edu; robert.wuebker@eccles.utah.edu; todd.zenger@eccles.utah.edu					Acs ZJ, 1990, INNOVATION SMALL FIR; Afuah A, 2012, ACAD MANAGE REV, V37, P355, DOI 10.5465/amr.2010.0146; Ahuja G, 2000, STRATEGIC MANAGE J, V21, P317, DOI 10.1002/(SICI)1097-0266(200003)21:3<317::AID-SMJ90>3.0.CO;2-B; Argyres NS, 2012, ORGAN SCI, V23, P1643, DOI 10.1287/orsc.1110.0736; Armisen A, 2015, BUS HORIZONS, V58, P389, DOI 10.1016/j.bushor.2015.03.004; BANTEL KA, 1989, STRATEGIC MANAGE J, V10, P107, DOI 10.1002/smj.4250100709; Ben-Menahem S, 2015, ACAD MANAGE J, DOI [10.5465/amj.2013.1214, DOI 10.5465/AMJ.2013.1214]; Bongsun K, 2015, EUROPEAN MANAGEMENT; Boudreau KJ, 2013, HARVARD BUS REV, V91, P60; Boudreau KJ, 2011, MANAGE SCI, V57, P843, DOI 10.1287/mnsc.1110.1322; Boumgarden P, 2012, STRATEGIC MANAGE J, V33, P587, DOI 10.1002/smj.1972; Brandenburger AM, 1996, J ECON MANAGE STRAT, V5, P5; Breschi S, 2003, RES POLICY, V32, P69, DOI 10.1016/S0048-7333(02)00004-5; Chesbrough H, 2006, OPEN INNOVATION NEW; Chesbrough HW, 2013, OPEN BUSINESS MODELS; Cohen WM, 1996, ECON J, V106, P925, DOI 10.2307/2235365; Csaszar FA, 2016, STRATEGIC MANAGE J, V37, P2031, DOI 10.1002/smj.2440; CYERT R.M., 1963, BEHAV THEORY FIRM; Dahlander L, 2010, RES POLICY, V39, P699, DOI 10.1016/j.respol.2010.01.013; Demsetz H., 1988, J LAW ECON ORGAN, V4, P141; Dyer JH, 2009, HARVARD BUS REV, V87, P60; Einstein A, 1938, EVOLUTION PHYS, P92; Felin T, 2015, ORGAN SCI, V27, P222; Felin T, 2014, RES POLICY, V43, P914, DOI 10.1016/j.respol.2013.09.006; Felin T, 2009, STRATEG ENTREP J, V3, P127, DOI 10.1002/sej.67; Fey CF, 2005, J MANAGE, V31, P597, DOI 10.1177/0149206304272346; Fleming L, 2007, ORGAN SCI, V18, P165, DOI 10.1287/orsc.1060.0242; Foss NJ, 2011, ORGAN SCI, V22, P980, DOI 10.1287/orsc.1100.0584; Foss N. 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J	Pohlig, F; Lenze, U; Muhlhofer, HML; Lenze, FW; Schauwecker, J; Knebel, C; Zimmermann, T; Herschbach, P				Pohlig, Florian; Lenze, Ulrich; Muhlhofer, Heinrich M. L.; Lenze, Florian W.; Schauwecker, Johannes; Knebel, Carolin; Zimmermann, Tanja; Herschbach, Peter			IT-based Psychosocial Distress Screening in Patients with Sarcoma and Parental Caregivers via Disease-specific Online Social Media Communities	IN VIVO			English	Article						Psychosocial distress; psycho-oncology; crowdsourcing; Facebook; osteosarcoma; Ewing's sarcoma	PIGMENTED VILLONODULAR SYNOVITIS; CANCER-PATIENTS; PROGRESSION QUESTIONNAIRE; CLINICAL-PRACTICE; EWINGS-SARCOMA; RARE CANCERS; OSTEOSARCOMA; CHILDREN; TUMORS; FEAR	Background: Psychosocial distress can be frequently observed in patients with sarcoma, depicting a relevant clinical problem. However, prospective data collection on psychosocial distress in patients with rare tumors is often time-consuming. In this context, social media such as Facebook can serve as a potential platform to expand research. The aim of this study was to assess the feasibility of psychosocial distress screening in patients with osteosarcoma and Ewing's sarcoma via social media. Materials and Methods: For this study an online questionnaire including general information and self-assessment distress measurement tools for patients and parents was created. The link to the questionnaire was then posted on the main page of the two largest disease-specific Facebook communities on osteosarcoma and Ewing's sarcoma. Results: Within 2 months, 28 patients and 58 parents of patients were enrolled. All patients with osteosarcoma and Ewing's sarcoma, as well as the majority of parental caregivers of such patients, showed relevant psychosocial distress levels. Conclusion: Crowdsourcing via disease-specific patient communities on Facebook is feasible and provides great potential for acquisition of medical data of rare diseases.	[Pohlig, Florian; Lenze, Ulrich; Muhlhofer, Heinrich M. L.; Lenze, Florian W.; Schauwecker, Johannes; Knebel, Carolin] Tech Univ Munich, Dept Orthopaed Surg, Munich, Germany; [Herschbach, Peter] Tech Univ Munich, Roman Herzog Comprehens Canc Ctr, Dept Psychosomat Med, Munich, Germany; [Herschbach, Peter] Tech Univ Munich, Rechts Isar Hosp, Munich, Germany; [Lenze, Florian W.] Traunstein Hosp, Dept Traumatol, Traunstein, Germany; [Zimmermann, Tanja] Hannover Med Sch, Dept Psychosomat Med & Psychotherapy, Hannover, Germany	Pohlig, F (reprint author), Tech Univ Munich, Dept Orthopaed Surg, Klinikum Rechts Isar, Ismaninger Str 22, D-81675 Munich, Germany.	Florian.Pohlig@mri.tum.de			Wilhelm-Sander-Foundation	The Authors wish to explicitly thank the Wilhelm-Sander-Foundation, a charitable, non-profit foundation whose purpose is to promote cancer research, for funding this study.	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J	Xu, G; Zhu, X; Fu, DJ; Dong, JW; Xiao, XM				Xu, Guang; Zhu, Xuan; Fu, Dongjie; Dong, Jinwei; Xiao, Xiangming			Automatic land cover classification of geo-tagged field photos by deep learning	ENVIRONMENTAL MODELLING & SOFTWARE			English	Article						Deep learning; Convolutional neural network; Transfer learning; Multinomial logistic regression; Land cover; Crowdsourced photos	DECIDUOUS RUBBER PLANTATIONS; FACE DETECTION; IMAGERY; BASIN; RECOGNITION; PALSAR	With more and more crowdsourcing geo-tagged field photos available online, they are becoming a potentially valuable source of information for environmental studies. However, the labelling and recognition of these photos are time-consuming. To utilise such information, a land cover type recognition model for field photos was proposed based on the deep learning technique. This model combines a pre-trained convolutional neural network (CNN) as the image feature extractor and the multinomial logistic regression model as the feature classifier. The pre-trained CNN model Inception-v3 was used in this study. The labelled field photos from the Global Geo-Referenced Field Photo Library (http://eomf.ou.eduiphotos) were chosen for model training and validation. The results indicated that our recognition model achieved an acceptable accuracy (48.40% for top-1 prediction and 76.24% for top-3 prediction) of land cover classification. With accurate self-assessment of confidence, the model can be applied to classify numerous online geo-tagged field photos for environmental information extraction. (C) 2017 Elsevier Ltd. All rights reserved.	[Xu, Guang; Zhu, Xuan] Monash Univ, Sch Earth Atmosphere & Environm, Clayton Campus, Clayton, Vic 3800, Australia; [Fu, Dongjie] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China; [Dong, Jinwei] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China; [Dong, Jinwei; Xiao, Xiangming] Univ Oklahoma, Dept Microbiol & Plant Biol, Norman, OK 73019 USA; [Dong, Jinwei; Xiao, Xiangming] Univ Oklahoma, Ctr Spatial Anal, Norman, OK 73019 USA	Xu, G (reprint author), Monash Univ, Sch Earth Atmosphere & Environm, Clayton Campus, Clayton, Vic 3800, Australia.	xg1990@gmail.com			NASA Land Use and Land Cover Change program [NNX14AD78G]; Key Research Program of Frontier Sciences; Chinese Academy of Sciences [QYZDB-SSW-DQC005]; Thousand Youth Talents Plan; Youth Science Funds of State Key Laboratory of Resources and Environmental Information System [O8R8A080YA]; National Science Foundation of China [41501473]; Institute of Geographic Sciences and Natural Resources Research [Y6V60206YZ]	We would like to thank Google for making the TensorFlow library and the Inception-v3 model available. We also would like to thank all the contributors of the Global Geo-Referenced Field Photo Library who make this study possible. This study was supported in part by the NASA Land Use and Land Cover Change program (NNX14AD78G), and the Key Research Program of Frontier Sciences, the Chinese Academy of Sciences (QYZDB-SSW-DQC005), the "Thousand Youth Talents Plan". This research was also supported by the Youth Science Funds of State Key Laboratory of Resources and Environmental Information System (O8R8A080YA), Chinese Academy of Sciences, the research grants (41501473) funded by National Science Foundation of China and the research grants (Y6V60206YZ) funded by Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences.	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J	Krishna, R; Zhu, YK; Groth, O; Johnson, J; Hata, K; Kravitz, J; Chen, S; Kalantidis, Y; Li, LJ; Shamma, DA; Bernstein, MS; Li, FF				Krishna, Ranjay; Zhu, Yuke; Groth, Oliver; Johnson, Justin; Hata, Kenji; Kravitz, Joshua; Chen, Stephanie; Kalantidis, Yannis; Li, Li-Jia; Shamma, David A.; Bernstein, Michael S.; Li Fei-Fei			Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations	INTERNATIONAL JOURNAL OF COMPUTER VISION			English	Article						Computer vision; Dataset; Image; Scene graph; Question answering; Objects; Attributes; Relationships; Knowledge; Language; Crowdsourcing	DATABASE; CLASSIFICATION; KNOWLEDGE; WORDNET; OBJECT	Despite progress in perceptual tasks such as image classification, computers still perform poorly on cognitive tasks such as image description and question answering. Cognition is core to tasks that involve not just recognizing, but reasoning about our visual world. However, models used to tackle the rich content in images for cognitive tasks are still being trained using the same datasets designed for perceptual tasks. To achieve success at cognitive tasks, models need to understand the interactions and relationships between objects in an image. When asked "What vehicle is the person riding?", computers will need to identify the objects in an image as well as the relationships riding(man, carriage) and pulling(horse, carriage) to answer correctly that "the person is riding a horse-drawn carriage." In this paper, we present the Visual Genome dataset to enable the modeling of such relationships. We collect dense annotations of objects, attributes, and relationships within each image to learn these models. Specifically, our dataset contains over 108K images where each image has an average of objects, attributes, and pairwise relationships between objects. We canonicalize the objects, attributes, relationships, and noun phrases in region descriptions and questions answer pairs to WordNet synsets. Together, these annotations represent the densest and largest dataset of image descriptions, objects, attributes, relationships, and question answer pairs.	[Krishna, Ranjay; Zhu, Yuke; Johnson, Justin; Hata, Kenji; Kravitz, Joshua; Chen, Stephanie; Bernstein, Michael S.; Li Fei-Fei] Stanford Univ, Stanford, CA 94305 USA; [Groth, Oliver] Tech Univ Dresden, Dresden, Germany; [Kalantidis, Yannis] Yahoo Inc, San Francisco, CA USA; [Li, Li-Jia] Snapchat Inc, Los Angeles, CA USA; [Shamma, David A.] Ctr Wiskunde & Informat, Amsterdam, Netherlands	Krishna, R (reprint author), Stanford Univ, Stanford, CA 94305 USA.	ranjaykrishna@cs.stanford.edu			Stanford Computer Science Department; Yahoo Labs; Brown Institute for Media Innovation; Toyota; Adobe; ONR MURI	We would like to start by thanking our sponsors: Stanford Computer Science Department, Yahoo Labs, The Brown Institute for Media Innovation, Toyota, Adobe and ONR MURI. Next, we specially thank Michael Stark, Yutian Li, Frederic Ren, Sherman Leung, Michelle Guo and Gavin Mai for their contributions. 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J. Comput. Vis.	MAY	2017	123	1			SI		32	73		10.1007/s11263-016-0981-7		42	Computer Science, Artificial Intelligence	Computer Science	ET4SY	WOS:000400276400003		No			2017-07-02	
J	Plummer, BA; Wang, LW; Cervantes, CM; Caicedo, JC; Hockenmaier, J; Lazebnik, S				Plummer, Bryan A.; Wang, Liwei; Cervantes, Chris M.; Caicedo, Juan C.; Hockenmaier, Julia; Lazebnik, Svetlana			Flickr30k Entities: Collecting Region-to-Phrase Correspondences for Richer Image-to-Sentence Models	INTERNATIONAL JOURNAL OF COMPUTER VISION			English	Article						Computer vision; Language; Region phrase correspondence; Datasets; Crowdsourcing		The Flickr30k dataset has become a standard benchmark for sentence-based image description. This paper presents Flickr30k Entities, which augments the 158k captions from Flickr30k with 244k coreference chains, linking mentions of the same entities across different captions for the same image, and associating them with 276k manually annotated bounding boxes. Such annotations are essential for continued progress in automatic image description and grounded language understanding. They enable us to define a new benchmark for localization of textual entity mentions in an image. We present a strong baseline for this task that combines an image-text embedding, detectors for common objects, a color classifier, and a bias towards selecting larger objects. While our baseline rivals in accuracy more complex state-of-the-art models, we show that its gains cannot be easily parlayed into improvements on such tasks as image-sentence retrieval, thus underlining the limitations of current methods and the need for further research.	[Plummer, Bryan A.; Wang, Liwei; Cervantes, Chris M.; Hockenmaier, Julia; Lazebnik, Svetlana] Univ Illinois, Urbana, IL 61801 USA; [Caicedo, Juan C.] Broad Inst MIT & Harvard, Boston, MA USA	Plummer, BA (reprint author), Univ Illinois, Urbana, IL 61801 USA.	bplumme2@illinois.edu			National Science Foundation [1053856, 1205627, 1405883, 1228082, 1302438, 1563727]; Xerox UAC; Sloan Foundation	This material is based upon work supported by the National Science Foundation under Grants No. 1053856, 1205627, 1405883, 1228082, 1302438, 1563727, as well as support from Xerox UAC and the Sloan Foundation. We thank the NVIDIA Corporation for the generous donation of the GPUs used for our experiments.	Antol S., 2015, ICCV; Chen X., 2015, CVPR; Deng J., 2009, CVPR; Devlin J., 2015, ACL; Dodge J., 2012, NAACL; Donahue J., 2015, CVPR; Everingham M., 2008, PASCAL VISUAL OBJECT; Everingham M., 2012, PASCAL VISUAL OBJECT; Fang H., 2015, CVPR; Farhadi A., 2010, ECCV; Fidler S., 2013, CVPR; Fukui A., 2016, ARXIV160601847; Gao H., 2015, NIPS; Girshick R., 2015, ICCV; Gong Y., 2014, ECCV; Gong YC, 2014, INT J COMPUT VISION, V106, P210, DOI 10.1007/s11263-013-0658-4; Grubinger M., 2006, INT WORKSH ONTOIMAGE, P13; Hodosh M., 2010, CONLL, P162; Hodosh M., 2013, JAIR; Hotelling H, 1936, BIOMETRIKA, V28, P321, DOI 10.1093/biomet/28.3-4.321; Hu R., 2016, CVPR; Johnson J., 2015, CVPR; Johnson J., 2016, CVPR; Karpathy A., 2015, CVPR; Karpathy A., 2014, NIPS; Kazemzadeh S., 2014, EMNLP; Kiros R., 2014, ARXIV14112539; Klein B., 2014, ARXIV14117399; Kong C., 2014, CVPR; Krishna R., 2016, ARXIV160207332; Kulkarni G., 2011, CVPR; Lebret R., 2015, ICML; Lev G., 2016, ECCV; Lin T., 2014, ECCV; Ma L., 2015, ICCV; Malinowski M., 2014, NIPS; Mao J., 2015, ICLR; Mao J., 2016, CVPR; McCarthy J. F., 1995, USING DECISION TREES; Mikolov T., 2013, NIPS; Ordonez V., 2011, NIPS; Perronnin Florent, 2010, ECCV; Plummer B., 2015, ICCV; Ramanathan V., 2014, ECCV; Rashtchian C., 2010, NAACL WORKSH CREAT S, P139; Ren M., 2015, NIPS; Rohrbach A., 2016, ECCV; Silberman N., 2012, ECCV; Simonyan K., 2014, 14091556 ARXIV, DOI DOI 10.1109/TNN.2010.2066286; Soon WM, 2001, COMPUT LINGUIST, V27, P521, DOI 10.1162/089120101753342653; Sorokin A., 2008, INT VIS WORKSH; Su H., 2012, AAAI TECHN REP; Tommasi T., 2016, BMVC; Uijlings JRR, 2013, INT J COMPUT VISION, V104, P154, DOI 10.1007/s11263-013-0620-5; Vinyals O., 2015, CVPR; Wang L., 2016, CVPR; Wang M., 2016, ECCV; Xu K., 2015, ICML; Yao BZ, 2010, P IEEE, V98, P1485, DOI 10.1109/JPROC.2010.2050411; Young P., 2014, P TACL, V2, P67; Yu L., 2015, ICCV; Zhang J., 2016, ECCV; Zitnick C. L., 2014, ECCV; Zitnick C. L., 2013, CVPR	64	0	0	1	1	SPRINGER	DORDRECHT	VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS	0920-5691	1573-1405		INT J COMPUT VISION	Int. J. Comput. Vis.	MAY	2017	123	1			SI		74	93		10.1007/s11263-016-0965-7		20	Computer Science, Artificial Intelligence	Computer Science	ET4SY	WOS:000400276400004		No			2017-07-02	
J	Meng, R; Chen, L; Tong, YX; Zhang, C				Meng, Rui; Chen, Lei; Tong, Yongxin; Zhang, Chen			Knowledge Base Semantic Integration Using Crowdsourcing	IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING			English	Article						Knowledge base; crowdsourcing; data integration		The semantic web has enabled the creation of a growing number of knowledge bases (KBs), which are designed independently using different techniques. Integration of KBs has attracted much attention as different KBs usually contain overlapping and complementary information. Automatic techniques for KB integration have been improved but far from perfect. Therefore, in this paper, we study the problem of knowledge base semantic integration using crowd intelligence. There are both classes and instances in a KB, in our work, we propose a novel hybrid framework for KB semantic integration considering the semantic heterogeneity of KB class structures. We first perform semantic integration of the class structures via crowdsourcing, then apply the blocking-based instance matching approach according to the integrated class structure. For class structure (taxonomy) semantic integration, the crowd is leveraged to help identifying the semantic relationships between classes to handle the semantic heterogeneity problem. Under the conditions of both large scale KBs and limited monetary budget for crowdsourcing, we formalize the class structure (taxonomy) semantic integration problem as a Local Tree Based Query Selection (LTQS) problem. We show that the LTQS problem is NP-hard and propose two greedy-based algorithms, i.e., static query selection and adaptive query selection. Furthermore, the KBs are usually of large scales and have millions of instances, direct pairwise-based instance matching is inefficient. Therefore, we adopt the blocking-based strategy for instance matching, taking advantage of the class structure (taxonomy) integration result. The experiments on real large scale KBs verify the effectiveness and efficiency of the proposed approaches.	[Meng, Rui; Chen, Lei; Zhang, Chen] Hong Kong Univ Sci & Technol, Dept Comp Sci & Engn, Kowloon, Hong Kong, Peoples R China; [Tong, Yongxin] Beihang Univ, State Key Lab Software Dev Environm, Sch Comp Sci & Engn, Beijing 100191, Peoples R China; [Zhang, Chen] Shandong Univ Finance & Econ, Jinan, Shandong, Peoples R China	Meng, R (reprint author), Hong Kong Univ Sci & Technol, Dept Comp Sci & Engn, Kowloon, Hong Kong, Peoples R China.	rmeng@cse.ust.hk; leichen@cse.ust.hk; yxtong@buaa.edu.cn; czhangad@cse.ust.hk			Hong Kong RGC Project [HKUST637/13]; National Grand Fundamental Research 973 Program of China [2014CB340303]; National Science Foundation of China (NSFC) [61502021, 61328202, 61532004]; NSFC Guang Dong Grant [U1301253]; Microsoft Research Asia Fellowship	The authors are grateful to anonymous reviewers for their constructive comments on this work. The work is partially supported by the Hong Kong RGC Project N HKUST637/13, National Grand Fundamental Research 973 Program of China under Grant 2014CB340303, the National Science Foundation of China (NSFC) under Grant No. 61502021, 61328202, and 61532004, NSFC Guang Dong Grant No. U1301253, and Microsoft Research Asia Fellowship 2012. The Fostering Project of Dominant Discipline and Talent Team of Shandong Province Higher Education Institutions.	Auer S., 2007, P 6 INT SEM WEB C 2, P722, DOI DOI 10.1007/978-3-540-76298-0_52; Aumueller D., 2005, P 2005 ACM SIGMOD IN, P906, DOI 10.1145/1066157.1066283; Bollacker K., 2008, P 2008 ACM SIGMOD IN, P1247, DOI DOI 10.1145/1376616.1376746; Bragg J., 2013, P 1 AAAI C HUM COMP, P25; Brodie M. L., 2012, KNOWLEDGE BASE MANAG; Carlson A, 2010, PROCEEDINGS OF THE TWENTY-FOURTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE (AAAI-10), P1306; Chen Z, 2014, PVLDB, V7, P1629; Chilton L. 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G., 2011, P VLDB, V4, P267; Sarasua C., 2012, P INT SEM WEB C, P525; Shi F., 2009, P INT C SEM WEB ICSW, P585; Shvaiko Pavel, 2013, KNOWLEDGE DATA ENG I, V25, P158; Simpson E. D., 2015, P 24 INT C WORLD WID, P992; Suchanek F. M., 2011, P VLDB ENDOWMENT, V5, P157; Udrea O., 2007, P ACM SIGMOD INT C M, P449, DOI DOI 10.1145/1247480.1247531; Vesdapunt N., 2014, P VLDB ENDOWMENT, V7, P1071; Wang J., 2012, P VLDB ENDOW, V5, P1483, DOI [DOI 10.14778/2350229.2350263, 10.14778/2350229.2350263]; Wang JS, 2013, ADV INTEL SYS RES, V42, P229; Wu W., 2012, P 2012 ACM SIGMOD IN, P481, DOI DOI 10.1145/2213836.2213891; Zhang C.J., 2013, PVLDB, V6, P757; Zheng Y., 2015, P ACM SIGMOD INT C M, P1031	44	0	0	8	8	IEEE COMPUTER SOC	LOS ALAMITOS	10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1314 USA	1041-4347	1558-2191		IEEE T KNOWL DATA EN	IEEE Trans. Knowl. Data Eng.	MAY 1	2017	29	5					1087	1100		10.1109/TKDE.2017.2656086		14	Computer Science, Artificial Intelligence; Computer Science, Information Systems; Engineering, Electrical & Electronic	Computer Science; Engineering	ES1LO	WOS:000399289300012		No			2017-07-02	
J	Huang, C; Wang, D; Mann, B				Huang, Chao; Wang, Dong; Mann, Brian			Towards social-aware interesting place finding in social sensing applications	KNOWLEDGE-BASED SYSTEMS			English	Article						Interesting place finding; Social dependency; Social sensing; Crowdsourcing; Expectation maximization	MAXIMUM-LIKELIHOOD-ESTIMATION; ALGORITHM; MEDIA; MODEL	This paper develops a principled approach to accurately identify interesting places in a city through social sensing applications. Social sensing has emerged as a new application paradigm, where a crowd of social sources (humans or devices on their behalf) collectively contribute a large amount of observations about the physical world. This paper studies an interesting place finding problem, in which the goal is to correctly identify the interesting places in a city. Important challenges exist in solving this problem: (i) the interestingness of a place is not only related to the number of users who visit it, but also depends upon the travel experience of the visiting users; (ii) the user's social connections could directly affect their visiting behavior and the interestingness judgment of a given place. In this paper, we develop a new Social-aware Interesting Place Finding Plus (SIPF+) approach that addresses the above challenges by explicitly incorporating both the user's travel experience and social relationship into a rigorous analytical framework. The SIPF+ scheme can find interesting places not typically identified by traditional travel websites (e.g., TripAdvisor, Expedia). We compare our solution with state-of-the-art baselines using two real-world datasets collected from location-based social network services and verified the effectiveness of our approach. (C) 2017 Elsevier B.V. All rights reserved.	[Huang, Chao; Wang, Dong; Mann, Brian] Univ Notre Dame, Dept Comp Sci & Engn, Notre Dame, IN 46556 USA	Wang, D (reprint author), Univ Notre Dame, Dept Comp Sci & Engn, Notre Dame, IN 46556 USA.	dwang5@nd.edu			National Science Foundation [CBET-1637251, CNS-1566465, IIS-1447795]; Army Research Office [W911NF16-1-0388]	This material is based upon work supported by the National Science Foundation under Grant No. CBET-1637251, CNS-1566465 and IIS-1447795 and Army Research Office under Grant W911NF16-1-0388. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Office or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation here on.	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MAY 1	2017	123						31	40		10.1016/j.knosys.2017.02.006		10	Computer Science, Artificial Intelligence	Computer Science	ES6BY	WOS:000399632500003		No			2017-07-02	
J	Kramer, JLK; Geisler, F; Ramer, L; Plunet, W; Cragg, JJ				Kramer, John L. K.; Geisler, Fred; Ramer, Leanne; Plunet, Ward; Cragg, Jacquelyn J.			Open Access Platforms in Spinal Cord Injury: Existing Clinical Trial Data to Predict and Improve Outcomes	NEUROREHABILITATION AND NEURAL REPAIR			English	Article						spinal cord injury; disease progression; heterogeneity; clinical trials; open access; crowdsourcing; SCI; recovery profile	PROGRESSION; RECOVERY	Recovery from acute spinal cord injury (SCI) is characterized by extensive heterogeneity, resulting in uncertain prognosis. Reliable prediction of recovery in the acute phase benefits patients and their families directly, as well as improves the likelihood of detecting efficacy in clinical trials. This issue of heterogeneity is not unique to SCI. In fields such as traumatic brain injury, Parkinson's disease, and amyotrophic lateral sclerosis, one approach to understand variability in recovery has been to make clinical trial data widely available to the greater research community. We contend that the SCI community should adopt a similar approach in providing open access clinical trial data.	[Kramer, John L. K.; Plunet, Ward; Cragg, Jacquelyn J.] Univ British Columbia, Vancouver, BC, Canada; [Geisler, Fred] Rhausler Inc, Can Carlos, CA USA; [Ramer, Leanne] Simon Fraser Univ, Dept Biomed Physiol & Kinesiol, Burnaby, BC, Canada	Kramer, JLK (reprint author), Univ British Columbia, Vancouver, BC, Canada.; Kramer, JLK (reprint author), Univ British Columbia, Sch Kinesiol, ICORD, Vancouver, BC, Canada.	kramer@icord.org			Wings for Life Spinal Cord Research Foundation; Rick Hansen Institute; Michael Smith Foundation for Health Research	The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Dr Kramer's laboratory is supported by the Wings for Life Spinal Cord Research Foundation, the Rick Hansen Institute, and the Michael Smith Foundation for Health Research. Dr Cragg is a Society in Science Branco Weiss Postdoctoral Fellow and is also supported by the Michael Smith Foundation for Health Research.	Atassi N, 2014, NEUROLOGY, V83, P1719, DOI 10.1212/WNL.0000000000000951; Bedlack RS, 2016, NEUROLOGY, V86, P808, DOI 10.1212/WNL.0000000000002251; Bracken MB, 1997, JAMA-J AM MED ASSOC, V277, P1597, DOI 10.1001/jama.277.20.1597; GEISLER FH, 1991, NEW ENGL J MED, V324, P1829, DOI 10.1056/NEJM199106273242601; Geisler FH, 2001, SPINE, V26, pS87, DOI 10.1097/00007632-200112151-00015; Golle P., 2006, P 5 ACM WORKSH PRIV, P77, DOI 10.1145/1179601.1179615; Hawryluk GWJ, 2008, NEUROSURG FOCUS, V25, DOI 10.3171/FOC.2008.25.11.E14; Hothorn T, 2014, AMYOTROPH LAT SCL FR, V15, P444, DOI 10.3109/21678421.2014.893361; Kirshblum SC, 2011, J SPINAL CORD MED, V34, P547, DOI [10.1179/204577211X13207446293695, 10.1179/107902611X13186000420242]; Kuffner R, 2015, NAT BIOTECHNOL, V33, P51, DOI 10.1038/nbt.3051; Lo B, 2015, JAMA-J AM MED ASSOC, V313, P793, DOI DOI 10.1001/JAMA.2015.292; Longo DL, 2016, NEW ENGL J MED, V374, P276, DOI 10.1056/NEJMe1516564; Lunetta C, 2016, AMYOTROPH LAT SCL FR, V17, P93, DOI 10.3109/21678421.2015.1083585; MCCARTHY M, 2014, BMJ-BRIT MED J, V348, DOI DOI 10.1136/BMJ.G1135; Navarro Robert, 2008, Inform Prim Care, V16, P257; Nielson JL, 2015, NAT COMMUN, V6, DOI 10.1038/ncomms9581; Steeves JD, 2011, SPINAL CORD, V49, P257, DOI 10.1038/sc.2010.99; Sweeney L, 2000, 3 CARN MELL U SCH CO, P1; Taichman DB, 2016, PLOS MED, V13, DOI 10.1371/journal.pmed.1001950; Wu X, 2015, SPINAL CORD, V53, P84, DOI 10.1038/sc.2014.232	20	0	0	0	0	SAGE PUBLICATIONS INC	THOUSAND OAKS	2455 TELLER RD, THOUSAND OAKS, CA 91320 USA	1545-9683	1552-6844		NEUROREHAB NEURAL RE	Neurorehabil. Neural Repair	MAY	2017	31	5					399	401		10.1177/1545968316688801		3	Clinical Neurology; Rehabilitation	Neurosciences & Neurology; Rehabilitation	ES7EE	WOS:000399711600001	28107789	No			2017-07-02	
J	Loor, M; De Tre, G				Loor, Marcelo; De Tre, Guy			On the need for augmented appraisal degrees to handle experience-based evaluations	APPLIED SOFT COMPUTING			English	Article						Fuzzy information processing; Augmented (fuzzy) computation; Connotation differential; Semantic richer comparison; Crowd-sourced (fuzzy) data	INTUITIONISTIC FUZZY-SETS; GROUP DECISION-MAKING; CITIZEN SCIENCE; INFORMATION; QUALITY	Experience-based evaluations, i.e., evaluations resulting from what one has learned or understood about a particular topic by experience, are an important component in modern information management. This is especially the case when data from social media or crowdsourcing are involved. In this paper, techniques for handling and comparing experience-based (fuzzy) evaluations are proposed and studied. Since such evaluations could be fairly subjective, their comparison could be affected not only by the magnitude of each appraisal, but also by its context- herein, by 'context of an evaluation' is meant the conditions that arise when the evaluation is carried out, which mainly depend on the experience of an evaluator about the topic under consideration. Therefore, to characterize in a better way the connotative meaning in each experience-based evaluation, an augmented appraisal degree, AAD for short, is proposed as a novel generalization of a membership (or non-membership) degree. Along with the definition of an AAD, an augmented framework is described. The augmented framework includes several concepts, operators and functions that support different methods of computation with (collections of) AADs. We pay special attention to the description, use, potential benefits and applications of this augmented framework. (C) 2017 Elsevier B.V. All rights reserved.	[Loor, Marcelo; De Tre, Guy] Univ Ghent, Dept Telecommun & Informat Proc, Sint Pietersnieuwstr 41, B-9000 Ghent, Belgium; [Loor, Marcelo] ESPOL Univ, Dept Elect & Comp Engn, Campus Gustavo Galindo 5,Km 30-5 Via Perimetral, Guayaquil, Ecuador	Loor, M (reprint author), Univ Ghent, Dept Telecommun & Informat Proc, Sint Pietersnieuwstr 41, B-9000 Ghent, Belgium.	Marcelo.Loor@UGent.be; Guy.DeTre@UGent.be					Atanassov KT, 2012, STUD FUZZ SOFT COMP, V283, P1, DOI 10.1007/978-3-642-29127-2; ATANASSOV KT, 1986, FUZZY SET SYST, V20, P87, DOI 10.1016/S0165-0114(86)80034-3; Bordogna G, 2014, INFORM SCIENCES, V258, P312, DOI 10.1016/j.ins.2013.07.013; Brabham DC, 2013, MIT PRESS ESSENT, P1; Crall AW, 2011, CONSERV LETT, V4, P433, DOI 10.1111/j.1755-263X.2011.00196.x; De Tre G, 2009, LECT NOTES ARTIF INT, V5822, P593, DOI 10.1007/978-3-642-04957-6_51; Dubois D., 2000, FUZZY SETS SERIES, V7, P21; EKMAN G, 1963, PSYCHOMETRIKA, V28, P33, DOI 10.1007/BF02289545; Good BM, 2013, BIOINFORMATICS, V29, P1925, DOI 10.1093/bioinformatics/btt333; Goodchild MF, 2007, GEOJOURNAL, V69, P211, DOI 10.1007/s10708-007-9111-y; Hand E, 2010, NATURE, V466, P685, DOI 10.1038/466685a; Perez IJ, 2014, IEEE T SYST MAN CY-S, V44, P494, DOI 10.1109/TSMC.2013.2259155; Loor Marcelo, 2014, Proceedings of the International Conference on Fuzzy Computation Theory and Applications FCTA 2014, P127; Loor M., 2014, MODERN APPROACHES FU, VI, P105; Loor M., 2015, P 7 INT JOINT C COMP, V2, P57; Lowry CS, 2013, GROUND WATER, V51, P151, DOI 10.1111/j.1745-6584.2012.00956.x; Matthe T., 2009, P 2009 ACM S APPL CO, P1699, DOI 10.1145/1529282.1529664; Morente-Molinera JA, 2016, INFORM SCIENCES, V328, P418, DOI 10.1016/j.ins.2015.08.051; Morente-Molinera JA, 2015, KNOWL-BASED SYST, V88, P154, DOI 10.1016/j.knosys.2015.07.035; Ovchinnikov S, 2000, HDB FUZZ SET SER, V7, P233; Palmer M., 2013, CROWDSOURCING GEOGRA, P287; Szmidt E, 2005, LECT NOTES ARTIF INT, V3558, P272; Szmidt E, 2000, FUZZY SET SYST, V114, P505, DOI 10.1016/S0165-0114(98)00244-9; Szmidt E., 2004, P INT JOINT C NEUR N, V2, P1129; Szmidt E., 2013, 8 C EUR SOC FUZZ LOG, P840; Szmidt E, 2008, STUD COMPUT INTELL, V109, P455; TVERSKY A, 1977, PSYCHOL REV, V84, P327, DOI 10.1037/0033-295X.84.4.327; Vlachos IK, 2007, PATTERN RECOGN LETT, V28, P197, DOI 10.1016/j.patrec.2006.07.004; Yager RR, 2013, PROCEEDINGS OF THE 2013 JOINT IFSA WORLD CONGRESS AND NAFIPS ANNUAL MEETING (IFSA/NAFIPS), P57, DOI 10.1109/IFSA-NAFIPS.2013.6608375; Yager RR, 2013, INT J INTELL SYST, V28, P436, DOI 10.1002/int.21584; ZADEH LA, 1965, INFORM CONTROL, V8, P338, DOI 10.1016/S0019-9958(65)90241-X; Zadeh L. A., 1972, J CYBERNETICS, V2, P4, DOI DOI 10.1080/01969727208542910; Zadeh LA, 2013, INFORM SCIENCES, V248, P1, DOI 10.1016/j.ins.2013.06.003; Zadeh LA, 2008, INFORM SCIENCES, V178, P2751, DOI 10.1016/j.ins.2008.02.012	34	0	0	2	2	ELSEVIER SCIENCE BV	AMSTERDAM	PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS	1568-4946	1872-9681		APPL SOFT COMPUT	Appl. Soft. Comput.	MAY	2017	54						284	295		10.1016/j.asoc.2017.01.009		12	Computer Science, Artificial Intelligence; Computer Science, Interdisciplinary Applications	Computer Science	EN3IC	WOS:000395901200019		No			2017-07-02	
J	Goh, DHL; Pe-Than, EPP; Lee, CS				Goh, Dion Hoe-Lian; Pe-Than, Ei Pa Pa; Lee, Chei Sian			Perceptions of virtual reward systems in crowdsourcing games	COMPUTERS IN HUMAN BEHAVIOR			English	Article						Crowdsourcing games; Virtual reward systems; Points; Badges; Experiments; Perceived output quality; Perceived enjoyment; Motivational needs	ENGAGEMENT; ENJOYMENT; QUALITY; SATISFACTION; PERSPECTIVE; BEHAVIOR; TRUST; NEEDS; WEB	The gaming approach to crowdsourcing is a major way to foster engagement and sustained participation. Also known as crowdsourcing games, players contribute their effort to tackle problems and receive enjoyment in return. As in any game, a fundamental mechanism in crowdsourcing games is its virtual reward system. This paper investigates how virtual reward systems evoke intrinsic motivation, perceived enjoyment and output quality in the context of crowdsourcing games. Three mobile applications for crowdsourcing location-based content were developed for an experimental study. The Track version offered a points-based reward system for actions such as contribution of content. The Badge version offered different badges for collection while the Share version served as a control which did not have any virtual reward system. For each application, participants performed a series of tasks after which a questionnaire survey Was administered. Results showed that Badge and Track enhanced enjoyment emotionally, cognitively and behaviorally. They also increased perceptions of the quality of outputs when compared to Share. As well, they better satisfied the motivational needs for autonomy and competence than Share. Interestingly, there were also significant differences in how Badge and Track were perceived. (C) 2017 Elsevier Ltd. All rights reserved.	[Goh, Dion Hoe-Lian; Pe-Than, Ei Pa Pa; Lee, Chei Sian] Nanyang Technol Univ, Wee Kim Wee Sch Commun & Informat, 31Nanyang Link,SCI Bldg, Singapore 637718, Singapore	Goh, DHL (reprint author), Nanyang Technol Univ, Wee Kim Wee Sch Commun & Informat, 31Nanyang Link,SCI Bldg, Singapore 637718, Singapore.	ashlgoh@ntu.edu.sg; ei1@ntu.edu.sg; leecs@ntu.edu.sg			MOE/Tier 1 grant [RG64/14]	This work was supported by MOE/Tier 1 grant RG64/14.	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F., 1974, BEHAVIORISM; Wyeth P., 2005, ACM COMPUTERS ENTERT, V3, P1, DOI DOI 10.1145/1077246.1077253; Thomsen D., 2013, HDB HUMAN COMPUTATIO, P265; Tuite K., 2011, P SIGCHI C HUM FACT, P1383, DOI DOI 10.1145/1978942.1979146; von Ahn L, 2004, P SIGCHI C HUM FACT, P319, DOI [DOI 10.1145/985692.985733, DOI 10.1145/985692.985733.ISBN]; Vorderer P, 2004, COMMUN THEOR, V14, P388, DOI 10.1111/j.1468-2885.2004.tb00321.x; Wang HH, 2011, J NANOMATER, DOI 10.1155/2011/547103; Wang R. Y., 1996, Journal of Management Information Systems, V12, P5; Wetzel R., 2012, P INT C FDN DIG GAM, P238; Wu J., 2007, J ELECTRON COMMER RE, V8, P128; Wu JH, 2010, COMPUT HUM BEHAV, V26, P1862, DOI 10.1016/j.chb.2010.07.033; Yuen M. C., 2009, P 2009 INT C COMP SC, P723; Zuckerman O., 2014, PERS UBIQUIT COMPUT, V18, P1704	56	0	0	6	6	PERGAMON-ELSEVIER SCIENCE LTD	OXFORD	THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND	0747-5632	1873-7692		COMPUT HUM BEHAV	Comput. Hum. Behav.	MAY	2017	70						365	374		10.1016/j.chb.2017.01.006		10	Psychology, Multidisciplinary; Psychology, Experimental	Psychology	EO8OP	WOS:000396949400041		No			2017-07-02	
J	Peer, E; Brandimarte, L; Samat, S; Acquisti, A				Peer, Eyal; Brandimarte, Laura; Samat, Sonam; Acquisti, Alessandro			Beyond the Turk: Alternative platforms for crowdsourcing behavioral research	JOURNAL OF EXPERIMENTAL SOCIAL PSYCHOLOGY			English	Article						Online research; Crowdsourcing; Data quality; Amazon Mechanical Turk; Prolific Academic; CrowdFlower	AMAZON MECHANICAL TURK; CONSEQUENCES; WORKERS	The success of Amazon Mechanical Turk (MTurk) as an online research platform has come at a price: MTurk has suffered from slowing rates of population replenishment, and growing participant non-naivety. Recently, a number of alternative platforms have emerged, offering capabilities similar to MTurk but providing access to new and more naive populations. After surveying several options, we empirically examined two such platforms, CrowdFlower (CF) and Prolific Academic (ProA). In two studies, we found that participants on both platforms were more naive and less dishonest compared to MTurk participants. Across the three platforms, CF provided the best response rate, but CF participants failed more attention-check questions and did not reproduce known effects replicated on ProA and MTurk. Moreover, ProA participants produced data quality that was higher than CF's and comparable to MTurk's. ProA and CF participants were also much more diverse than participants from MTurk. (C) 2017 Elsevier Inc. All rights reserved.	[Peer, Eyal] Bar Ilan Univ, Grad Sch Business Adm, IL-52900 Ramat Gan, Israel; [Brandimarte, Laura] Univ Arizona, Eller Coll Management, Tucson, AZ USA; [Samat, Sonam; Acquisti, Alessandro] Carnegie Mellon Univ, Heinz Coll, Pittsburgh, PA 15213 USA	Peer, E (reprint author), Bar Ilan Univ, Grad Sch Business Adm, IL-52900 Ramat Gan, Israel.	eyal.peer@biu.ac.il					Buhrmester M, 2011, PERSPECT PSYCHOL SCI, V6, P3, DOI 10.1177/1745691610393980; CACIOPPO JT, 1984, J PERS ASSESS, V48, P306, DOI 10.1207/s15327752jpa4803_13; Chandler J, 2015, PSYCHOL SCI, V26, P1131, DOI 10.1177/0956797615585115; Chandler J, 2014, BEHAV RES METHODS, V46, P112, DOI 10.3758/s13428-013-0365-7; Crump MJC, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0057410; Fort K, 2011, COMPUT LINGUIST, V37, P413, DOI 10.1162/COLI_a_00057; Goodman JK, 2013, J BEHAV DECIS MAKING, V26, P213, DOI 10.1002/bdm.1753; HAKSTIAN AR, 1976, PSYCHOMETRIKA, V41, P219, DOI 10.1007/BF02291840; Henrich J, 2010, NATURE, V466, P29, DOI 10.1038/466029a; Kahneman D., 1982, JUDGMENT UNCERTAINTY, P201, DOI DOI 10.1017/CBO9780511809477.015; Klein RA, 2014, SOC PSYCHOL-GERMANY, V45, P142, DOI 10.1027/1864-9335/a000178; LORGE I, 1936, THE JOURNAL OF SOCIA, V7, P386; Mason W, 2012, BEHAV RES METHODS, V44, P1, DOI 10.3758/s13428-011-0124-6; Oppenheimer DM, 2009, JUDGM DECIS MAK, V4, P326; Oppenheimer DM, 2009, J EXP SOC PSYCHOL, V45, P867, DOI 10.1016/j.jesp.2009.03.009; Paolacci G, 2010, JUDGM DECIS MAK, V5, P5, DOI DOI 10.1111/NTWE.12038; Paolacci G, 2014, CURR DIR PSYCHOL SCI, V23, P184, DOI 10.1177/0963721414531598; Peer E, 2014, BEHAV RES METHODS, V46, P1023, DOI 10.3758/s13428-013-0434-y; Rand DG, 2012, J THEOR BIOL, V299, P172, DOI 10.1016/j.jtbi.2011.03.004; Rosenberg M., 1979, ROSENBERG SELF ESTEE; Simcox T, 2014, BEHAV RES METHODS, V46, P95, DOI 10.3758/s13428-013-0345-y; Sprouse J, 2011, BEHAV RES METHODS, V43, P155, DOI 10.3758/s13428-010-0039-7; Stewart N, 2015, JUDGM DECIS MAK, V10, P479; STRATHMAN A, 1994, J PERS SOC PSYCHOL, V66, P742, DOI 10.1037/0022-3514.66.4.742; TVERSKY A, 1981, SCIENCE, V211, P453, DOI 10.1126/science.7455683; Vakharia D., 2015, P ICONFERENCE 2015; Woods AT, 2015, PEERJ, V3, DOI 10.7717/peerj.1058	27	4	4	12	12	ACADEMIC PRESS INC ELSEVIER SCIENCE	SAN DIEGO	525 B ST, STE 1900, SAN DIEGO, CA 92101-4495 USA	0022-1031	1096-0465		J EXP SOC PSYCHOL	J. Exp. Soc. Psychol.	MAY	2017	70						153	163		10.1016/j.jesp.2017.01.006		11	Psychology, Social	Psychology	EP4RB	WOS:000397366500017		No			2017-07-02	
J	Probst, T; Pryss, RC; Langguth, B; Spiliopoulou, M; Landgrebe, M; Vesala, M; Harrison, S; Schobel, J; Reichert, M; Stach, M; Schlee, W				Probst, Thomas; Pryss, Ruediger C.; Langguth, Berthold; Spiliopoulou, Myra; Landgrebe, Michael; Vesala, Markku; Harrison, Stephen; Schobel, Johannes; Reichert, Manfred; Stach, Michael; Schlee, Winfried			Outpatient Tinnitus Clinic, Self-Help Web Platform, or Mobile Application to Recruit Tinnitus Study Samples?	FRONTIERS IN AGING NEUROSCIENCE			English	Article						tinnitus; recruitment; crowdsourcing; crowdsensing; clinical data	TRACKYOURTINNITUS APPLICATION; INTERNET; HEALTH; INTERVENTIONS; PREVALENCE; EFFICACY	For understanding the heterogeneity of tinnitus, large samples are required. However, investigations on how samples recruited by different methods differ from each other are lacking. In the present study, three large samples each recruited by different means were compared: N = 5017 individuals registered at a self-help web platform for tinnitus (crowdsourcing platform Tinnitus Talk), N = 867 users of a smart mobile application for tinnitus (crowdsensing platform TrackYourTinnitus), and N = 3786 patients contacting an outpatient tinnitus clinic (Tinnitus Center of the University Hospital Regensburg). The three samples were compared regarding age, gender, and duration of tinnitus (month or years perceiving tinnitus; subjective report) using chi-squared tests. The three samples significantly differed from each other in age, gender and tinnitus duration (p < 0.05). Users of the TrackYourTinnitus crowdsensing platform were younger, users of the Tinnitus Talk crowdsourcing platform had more often female gender, and users of both newer technologies (crowdsourcing and crowdsensing) had more frequently acute/subacute tinnitus (< 3 months and 4-6 months) as well as a very long tinnitus duration (> 20 years). The implications of these findings for clinical research are that newer technologies such as crowdsourcing and crowdsensing platforms offer the possibility to reach individuals hard to get in contact with at an outpatient tinnitus clinic. Depending on the aims and the inclusion/exclusion criteria of a given study, different recruiting strategies (clinic and/or newer technologies) offer different advantages and disadvantages. In general, the representativeness of study results might be increased when tinnitus study samples are recruited in the clinic as well as via crowdsourcing and crowdsensing.	[Probst, Thomas] Georg August Univ Gottingen, Georg Elias Muller Inst Psychol, Gottingen, Germany; [Probst, Thomas; Pryss, Ruediger C.; Schobel, Johannes; Reichert, Manfred; Stach, Michael] Ulm Univ, Inst Databases & Informat Syst, Ulm, Germany; [Langguth, Berthold; Landgrebe, Michael; Schlee, Winfried] Univ Regensburg, Dept Psychiat & Psychotherapy, Univ Regensburg Bezirksklinikum Regensburg, Regensburg, Germany; [Spiliopoulou, Myra] Otto von Guericke Univ, Dept Tech & Business Informat Syst, Magdeburg, Germany; [Landgrebe, Michael] Clin Lech Mangfall, Agatharied, Germany; [Vesala, Markku; Harrison, Stephen] Tinnitus Hub Ltd, Hemsworth, England	Probst, T (reprint author), Georg August Univ Gottingen, Georg Elias Muller Inst Psychol, Gottingen, Germany.; Probst, T (reprint author), Ulm Univ, Inst Databases & Informat Syst, Ulm, Germany.	thomas.probst@ur.de			German Research Foundation (DFG) within the funding programme Open Access Publishing	This work was supported by the German Research Foundation (DFG) within the funding programme Open Access Publishing. The authors would like to thank Ankur Bahre (Otto-vonGuericke-University Magdeburg) for providing helpful references and Vishnu Unnikrishnan (Otto-von-Guericke-University Magdeburg) for the statistical work with the three samples.	ABRAMSON LY, 1978, J ABNORM PSYCHOL, V87, P49, DOI 10.1037//0021-843X.87.1.49; Andersson G, 2015, AM J AUDIOL, V24, P299, DOI 10.1044/2015_AJA-14-0080; Baguley D, 2013, LANCET, V382, P1600, DOI 10.1016/S0140-6736(13)60142-7; Bevelander KE, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0087756; Bhatt JM, 2016, JAMA OTOLARYNGOL, V142, P959, DOI 10.1001/jamaoto.2016.1700; Briones EM, 2017, BEHAV RES METHODS, V49, P320, DOI 10.3758/s13428-016-0710-8; Chandler J, 2016, ANNU REV CLIN PSYCHO, V12, P53, DOI 10.1146/annurev-clinpsy-021815-093623; Donker T, 2013, J MED INTERNET RES, V15, DOI 10.2196/jmir.2791; Estelles-Arolas E, 2012, J INF SCI, V38, P189, DOI 10.1177/0165551512437638; Gallus S, 2015, NEUROEPIDEMIOLOGY, V45, P12, DOI 10.1159/000431376; Ganti R. 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Aging Neurosci.	APR 21	2017	9								113	10.3389/fnagi.2017.00113		7	Geriatrics & Gerontology; Neurosciences	Geriatrics & Gerontology; Neurosciences & Neurology	ET3PW	WOS:000400192900001	28484389	gold			2017-07-02	
J	Wren, JD; Georgescu, C; Giles, CB; Hennessey, J				Wren, Jonathan D.; Georgescu, Constantin; Giles, Cory B.; Hennessey, Jason			Use it or lose it: citations predict the continued online availability of published bioinformatics resources	NUCLEIC ACIDS RESEARCH			English	Article							URL DECAY; JOURNALS; REFERENCES; MEDLINE; MITIGATION; ABSTRACTS; ARTICLES; SCIENCE; TRENDS	Scientific Data Analysis Resources (SDARs) such as bioinformatics programs, web servers and databases are integral to modern science, but previous studies have shown that the Uniform Resource Locators (URLs) linking to them decay in a time-dependent manner, with similar to 27% decayed to date. Because SDARs are overrepresented among science's most cited papers over the past 20 years, loss of widely used SDARs could be particularly disruptive to scientific research. We identified URLs in MEDLINE abstracts and used crowdsourcing to identify which reported the creation of SDARs. We used the Internet Archive's Wayback Machine to approximate 'death dates' and calculate citations/year over each SDAR's lifespan. At first glance, decayed SDARs did not significantly differ from available SDARs in their average citations per year over their lifespan or journal impact factor (JIF). But the most cited SDARs were 94% likely to be relocated to another URL versus only 34% of uncited ones. Taking relocation into account, we find that citations are the strongest predictors of current online availability after time since publication, and JIF modestly predictive. This suggests that URL decay is a general, persistent phenomenon affecting all URLs, but the most useful/recognized SDARs are more likely to persist.	[Wren, Jonathan D.; Georgescu, Constantin; Giles, Cory B.] Oklahoma Med Res Fdn, Arthrit & Clin Immunol Res Program, 825 NE 13th St, Oklahoma City, OK 73104 USA; [Wren, Jonathan D.] Univ Oklahoma, Hlth Sci Ctr, Dept Biochem & Mol Biol, 940 Stanton L Young Blvd, Oklahoma City, OK 73104 USA; [Hennessey, Jason] Boston Univ, Dept Comp Sci, 111 Cummington Mall, Boston, MA 02215 USA	Wren, JD (reprint author), Oklahoma Med Res Fdn, Arthrit & Clin Immunol Res Program, 825 NE 13th St, Oklahoma City, OK 73104 USA.; Wren, JD (reprint author), Univ Oklahoma, Hlth Sci Ctr, Dept Biochem & Mol Biol, 940 Stanton L Young Blvd, Oklahoma City, OK 73104 USA.	jonathan-wren@omrf.org			National Science Foundation [NSF grant] [ACI-1345426]; Institutional funding (OMRF)	National Science Foundation [NSF grant #ACI-1345426]. Funding for open access charge: Institutional funding (OMRF).	Carnevale RJ, 2007, INT J MED INFORM, V76, P269, DOI 10.1016/j.ijmedinf.2005.12.001; Dellavalle RP, 2003, SCIENCE, V302, P787, DOI 10.1126/science.1088234; Ducut E, 2008, BMC MED INFORM DECIS, V8, DOI 10.1186/1472-6947-8-23; Trudel M., 2005, J MED INTERNET RES, V7, pe60; Eysenbach Gunther, 2006, AMIA Annu Symp Proc, P919; Good BM, 2013, BIOINFORMATICS, V29, P1925, DOI 10.1093/bioinformatics/btt333; Habibzadeh P, 2013, APPL CLIN INFORM, V4, P455, DOI 10.4338/ACI-2013-07-RA-0055; Hennessey J, 2014, BMC BIOINFORMATICS, V15, DOI 10.1186/1471-2105-15-S11-S7; Hennessey J, 2013, BMC BIOINFORMATICS, V14, DOI 10.1186/1471-2105-14-S14-S5; Howison J, 2016, J ASSOC INF SCI TECH, V67, P2137, DOI 10.1002/asi.23538; Kelly DP, 2004, PLOS BIOL, V2, P441, DOI 10.1371/journal.pbio.0020099; Parvanta Claudia, 2013, Health Promot Pract, V14, P163, DOI 10.1177/1524839912470654; Peng RD, 2011, SCIENCE, V334, P1226, DOI 10.1126/science.1213847; Perez-Iratxeta C, 2007, BRIEF BIOINFORM, V8, P88, DOI 10.1093/bib/bbl035; Ranard BL, 2014, J GEN INTERN MED, V29, P187, DOI 10.1007/s11606-013-2536-8; Rung J, 2013, NAT REV GENET, V14, P89, DOI 10.1038/nrg3394; Thorp AW, 2011, ANN EMERG MED, V57, P165, DOI 10.1016/j.annemergmed.2010.11.029; Wagner C, 2009, J MED LIBR ASSOC, V97, P122, DOI 10.3163/1536-5050.97.2.009; Whitfield J, 2004, NATURE, V428, P592, DOI 10.1038/428592a; Wren JD, 2004, BIOINFORMATICS, V20, P668, DOI 10.1093/bioinformatics/btg465; Wren JD, 2008, BIOINFORMATICS, V24, P1381, DOI 10.1093/bioinformatics/btn127; Wren JD, 2006, ARCH DERMATOL, V142, P1147, DOI 10.1001/archderm.142.9.1147; Wren JD, 2016, BIOINFORMATICS, V32, P2686, DOI 10.1093/bioinformatics/btw284	23	0	0	8	8	OXFORD UNIV PRESS	OXFORD	GREAT CLARENDON ST, OXFORD OX2 6DP, ENGLAND	0305-1048	1362-4962		NUCLEIC ACIDS RES	Nucleic Acids Res.	APR 20	2017	45	7					3627	3633		10.1093/nar/gkx182		7	Biochemistry & Molecular Biology	Biochemistry & Molecular Biology	ES3SD	WOS:000399448400012	28334982	gold			2017-07-02	
J	Lopez-Aparicio, S; Vogt, M; Schneider, P; Kahila-Tani, M; Broberg, A				Lopez-Aparicio, Susana; Vogt, Matthias; Schneider, Philipp; Kahila-Tani, Maarit; Broberg, Anna			Public participation GIS for improving wood burning emissions from residential heating and urban environmental management	JOURNAL OF ENVIRONMENTAL MANAGEMENT			English	Article						Crowdsourcing; Fuelwood; Urban emissions; Public participation GIS; Co-benefit	AIR-POLLUTION; GEOGRAPHIC INFORMATION; SYSTEMS	A crowdsourcing study supported by a public participation GIS tool was designed and carried out in two Norwegian regions. The aim was to improve the knowledge about emissions from wood burning for residential heating in urban areas based on the collection of citizens' localized insights. We focus on three main issues: 1) type of dwelling and residential heating source; 2) wood consumption and type of wood appliances; and 3) citizens' perception of the urban environment. Our study shows the importance of wood burning for residential heating, and of the resulted particle emissions, in Norwegian urban areas. Citizens' localized insights on environmental perception highlight the areas in the city that require particular attention as part of clean air strategies. Information about environmental perception is combined with existing environmental data showing certain correlation. The results support the urban environmental management based on co-benefit approaches, achieving several outcomes from a single policy measure. Measures to reduce urban air pollution will have a positive impact on the citizens' environmental perception, and therefore on their quality of life, in addition to reducing the negative consequences of air pollution on human health. The characterization of residential heating by fuelwood is still a challenging activity. Our study shows the potential of a crowdsourcing method as means for bottom-up approaches designed to increase our knowledge on human activities at urban scale that result on emissions. (C) 2017 The Authors. Published by Elsevier Ltd.	[Lopez-Aparicio, Susana; Vogt, Matthias; Schneider, Philipp] NILU Norwegian Inst Air Res, Inst Veien 18, N-2027 Kjeller, Norway; [Kahila-Tani, Maarit] Aalto Univ, Dept Real Estate Planning & Geoinformat, Espoo, Finland; [Broberg, Anna] Mapita Ltd, Helsinki, Finland	Lopez-Aparicio, S (reprint author), NILU Norwegian Inst Air Res, Inst Veien 18, N-2027 Kjeller, Norway.	sla@nilu.no			Research Council of Norway through the financing of the iResponse project [247884/070]	This study was made possible thanks to the financial support of the Research Council of Norway through the financing of the iResponse project (247884/070). Special thanks are due to the members of the iResponse project for their support and helpful discussions. We would like to thank all citizens participating in the PPGIS survey.	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Environ. Manage.	APR 15	2017	191						179	188		10.1016/j.jenvman.2017.01.018		10	Environmental Sciences	Environmental Sciences & Ecology	EO8RJ	WOS:000396957300019	28092754	No			2017-07-02	
J	Viana, P; Pinto, JP				Viana, Paula; Pinto, Jose Pedro			A collaborative approach for semantic time-based video annotation using gamification	HUMAN-CENTRIC COMPUTING AND INFORMATION SCIENCES			English	Article						Tagging; Video annotation; Gamification; Crowdsource; Metadata	SYSTEMS	Efficient access to large scale video assets, may it be our life memories in our hard drive or a broadcaster archive which the company is eager to sell, requires content to be conveniently annotated. Manually annotating video content is, however, an intellectually expensive and time-consuming process. In this paper we argue that crowdsourcing, an approach that relies on a remote task force to perform activities that are costly or time-consuming using traditional methods, is a suitable alternative and we describe a solution based on gamification mechanisms for collaboratively collecting timed metadata. Tags introduced by registered players are validated based on a collaborative scoring mechanism that excludes erratic annotations. Voting mechanisms, enabling users to approve or refuse existing tags, provide an extra guarantee on the quality of the annotations. The sense of community is also created as users may watch the crowd's favourite moments of the video provided by a summarization functionality. The system was tested with a pool of volunteers in order to evaluate the quality of the contributions. The results suggest that crowdsourced annotation can describe objects, persons, places, etc. correctly, as well as be very accurate in time.	[Viana, Paula; Pinto, Jose Pedro] INESC TEC, Campus FEUP,Rua Dr Roberto Frias 378, P-4200465 Oporto, Portugal; [Viana, Paula] Polytech Porto, ISEP P Porto Sch Engn, Rua Dr Antonio Bernardino de Almeida 431, P-4200072 Oporto, Portugal	Viana, P (reprint author), INESC TEC, Campus FEUP,Rua Dr Roberto Frias 378, P-4200465 Oporto, Portugal.	paula.viana@inesctec.pt			North Portugal Regional Operational Programme (NORTE), under the PORTUGAL Partnership Agreement; European Regional Development Fund (ERDF) [NORTE-01- 0145-FEDER-000020]	North Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, and through the European Regional Development Fund (ERDF) within FourEyes, a Research Line within project "TEC4Growth - Pervasive Intelligence, Enhancers and Proofs of Concept with Industrial Impact/NORTE-01- 0145-FEDER-000020".	Altadmri A, 2014, MULTIMED TOOLS APPL, V72, P1167, DOI 10.1007/s11042-013-1363-6; Baidya E, 2014, INT CONF CONTEMP, P37, DOI 10.1109/IC3.2014.6897144; Ballesteros Luis Guillermo Martinez, 2010, Proceedings of the 2010 IEEE ANDESCON, DOI 10.1109/ANDESCON.2010.5632320; Bertini M, 2005, P 13 ANN ACM INT C M, P395, DOI 10.1145/1101149.1101235; Brooklyn Museum-Tag! You're it!, 2015, TAG YOUR IT TAG YOUR; Chu W-T, 2011, P INT ACM WORKSH SOC, P35; Chua T-S, 2009, NUS WIDE REAL WORLD; Davis SJ, 2009, IEEE MULTIMEDIA, V16, P52, DOI 10.1109/MMUL.2009.95; Eggink J, 2013, 2013 14 I NT WORKSH, P1; Ferracani A, 2015, P 23 ACM INT C MULT, P757; Golder SA, 2006, J INF SCI, V32, P198, DOI 10.1177/0165551506062337; Hildebrand M, 2013, P 21 ACM INT C MULT, P823; Larson M, 2011, P 1 ACM INT C MULT R; Li G, 2011, P 1 ACM INT C MULT R; Li QF, 2008, IEEE MULTIMEDIA, V15, P14, DOI 10.1109/MMUL.2008.54; Marlow C, 2006, ACM 7 C HYP HYP, P31; Metadata Games, 2015, MET GAM PLAY TAG; Miettinen V, 2011, P 4 ACM WORKSH ONL B, P55; Mishne G, 2006, P 15 INT C WORLD WID, P953, DOI DOI 10.1145/1135777.1135961; Moxley E, 2008, 2008 IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA AND EXPO, VOLS 1-4, P685, DOI 10.1109/ICME.2008.4607527; Nga DH, 2013, P 21 ACM INT C MULT, P525; OntoGames, 2015, GAM DEM CONT CREAT; Pinto JP, 2015, P 12 EUR C VIS MED P; Pinto JP, 2013, P 21 ACM INT C MULT, P25; Riek LD, 2011, P 4 INT C AFF COMP I, P277; Siorpaes K, 2008, IEEE INTELL SYST, V23, P50, DOI 10.1109/MIS.2008.45; Snoek CGM, 2010, P INT C MULT MM 10, P1535, DOI 10.1145/1873951.1874278; Soares M, 2015, MULTIMED TOOLS APPL, V74, P7015, DOI 10.1007/s11042-014-1950-1; Sood S, 2007, TAGASSIST AUTOMATIC; Tiltfactor, 2015, TILTF GAM; Tran H-T, 2013, EXTRACTION GESTION C, P461; Viddler, 2015, VIDDL INT VID TRAIN; videoTag, 2015, VID VID TAGG GAM SOC; Wu B, 2014, P 20 ACM SIGKKD INT, P721; Xu P, 2014, P 2014 INT ACM WORKS, P57; Yang HJ, 2014, IEEE T LEARN TECHNOL, V7, P142, DOI 10.1109/TLT.2014.2307305; Yang HJ, 2014, MULTIMED TOOLS APPL, V69, P217, DOI 10.1007/s11042-012-1250-6; Yang Q, 2008, P INT C IM VID RETR, P591, DOI 10.1145/1386352.1386438; Yang Y, 2011, P INT C MULT, P1137; Yao T, 2013, P ACM MULT, P977	40	0	0	1	1	SPRINGER HEIDELBERG	HEIDELBERG	TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY	2192-1962			HUM-CENTRIC COMPUT I	Human-centric Comput. Inf. Sci.	APR 12	2017	7								13	10.1186/s13673-017-0094-5		21	Computer Science, Information Systems	Computer Science	EW0UL	WOS:000402206600001		gold			2017-07-02	
J	Ciavarrini, G; Luconi, V; Vecchio, A				Ciavarrini, Gloria; Luconi, Valerio; Vecchio, Alessio			Smartphone-based geolocation of Internet hosts	COMPUTER NETWORKS			English	Article						IP geolocation; Smartphone; Crowdsourcing; Network measurement		The location of Internet hosts is frequently used in distributed applications and networking services. Examples include customized advertising, distribution of content, and position-based security. Unfortunately the relationship between an IP address and its position is in general very weak. This motivates the study of measurement-based IP geolocation techniques, where the position of the target host is actively estimated using the delays between a number of landmarks and the target itself. This paper discusses an IP geolocation method based on crowdsourcing where the smartphones of users operate as landmarks. Since smartphones rely on wireless connections, a specific delay-distance model was derived to capture the characteristics of this novel operating scenario. (C) 2017 Elsevier B.V. All rights reserved.	[Ciavarrini, Gloria; Vecchio, Alessio] Univ Pisa, Dip Ingn Informaz, Largo L Lazzarino 1, I-56122 Pisa, Italy; [Luconi, Valerio] CNR, Ist Informat & Telemat, Via G Moruzzi 1, I-56124 Pisa, Italy	Vecchio, A (reprint author), Univ Pisa, Dip Ingn Informaz, Largo L Lazzarino 1, I-56122 Pisa, Italy.	gloria.ciavarrini@for.unipi.it; valerio.luconi@iit.cnr.it; alessio.vecchio@unipi.it					Choffnes DR, 2010, ACM SIGCOMM COMP COM, V40, P387, DOI 10.1145/1851275.1851228; Chun B, 2003, ACM SIGCOMM COMP COM, V33, P3, DOI 10.1145/956993.956995; Daigle L., 2004, 3912 RFC, DOI 10.17487/RFC3912; Davis C., 1996, 1876 RFC NETW WORK G; Dong ZQ, 2012, COMPUT NETW, V56, P85, DOI 10.1016/j.comnet.2011.08.011; Duda R., 2000, PATTERN CLASSIFICATI; Faggiani A., 2012, P 10 INT S MOD OPT M, P318; Faggiani A., 2013, P 1 INT WORKSH SENS, DOI [10.1145/2536714.2536717, DOI 10.1145/2536714.2536717]; Faggiani A, 2014, IEEE COMMUN MAG, V52, P106, DOI 10.1109/MCOM.2014.6710071; Freedman M.J., 2005, P 5 ACM SIGCOMM C IN, P13; Gondree M., 2013, P 3 ACM C DAT APPL S, P25, DOI DOI 10.1145/2435349.2435353; Gregori E, 2013, INT CONF PERVAS COMP, P248; Gueye B, 2006, IEEE ACM T NETWORK, V14, P1219, DOI 10.1109/TNET.2006.886332; Hawkinson J., 1996, 1930 RFC; HORTON JJ, 2010, P ACM 11 ACM C EL CO, V11, P209, DOI DOI 10.1145/1807342.1807376; Howe J, 2008, CROWDSOURCING POWER; Katz-Bassett E., 2006, P 6 ACM SIGCOMM C IN, P71, DOI 10.1145/1177080.1177090; Komosny D, 2015, 2015 38TH INTERNATIONAL CONFERENCE ON TELECOMMUNICATIONS AND SIGNAL PROCESSING (TSP), P642, DOI 10.1109/TSP.2015.7296342; Laki S, 2010, COMPUT NETW, V54, P1490, DOI 10.1016/j.comnet.2009.12.004; Laki S., 2011, P IEEE INFOCOM, P3173, DOI 10.1109/INFCOM.2011.5935165; Li W., 2015, 2015 IEEE C COMP COM, P370, DOI [10.1109/INFOCOM.2015.7218402, DOI 10.1109/INFOCOM.2015.7218402]; Mao A., 2013, 1 AAAI C HUM COMP CR; Matthews W, 2000, IEEE COMMUN MAG, V38, P130, DOI 10.1109/35.841837; Padmanabhan VN, 2001, ACM SIGCOMM COMP COM, V31, P173, DOI 10.1145/964723.383073; Poese I, 2011, ACM SIGCOMM COMP COM, V41, P53, DOI 10.1145/1971162.1971171; Wong B., 2007, 2007 P NSDI, V7, P23; Yang DJ, 2012, MOBICOM 12: PROCEEDINGS OF THE 18TH ANNUAL INTERNATIONAL CONFERENCE ON MOBILE COMPUTING AND NETWORKING, P173; Youn I., 2009, P 18 INT C COMP COMM, P1, DOI 10.1109/ICCCN.2009.5235373; Zhang M, 2006, USENIX Association Proceedings of the 2006 USENIX Annual Technical Conference, P369; Ziviani A, 2005, COMPUT NETW, V47, P503, DOI 10.1016/j.comnet.2004.08.013; [Anonymous], 2016, GEOLP	31	0	0	4	4	ELSEVIER SCIENCE BV	AMSTERDAM	PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS	1389-1286	1872-7069		COMPUT NETW	Comput. Netw.	APR 7	2017	116						22	32		10.1016/j.comnet.2017.02.006		11	Computer Science, Hardware & Architecture; Computer Science, Information Systems; Engineering, Electrical & Electronic; Telecommunications	Computer Science; Engineering; Telecommunications	EP9LE	WOS:000397694300003		No			2017-07-02	
J	Salk, CF; Sturn, T; See, L; Fritz, S				Salk, Carl F.; Sturn, Tobias; See, Linda; Fritz, Steffen			Limitations of Majority Agreement in Crowdsourced Image Interpretation	TRANSACTIONS IN GIS			English	Article							CITIZEN SCIENCE; QUALITY	Crowdsourcing can efficiently complete tasks that are difficult to automate, but the quality of crowd-sourced data is tricky to evaluate. Algorithms to grade volunteer work often assume that all tasks are similarly difficult, an assumption that is frequently false. We use a cropland identification game with over 2,600 participants and 165,000 unique tasks to investigate how best to evaluate the difficulty of crowd-sourced tasks and to what extent this is possible based on volunteer responses alone. Inter-volunteer agreement exceeded 90% for about 80% of the images and was negatively correlated with volunteer-expressed uncertainty about image classification. A total of 343 relatively difficult images were independently classified as cropland, non-cropland or impossible by two experts. The experts disagreed weakly (one said impossible while the other rated as cropland or non-cropland) on 27% of the images, but disagreed strongly (cropland vs. non-cropland) on only 7%. Inter-volunteer disagreement increased significantly with inter-expert disagreement. While volunteers agreed with expert classifications for most images, over 20% would have been mis-categorized if only the volunteers' majority vote was used. We end with a series of recommendations for managing the challenges posed by heterogeneous tasks in crowdsourcing campaigns.	[Salk, Carl F.; Sturn, Tobias; See, Linda; Fritz, Steffen] Int Inst Appl Syst Anal, Laxenburg, Austria; [Salk, Carl F.] Swedish Univ Agr Sci, Alnarp, Sweden	Salk, CF (reprint author), Int Inst Appl Syst Anal, Ecosyst Serv & Management Program, Schlosspl 1, A-2361 Laxenburg, Austria.	salk@iiasa.ac.at			IIASA postdoctoral fellowship; ERC CrowdLand project [617754]; ERC SIGMA project [603719]	This research was supported by a IIASA postdoctoral fellowship to Carl Salk and the ERC CrowdLand (617754) and SIGMA (603719) projects.	Allahbakhsh M, 2013, IEEE INTERNET COMPUT, V17, P76, DOI 10.1109/MIC.2013.20; Bachrach Y, 2012, P 29 INT C MACH LEAR; Battersby SE, 2012, PHOTOGRAMM ENG REM S, V78, P625; Bernstein Michael S., 2010, P 23 ANN ACM S US IN, P313, DOI DOI 10.1145/1866029.1866078; Bianchetti R A, 2014, THESIS; Bohannon J, 2009, WIRED MAGAZINE, P17; Bonney R, 2009, BIOSCIENCE, V59, P977, DOI 10.1525/bio.2009.59.11.9; Buhrmester M, 2011, PERSPECT PSYCHOL SCI, V6, P3, DOI 10.1177/1745691610393980; Dawid A P, 1979, APPL STAT, V28, P20, DOI DOI 10.2307/2346806; FAO, 2013, FAO GLOSS; Fritz S, 2013, ENVIRON SCI TECHNOL, V47, P1688, DOI 10.1021/es303141h; Goodchild MF, 2007, GEOJOURNAL, V69, P211, DOI 10.1007/s10708-007-9111-y; Haklay M, 2013, CROWDSOURCING GEOGRA, P105, DOI DOI 10.1007/978-94-007-4587-2_7; Hoffman R R, 1990, GEOCARTO INT, V2, P3; Howe J, 2006, WIRED, P14; Hunter J, 2013, CONCURR COMP-PRACT E, V25, P454, DOI 10.1002/cpe.2923; Ipeirotis P G, 2010, P 2 HUM COMP WORKSH; Lintott CJ, 2008, MON NOT R ASTRON SOC, V389, P1179, DOI 10.1111/j.1365-2966.2008.13689.x; Lloyd R., 2002, CARTOGR GEOGR INF SC, V29, P3, DOI DOI 10.1559/152304002782064592; Mekler E D, 2013, P 1 INT C GAM DES RE, P66, DOI DOI 10.1145/2583008.2583017; Oreg S, 2008, COMPUT HUM BEHAV, V24, P2055, DOI 10.1016/j.chb.2007.09.007; Pourabdollah A, 2013, ISPRS INT GEO-INF, V2, P704, DOI 10.3390/ijgi2030704; R Core Team, 2014, R LANG ENV STAT COMP; Raddick M J, 2013, ASTRON ED REV, V12, DOI DOI 10.3847/AER2011021; Salk C F, 2015, INT J DIGIT IN PRESS, V8; See L, 2014, P 17 AGILE INT C GEO; See L, 2015, ISPRS J PHOTOGRAMM, V103, P48, DOI 10.1016/j.isprsjprs.2014.06.016; Silvertown J, 2009, TRENDS ECOL EVOL, V24, P467, DOI 10.1016/j.tree.2009.03.017; von Ahn L, 2004, P SIGCHI C HUM FACT, P319, DOI [DOI 10.1145/985692.985733, DOI 10.1145/985692.985733.ISBN]; Wang J, 2013, CBA1306 NEW YORK U S; Welinder P, 2010, P 24 INT C ADV NEUR; Whitehill J, 2009, P ADV NEUR INF PROC, P2035; Zhao YY, 2014, INT J REMOTE SENS, V35, P4795, DOI 10.1080/01431161.2014.930202	33	0	0	0	0	WILEY	HOBOKEN	111 RIVER ST, HOBOKEN 07030-5774, NJ USA	1361-1682	1467-9671		T GIS	Trans. GIS	APR	2017	21	2					207	223		10.1111/tgis.12194		17	Geography	Geography	EX6CK	WOS:000403329800003		No			2017-07-02	
J	Poblet, M; Fitzpatrick, M; Chhetri, P				Poblet, Marta; Fitzpatrick, Mari; Chhetri, Prem			Microtasking: redefining crowdsourcing practices in emergency management	AUSTRALIAN JOURNAL OF EMERGENCY MANAGEMENT			English	Article								This paper examines the roles, types and forms of virtual microtasking for emergency information management in order to better understand collective intelligence mechanisms and the potential for logistics response. Using three case studies this paper reviews the emerging body of knowledge in microtasking practices in emergency management to demonstrate how crowd-sourced information is captured and processed during emergency events to provide critical intelligence throughout the emergency cycle. It also considers the impact of virtual information collection, collation and management on traditional humanitarian operations and relief efforts. Based on the case studies the emergent forms of microtasking for emergency information management were identified. Opportunities for continuities, adaptations and innovations are explained. The contribution of virtual microtasking extends to all supply chain strategic domains to help maximise resource use and optimise service delivery response.	[Poblet, Marta] RMIT Univ, Melbourne, Vic, Australia; [Fitzpatrick, Mari] RMIT Univ, Grad Sch Business & Law, Melbourne, Vic, Australia; [Chhetri, Prem] RMIT Univ, Geologist, Melbourne, Vic, Australia	Poblet, M (reprint author), RMIT Univ, Melbourne, Vic, Australia.						Benkler Y, 2013, PEER PRODUCTIO UNPUB; Blumberg M, 2013, HDB HUMAN COMPUTATIO, P5; Blumberg M, 2013, HDB HUMAN COMPUTATIO, P3; Bollier D, 2014, WEIGHTLESS MARKETPLA; Cloutier P, 2014, DIGITAL VOLUNTEERS E, P1; Cobb C, 2014, COMPUTER SUPPORTED C, V14, P1; Estelles-Arolas E, 2012, J INF SCI, V38, P189, DOI 10.1177/0165551512437638; Franzoni C, 2014, RES POLICY, V43, P1, DOI 10.1016/j.respol.2013.07.005; Hossain Mokter, 2015, Strategic Outsourcing, V8, P2, DOI 10.1108/SO-12-2014-0029; Kittur A, 2013, P 2013 C COMP SUPP C, P1301, DOI DOI 10.1145/2441776.2441923; Liu S, 2014, COMPUTER SUPPORTED C, V23, P389; Luz N, 2014, ARTIF INTELL, P1; Manyika J, 2014, GLOBAL FLOWS DIGITAL, P1; Mees B, 2016, AUST J EMERG MANAG, V31, P38; Michelucci P, 2013, HDB HUMAN COMPUTATIO; MUNRO R, 2013, J INFORM RETRIEVAL, V16, P210, DOI DOI 10.1007/S10791-012-9203-2; Novak J, 2013, HDB HUMAN COMPUTATIO, P421; Conference CHI, 2011, CHI C 7 12 MAY 2011; Reuter S, 2014, NAT VOAD C 2014; Saito S, 2014, UNIVERSAL ACCESS HUM, DOI [10.1007/978-3-319-07440-5_37, DOI 10.1007/978-3-319-07440-5_37]; Starbird K, 2013, P 2013 C COMP SUPP C, P491, DOI DOI 10.1145/2441776.2441832	21	0	0	0	0	EMERGENCY MANAGEMENT AUSTRALIA	MOUNT MACEDON	601 MOUNT MACEDON RD, MOUNT MACEDON, VIC 3441, AUSTRALIA	1324-1540			AUST J EMERG MANAG	Aust. J. Emerg. Manag.	APR	2017	32	2					47	53				7	Public, Environmental & Occupational Health	Public, Environmental & Occupational Health	EX2JO	WOS:000403052700017		No			2017-07-02	
J	McDuff, D; el Kaliouby, R				McDuff, Daniel; el Kaliouby, Rana			Applications of Automated Facial Coding in Media Measurement	IEEE TRANSACTIONS ON AFFECTIVE COMPUTING			English	Article						Facial expressions; facial coding; emotion; media measurement; advertising; marketing; crowdsourcing	SEX-DIFFERENCES; ADVERTISEMENT; RECOGNITION; COMMERCIALS; RESPONSES; PATTERNS; SMILE; SCALE; ADS	Facial coding has become a common tool in media measurement, with large companies (e.g., Unilever) using it to test all of their new video ad content. Facial reactions capture the in-the-moment response of an individual and these data complement self-report measures. Two advancements in affective computing have made measurement possible at scale: 1) computer vision algorithms are used to automatically code sign and message judgments based on facial muscle movements, 2) video data are collected by recording responses in everyday environments via the viewer's own webcam over the Internet. We present results of online facial coding studies of video ads, movie trailers, political content, and long-form TV shows. We explain how these data can be used in market research. Despite the ability to measure facial behavior in a scalable and quantifiable way, the interpretation of these data is still challenging without baselines and comparative measures. Over the past four years we have collected and coded over two million responses to everyday media content. Our huge dataset allows us to calculate reliable normative distributions of responses across different media types. We present these data and argue that this provides a context within which to interpret facial responses more accurately.	[McDuff, Daniel; el Kaliouby, Rana] Affectiva, Waltham, MA 02452 USA; [McDuff, Daniel] MIT, Media Lab, Cambridge, MA 02139 USA	McDuff, D (reprint author), Affectiva, Waltham, MA 02452 USA.; McDuff, D (reprint author), MIT, Media Lab, Cambridge, MA 02139 USA.	djmcduff@media.mit.edu; kaliouby@affectiva.com					Cohn J. F., 2007, HDB EMOTION ELICITAT, P203; D'Mello S, 2007, IEEE INTELL SYST, V22, P53, DOI 10.1109/MIS.2007.79; Dalai N., 2005, PROC CVPR IEEE, V1, P886, DOI DOI 10.1109/CVPR.2005.177; DERBAIX CM, 1995, J MARKETING RES, V32, P470, DOI 10.2307/3152182; Ekman P., 1978, MANUAL FACIAL ACTION; Fasel B., 2002, P INT C PATT REC ICP, V2, P40; FRIDLUND AJ, 1991, J PERS SOC PSYCHOL, V60, P229, DOI 10.1037/0022-3514.60.2.229; Friesen W. V., 1973, THESIS U CALIFORNIA; Girard J. M., 2015, IEEE INT C AUT FAC G, P1; Hernandez J., 2013, PRODUCTION PLANNING, P1; Joho H, 2011, MULTIMED TOOLS APPL, V51, P505, DOI 10.1007/s11042-010-0632-x; Kassam K. S., 2010, ASSESSMENT EMOTIONAL; LaFrance M, 2003, PSYCHOL BULL, V129, P305, DOI 10.1037/0033-2909.129.2.305; Matsugu M, 2003, NEURAL NETWORKS, V16, P555, DOI 10.1016/S0893-6080(03)00115-1; MATSUMOTO D, 1990, MOTIV EMOTION, V14, P195, DOI 10.1007/BF00995569; McDuff D., J NONVERBAL IN PRESS; McDuff D., 2013, P 10 IEEE INT C WORK, P1; McDuff D., 2012, AFFECTIVE COMPUTING, V3, P456; McDuff D, 2015, IEEE T AFFECT COMPUT, V6, P223, DOI 10.1109/TAFFC.2014.2384198; Mcduff D, 2013, INT CONF AFFECT, P369, DOI 10.1109/ACII.2013.67; McDuff D. J., 2014, THESIS MIT CAMBRIDGE; Micu AC, 2010, J ADVERTISING RES, V50, P137, DOI 10.2501/S0021849910091300; Navarathna R, 2014, 2014 IEEE WINTER CONFERENCE ON APPLICATIONS OF COMPUTER VISION (WACV), P1058, DOI 10.1109/WACV.2014.6835987; Ojala T, 2002, IEEE T PATTERN ANAL, V24, P971, DOI 10.1109/TPAMI.2002.1017623; Otta E, 1998, PSYCHOL REP, V83, P907, DOI 10.2466/PR0.83.7.907-913; Poh MZ, 2011, IEEE T BIO-MED ENG, V58, P7, DOI 10.1109/TBME.2010.2086456; Senechal T., 2013, P 10 IEEE INT C AUT, P1, DOI DOI 10.1109/FG2013.6553776; Soleymani M., 2009, INT J SEMANTIC COMPU, V3, P235; Soleymani M, 2012, IEEE T AFFECT COMPUT, V3, P211, DOI 10.1109/T-AFFC.2011.37; Soleymani M, 2008, IEEE INT SYM MULTIM, P228, DOI 10.1109/ISM.2008.14; Teixeira T, 2014, MARKET SCI, V33, P809, DOI 10.1287/mksc.2014.0854; Teixeira TS, 2010, MARKET SCI, V29, P783, DOI 10.1287/mksc.1100.0567; Valstar M., 2015, UNDERSTANDING FACIAL, P143; Viola P, 2001, PROC CVPR IEEE, P511; Wang SF, 2014, IMAGE VISION COMPUT, V32, P682, DOI 10.1016/j.imavis.2014.04.013; Warren S. D., 1890, HARVARD LAW REV, V4, P193, DOI DOI 10.2307/1321160; Xiong XH, 2013, PROC CVPR IEEE, P532, DOI 10.1109/CVPR.2013.75; Yang SF, 2014, IEEE T AFFECT COMPUT, V5, P432, DOI 10.1109/TAFFC.2014.2364581; Zhao S., 2011, P 19 ACM INT C MULT, P1473	39	0	0	0	0	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC	PISCATAWAY	445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA	1949-3045			IEEE T AFFECT COMPUT	IEEE Trans. Affect. Comput.	APR-JUN	2017	8	2					148	160		10.1109/TAFFC.2016.2571284		13	Computer Science, Artificial Intelligence; Computer Science, Cybernetics	Computer Science	EW7QS	WOS:000402709900002		No			2017-07-02	
J	Pu, LJ; Chen, X; Xu, JD; Fu, XM				Pu, Lingjun; Chen, Xu; Xu, Jingdong; Fu, Xiaoming			Crowd Foraging: A QoS-Oriented Self-Organized Mobile Crowdsourcing Framework Over Opportunistic Networks	IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS			English	Article						Mobile crowdsourcing; service quality; worker recruitment; opportunistic networks	SOCIAL NETWORKS	Recent years have witnessed the proliferation of mobile crowdsourcing that brings a new opportunity to leverage human intelligence and movement behaviors to wider application areas. In parallel with the development of online centralized platforms, we look into the realization of self-organized mobile crowdsourcing drawing on opportunistic networks, and propose the Crowd Foraging framework, in which a mobile task requester can proactively recruit a massive crowd of opportunistic encountered mobile workers in real time for quick and high-quality results. We present a comprehensive framework model that fully integrates human behavior factors for modeling task profile, worker arrival, and work ability, and then introduce a service quality concept to indicate the expected service gain that a requester can enjoy when she recruits an arrival worker by jointly considering the work ability of workers as well as timeliness and reward of tasks. Furthermore, we formulate a sequential worker recruitment problem as an online multiple stopping problem to maximize the expected sum of service quality, and accordingly derive an optimal worker recruitment policy through the dynamic programming principle, which exhibits a nice threshold-based structure. We provide data-driven case studies to validate the assumptions used in the policy design, and conduct extensive trace-driven numerical evaluations, which demonstrate that our policy can achieve superior performance (e.g., improve more than 30% performance over classic policies). Besides, our Android prototype shows that the Crowd Foraging framework is cost-efficient, such as requiring less than 7 s and 6 J in terms of time and energy consumption for the optimal threshold calculation in our policy in most cases.	[Pu, Lingjun; Xu, Jingdong] Nankai Univ, Coll Comp & Control Engn, Tianjin 300071, Peoples R China; [Chen, Xu] Sun Yat Sen Univ, Sch Data & Comp Sci, Guangzhou 510006, Guangdong, Peoples R China; [Chen, Xu] Minist Educ, Key Lab Machine Intelligence & Adv Comp, Guangzhou 510006, Guangdong, Peoples R China; [Fu, Xiaoming] Univ Gottingen, Inst Comp Sci, D-37073 Gottingen, Germany	Chen, X (reprint author), Sun Yat Sen Univ, Sch Data & Comp Sci, Guangzhou 510006, Guangdong, Peoples R China.; Chen, X (reprint author), Minist Educ, Key Lab Machine Intelligence & Adv Comp, Guangzhou 510006, Guangdong, Peoples R China.	pulingjun@nankai.edu.cn; chenxu35@mail.sysu.edu.cn; xujd@nankai.edu.cn; fu@cs.uni-goettingen.de			National Key Research and Development Program of China [2016YFB0201900]; Sun Yat-Sen University; EU FP7 IRSES MobileCloud Project [612212]; EU-Japan Horizon2020 ICN2020 Project through EU [723014]; NICT [184]; Alexander Humboldt Foundation; Natural Science Foundation of Tianjin, China [16JCQNJC00700]	This work was supported in part by the National Key Research and Development Program of China under Grant 2016YFB0201900, in part by the Start-Up Fund from Sun Yat-Sen University, in part by the EU FP7 IRSES MobileCloud Project under Grant 612212, in part by the EU-Japan Horizon2020 ICN2020 Project through EU under Grant 723014 and NICT under Grant 184, in part by the Alexander Humboldt Foundation, and in part by the Natural Science Foundation of Tianjin, China, under Grant 16JCQNJC00700. Part of the results in this paper was presented at the Proceedings of the IEEE International Conference on Computer Communications, April 10-15, 2016, San Francisco, CA, USA. (Corresponding author: Xu Chen).	Agapie E., 2015, P AAAI C HUM COMP CR, P2; Asadi A., 2014, IEEE COMMUNICATIONS, V4, P1801; Babaioff M, 2007, LECT NOTES COMPUT SC, V4627, P16; Blondel VD, 2008, J STAT MECH-THEORY E, DOI 10.1088/1742-5468/2008/10/P10008; Boutsis I, 2014, INT CON DISTR COMP S, P1, DOI 10.1109/ICDCS.2014.9; Cai H, 2009, IEEE ACM T NETWORK, V17, P1578, DOI 10.1109/TNET.2008.2011734; Chang W, 2015, IEEE T PARALL DISTR, V26, P2020, DOI 10.1109/TPDS.2014.2330298; Difallah D. 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J	Xiang, LY; Tai, TY; Li, BC; Li, B				Xiang, Liyao; Tai, Tzu-Yin; Li, Baochun; Li, Bo			Tack: Learning Towards Contextual and Ephemeral Indoor Localization With Crowdsourcing	IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS			English	Article						Smart devices; bluetooth; crowdsourcing; indoor environments; localization; mobile computing; inference mechanisms; particle filters		At events, such as conferences, indoor localization is both contextual and ephemeral, in that localization is only needed within the context of and for the duration of the event. As such, the costs and requirements of providing such services need to be minimal. In this paper, we design, implement, and evaluate Tack, a new mobile application framework that is specifically engineered to support such contextual and ephemeral indoor localization during an event. To provide location-based services with Tack, an event organizer only needs to bring and place a small number of (reusable) beacons around the venue before the event begins. As a system framework, Tack uses a combination of known beacon locations, contacts over bluetooth low energy, crowdsourcing, and dead-reckoning to estimate and refine user locations. To make our location estimates more accurate, we embrace the inherent nature of beacons, design crowdsourcing-based inference algorithms, and present an extensive evaluation by running real-world experiments with iOS devices and beacons. Tack has been implemented as an open-source framework on the iOS platform and can be used by mobile applications designed for events with location-based services.	[Xiang, Liyao] Univ Toronto, Dept Elect & Comp Engn, Toronto, ON M5S 3G4, Canada; [Tai, Tzu-Yin] Univ Toronto, Toronto, ON M5S 3G4, Canada; Hong Kong Univ Sci & Technol, Dept Comp Sci & Engn, Hong Kong, Hong Kong, Peoples R China	Xiang, LY (reprint author), Univ Toronto, Dept Elect & Comp Engn, Toronto, ON M5S 3G4, Canada.	liyaox@ece.utoronto.ca; nina.tai@mail.utoronto.ca; bli@ece.toronto.edu; bli@cse.ust.hk			RGC [615613, 16211715, C7036-15G (CRF)]; NSF China [U1301253]	This work was supported in part by RGC under Contract 615613, Contract 16211715, and C7036-15G (CRF), and in part by NSF China under Contract U1301253.	Abdelnasser H, 2016, IEEE T MOBILE COMPUT, V15, P1770, DOI 10.1109/TMC.2015.2478451; Bahl P., 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064), P775, DOI 10.1109/INFCOM.2000.832252; Chintalapudi K, 2010, MOBICOM 10 & MOBIHOC 10: PROCEEDINGS OF THE 16TH ANNUAL INTERNATIONAL CONFERENCE ON MOBILE COMPUTING AND NETWORKING AND THE 11TH ACM INTERNATIONAL SYMPOSIUM ON MOBILE AD HOC NETWORKING AND COMPUTING, P173; Constandache I., 2010, P IEEE INFOCOM, P1, DOI DOI 10.1109/INECOM.2010.5462058; Constandache I, 2010, MOBICOM 10 & MOBIHOC 10: PROCEEDINGS OF THE 16TH ANNUAL INTERNATIONAL CONFERENCE ON MOBILE COMPUTING AND NETWORKING AND THE 11TH ACM INTERNATIONAL SYMPOSIUM ON MOBILE AD HOC NETWORKING AND COMPUTING, P149; He SN, 2017, IEEE T MOBILE COMPUT, V16, P1897, DOI 10.1109/TMC.2016.2608946; Jun J., 2013, P 11 ACM C EMB NETW, P14; Rai A, 2012, MOBICOM 12: PROCEEDINGS OF THE 18TH ANNUAL INTERNATIONAL CONFERENCE ON MOBILE COMPUTING AND NETWORKING, P293; Rekleitis I. M., 2004, TRCIM0402 MCGILL U; Shen G., 2013, P 10 USENIX C NETW S, P85; Sorour S, 2015, IEEE T MOBILE COMPUT, V14, P1031, DOI 10.1109/TMC.2014.2343636; Wang H., 2012, P ACM MOB JUN, V10, P197, DOI DOI 10.HTTP://DX.D0I.0M/10.1145/2307636.2307655; Wang PC, 2011, ACM SIGCOMM COMP COM, V41, P386, DOI 10.1145/2043164.2018481; Wu CS, 2015, IEEE T MOBILE COMPUT, V14, P444, DOI 10.1109/TMC.2014.2320254; Xie HW, 2016, IEEE T MOBILE COMPUT, V15, P1877, DOI 10.1109/TMC.2015.2480064; Xiong J., 2013, P 10 USENIX C NETW S, P71; Youssef M, 2005, Proceedings of the Third International Conference on Mobile Systems, Applications, and Services (MobiSys 2005), P205, DOI 10.1145/1067170.1067193; Zafari F., 2015, P IEEE GLOB COMM C G, P1; Zheng Y., 2014, P 20 ANN INT C MOB C, P471	19	0	0	0	0	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC	PISCATAWAY	445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA	0733-8716	1558-0008		IEEE J SEL AREA COMM	IEEE J. Sel. Areas Commun.	APR	2017	35	4					863	879		10.1109/JSAC.2017.2679605		17	Engineering, Electrical & Electronic; Telecommunications	Engineering; Telecommunications	EW0AX	WOS:000402151400004		No			2017-07-02	
J	Zhang, YR; Jiang, CJ; Song, LY; Pan, M; Dawy, Z; Han, Z				Zhang, Yanru; Jiang, Chunxiao; Song, Lingyang; Pan, Miao; Dawy, Zaher; Han, Zhu			Incentive Mechanism for Mobile Crowdsourcing Using an Optimized Tournament Model	IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS			English	Article						Mobile crowdsourcing; incentive mechanism; contract theory; moral hazard; tournament	DESIGN; CONTRACTS; CONTESTS	With the wide adoption of smart mobile devices, there is a rapid development of location-based services. One key feature of supporting a pleasant/excellent service is the access to adequate and comprehensive data, which can be obtained by mobile crowdsourcing. The main challenge in crowdsourcing is how the service provider (principal) incentivizes a large group of mobile users to participate. In this paper, we investigate the problem of designing a crowdsourcing tournament to maximize the principal's utility in crowdsourcing and provide continuous incentives for users by rewarding them based on the rank achieved. First, we model the user's utility of reward from achieving one of the winning ranks in the tournament. Then, the utility maximization problem of the principal is formulated, under the constraint that the user maximizes its own utility by choosing the optimal effort in the crowdsourcing tournament. Finally, we present numerical results to show the parameters' impact on the tournament design and compare the system performance under the different proposed incentive mechanisms. We show that by using the tournament, the principal successfully maximizes the utilities, and users obtain the continuous incentives to participate in the crowdsourcing activity.	[Zhang, Yanru; Pan, Miao; Han, Zhu] Univ Houston, Dept Elect & Comp Engn, Houston, TX 77004 USA; [Jiang, Chunxiao] Tsinghua Univ, Tsinghua Space Ctr, Beijing 100084, Peoples R China; [Song, Lingyang] Peking Univ, Sch Elect Engn & Comp Sci, Beijing 100871, Peoples R China; [Dawy, Zaher] Amer Univ Beirut, Elect & Comp Engn Dept, Beirut 11072020, Lebanon	Zhang, YR (reprint author), Univ Houston, Dept Elect & Comp Engn, Houston, TX 77004 USA.	yzhang82@uh.edu; jchx@tsinghua.edu.cn; lingyang.song@pku.edu.cn; mpan2@uh.edu; zd03@aub.edu.lb; zhan2@uh.edu			U.S. National Science Foundation [CNS-1343361, CNS-1350230, CPS-1646607]	The work of M. Pan was supported by the U.S. National Science Foundation under Grant CNS-1343361, Grant CNS-1350230 (CAREER), and Grant CPS-1646607.	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APR	2017	35	4					880	892		10.1109/JSAC.2017.2680798		13	Engineering, Electrical & Electronic; Telecommunications	Engineering; Telecommunications	EW0AX	WOS:000402151400005		No			2017-07-02	
J	Gan, XY; Wang, X; Niu, WH; Hang, G; Tian, XH; Wang, XB; Xu, J				Gan, Xiaoying; Wang, Xiong; Niu, Wenhao; Hang, Gai; Tian, Xiaohua; Wang, Xinbing; Xu, Jun			Incentivize Multi-Class Crowd Labeling Under Budget Constraint	IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS			English	Article						Crowdsourcing; multi-class labeling; budget; reverse auction	AUCTION	Crowdsourcing systems allocate tasks to a group of workers over the Internet, which have become an effective paradigm for human-powered problem solving, such as image classification, optical character recognition, and proofreading. In this paper, we focus on incentivizing crowd workers to label a set of multi-class labeling tasks under strict budget constraint. We properly profile the tasks' difficulty levels and workers' quality in crowdsourcing systems, where the collected labels are aggregated with sequential Bayesian approach. To stimulate workers to undertake crowd labeling tasks, the interaction between workers and the platform is modeled as a reverse auction. We reveal that the platform utility maximization could be intractable, for which an incentive mechanism that determines the winning bid and payments with polynomial-time computation complexity is developed. Moreover, we theoretically prove that our mechanism is truthful, individually rational, and budget feasible. Through extensive simulations, we demonstrate that our mechanism utilizes budget efficiently to achieve high platform utility with polynomial computation complexity.	[Gan, Xiaoying; Wang, Xiong; Niu, Wenhao; Hang, Gai; Tian, Xiaohua; Wang, Xinbing] Shanghai Jiao Tong Univ, Dept Elect Engn, Shanghai 200240, Peoples R China; [Gan, Xiaoying] Xidian Univ, State Key Lab Integrated Serv Networks, Xian 710071, Peoples R China; [Xu, Jun] Georgia Inst Technol, Sch Comp Sci, Atlanta, GA 30332 USA	Gan, XY (reprint author), Shanghai Jiao Tong Univ, Dept Elect Engn, Shanghai 200240, Peoples R China.; Gan, XY (reprint author), Xidian Univ, State Key Lab Integrated Serv Networks, Xian 710071, Peoples R China.	ganxiaoying@sjtu.edu.cn; wangxiongsjtu@sjtu.edu.cn; 1187203155@sjtu.edu.cn; hanggai@sjtu.edu.cn; xtian@sjtu.edu.cn; xwang8@sjtu.edu.cn; jx@cc.gatech.edu			NSF China [61672342, 91438115, 61671478, 61532012, 61325012, 61428205, 61521062, 61572319]; China Postdoctoral Science Foundation; US NSF [CNS-1302197]	This work was supported in part by the NSF China under Grant 61672342. Grant 91438115. Grant 61671478, Grant 61532012, Grant 61325012, Grant 61428205, Grant 61521062, and Grant 61572319, in part by the China Postdoctoral Science Foundation, and in part by US NSF under Grant CNS-1302197. This paper was presented at the IEEE INFOCOM 2015 [25].	Abramowitz M., 1972, HDB MATH FUNCTIONS F; Ahn L.V., 2006, COMPUTER, V39, DOI DOI 10.1109/MC.2006.196; Aumann Robert, 1995, GAME ECON BEHAV, V8, P263; Chen X, 2013, ICML, V2013, P64; Duan LJ, 2014, IEEE T MOBILE COMPUT, V13, P2320, DOI 10.1109/TMC.2014.2307327; Feng XX, 2014, IEEE T COMMUN, V62, P2651, DOI 10.1109/TCOMM.2014.2322352; Feng ZN, 2014, IEEE INFOCOM SER, P1231, DOI 10.1109/INFOCOM.2014.6848055; He SB, 2014, IEEE INFOCOM SER, P745, DOI 10.1109/INFOCOM.2014.6848001; Jaimes LG, 2012, INT CONF PERVAS COMP, P103, DOI 10.1109/PerCom.2012.6199855; Jain S, 2009, 10TH ACM CONFERENCE ON ELECTRONIC COMMERCE - EC 2009, P129; Karger D. R., 2013, P ACM SIGMETRICS INT, P81; Karger D. R., 2011, P ADV NEUR INF PROC, P1953; Lee J., 2010, P IEEE INT C PERV CO, P60; MYERSON RB, 1981, MATH OPER RES, V6, P58, DOI 10.1287/moor.6.1.58; Raykar V. C., 2011, P ADV NEUR INF PROC, P1809; Raykar VC, 2010, J MACH LEARN RES, V11, P1297; Singer Y, 2010, ANN IEEE SYMP FOUND, P765, DOI 10.1109/FOCS.2010.78; Yang DJ, 2012, MOBICOM 12: PROCEEDINGS OF THE 18TH ANNUAL INTERNATIONAL CONFERENCE ON MOBILE COMPUTING AND NETWORKING, P173; Zhang Q., 2015, P IEEE INFOCOM, P2812; Zhang Y, 2012, 2012 PROCEEDINGS IEEE INFOCOM, P2140, DOI 10.1109/INFCOM.2012.6195597	20	0	0	1	1	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC	PISCATAWAY	445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA	0733-8716	1558-0008		IEEE J SEL AREA COMM	IEEE J. Sel. Areas Commun.	APR	2017	35	4					893	905		10.1109/JSAC.2017.2680838		13	Engineering, Electrical & Electronic; Telecommunications	Engineering; Telecommunications	EW0AX	WOS:000402151400006		No			2017-07-02	
J	Wang, LL; Liu, GZ; Sun, LJ				Wang, Lingling; Liu, Guozhu; Sun, Lijun			A Secure and Privacy-Preserving Navigation Scheme Using Spatial Crowdsourcing in Fog-Based VANETs	SENSORS			English	Article						fog-based VANETs; real-time navigation; privacy-preserving; spatial crowdsourcing	PROTOCOL; PAIRINGS; NETWORKS	Fog-based VANETs (Vehicular ad hoc networks) is a new paradigm of vehicular ad hoc networks with the advantages of both vehicular cloud and fog computing. Real-time navigation schemes based on fog-based VANETs can promote the scheme performance efficiently. In this paper, we propose a secure and privacy-preserving navigation scheme by using vehicular spatial crowdsourcing based on fog-based VANETs. Fog nodes are used to generate and release the crowdsourcing tasks, and cooperatively find the optimal route according to the real-time traffic information collected by vehicles in their coverage areas. Meanwhile, the vehicle performing the crowdsourcing task can get a reasonable reward. The querying vehicle can retrieve the navigation results from each fog node successively when entering its coverage area, and follow the optimal route to the next fog node until it reaches the desired destination. Our scheme fulfills the security and privacy requirements of authentication, confidentiality and conditional privacy preservation. Some cryptographic primitives, including the Elgamal encryption algorithm, AES, randomized anonymous credentials and group signatures, are adopted to achieve this goal. Finally, we analyze the security and the efficiency of the proposed scheme.	[Wang, Lingling; Liu, Guozhu; Sun, Lijun] Qingdao Univ Sci & Technol, Sch Informat Sci & Technol, Qingdao 266061, Peoples R China	Wang, LL (reprint author), Qingdao Univ Sci & Technol, Sch Informat Sci & Technol, Qingdao 266061, Peoples R China.	teacherwll@163.com; LGZ_0228@163.com; lijunsun@qust.edu.cn			Fund Project of Domestic Visiting Scholars of Excellent Backbone Teachers of Higher Education Institutions in Shandong Province	The research was sponsored by the Fund Project of Domestic Visiting Scholars of Excellent Backbone Teachers of Higher Education Institutions in Shandong Province.	Behrendt K., 2005, P DISTR SAN DIEG CA; Bellare M, 2013, LECT NOTES COMPUT SC, V7881, P296, DOI 10.1007/978-3-642-38348-9_18; Bonomi F., 2012, ED MCC WORKSH MOB CL, P13; Camenisch J., 2002, P 3 C SEC COMM NETW, P268; Chaum D., 1991, P 10 ANN INT C THEOR, P257, DOI DOI 10.1007/3-540-46416-6_22; Chen L, 2007, INT J INF SECUR, V6, P213, DOI 10.1007/s10207-006-0011-9; Chen P.-Y., 2010, P IEEE CUST INT CIRC, P1, DOI DOI 10.1109/CICC.2010.5617444; Chim TW, 2014, IEEE T COMPUT, V63, P510, DOI 10.1109/TC.2012.188; Cho W., 2013, J WIREL MOB NETW UBI, V4, P80; Galbraith SD, 2008, DISCRETE APPL MATH, V156, P3113, DOI 10.1016/j.dam.2007.12.010; Gentry C, 2002, LECT NOTES COMPUT SC, V2501, P548; Hur J, 2016, IEEE T KNOWL DATA EN, V28, P3113, DOI 10.1109/TKDE.2016.2580139; Leontiadis I., 2010, P IEEE INFOCOM, P1; Lin XD, 2008, IEEE COMMUN MAG, V46, P88, DOI 10.1109/MCOM.2008.4481346; Lin XD, 2007, IEEE T VEH TECHNOL, V56, P3442, DOI 10.1109/TVT.2007.906878; Lin XD, 2008, IEEE T WIREL COMMUN, V7, P4987, DOI 10.1109/T-WC.2008.070773; Liu CG, 2013, J HIGH SPEED NETW, V19, P311, DOI 10.3233/JHS-130480; Lu RX, 2009, IEEE INFOCOM SER, P1413, DOI 10.1109/INFCOM.2009.5062057; Lu RX, 2009, IEEE T VEH TECHNOL, V58, P1454, DOI 10.1109/TVT.2008.925304; Luan T. H., 2015, ARXIV150201815; Mao B., 2013, IEEE T COMPUT, V25, P1775; Miyaji A, 2001, IEICE T FUND ELECTR, VE84A, P1234; Ni J. B., 2016, P IEEE 84 VEH TECHN; Olariu S., 2013, NEXT PARADIGM SHIFT, P645; Pointcheval D., 2016, P CT RSA 2016 SAN FR, V9610, P111; SCHNORR CP, 1990, LECT NOTES COMPUT SC, V434, P688; Scott M., EFFICIENT IMPLEMENTA; Sur C, 2016, INT J COMPUT MATH, V93, P325, DOI 10.1080/00207160.2014.934685; Yan GJ, 2013, IEEE T INTELL TRANSP, V14, P284, DOI 10.1109/TITS.2012.2211870; Yan Z, 2016, IEEE CLOUD COMPUT, V3, P28, DOI 10.1109/MCC.2016.29; Yu R, 2013, IEEE NETWORK, V27, P48, DOI 10.1109/MNET.2013.6616115; Zheng J. R., 2015, CHINA DAILY; [Anonymous], 1995, GLOBAL POSITIONING S	33	0	0	0	0	MDPI AG	BASEL	ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND	1424-8220			SENSORS-BASEL	Sensors	APR	2017	17	4							668	10.3390/s17040668		15	Chemistry, Analytical; Electrochemistry; Instruments & Instrumentation	Chemistry; Electrochemistry; Instruments & Instrumentation	EU1YU	WOS:000400822900009		gold			2017-07-02	
J	Zhou, BD; Li, QQ; Mao, QZ; Tu, W				Zhou, Baoding; Li, Qingquan; Mao, Qingzhou; Tu, Wei			A Robust Crowdsourcing-Based Indoor Localization System	SENSORS			English	Article						indoor localization; crowdsourcing; radio map; smartphone	NAVIGATION	WiFi fingerprinting-based indoor localization has been widely used due to its simplicity and can be implemented on the smartphones. The major drawback of WiFi fingerprinting is that the radio map construction is very labor-intensive and time-consuming. Another drawback of WiFi fingerprinting is the Received Signal Strength (RSS) variance problem, caused by environmental changes and device diversity. RSS variance severely degrades the localization accuracy. In this paper, we propose a robust crowdsourcing-based indoor localization system (RCILS). RCILS can automatically construct the radio map using crowdsourcing data collected by smartphones. RCILS abstracts the indoor map as the semantics graph in which the edges are the possible user paths and the vertexes are the location where users may take special activities. RCILS extracts the activity sequence contained in the trajectories by activity detection and pedestrian dead-reckoning. Based on the semantics graph and activity sequence, crowdsourcing trajectories can be located and a radio map is constructed based on the localization results. For the RSS variance problem, RCILS uses the trajectory fingerprint model for indoor localization. During online localization, RCILS obtains an RSS sequence and realizes localization by matching the RSS sequence with the radio map. To evaluate RCILS, we apply RCILS in an office building. Experiment results demonstrate the efficiency and robustness of RCILS.	[Zhou, Baoding; Li, Qingquan; Tu, Wei] Shenzhen Univ, Shenzhen Key Lab Spatial Smart Sensing & Serv, Shenzhen 518060, Peoples R China; [Zhou, Baoding; Li, Qingquan; Tu, Wei] Shenzhen Univ, Natl Adm Surveying Mapping & Geoinformat, Key Lab Geoenvironm Monitoring Coastal Zone, Shenzhen 518060, Peoples R China; [Mao, Qingzhou] Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430079, Peoples R China	Li, QQ; Tu, W (reprint author), Shenzhen Univ, Shenzhen Key Lab Spatial Smart Sensing & Serv, Shenzhen 518060, Peoples R China.; Li, QQ; Tu, W (reprint author), Shenzhen Univ, Natl Adm Surveying Mapping & Geoinformat, Key Lab Geoenvironm Monitoring Coastal Zone, Shenzhen 518060, Peoples R China.	bdzhou@szu.edu.cn; liqq@szu.edu.cn; qzhmao@whu.edu.cn; tuwei@szu.edu.cn			National Key Research Development Program of China [2016YFB0502203]; China Postdoctoral Science Foundation [2015M580732, 2016T90800]; Open Research Fund Program of State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing [16I02]; Shenzhen Future Industry Development Funding Program [201507211219247860]; National Natural Science Foundation of China [41371377, 91546106, 41401444]	This work was supported in part by the National Key Research Development Program of China (2016YFB0502203); by the China Postdoctoral Science Foundation (2015M580732, 2016T90800); by the Open Research Fund Program of State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing (16I02); by the Shenzhen Future Industry Development Funding Program (201507211219247860); and by the National Natural Science Foundation of China (41371377, 91546106, 41401444).	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A., 2008, P 6 INT C ADV MOB CO, P178, DOI 10.1145/1497185.1497223; Woodman O, 2009, LECT NOTES COMPUT SC, V5538, P238, DOI 10.1007/978-3-642-01516-8_17; Wu CS, 2015, IEEE T MOBILE COMPUT, V14, P444, DOI 10.1109/TMC.2014.2320254; Wu CS, 2013, IEEE T PARALL DISTR, V24, P839, DOI 10.1109/TPDS.2012.179; Yang Z, 2012, MOBICOM 12: PROCEEDINGS OF THE 18TH ANNUAL INTERNATIONAL CONFERENCE ON MOBILE COMPUTING AND NETWORKING, P269; Ye X., 2016, P 2016 13 ANN IEEE I, P1; Zhang C, 2015, IEEE T MOBILE COMPUT, V14, P387, DOI 10.1109/TMC.2014.2319824; Zhou BD, 2015, IEEE T INTELL TRANSP, V16, P2774, DOI 10.1109/TITS.2015.2423326; Zhou BD, 2015, IEEE T HUM-MACH SYST, V45, P562, DOI 10.1109/THMS.2014.2368092	31	0	0	1	1	MDPI AG	BASEL	ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND	1424-8220			SENSORS-BASEL	Sensors	APR	2017	17	4							864	10.3390/s17040864		16	Chemistry, Analytical; Electrochemistry; Instruments & Instrumentation	Chemistry; Electrochemistry; Instruments & Instrumentation	EU1YU	WOS:000400822900205		gold			2017-07-02	
J	Siriba, DN; Dalyot, S				Siriba, David N.; Dalyot, Sagi			Adoption of volunteered geographic information into the formal land administration system in Kenya	LAND USE POLICY			English	Article						Community-led land mapping; Formalization; Integration; Land administration; VGI; Crowdsourcing	DOMAIN MODEL	Individualization of tenure through title registration programmes introduced in many African countries after independence with the promise of security of tenure and increased agricultural productivity has, instead, had the opposite effect. Informal land arrangements continue to emerge as a result of the slow pace of land adjudication (formalization) and updating of land information systems. The trend towards computerization of land information systems has only put focus on already existing formal land tenure arrangements, leaving out the informal social tenure arrangements. As a result, there are now many efforts worldwide motivated by the introduction of the Social Tenure Domain Model (STDM), and freely available and easy-to-use technology tools to identify, document and map land in support of informal land administration arrangements. Actions are made towards the use of community-generated information to support land administration. Using theories from the interplay between formal and informal institutions, this paper discusses the potential outcomes in adopting Volunteered Geographic Information (VGI) in land administration in Kenya. Two case studies are presented that demonstrate the complementary-accommodating, versus the substitutive-competing approaches. These are then compared with the formal land adjudication process in Kenya. It is established that because of the direct involvement of the national mapping agency in land adjudication where VGI is utilized, the outcome is a case of formal adoption of VGI, while in the other case, where there is little or no involvement by the national mapping agency, the outcome is more of competition and substitution. The latter is an example in which the VGI is used just like any other information to inform policy making, rather than taking it as the authoritative source. We argue that since informality is - and will always be - part and parcel of land administration in many African countries as a result of ingrained social relations and power structures, adopting crowdsourced land information into existing formal land administration systems should consider the particular land administration process, satisfying innate demands and requirements, thus re-engineered to accommodate VGI. (C) 2017 Elsevier Ltd. All rights reserved.	[Siriba, David N.] Univ Nairobi, Dept Geospatial & Space Technol, POB 30197, Nairobi 00100, Kenya; [Dalyot, Sagi] Technion Israel Inst Technol, Fac Civil & Environm Engn, Transportat & Geoinformat Engn, IL-32000 Haifa, Israel	Dalyot, S (reprint author), Technion Israel Inst Technol, Fac Civil & Environm Engn, Transportat & Geoinformat Engn, IL-32000 Haifa, Israel.	dnsiriba@uonbi.ac.ke; dalyot@technion.ac.il					Arsanjani JJ., 2015, OPENSTREETMAP GLSCIE; Augustinus A, 2010, P 24 FIG INT C 2010; Bajpai V., 2013, EM TRENDS APPL COMP, P58; Besteman V., 1994, J INT AFR I, V64, P484; Brabham DC, 2008, CONVERGENCE-US, V14, P75, DOI DOI 10.1177/1354856507084420; De Soto Hernando, 2003, MYSTERY CAPITAL WHY; Estelles-Arolas E, 2012, J INF SCI, V38, P189, DOI 10.1177/0165551512437638; Fairbairn D., 2015, 27 INT CART C 16 GEN; FIG, 2014, FIG PUBLICATION, V60; Haklay M., 2014, CROWDSOURCED GEOGRAP; Harvey F., 2013, CROWDSOURCING GEOGRA, P30; HELMKE G, 2004, PERSPECTIVES POLITIC, V0002; ISO, 2012, 19152 ISO; Karanja I, 2010, ENVIRON URBAN, V22, P217, DOI 10.1177/0956247809362642; Kuria, 2015, KIJ NYAND PUBL LAND; Lemmen C., 2010, SOCIAL TENURE DOMAIN, V52; Lemmen C, 2015, LAND USE POLICY, V49, P535, DOI 10.1016/j.landusepol.2015.01.014; McLaren R., 2011, INT FEDERATION SURVE; Navratil G., 2013, INT ARCH PHOTOGRAMME, VXL-2; Newman G, 2011, ECOL INFORM, V6, P217, DOI 10.1016/j.ecoinf.2011.03.002; National Research Council (NRC), 1993, COORD SPAT DAT INFR; Olteanu-Raimond A. -M., 2016, T GIS, DOI http://dx.doi.org/10.1111/tgis.12189; Panek J., 2015, ELECT J INFORM SYSTE, V68, P1; Schaefer P., 2014, POLICY ANAL NO 765, P157; UNDP, 2014, INF JUST SYST CHART; van Oosterom P, 2015, LAND USE POLICY, V49, P527, DOI 10.1016/j.landusepol.2015.09.032; van Tatenhove I., 2006, PERSPECT EUR POLITIC, V7, P8; Williamson I., 2010, LAND ADM SUSTAINABLE	28	0	0	0	0	ELSEVIER SCI LTD	OXFORD	THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND	0264-8377	1873-5754		LAND USE POLICY	Land Use Pol.	APR	2017	63						279	287		10.1016/j.landusepol.2017.01.036		9	Environmental Studies	Environmental Sciences & Ecology	EU9ZQ	WOS:000401398600026		No			2017-07-02	
J	Peters, SAE; Dunford, E; Ware, LJ; Harris, T; Walker, A; Wicks, M; Van Zyl, T; Swanepoel, B; Charlton, KE; Woodward, M; Webster, J; Neal, B				Peters, Sanne A. E.; Dunford, Elizabeth; Ware, Lisa J.; Harris, Teresa; Walker, Adele; Wicks, Mariaan; van Zyl, Tertia; Swanepoel, Bianca; Charlton, Karen E.; Woodward, Mark; Webster, Jacqui; Neal, Bruce			The Sodium Content of Processed Foods in South Africa during the Introduction of Mandatory Sodium Limits	NUTRIENTS			English	Article						salt intake; sodium legislation; South Africa; packaged food; nutritional composition	SALT REDUCTION INITIATIVES; CARDIOVASCULAR-DISEASE; PROGRAMS; POPULATION; POTASSIUM; TARGETS; IMPACT; UK	Background: In June 2016, the Republic of South Africa introduced legislation for mandatory limits for the upper sodium content permitted in a wide range of processed foods. We assessed the sodium levels of packaged foods in South Africa during the one-year period leading up to the mandatory implementation date of the legislation. Methods: Data on the nutritional composition of packaged foods was obtained from nutrition information panels on food labels through both in-store surveys and crowdsourcing by users of the HealthyFood Switch mobile phone app between June 2015 and August 2016. Summary sodium levels were calculated for 15 food categories, including the 13 categories covered by the sodium legislation. The percentage of foods that met the government's 2016 sodium limits was also calculated. Results: 11,065 processed food items were included in the analyses; 1851 of these were subject to the sodium legislation. Overall, 67% of targeted foods had a sodium level at or below the legislated limit. Categories with the lowest percentage of foods that met legislated limits were bread (27%), potato crisps (41%), salt and vinegar flavoured snacks (42%), and raw processed sausages (45%). About half (49%) of targeted foods not meeting the legislated limits were less than 25% above the maximum sodium level. Conclusion: Sodium levels in two-thirds of foods covered by the South African sodium legislation were at or below the permitted upper levels at the mandatory implementation date of the legislation and many more were close to the limit. The South African food industry has an excellent opportunity to rapidly meet the legislated requirements.	[Peters, Sanne A. E.; Woodward, Mark] Univ Oxford, George Inst Global Hlth, Oxford OX1 3QX, England; [Dunford, Elizabeth] Univ N Carolina, Carolina Populat Ctr, Chapel Hill, NC 27516 USA; [Dunford, Elizabeth; Woodward, Mark; Webster, Jacqui; Neal, Bruce] Univ Sydney, George Inst Global Hlth, Sydney, NSW 2050, Australia; [Ware, Lisa J.] North West Univ, Hypertens Africa Res Team, ZA-2520 Potchefstroom, South Africa; [Harris, Teresa; Walker, Adele] Discovery Vital, ZA-2146 Sandton, South Africa; [Wicks, Mariaan; van Zyl, Tertia; Swanepoel, Bianca] North West Univ, Ctr Excellence Nutr, ZA-2520 Potchefstroom, South Africa; [Charlton, Karen E.] Univ Wollongong, Sch Med, Wollongong, NSW 2522, Australia; [Woodward, Mark] Johns Hopkins Univ, Dept Epidemiol, Baltimore, MD 21218 USA; [Neal, Bruce] Univ Sydney, Charles Perkins Ctr, Sydney, NSW 2006, Australia; [Neal, Bruce] Royal Prince Alfred Hosp, Camperdown, NSW 2050, Australia; [Neal, Bruce] Imperial Coll London, London SW7 2AZ, England	Peters, SAE (reprint author), Univ Oxford, George Inst Global Hlth, Oxford OX1 3QX, England.	sanne.peters@georgeinstitute.ox.ac.uk; edunford@georgeinstitute.org.au; lisa.ware@nwu.ac.za; terryh@discovery.co.za; adelewa@discovery.co.za; 13009494@nwu.ac.za; tertia.vanzyl@nwu.ac.za; biancaswanepoel.nwu@gmail.com; karenc@uow.edu.au; markw@georgeinstitute.org.au; jwebster@georgeinstitute.org.au; bneal@georgeinstitute.org.au					Sixty-Sixth World Health Assembly, 2013, FOLL UP POL DECL HIG; Bertram MY, 2012, SAMJ S AFR MED J, V102, P743, DOI [10.7196/SAMJ.5832, 10.7196/samj.5832]; Charlton K, 2016, BMJ OPEN, V6, DOI 10.1136/bmjopen-2016-013316; Charlton K, 2014, NUTRIENTS, V6, P3672, DOI 10.3390/nu6093672; Charlton KE, 2005, NUTRITION, V21, P39, DOI 10.1016/j.nut.2004.09.007; Christoforou A, 2016, J EPIDEMIOL COMMUN H, V70, P1140, DOI 10.1136/jech-2015-206997; Department of Health, F9 SALT RED 2017; Dunford E, 2014, JMIR MHEALTH UHEALTH, V2, DOI 10.2196/mhealth.3230; Dunford E, 2012, EUR J PREV CARDIOL, V19, P1326, DOI 10.1177/1741826711425777; Eyles H, 2016, BRIT J NUTR, V115, P1835, DOI 10.1017/S000711451600088X; Eyles H, 2013, PREV MED, V57, P555, DOI 10.1016/j.ypmed.2013.07.024; Fabiansson SU, 2006, ASIA PAC J CLIN NUTR, V15, P451; Food Standards Agency, SALT RED TARG 2017; Forouzanfar MH, 2016, LANCET, V388, P1659; He F.J., 2013, COCHRANE DB SYST REV, V3; Hofman K.J., 2013, INTERSECTORIAL CASE; Mozaffarian D, 2014, NEW ENGL J MED, V371, P624, DOI 10.1056/NEJMoa1304127; Sadler K., 2012, DIET NUTR SURVEY ASS; Swanepoel B, 2016, J AM SOC HYPERTENS, V10, P829, DOI 10.1016/j.jash.2016.08.007; Trevena H, 2014, NUTRIENTS, V6, P3802, DOI 10.3390/nu6093802; Trieu K, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0130247; Watkins DA, 2016, HEALTH POLICY PLANN, V31, P75, DOI 10.1093/heapol/czv023; Webster JL, 2011, J HYPERTENS, V29, P1043, DOI 10.1097/HJH.0b013e328345ed83; Webster J, 2014, NUTRIENTS, V6, P3274, DOI 10.3390/nu6083274; WHO, 2012, GUID SOD INT AD CHIL; World Health Organization, 2010, GLOBAL STATUS REPORT	26	0	0	2	2	MDPI AG	BASEL	ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND	2072-6643			NUTRIENTS	Nutrients	APR	2017	9	4							404	10.3390/nu9040404		15	Nutrition & Dietetics	Nutrition & Dietetics	EU9JI	WOS:000401355600089		gold			2017-07-02	
J	Yang, G; He, SB; Shi, ZG				Yang, Guang; He, Shibo; Shi, Zhiguo			Leveraging Crowdsourcing for Efficient Malicious Users Detection in Large-Scale Social Networks	IEEE INTERNET OF THINGS JOURNAL			English	Article						Crowdsourcing; large-scale networks; malicious users detection	WIRELESS SENSOR NETWORKS; INTRUSION-DETECTION SYSTEM; MOBILE NETWORKS; PRIVACY; PERFORMANCE; DEPLOYMENT; COVERAGE	The past few years have witnessed the dramatic popularity of large-scale social networks where malicious nodes detection is one of the fundamental problems. Most existing works focus on actively detecting malicious nodes by verifying signal correlation or behavior consistency. It may not work well in large-scale social networks since the number of users is extremely large and the difference between normal users and malicious users is inconspicuous. In this paper, we propose a novel approach that leverages the power of users to perform the detection task. We design incentive mechanisms to encourage the participation of users under two scenarios: 1) full information and 2) partial information. In full information scenario, we design a specific incentive scheme for users according to their preferences, which can provide the desirable detection result and minimize overall cost. In partial information scenario, assuming that we only have statistical information about users, we first transform the incentive mechanism design to an optimization problem, and then design the optimal incentive scheme under different system parameters by solving the optimization problem. We perform extensive simulations to validate the analysis and demonstrate the impact of system factors on the overall cost.	[Yang, Guang; Shi, Zhiguo] Zhejiang Univ, Coll Informat Sci & Elect Engn, Hangzhou 310027, Zhejiang, Peoples R China; [He, Shibo] Zhejiang Univ, State Key Lab Ind Control Technol, Hangzhou 310027, Zhejiang, Peoples R China	He, SB (reprint author), Zhejiang Univ, State Key Lab Ind Control Technol, Hangzhou 310027, Zhejiang, Peoples R China.	shibohe@ieee.org			Zhejiang Provincial Natural Science Foundation of China [LR16F010002]; Natural Science Foundation of China [61402405, 61528105]	This work was supported in part by the Zhejiang Provincial Natural Science Foundation of China under Grant LR16F010002 and in part by the Natural Science Foundation of China under Grant 61402405 and Grant 61528105. (Corresponding author: Shibo He.)	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APR	2017	4	2					330	339		10.1109/JIOT.2016.2560518		10	Computer Science, Information Systems; Engineering, Electrical & Electronic; Telecommunications	Computer Science; Engineering; Telecommunications	ET8TN	WOS:000400574300005		No			2017-07-02	
J	Zhuo, GQ; Jia, Q; Guo, L; Li, M; Li, P				Zhuo, Gaoqiang; Jia, Qi; Guo, Linke; Li, Ming; Li, Pan			Privacy-Preserving Verifiable Set Operation in Big Data for Cloud-Assisted Mobile Crowdsourcing	IEEE INTERNET OF THINGS JOURNAL			English	Article						Big data; mobile crowdsourcing; privacy; verifiable computation	AUTHENTICATION SYSTEM; NETWORKS; AGGREGATION; FRAMEWORK; SEARCH; FINE	The ubiquity of smartphones makes the mobile crowdsourcing possible, where the requester (task owner) can crowdsource data from the workers (smartphone users) by using their sensor-rich mobile devices. However, data collection, data aggregation, and data analysis have become challenging problems for a resource constrained requester when data volume is extremely large, i.e., big data. In particular to data analysis, set operations, including intersection, union, and complementation, exist in most big data analysis for filtering redundant data and preprocessing raw data. Facing challenges in terms of limited computation and storage resources, cloud-assisted approaches may serve as a promising way to tackle the big data analysis issue. However, workers may not be willing to participate if the privacy of their sensing data and identity are not well preserved in the untrusted cloud. In this paper, we propose to the use cloud to compute a set operation for the requester, at the same time workers' data privacy and identities privacy are well preserved. Besides, the requester can verify the correctness of set operation results. We also extend our scheme to support data preprocessing, with which invalid data can be excluded before data analysis. By using batch verification and data update methods, the proposed scheme greatly reduces the computational cost. Extensive performance analysis and experiment based on real cloud system have shown both the feasibility and efficiency of our proposed scheme.	[Zhuo, Gaoqiang; Jia, Qi; Guo, Linke] SUNY Binghamton, Dept Elect & Comp Engn, Binghamton, NY 13902 USA; [Li, Ming] Univ Nevada, Dept Comp Sci & Engn, Reno, NV 89557 USA; [Li, Pan] Case Western Reserve Univ, Dept Elect Engn & Comp Sci, Cleveland, OH 44106 USA	Zhuo, GQ (reprint author), SUNY Binghamton, Dept Elect & Comp Engn, Binghamton, NY 13902 USA.	gzhuo1@binghamton.edu; qjia1@binghamton.edu; lguo@binghamton.edu; mingli@unr.edu; lipan@case.edu			U.S. National Science Foundation [CNS-1343220, CNS-1149786]; National Science Foundation [CNS-1566634]	The work of P. Li was supported in part by the U.S. National Science Foundation under Grant CNS-1343220 and Grant CNS-1149786. The work of M. Li was supported in part by the National Science Foundation under Grant CNS-1566634.	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APR	2017	4	2					572	582		10.1109/JIOT.2016.2585592		11	Computer Science, Information Systems; Engineering, Electrical & Electronic; Telecommunications	Computer Science; Engineering; Telecommunications	ET8TN	WOS:000400574300030		No			2017-07-02	
J	Litman, L; Robinson, J; Abberbock, T				Litman, Leib; Robinson, Jonathan; Abberbock, Tzvi			TurkPrime.com: A versatile crowdsourcing data acquisition platform for the behavioral sciences	BEHAVIOR RESEARCH METHODS			English	Article						Mechanical Turk; Crowdsourcing; Online research	MECHANICAL TURK; QUALITY	In recent years, Mechanical Turk (MTurk) has revolutionized social science by providing a way to collect behavioral data with unprecedented speed and efficiency. However, MTurk was not intended to be a research tool, and many common research tasks are difficult and time-consuming to implement as a result. TurkPrime was designed as a research platform that integrates with MTurk and supports tasks that are common to the social and behavioral sciences. Like MTurk, TurkPrime is an Internet-based platform that runs on any browser and does not require any downloads or installation. Tasks that can be implemented with TurkPrime include: excluding participants on the basis of previous participation, longitudinal studies, making changes to a study while it is running, automating the approval process, increasing the speed of data collection, sending bulk e-mails and bonuses, enhancing communication with participants, monitoring dropout and engagement rates, providing enhanced sampling options, and many others. This article describes how TurkPrime saves time and resources, improves data quality, and allows researchers to design and implement studies that were previously very difficult or impossible to carry out on MTurk. TurkPrime is designed as a research tool whose aim is to improve the quality of the crowdsourcing data collection process. Various features have been and continue to be implemented on the basis of feedback from the research community. TurkPrime is a free research platform.	[Litman, Leib; Robinson, Jonathan; Abberbock, Tzvi] Lander Coll, Flushing, NY 11367 USA; [Litman, Leib] Lander Coll, Dept Psychol, 75-31 150th St, Flushing, NY 11367 USA	Litman, L (reprint author), Lander Coll, Flushing, NY 11367 USA.; Litman, L (reprint author), Lander Coll, Dept Psychol, 75-31 150th St, Flushing, NY 11367 USA.	leib.litman@touro.edu					Berinsky AJ, 2012, POLIT ANAL, V20, P351, DOI 10.1093/pan/mpr057; Buccafusco C, 2014, TEX LAW REV, V92, P1921; Buhrmester M, 2011, PERSPECT PSYCHOL SCI, V6, P3, DOI 10.1177/1745691610393980; Chandler J., 2013, METHODOLOGICAL UNPUB; Chandler J, 2015, PSYCHOL SCI, V26, P1131, DOI 10.1177/0956797615585115; Chilton L. B., 2010, P ACM SIGKDD WORKSH, P1, DOI DOI 10.1145/1837885.1837889; Eysenbach G, 2004, J MED INTERNET RES, V6, P12, DOI 10.2196/jmir.6.3.e34; Gosling S. D., 2010, ADV METHODS CONDUCTI; Gureckis TM, 2016, BEHAV RES METHODS, V48, P829, DOI 10.3758/s13428-015-0642-8; Henrich J, 2010, BEHAV BRAIN SCI, V33, P61, DOI 10.1017/S0140525X0999152X; Kraut R., 2004, PSYCHOL RES ONLINE, V59, P105, DOI DOI 10.1037/0003-066X.59.2.105; Litman L, 2015, BEHAV RES METHODS, V47, P519, DOI 10.3758/s13428-014-0483-x; Mason W, 2012, BEHAV RES METHODS, V44, P1, DOI 10.3758/s13428-011-0124-6; Nosek BA, 2002, GROUP DYN-THEOR RES, V6, P101, DOI 10.1037//1089-2699.6.1.101; Paolacci G, 2010, JUDGM DECIS MAK, V5, P5, DOI DOI 10.1111/NTWE.12038; Peer E., 2012, SELECTIVELY RE UNPUB; Peer E, 2014, BEHAV RES METHODS, V46, P1023, DOI 10.3758/s13428-013-0434-y; Rosenzweig C., 2015, S M ASS PSYCH SCI NE; SHAPIRO DN, 2013, CLIN PSYCHOL SCI, V1, P213, DOI DOI 10.1177/2167702612469015; Sprouse J, 2011, BEHAV RES METHODS, V43, P155, DOI 10.3758/s13428-010-0039-7; Von Emden R., 2015, EXPLORATORY TURKPRIM	21	1	1	4	4	SPRINGER	NEW YORK	233 SPRING ST, NEW YORK, NY 10013 USA	1554-351X	1554-3528		BEHAV RES METHODS	Behav. Res. Methods	APR	2017	49	2					433	442		10.3758/s13428-016-0727-z		10	Psychology, Mathematical; Psychology, Experimental	Psychology	ET6HJ	WOS:000400391800003	27071389	No			2017-07-02	
J	Espinoza, SEE; De la Fuente, AEV; Contreras, CAM				Espinoza Espinoza, Sebastian Eduardo; Vivaceta De la Fuente, Anibal Enrique; Machuca Contreras, Constanza Andrea			Valparaiso's 2014 Fire: Evaluation of Environmental and Epidemiological Risk Factors During the Emergency Through a Crowdsourcing Tool	DISASTER MEDICINE AND PUBLIC HEALTH PREPAREDNESS			English	Article						urban fire; environmental risk factors; epidemiology; emergencies and disasters; crowdsourcing	DISASTERS; HEALTH	Objective: To describe and relate the main environmental risk factors in the emergency process after a large urban fire in Valparaiso, Chile, in April 2014. Methods: An observational, cross-sectional descriptive study was performed. All 243 reports from an ad hoc web/mobile website created on the Ushahidi/Crowdmap platform were reviewed. Reports were recorded in a new database with dichotomist variables based on either the presence or absence of the relevant category in each report. Results: Almost one-third of the reports presented data about garbage (30%) and chemical toilets (29%). Reports related to water, infrastructural damage, and garbage had significant associations with 4 categories by chi-square test. In the logistic regression model for chemical toilets, only the variable of water was significant (P value=0.00; model P value: 0.00; R-2: 11.7%). The garbage category confirmed infrastructural damage (P value: 0.00), water (P value: 0.028), and vectors (P value: 0.00) as predictors (model P value: 0.00; R-2: 23.09%). Conclusions: Statistically significant evidence was found for the statistical dependence of 7 out of 10 studied variables. The most frequent environmental risk factors in the reports were garbage, chemical toilets, and donation centers. The highest correlation found was for damaged infrastructure, vectors, and garbage.	[Espinoza Espinoza, Sebastian Eduardo; Machuca Contreras, Constanza Andrea] Univ Valparaiso, Sch Dent, Dept Publ Hlth, Valparaiso, Chile; [Vivaceta De la Fuente, Anibal Enrique] Univ Valparaiso, Sch Med, Dept Publ Hlth, Valparaiso, Chile	Espinoza, SEE (reprint author), 211 Subida Carvallo, Valparaiso, Chile.	sebastian.espinoza@uv.cl					Astorga M, 2014, REV CHILENA SALUD PU, V18, P199; Datar A, 2013, SOC SCI MED, V76, P83, DOI 10.1016/j.socscimed.2012.10.008; Dominici F, 2005, EPIDEMIOL REV, V27, P9, DOI 10.1093/epirev/mxi009; Korteweg HA, 2010, BMC PUBLIC HEALTH, V10, DOI 10.1186/1471-2458-10-295; Noji Eric K., 2000, IMPACTO DESASTRES SA; Pan American Health Association Ministry of Health Office, 2010, GUIA VIG EP EM DES; Petersen K, 2014, SOCIOL REV, V62, P91, DOI 10.1111/1467-954X.12125; van den Berg Bellis, 2008, Prehosp Disaster Med, V23, ps55; Zook M., 2010, World Medical and Health Policy, V2, P7, DOI 10.2202/1948-4682.1069	9	0	0	4	4	CAMBRIDGE UNIV PRESS	NEW YORK	32 AVENUE OF THE AMERICAS, NEW YORK, NY 10013-2473 USA	1935-7893	1938-744X		DISASTER MED PUBLIC	Dis. Med. Public Health Prep.	APR	2017	11	2					239	243		10.1017/dmp.2016.117		5	Public, Environmental & Occupational Health	Public, Environmental & Occupational Health	ET1CR	WOS:000400004000014	27618881	No			2017-07-02	
J	Wang, X; Ding, L; Wang, Q; Xie, J; Wang, TY; Tian, XH; Guan, YF; Wang, XB				Wang, Xiong; Ding, Lei; Wang, Qi; Xie, Jin; Wang, Tianyi; Tian, Xiaohua; Guan, Yunfeng; Wang, Xinbing			A Picture is Worth a Thousand Words: Share Your Real-Time View on the Road	IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY			English	Article						Crowdsourcing system; on-demand; real-time; visual	DATA FUSION; PREDICTION; FEATURES; SYSTEMS	The visual information provided by applications facilitating urban communications such as Google Street View and Waze scene report is intuitionistic and useful since it conforms to human cognitive habits. However, current street view services cannot provide real-time information, and the scene report service is passive. An on-demand and real-time visual-information-providing mechanism is still unavailable. In this paper, we develop the crowdsourcing-based Real-time View Share (RVShare) system, which provides pictures of requested locations taken by travelers just passing by. To enable the RVShare system, we propose a view-sharing job distribution mechanism, where a wavelet-based vehicle prediction scheme and a tree-searching-based tracking scheme are developed to select vehicles for view sharing. We also design a simple but effective incentive mechanism to encourage more travelers to participate into the view-sharing activity, where the rewarding process takes the quality of uploaded pictures into account. Moreover, we develop a processing flow for uploaded pictures to improve the accuracy of the picture quality evaluation and verify the picture content. Comprehensive experiment results from road tests are conducted to evaluate the performance of the RVShare system.	[Wang, Xiong; Wang, Tianyi; Tian, Xiaohua; Guan, Yunfeng; Wang, Xinbing] Shanghai Jiao Tong Univ, Dept Elect Engn, Shanghai 200240, Peoples R China; [Ding, Lei] Univ Calif Los Angeles, Dept Elect Engn, Los Angeles, CA 90024 USA; [Wang, Qi] Columbia Univ, Dept Comp Sci, New York, NY 10027 USA; [Xie, Jin] Northeastern Univ, Dept Elect & Comp Engn, Boston, MA 02115 USA; [Tian, Xiaohua] Southeast Univ, Natl Mobile Communicat Res Lab, Nanjing 210096, Jiangsu, Peoples R China	Wang, X (reprint author), Shanghai Jiao Tong Univ, Dept Elect Engn, Shanghai 200240, Peoples R China.	wangxiongsjtu@sjtu.edu.cn; stoner@sjtu.edu.cn; paoptu023@sjtu.edu.cn; xiejin@sjtu.edu.cn; c86668248@sjtu.edu.cn; xtian@sjtu.edu.cn; yfguan69@yahoo.com; xwang8@sjtu.edu.cn			National Natural Science Foundation of China [61532012, 61325012, 61271219, 61521062, 61428205, 91438115, 61572319, U1405251]; National Mobile Communications Research Laboratory, Southeast University [2014D07]	This work was supported in part by the National Natural Science Foundation of China under Grant 61532012, Grant 61325012, Grant 61271219, Grant 61521062, Grant 61428205, Grant 91438115, Grant 61572319, and Grant U1405251 and in part by the National Mobile Communications Research Laboratory, Southeast University under Grant 2014D07.	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Veh. Technol.	APR	2017	66	4					2902	2914		10.1109/TVT.2016.2592685		13	Engineering, Electrical & Electronic; Telecommunications; Transportation Science & Technology	Engineering; Telecommunications; Transportation	ES7RZ	WOS:000399749500002		No			2017-07-02	
J	Bateman, DR; Brady, E; Wilkerson, D; Yi, EH; Karanam, Y; Callahan, CM				Bateman, Daniel Robert; Brady, Erin; Wilkerson, David; Yi, Eun-Hye; Karanam, Yamini; Callahan, Christopher M.			Comparing Crowdsourcing and Friendsourcing: A Social Media-Based Feasibility Study to Support Alzheimer Disease Caregivers	JMIR RESEARCH PROTOCOLS			English	Article						Alzheimer disease; Alzheimer disease and related dementias; caregivers; mobile health; social media; crowdsourcing; friendsourcing; emotional support; informational support; online support	AMAZON MECHANICAL TURK; HEALTH-CARE; DEMENTIA; PREVALENCE; PEOPLE; INTERVENTIONS; METAANALYSIS; DEPRESSION; OUTCOMES; PATIENT	Background: In the United States, over 15 million informal caregivers provide unpaid care to people with Alzheimer disease (AD). Compared with others in their age group, AD caregivers have higher rates of stress, and medical and psychiatric illnesses. Psychosocial interventions improve the health of caregivers. However, constraints of time, distance, and availability inhibit the use of these services. Newer online technologies, such as social media, online groups, friendsourcing, and crowdsourcing, present alternative methods of delivering support. However, limited work has been done in this area with caregivers. Objective: The primary aims of this study were to determine (1) the feasibility of innovating peer support group work delivered through social media with friendsourcing, (2) whether the intervention provides an acceptable method for AD caregivers to obtain support, and (3) whether caregiver outcomes were affected by the intervention. A Facebook app provided support to AD caregivers through collecting friendsourced answers to caregiver questions from participants' social networks. The study's secondary aim was to descriptively compare friendsourced answers versus crowdsourced answers. Methods: We recruited AD caregivers online to participate in a 6-week-long asynchronous, online, closed group on Facebook, where caregivers received support through moderator prompts, group member interactions, and friendsourced answers to caregiver questions. We surveyed and interviewed participants before and after the online group to assess their needs, views on technology, and experience with the intervention. Caregiver questions were pushed automatically to the participants' Facebook News Feed, allowing participants' Facebook friends to see and post answers to the caregiver questions (Friendsourced answers). Of these caregiver questions, 2 were pushed to crowdsource workers through the Amazon Mechanical Turk platform. We descriptively compared characteristics of these crowdsourced answers with the friendsourced answers. Results: In total, 6 AD caregivers completed the initial online survey and semistructured telephone interview. Of these, 4 AD caregivers agreed to participate in the online Facebook closed group activity portion of the study. Friendsourcing and crowdsourcing answers to caregiver questions had similar rates of acceptability as rated by content experts: 90% (27/ 30) and 100% (45/ 45), respectively. Rates of emotional support and informational support for both groups of answers appeared to trend with the type of support emphasized in the caregiver question (emotional vs informational support question). Friendsourced answers included more shared experiences (20/ 30, 67%) than did crowdsourced answers (4/ 45, 9%). Conclusions: We found an asynchronous, online, closed group on Facebook to be generally acceptable as a means to deliver support to caregivers of people with AD. This pilot is too small to make judgments on effectiveness; however, results trended toward an improvement in caregivers' self-efficacy, sense of support, and perceived stress, but these results were not statistically significant. Both friendsourced and crowdsourced answers may be an acceptable way to provide informational and emotional support to caregivers of people with AD.	[Bateman, Daniel Robert; Brady, Erin; Wilkerson, David; Yi, Eun-Hye; Callahan, Christopher M.] Indiana Univ Ctr Aging Res, 1101 W Tenth St, Indianapolis, IN 46202 USA; [Bateman, Daniel Robert] Indiana Univ Sch Med, Dept Psychiat, Indianapolis, IN 46202 USA; [Bateman, Daniel Robert; Brady, Erin; Wilkerson, David; Yi, Eun-Hye; Callahan, Christopher M.] Regenstrief Inst Hlth Care, Indianapolis, IN 46202 USA; [Bateman, Daniel Robert; Callahan, Christopher M.] Indiana Alzheimer Disease Ctr, Indianapolis, IN 46202 USA; [Brady, Erin; Karanam, Yamini] Indiana Univ Purdue Univ, Sch Informat & Comp, Dept Human Centered Comp, Indianapolis, IN 46202 USA; [Wilkerson, David; Yi, Eun-Hye] Indiana Univ, Sch Social Work, Indianapolis, IN 46204 USA; [Callahan, Christopher M.] Indiana Univ Sch Med, Dept Med, Indianapolis, IN 46202 USA	Bateman, DR (reprint author), Indiana Univ Ctr Aging Res, 1101 W Tenth St, Indianapolis, IN 46202 USA.	darbate@iupui.edu			The Regenstrief Institute	This work was funded by an Innovations grant from The Regenstrief Institute.We would like to especially thank Bill Bennett,Alita Pinto,Richard Holden PhD,and Hugh Hendrie MB ChB DSc.	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Protoc.	APR	2017	6	4							e56	10.2196/resprot.6904		16	Health Care Sciences & Services	Health Care Sciences & Services	ES2UE	WOS:000399382600007	28396304	gold			2017-07-02	
J	Tsvetkova, M; Yasseri, T; Meyer, ET; Pickering, JB; Engen, V; Walland, P; Luders, M; Folstad, A; Bravos, G				Tsvetkova, Milena; Yasseri, Taha; Meyer, Eric T.; Pickering, J. Brian; Engen, Vegard; Walland, Paul; Luders, Marika; Folstad, Asbjorn; Bravos, George			Understanding Human-Machine Networks: A Cross-Disciplinary Survey	ACM COMPUTING SURVEYS			English	Article						Crowdsourcing; mass collaboration; crowdsensing; social media; peer-to-peer; complex networks; human-machine networks	PARTICIPATORY SENSING SYSTEMS; SOURCE SOFTWARE-DEVELOPMENT; WORLD-WIDE-WEB; SOCIAL-INFLUENCE; PROJECT SUCCESS; VIRTUAL WORLDS; ONLINE GAMES; TRUST; PRIVACY; MODEL	In the current hyperconnected era, modern Information and Communication Technology (ICT) systems form sophisticated networks where not only do people interact with other people, but also machines take an increasingly visible and participatory role. Such Human-Machine Networks (HMNs) are embedded in the daily lives of people, both for personal and professional use. They can have a significant impact by producing synergy and innovations. The challenge in designing successful HMNs is that they cannot be developed and implemented in the same manner as networks of machines nodes alone, or following a wholly humancentric view of the network. The problem requires an interdisciplinary approach. Here, we review current research of relevance to HMNs across many disciplines. Extending the previous theoretical concepts of sociotechnical systems, actor-network theory, cyber-physical-social systems, and social machines, we concentrate on the interactions among humans and between humans and machines. We identify eight types of HMNs: public-resource computing, crowdsourcing, web search engines, crowdsensing, online markets, social media, multiplayer online games and virtual worlds, and mass collaboration. We systematically select literature on each of these types and review it with a focus on implications for designing HMNs. Moreover, we discuss risks associated with HMNs and identify emerging design and development trends.	[Tsvetkova, Milena] London Sch Econ & Polit Sci, Dept Methodol, Houghton St, London WC2A 2AE, England; [Yasseri, Taha; Meyer, Eric T.] Univ Oxford, Oxford Internet Inst, 1 St Giles, Oxford OX1 3JS, England; [Pickering, J. Brian; Engen, Vegard; Walland, Paul] Univ Southampton, IT Innovat Ctr, Gamma House,Enterprise Rd, Southampton SO16 7NS, Hants, England; [Luders, Marika] Univ Oslo, Dept Media & Commun, Postboks 1093 Blindern, N-0317 Oslo, Norway; [Folstad, Asbjorn] SINTEF, Forskningsveien 1, N-0373 Oslo, Norway; [Bravos, George] Athens Technol Ctr, Chalandri 15233, Greece	Tsvetkova, M (reprint author), London Sch Econ & Polit Sci, Dept Methodol, Houghton St, London WC2A 2AE, England.	m.tsvetkova@lse.ac.uk; taha.yasseri@oii.ox.ac.uk; eric.meyer@oii.ox.ac.uk; jbp@it-innovation.soton.ac.uk; ve@it-innovation.soton.ac.uk; pww@it-innovation.soton.ac.uk; marika.luders@media.uio.no; Asbjorn.Folstad@sintef.no; gebravos@gmail.com			European Union [645043]	This project has received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No 645043.	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Surv.	APR	2017	50	1							12	10.1145/3039868		35	Computer Science, Theory & Methods	Computer Science	ER9BP	WOS:000399118600012		No			2017-07-02	
J	Poussin, C; Belcastro, V; Martin, F; Boue, S; Peitsch, MC; Hoeng, J				Poussin, Carine; Belcastro, Vincenzo; Martin, Florian; Boue, Stephanie; Peitsch, Manuel C.; Hoeng, Julia			Crowd-Sourced Verification of Computational Methods and Data in Systems Toxicology: A Case Study with a Heat-Not-Burn Candidate Modified Risk Tobacco Product	CHEMICAL RESEARCH IN TOXICOLOGY			English	Article; Proceedings Paper	International Systems Toxicology Meeting	2016	SWITZERLAND				DIFFERENTIAL DNA METHYLATION; SMOKING-CESSATION; CARDIOVASCULAR-DISEASE; NETWORK MODELS; EXPOSURE; BLOOD; SIGNATURE; DISCOVERY; IMPROVER; INFLAMMATION	Systems toxicology intends to quantify the effect of toxic molecules in biological systems and unravel their mechanisms of toxicity. The development of advanced computational methods is required for analyzing and integrating high throughput data generated for this purpose as well as for extrapolating predictive toxicological outcomes and risk estimates. To ensure the performance and reliability of the methods and verify conclusions from systems toxicology data analysis, it is important to conduct unbiased evaluations by independent third parties. As a case study, we report here the results of an independent verification of methods and data in systems toxicology by crowdsourcing. The sbv IMPROVER systems toxicology computational challenge aimed to evaluate computational methods for the development of blood-based gene expression signature classification models with the ability to predict smoking exposure status. Participants created/trained models on blood gene expression data sets including smokers/mice exposed to 3R4F (a reference cigarette) or noncurrent smokers/Sham (mice exposed to air). Participants applied their models on unseen data to predict whether subjects classify closer to smoke-exposed or nonsmoke exposed groups. The data sets also included data from subjects that had been exposed to potential modified risk tobacco products (MRTPs) or that had switched to a MRTP after exposure to conventional cigarette smoke. The scoring of anonymized participants' predictions was done using predefined metrics. The top 3 performers' methods predicted class labels with area under the precision recall scores above 0.9. Furthermore, although various computational approaches were used, the crowd's results confirmed our own data analysis outcomes with regards to the classification of MRTP-related samples. Mice exposed directly to a MRTP were classified closer to the Sham group. After switching to a MRTP, the confidence that subjects belonged to the smoke-exposed group decreased significantly. Smoking exposure gene signatures that contributed to the group separation included a core set of genes highly consistent across teams such as AHRR, LRRN3, SASH1, and P2RY6. In conclusion, crowdsourcing constitutes a pertinent approach, in complement to the classical peer review process, to independently and unbiasedly verify computational methods and data for risk assessment using systems toxicology.	[Poussin, Carine; Belcastro, Vincenzo; Martin, Florian; Boue, Stephanie; Peitsch, Manuel C.; Hoeng, Julia] Philip Morris Prod SA, PMI R&D, Quai Jeanrenaud 5, CH-2000 Neuchatel, Switzerland	Poussin, C (reprint author), Philip Morris Prod SA, PMI R&D, Quai Jeanrenaud 5, CH-2000 Neuchatel, Switzerland.	carine.poussin@pmi.com			Philip Morris International	Philip Morris International is the sole source of funding and sponsor of this project.	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APR	2017	30	4					934	945		10.1021/acs.chemrestox.6b00345		12	Chemistry, Medicinal; Chemistry, Multidisciplinary; Toxicology	Pharmacology & Pharmacy; Chemistry; Toxicology	ES5ZT	WOS:000399626100007	28085253	No			2017-07-02	
J	Thammasudjarit, R; Plangprasopchok, A; Pluempitiwiriyawej, C				Thammasudjarit, Ratchainant; Plangprasopchok, Anon; Pluempitiwiriyawej, Charnyote			A Novel Label Aggregation with Attenuated Scores for Ground-Truth Identification of Dataset Annotation with Crowdsourcing	IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS			English	Article; Proceedings Paper	8th Forum on Data Engineering and Information Management (DEIM)	MAR, 2016	Fukuoka, JAPAN			ground-truth identification; crowdsourcing; label aggregation; attenuation scoring	ALGORITHM	Ground-truth identification - the process, which infers the most probable labels, for a certain dataset, from crowdsourcing annotations - is a crucial task to make the dataset usable, e.g., for a supervised learning problem. Nevertheless, the process is challenging because annotations from multiple annotators are inconsistent and noisy. Existing methods require a set of data sample with corresponding ground-truth labels to precisely estimate annotator performance but such samples are difficult to obtain in practice. Moreover, the process requires a post-editing step to validate indefinite labels, which are generally unidentifiable without thoroughly inspecting the whole annotated data. To address the challenges, this paper introduces: 1) Attenuated score (A-score) - an indicator that locally measures annotator performance for segments of annotation sequences, and 2) label aggregation method that applies A-score for ground-truth identification. The experimental results demonstrate that A-score label aggregation outperforms majority vote in all datasets by accurately recovering more labels. It also achieves higher F1 scores than those of the strong baselines in all multi-class data. Additionally, the results suggest that A-score is a promising indicator that helps identifying indefinite labels for the postediting procedure.	[Thammasudjarit, Ratchainant; Pluempitiwiriyawej, Charnyote] Mahidol Univ, Fac Informat & Commun Technol, Salaya, Nakhon Pathom, Thailand; [Plangprasopchok, Anon] Natl Elect & Comp Technol Ctr, Pathum Thani, Thailand	Thammasudjarit, R (reprint author), Mahidol Univ, Fac Informat & Commun Technol, Salaya, Nakhon Pathom, Thailand.	ratchainant.tha@student.mahidol.ac.th; anon.plangplasopchok@nectec.or.th; charnyote.plu@mahidol.ac.th					Chen X., 2013, P 30 INT C MACH LEAR, P64; Chung MJY, 2014, IEEE INT CONF ROBOT, P4777, DOI 10.1109/ICRA.2014.6907558; Dawid A P, 1979, APPL STAT, V28, P20, DOI DOI 10.2307/2346806; Demartini G., 2012, P 21 INT C WORLD WID, P469, DOI DOI 10.1145/2187836.2187900; DEMPSTER AP, 1977, J ROY STAT SOC B MET, V39, P1; Deng J., 2009, 2009 IEEE C COMP VIS, P2, DOI 10.1109/ICEMI.2009.5274591; Georgescu M., 2014, P 4 INT C WEB INT MI; Hovy D., 2014, P 52 ANN M ASS COMP, V2, P377; Hovy D., 2013, NAACL HLT 13, V3, P1120; Hsueh P.-Y., 2009, P NAACL HLT 2009 WOR, P27, DOI 10.3115/1564131.1564137; Leech G., 2005, DEV LINGUISTIC CORPO, P17; LITTLESTONE N, 1994, INFORM COMPUT, V108, P212, DOI 10.1006/inco.1994.1009; Liu Q., 2012, P ADV NEUR INF PROC, P701; Raykar VC, 2010, J MACH LEARN RES, V11, P1297; Rodrigues F, 2013, PATTERN RECOGN LETT, V34, P1428, DOI 10.1016/j.patrec.2013.05.012; Sheshadri A., 2013, P 1 AAAI C HUM COMP, P156; Snow R., 2008, P C EMP METH NAT LAN, P254, DOI 10.3115/1613715.1613751; Thammasudjarit R., 2016, S NAT LANG PROC; Tian Y., 2012, P 18 ACM SIGKDD INT, P226; Viera AJ, 2005, FAM MED, V37, P360; Whitehill J., 2009, ADV NEURAL INFORM PR, P1; Wu X., 2012, P 26 AAAI C ART INT, P1713; Zhou D., 2012, ADV NEURAL INFORM PR, V25, P2204; Zhou D., 2014, P 31 INT C MACH LEAR, P262	24	0	0	2	2	IEICE-INST ELECTRONICS INFORMATION COMMUNICATIONS ENG	TOKYO	KIKAI-SHINKO-KAIKAN BLDG, 3-5-8, SHIBA-KOEN, MINATO-KU, TOKYO, 105-0011, JAPAN	1745-1361			IEICE T INF SYST	IEICE Trans. Inf. Syst.	APR	2017	E100D	4					750	757		10.1587/transinf.2016DAP0024		8	Computer Science, Information Systems; Computer Science, Software Engineering	Computer Science	ES2PT	WOS:000399371100017		No			2017-07-02	
J	Gong, YW				Gong, Yiwei			Estimating participants for knowledge-intensive tasks in a network of crowdsourcing marketplaces	INFORMATION SYSTEMS FRONTIERS			English	Article						Knowledge-intensive crowdsourcing; Flexibility; Search friction; Estimation algorithm	INFORMATION-SYSTEMS; MANAGEMENT-SYSTEMS; SEARCH; AHP; MODEL; CAPABILITIES; EQUILIBRIUM; PERSPECTIVE; FRAMEWORK; DECISION	Crowdsourcing has become an increasingly attractive practice for companies to abstain on-demand workforce and higher level of flexibility in open contexts. While knowledge-intensive crowdsourcing is expected to be prosperous, most current crowdsourcing calls are still about general and low-priced tasks. An obstacle of conducing knowledge-intensive crowdsourcing is the lack of diversity of expertise and the small scale of crowd in isolated crowdsourcing marketplaces. In this paper, a network of crowdsourcing marketplaces is envisioned for efficient knowledge-intensive crowdsourcing and engagement of massive and diverse participants across different marketplaces. Based on an algorithm for estimating participants for knowledge-intensive crowdsourcing tasks, an experiment with 100 simulations indicates that conducting crowdsourcing tasks in a network of crowdsourcing marketplaces results in higher customer satisfaction than doing that in isolated marketplaces. This finding advocates the development of a network of crowdsourcing marketplaces to open up the potential of knowledge-intensive crowdsourcing.	[Gong, Yiwei] Wuhan Univ, Sch Informat Management, Wuhan 430072, Hubei, Peoples R China	Gong, YW (reprint author), Wuhan Univ, Sch Informat Management, Wuhan 430072, Hubei, Peoples R China.	yiweigong@whu.edu.cn			National Natural Science Foundation of China [71501145]	This work is supported by the National Natural Science Foundation of China (Grand No. 71501145).	Abascal-Mena R., 2014, 6 INT C SOC COMP SOC; Afuah A, 2012, ACAD MANAGE REV, V37, P355, DOI 10.5465/amr.2010.0146; Alavi M, 2001, MIS QUART, V25, P107, DOI 10.2307/3250961; Boudreau KJ, 2013, HARVARD BUS REV, V91, P60; Brabham DC, 2008, CONVERGENCE-US, V14, P75, DOI DOI 10.1177/1354856507084420; Chen MF, 2004, MATH COMPUT MODEL, V40, P1473, DOI 10.1016/j.mcm.2005.01.006; Corvello Vincenzo, 2013, Journal of Technology Management & Innovation, V8, P166, DOI 10.4067/S0718-27242013000200014; Deng Julong, 1989, Journal of Grey Systems, V1, P1; DIAMOND PA, 1982, J POLIT ECON, V90, P881, DOI 10.1086/261099; Difallah D. 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Syst. Front.	APR	2017	19	2					301	319		10.1007/s10796-016-9674-6		19	Computer Science, Information Systems; Computer Science, Theory & Methods	Computer Science	ER7UA	WOS:000399017900009		No			2017-07-02	
J	Vernez, SL; Huynh, V; Osann, K; Okhunov, Z; Landman, J; Clayman, RV				Vernez, Simone L.; Huynh, Victor; Osann, Kathryn; Okhunov, Zhamshid; Landman, Jaime; Clayman, Ralph V.			C-SATS: Assessing Surgical Skills Among Urology Residency Applicants	JOURNAL OF ENDOUROLOGY			English	Article						clinical competence; crowdsourcing; education; interviews; residency; validation studies	CROWD-SOURCED ASSESSMENT; TECHNICAL SKILLS; ASSESSMENT-TOOL; SURGERY; PERFORMANCE; SIMULATOR	Background: We hypothesized that surgical skills assessment could aid in the selection process of medical student applicants to a surgical program. Recently, crowdsourcing has been shown to provide an accurate assessment of surgical skills at all levels of training. We compared expert and crowd assessment of surgical tasks performed by resident applicants during their interview day at the urology program at the University of California, Irvine. Materials and Methods: Twenty-five resident interviewees performed four tasks: open square knot tying, laparoscopic peg transfer, robotic suturing, and skill task 8 on the LAP Mentor (TM) (Simbionix Ltd., Lod, Israel). Faculty experts and crowd workers (Crowd-Sourced Assessment of Technical Skills [C-SATS], Seattle, WA) assessed recorded performances using the Objective Structured Assessment of Technical Skills (OSATS), Global Evaluative Assessment of Robotic Skills (GEARS), and the Global Operative Assessment of Laparoscopic Skills (GOALS) validated assessment tools. Results: Overall, 3938 crowd assessments were obtained for the four tasks in less than 3.5 hours, whereas the average time to receive 150 expert assessments was 22 days. Inter-rater agreement between expert and crowd assessment scores was 0.62 for open knot tying, 0.92 for laparoscopic peg transfer, and 0.86 for robotic suturing. Agreement between applicant rank on skill task 8 on the LAP Mentor assessment and crowd assessment was 0.32. The crowd match rank based solely on skills performance did not compare well with the final faculty match rank list (0.46); however, none of the bottom five crowd-rated applicants appeared in the top five expert-rated applicants and none of the top five crowd-rated applicants appeared in the bottom five expertrated applicants. Conclusions: Crowd-source assessment of resident applicant surgical skills has good inter-rater agreement with expert physician raters but not with a computer-based objective motion metrics software assessment. Overall applicant rank was affected to some degree by the crowd performance rating.	[Vernez, Simone L.; Huynh, Victor; Okhunov, Zhamshid; Landman, Jaime; Clayman, Ralph V.] Univ Calif Irvine, Dept Urol, 333 City Blvd West,Suite 2100, Orange, CA 92868 USA; [Osann, Kathryn] Univ Calif Irvine, Dept Med, Hematol Oncol Div, Orange, CA 92668 USA	Clayman, RV (reprint author), Univ Calif Irvine, Dept Urol, 333 City Blvd West,Suite 2100, Orange, CA 92868 USA.	rclayman@uci.edu					Birkmeyer JD, 2013, NEW ENGL J MED, V369, P1434, DOI 10.1056/NEJMsa1300625; Chen C, 2014, J SURG RES, V187, P65, DOI 10.1016/j.jss.2013.09.024; Cronbach LJ, 2004, EDUC PSYCHOL MEAS, V64, P391, DOI 10.1177/0013164404266386; Ghani KR, 2016, EUR UROL, V69, P547, DOI 10.1016/j.eururo.2015.11.028; Goh AC, 2012, J UROLOGY, V187, P247, DOI 10.1016/j.juro.2011.09.032; Holst D, 2015, J ENDOUROL, V29, P1183, DOI 10.1089/end.2015.0104; Holst D, 2015, J ENDOUROL, V29, P604, DOI 10.1089/end.2014.0616; Kowalewski TM, 2016, J UROLOGY, V195, P1859, DOI 10.1016/j.juro.2016.01.005; Lange PH, 2008, AUA NEWS, V13, P1; Matsuda T, 2006, J UROLOGY, V176, P2168, DOI 10.1016/j.juro.2006.07.034; Matsuda T, 2012, J ENDOUROL, V26, P1506, DOI 10.1089/end.2012.0183; McDougall EM, 2006, J AM COLL SURGEONS, V202, P779, DOI 10.1016/j.jamcollsurg.2006.01-004; Polin MR, 2016, AM J OBSTET GYNECOL, V215, DOI 10.1016/j.ajog.2016.06.033; Powers MK, 2016, J ENDOUROL, V30, P447, DOI 10.1089/end.2015.0665; Scott DJ, 2000, SURGERY, V128, P613, DOI 10.1067/msy.2000.108115; Steers WD, 2005, J UROLOGY, V173, P1451, DOI 10.1097/01.ju.0000159652.29026.28; van Hove PD, 2010, BRIT J SURG, V97, P972, DOI 10.1002/bjs.7115; Vassiliou MC, 2005, AM J SURG, V190, P107, DOI 10.1016/j.amjsurg.2005.04.004; Weissbart SJ, 2015, UROLOGY, V85, P731, DOI 10.1016/j.urology.2014.12.041; White LW, 2015, J ENDOUROL, V29, P1295, DOI 10.1089/end.2015.0191	20	0	0	0	0	MARY ANN LIEBERT, INC	NEW ROCHELLE	140 HUGUENOT STREET, 3RD FL, NEW ROCHELLE, NY 10801 USA	0892-7790	1557-900X		J ENDOUROL	J. Endourol.	APR	2017	31			1			S95	S100		10.1089/end.2016.0569		6	Urology & Nephrology	Urology & Nephrology	ES4IX	WOS:000399498900018	27633332	No			2017-07-02	
J	Ahmetovic, D; Manduchi, R; Coughlan, JM; Mascetti, S				Ahmetovic, Dragan; Manduchi, Roberto; Coughlan, James M.; Mascetti, Sergio			Mind Your Crossings: Mining GIS Imagery for Crosswalk Localization	ACM TRANSACTIONS ON ACCESSIBLE COMPUTING			English	Article							BLIND PEDESTRIANS; PEOPLE	For blind travelers, finding crosswalks and remaining within their borders while traversing them is a crucial part of any trip involving street crossings. While standard Orientation & Mobility (O&M) techniques allow blind travelers to safely negotiate street crossings, additional information about crosswalks and other important features at intersections would be helpful in many situations, resulting in greater safety and/or comfort during independent travel. For instance, in planning a trip a blind pedestrian may wish to be informed of the presence of all marked crossings near a desired route. We have conducted a survey of several O&M experts from the United States and Italy to determine the role that crosswalks play in travel by blind pedestrians. The results show stark differences between survey respondents from the U.S. compared with Italy: the former group emphasized the importance of following standard O&M techniques at all legal crossings ( marked or unmarked), while the latter group strongly recommended crossing at marked crossings whenever possible. These contrasting opinions reflect differences in the traffic regulations of the two countries and highlight the diversity of needs that travelers in different regions may have. To address the challenges faced by blind pedestrians in negotiating street crossings, we devised a computer vision-based technique that mines existing spatial image databases for discovery of zebra crosswalks in urban settings. Our algorithm first searches for zebra crosswalks in satellite images; all candidates thus found are validated against spatially registered Google Street View images. This cascaded approach enables fast and reliable discovery and localization of zebra crosswalks in large image datasets. While fully automatic, our algorithm can be improved by a final crowdsourcing validation. To this end, we developed a Pedestrian Crossing Human Validation web service, which supports crowdsourcing, to rule out false positives and identify false negatives.	[Ahmetovic, Dragan] Carnegie Mellon Univ, 5000 Forbes Ave,Newell Simon Hall 4522, Pittsburgh, PA 15213 USA; [Manduchi, Roberto] Univ Calif Santa Cruz, 1156 High St,MS SOE3, Santa Cruz, CA 95064 USA; [Coughlan, James M.] Smith Kettlewell Eye Res Inst, 2318 Fillmore St, San Francisco, CA 94115 USA; [Mascetti, Sergio] Univ Milan, Dept Comp Sci, EveryWare Lab, Via Comel 39, I-20135 Milan, Italy	Ahmetovic, D (reprint author), Carnegie Mellon Univ, 5000 Forbes Ave,Newell Simon Hall 4522, Pittsburgh, PA 15213 USA.	dragan1@cmu.edu; manduchi@soe.ucsc.edu; coughlan@ski.org					Ahmetovic Dragan, 2011, P 13 INT C HUM COMP, P275; Ahmetovic Dragan, 2016, P 18 INT C HUM COMP, P90; Ahmetovic D., 2016, P 13 WEB ALL C W4A 1; Ahmetovic D, 2015, ASSETS'15: PROCEEDINGS OF THE 17TH INTERNATIONAL ACM SIGACCESS CONFERENCE ON COMPUTERS & ACCESSIBILITY, P251, DOI 10.1145/2700648.2809847; Ahmetovic D, 2014, INT C PATT RECOG, P2566, DOI 10.1109/ICPR.2014.443; Akinlar C, 2011, PATTERN RECOGN LETT, V32, P1633, DOI 10.1016/j.patrec.2011.06.001; Ancillotti Massimo, 2010, RIFORMA CODICE STRAD; Ashmead DH, 2005, J TRANSP ENG-ASCE, V131, P812, DOI 10.1061/(ASCE)0733-947X(2005)131:11(812); Barlow J. 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Access. Comput.	APR	2017	9	4	1		SI				11	10.1145/3046790		25	Computer Science, Interdisciplinary Applications	Computer Science	ER8SJ	WOS:000399092700002		No			2017-07-02	
J	Mohamed, R; Aly, H; Youssef, M				Mohamed, Reham; Aly, Heba; Youssef, Moustafa			Accurate Real-time Map Matching for Challenging Environments	IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS			English	Article						Map matching; Hidden Markov Model; cellular-based trajectories; crowdsourcing	PHONE	We present the SnapNet system, which provides accurate real-time map matching for cellular-based trajectory traces. Such traces are characterized by input locations that are far from the actual road segment, errors on the order of kilometers, back-and-forth transitions, and highly sparse input data. SnapNet applies a series of filters to handle the noisy locations and an interpolation stage to address the data sparseness. At the core of SnapNet is a novel incremental HMM algorithm that combines digital map hints in the estimation process and a number of heuristics to reduce the noise and provide real-time estimations. Evaluation of SnapNet using actual traces from different cities covering more than 400 km shows that it can achieve a precision and recall of more than 90% under noisy coarse-grained input location estimates. This maps to over 97% and 34% enhancement in precision and recall, respectively, when compared to the traditional HMM map-matching algorithms. Moreover, SnapNet has a latency of 0.58 ms per location estimate.	[Mohamed, Reham; Aly, Heba] Egypt Japan Univ Sci & Technol, Wireless Res Ctr, Alexandria 21934, Egypt; [Aly, Heba] Univ Maryland, College Pk, MD 20742 USA; [Youssef, Moustafa] Egypt Japan Univ Sci & Technol, Alexandria 21934, Egypt	Mohamed, R (reprint author), Egypt Japan Univ Sci & Technol, Wireless Res Ctr, Alexandria 21934, Egypt.	reham.mohamed@ejust.edu.eg; heba@cs.umd.edu; moustafa.youssef@ejust.edu.eg		Youssef, Moustafa/0000-0002-2063-4364			Al-Husseiny A., 2012, P 25 SBCCI, P1; Alt H, 2003, SIAM PROC S, P589; Aly H., 2015, P IEEE PERCOM, P163; Aly H., 2014, P 11 ANN IEEE INT C, P546; Aly H., 2013, P 21 ACM SIGSPATIAL, P154; Aly H, 2016, PERVASIVE MOB COMPUT, V26, P35, DOI 10.1016/j.pmcj.2015.10.019; Aly H., 2015, P 2015 IEEE 1 INT SM, P1; Alzantot M, 2012, IEEE WCNC, P3204, DOI 10.1109/WCNC.2012.6214359; Bader M., 2013, TEXTS COMPUTER SCI E; BEDNAR J, 1984, ACOUSTICS SPEECH SIG, V32, P145; Bernstein D., 1996, TECH REP; Blazquez CA, 2005, TRANSPORT RES REC, P68; Bloit J, 2008, INT CONF ACOUST SPEE, P2121, DOI 10.1109/ICASSP.2008.4518061; Brakatsoulas S., 2005, P 31 INT C VER LARG, P853; Cui YJ, 2003, IEEE T ROBOTIC AUTOM, V19, P15, DOI 10.1109/TRA.2002.807557; Ekiz N., 2005, INT J INF TECHNOL, V2, P132; Elhamshary M., 2015, P IPIN, P1; Elhamshary M., 2014, P ACM INT JOINT C PE, P607; Goh CY, 2012, IEEE INT C INTELL TR, P776, DOI 10.1109/ITSC.2012.6338627; Greenfeld J. S., 2002, 81 ANN M TRANSP RES; Guha S, 2012, ACM T SENSOR NETWORK, V8, DOI 10.1145/2240116.2240120; Guttman A., 1984, P ACM SIGMOD INT C M, P47, DOI DOI 10.1145/602259.602266; Hummel B., 2006, DYNAMIC MOBILE GIS I; Ibrahim M., 2011, P IEEE ICC, P1; Isaacson E., 1994, ANAL NUMERICAL METHO; Kassem N., 2012, P 75 IEEE VEH TECHN, P1; Krumm J., 2007, P SAE WORLD C, P1; Lee S, 2012, IEEE T WIREL COMMUN, V11, P2720, DOI 10.1109/TWC.2012.052412.110022; Li X., 2007, P IET C WIR MOB SENS, P454; Mohamed R., 2014, P 22 ACM SIGSPATIAL, P401; Mohssen N., 2014, P 11 INT C MOB UB SY, P70; Newson P., 2009, P 17 ACM SIGSPATIAL, P336, DOI DOI 10.1145/1653771.1653818; Phuyal B. P., 2002, P I NAV GPS ION GPS, P430; Quddus M.A., 2003, GPS SOLUTIONS J, V7, P157, DOI DOI 10.1007/S10291-003-0069-Z; Rabiner L. R., 1986, IEEE ASSP Magazine, V3, P4, DOI 10.1109/MASSP.1986.1165342; Schultes D., 2008, THESIS; Sramek R., 2007, ARXIV07040062; Thiagarajan A., 2011, P USENIX, P1; Thiagarajan A, 2009, SENSYS 09: PROCEEDINGS OF THE 7TH ACM CONFERENCE ON EMBEDDED NETWORKED SENSOR SYSTEMS, P85; Wang H, 2013, IEEE INFOCOM SER, P2733; White CE, 2000, TRANSPORT RES C-EMER, V8, P91, DOI 10.1016/S0968-090X(00)00026-7; Yang J.-S., 2005, J E ASIA SOC TRANSPO, V6, P2561, DOI DOI 10.11175/EASTS.6.2561	42	0	0	2	2	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC	PISCATAWAY	445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA	1524-9050	1558-0016		IEEE T INTELL TRANSP	IEEE Trans. Intell. Transp. Syst.	APR	2017	18	4					847	857		10.1109/TITS.2016.2591958		11	Engineering, Civil; Engineering, Electrical & Electronic; Transportation Science & Technology	Engineering; Transportation	ER7FN	WOS:000398975700014		No			2017-07-02	
J	Lewis, MW; Silkstone, N				Lewis, Matthew W.; Silkstone, Nicholas			Improvements in nowcasting capability: analysis of three structurally distinct severe thunderstorms across northern England on 1 July 2015	WEATHER			English	Article							SEA-BREEZE; PRECIPITATION; CLIMATOLOGY; SUPERCELL; STORMS	Three severe and very different storms developed across northern England on 1 July 2015 during a short-lived hot spell. These events are analysed using a mixture of traditional data sources, as well as the improved UK radar capability and the public crowdsourcing of data, which itself could have a powerful role in future nowcasting. The first storm developed during early afternoon from an area of medium-level instability, resulting in strong straight-line winds and localised flash flooding in northeast England. The second storm was rooted to the boundary layer and, from analysis of social media reports, produced a 130km swathe of large hail. Subsequent radar analysis showed this storm to have acquired characteristics of a supercell. Despite the loss of daytime heating, further thunderstorms developed across northwest England later in the evening, albeit rooted to a layer above the boundary layer. However, these storms still produced large hail and frequent lightning, with radar analysis showing the development of a rare elevated supercell.	[Lewis, Matthew W.; Silkstone, Nicholas] Operat Ctr, Met Off, Exeter, Devon, England	Lewis, MW (reprint author), Operat Ctr, Met Off, Exeter, Devon, England.	matthew.lewis@metoffice.gov.uk					Atlas D, 2004, J ATMOS SCI, V61, P1186, DOI 10.1175/1520-0469(2004)061<1186:POOAWM>2.0.CO;2; ATLAS D, 1960, J METEOROL, V17, P244, DOI 10.1175/1520-0469(1960)017<0244:RDOTSB>2.0.CO;2; BROWNING KA, 1964, J ATMOS SCI, V21, P634, DOI 10.1175/1520-0469(1964)021<0634:AAPTWS>2.0.CO;2; Dotzek N, 2009, ATMOS RES, V93, P457, DOI 10.1016/j.atmosres.2008.09.034; Fovell RG, 2005, MON WEATHER REV, V133, P264, DOI 10.1175/MWR-2852.1; Holley DM, 2014, INT J CLIMATOL, V34, P3811, DOI 10.1002/joc.3976; Jirak IL, 2003, MON WEATHER REV, V131, P2428, DOI 10.1175/1520-0493(2003)131<2428:SARSOM>2.0.CO;2; KLEMP JB, 1987, ANNU REV FLUID MECH, V19, P369, DOI 10.1146/annurev.fluid.19.1.369; Lac C, 2002, J ATMOS SCI, V59, P1293, DOI 10.1175/1520-0469(2002)059<1293:ROGWIT>2.0.CO;2; Lewis MW, 2010, ATMOS RES, V97, P194, DOI 10.1016/j.atmosres.2010.04.001; Miller RC., 1972, AWSTR200REV US AIR F; Milligan D, 2015, N E THUNDERSTORM REC; Paulitsch H, 2009, ADV GEOSCI, V20, P3; Rasmussen EN, 1998, WEATHER FORECAST, V13, P1148, DOI 10.1175/1520-0434(1998)013<1148:ABCOSD>2.0.CO;2; SRIVASTAVA RC, 1987, J ATMOS SCI, V44, P1752, DOI 10.1175/1520-0469(1987)044<1752:AMOIDD>2.0.CO;2; Webb JDC, 2009, ATMOS RES, V93, P587, DOI 10.1016/j.atmosres.2008.10.034; WEISMAN ML, 1982, MON WEATHER REV, V110, P504, DOI 10.1175/1520-0493(1982)110<0504:TDONSC>2.0.CO;2; Westbrook C, 2013, WEATHER, V68, P128, DOI 10.1002/wea.1997; Zrnic DS, 2010, J APPL METEOROL CLIM, V49, P687, DOI 10.1175/2009JAMC2300.1	19	0	0	1	1	WILEY	HOBOKEN	111 RIVER ST, HOBOKEN 07030-5774, NJ USA	0043-1656	1477-8696		WEATHER	Weather	APR	2017	72	4					91	98		10.1002/wea.2837		8	Meteorology & Atmospheric Sciences	Meteorology & Atmospheric Sciences	ER3VW	WOS:000398728800003		No			2017-07-02	
J	Filimowicz, MA; Tzankova, VK				Filimowicz, Michael A.; Tzankova, Veronika K.			Creative making, large lectures, and social media: Breaking with tradition in art and design education	ARTS AND HUMANITIES IN HIGHER EDUCATION			English	Article						Art and design education; large enrollments; online learning; social media; teaching creativity		The purpose of this article is to challenge the notion of small studio format delivery expectations in art and design education. Our research reports on an introductory Digital Photography course design that produced equivalent learning outcomes in a large enrollment lecture format. The objective of the project was to introduce (1) a case-based approach to teaching and learning and (2) a multitiered feedback model. The positive learning outcomes produced by this course design call into question the prevailing regimes of teaching creative production within the limits of small studio pedagogy. In addition, the multitiered feedback model we propose can be extended much beyond a classroom setting to include crowdsourcing' as a feedback model in Massive Open Online Courses, also known as MOOCs. Our approach is also highly suggestive of further investigation into applying Kant's notion of the sensus communis - the shared subjective but universal sense of the aesthetic - to common issues surrounding creativity, scale and evaluation.	[Filimowicz, Michael A.] Simon Fraser Univ, Sch Interact Arts & Technol, SIAT SFU Surrey Campus,250-13450 102 Ave,Podium, Surrey, BC V3T 0A3, Canada; [Tzankova, Veronika K.] Simon Fraser Univ, Sch Commun, Surrey, BC V5A 1S6, Canada	Filimowicz, MA (reprint author), Simon Fraser Univ, Sch Interact Arts & Technol, SIAT SFU Surrey Campus,250-13450 102 Ave,Podium, Surrey, BC V3T 0A3, Canada.	mfa13@sfu.ca			Simon Fraser University's Institute for the Study of Teaching and Learning in the Disciplines	The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by a Teaching and Learning Development Grant from Simon Fraser University's Institute for the Study of Teaching and Learning in the Disciplines.	College Art Association, 2011, STAND GUID; Creswell J. W., 1997, QUALITATIVE INQUIRY; DeCuir-Gunby J. T., 2008, BEST PRACTICES QUANT, P125; Flyvbjerg B., 2011, SAGE HDB QUALITATIVE, P301, DOI DOI 10.1016/B978-1-85617-726-9.00005-4; Forsey M, 2013, J SOCIOL, V49, P471, DOI 10.1177/1440783313504059; Kimmerle H, 2000, SCHRIFTEN PHILOS DIF; Kirmayer LJ, 2013, TRANSCULT PSYCHIATRY, V50, P165, DOI 10.1177/1363461513490626; Polanyi Michael, 2009, TACIT DIMENSION; Zahavi D., 2005, SUBJECTIVITY SELFHOO	9	0	0	6	6	SAGE PUBLICATIONS LTD	LONDON	1 OLIVERS YARD, 55 CITY ROAD, LONDON EC1Y 1SP, ENGLAND	1474-0222	1741-265X		ARTS HUM HIGH EDUC	Arts Hum. High. Educ.	APR	2017	16	2					156	172		10.1177/1474022214552197		17	Education & Educational Research	Education & Educational Research	EP6FU	WOS:000397474600003		No			2017-07-02	
J	McKercher, GR; Salmond, JA; Vanos, JK				McKercher, Grant R.; Salmond, Jennifer A.; Vanos, Jennifer K.			Characteristics and applications of small, portable gaseous air pollution monitors	ENVIRONMENTAL POLLUTION			English	Article						Air pollution; Monitoring; Low-cost sensors; Urban pollution; Ozone	HEART-RATE-VARIABILITY; PARTICULATE MATTER; PERSONAL EXPOSURE; ULTRAFINE PARTICLES; NITROGEN-DIOXIDE; CARBON-MONOXIDE; LOW-COST; QUALITY; SENSORS; OZONE	Background: Traditional approaches for measuring air quality based on fixed measurements are inadequate for personal exposure monitoring. To combat this issue, the use of small, portable gas-sensing air pollution monitoring technologies is increasing, with researchers and individuals employing portable and mobile methods to obtain more spatially and temporally representative air pollution data. However, many commercially available options are built for various applications and based on different technologies, assumptions, and limitations. A review of the monitor characteristics of small, gaseous monitors is missing from current scientific literature. Purpose: A state-of-the-art review of small, portable monitors that measure ambient gaseous outdoor pollutants was developed to address broad trends during the last 5-10 years, and to help future experimenters interested in studying gaseous air pollutants choose monitors appropriate for their application and sampling needs. Methods: Trends in small, portable gaseous air pollution monitor uses and technologies were first identified and discussed in a review of literature. Next, searches of online databases were performed for articles containing specific information related to performance, characteristics, and use of such monitors that measure one or more of three criteria gaseous air pollutants: ozone, nitrogen dioxide, and carbon monoxide. All data were summarized into reference tables for comparison between applications, physical features, sensing capabilities, and costs of the devices. Results: Recent portable monitoring trends are strongly related to associated applications and audiences. Fundamental research requires monitors with the best individual performance, and thus the highest cost technology. Monitor networking favors real-time capabilities and moderate cost for greater reproduction. Citizen science and crowdsourcing applications allow for lower-cost components; however important strengths and limitations for each application must be addressed or acknowledged for the given use. (C) 2016 Elsevier Ltd. All rights reserved.	[McKercher, Grant R.; Vanos, Jennifer K.] Texas Tech Univ, Dept Geosci, 3003 15th St, Lubbock, TX 79409 USA; [Salmond, Jennifer A.] Univ Auckland, Sch Environm, 10 Symonds St, Auckland 1010, New Zealand; [Vanos, Jennifer K.] Univ Calif San Diego, Scripps Inst Oceanog, 9500 Gilman Dr, La Jolla, CA 92093 USA	Vanos, JK (reprint author), Texas Tech Univ, Dept Geosci, 3003 15th St, Lubbock, TX 79409 USA.; Vanos, JK (reprint author), Univ Calif San Diego, Scripps Inst Oceanog, 9500 Gilman Dr, La Jolla, CA 92093 USA.	jkvanos@ucsd.edu					2B Technologies, 2012, UV POM MANUAL; 2B Technologies, 2016, PORN PERS OZON MON; Aeroqual, 2016, PORT FIX MON GAS SEN; Aeroqual, 2016, AER SER 200 300 500; Al-Ali AR, 2010, IEEE SENS J, V10, P1666, DOI 10.1109/JSEN.2010.2045890; Aleixandre M., 2012, CHEM ENG T, V30; Antonic A., 2014, SOFTW TEL COMP NETW, P423; Bales E., 2014, PERSONAL POLLUTION M; Baxter LK, 2013, J EXPO SCI ENV EPID, V23, P654, DOI 10.1038/jes.2013.62; Beckx C, 2009, ENVIRON IMPACT ASSES, V29, P179, DOI 10.1016/j.eiar.2008.10.001; Bereitschaft B, 2015, SUSTAIN CITIES SOC, V15, P64, DOI 10.1016/j.scs.2014.12.001; Boulos M.N.K, 2011, INT J HEALTH GEOGR, V10, P1; CairPol, 2016, AUT POLL SENS CAIRCL; Cao TT, 2016, SENSOR ACTUAT B-CHEM, V224, P936, DOI 10.1016/j.snb.2015.10.090; Castell Nuria, 2015, Urban Climate, V14, P370, DOI 10.1016/j.uclim.2014.08.002; Castell N., 2013, REAL WORLD APPL NEW; Cattaneo A, 2010, AEROSOL SCI TECH, V44, P370, DOI 10.1080/02786821003662934; Cavellin LD, 2016, ENVIRON SCI TECHNOL, V50, P313, DOI 10.1021/acs.est.5b04235; Chaudhry V, 2013, INT J ENV ENG MANAG, V4, P639; Component Distributors Inc, 2016, SGX SENS LIM FORM E2; de Nazelle A, 2012, ATMOS ENVIRON, V59, P151, DOI 10.1016/j.atmosenv.2012.05.013; Delgado-Saborit JM, 2012, J ENVIRON MONITOR, V14, P1824, DOI 10.1039/c2em10996d; Devarakonda S., 2013, P 2 ACM SIGKDD INT W, P15; Dutta P., 2009, P 7 ACM C EMB NETW S, P349, DOI 10.1145/1644038.1644095; e2v Technologies, 2008, MICS 4514 COMB CO NO; ELAMPARI K, 2010, INDIAN J SCI TECHNOL, V3, P900; Elen B, 2013, SENSORS-BASEL, V13, P221, DOI 10.3390/s130100221; Gerboles M., 2009, JT RES CENT ENV SUST; Good N., 2015, J EXPO SCI ENV EPIDE; Gozzi F., 2015, ATMOS POLLUT RES; Grant MJ, 2009, HEALTH INFO LIBR J, V26, P91, DOI 10.1111/j.1471-1842.2009.00848.x; Grineski S. 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G., 2007, EXPOSURE ANAL, P33; Zhu YF, 2002, J AIR WASTE MANAGE, V52, P1032	69	0	0	23	23	ELSEVIER SCI LTD	OXFORD	THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND	0269-7491	1873-6424		ENVIRON POLLUT	Environ. Pollut.	APR	2017	223						102	110		10.1016/j.envpol.2016.12.045		9	Environmental Sciences	Environmental Sciences & Ecology	EP4OJ	WOS:000397359500011	28162801	No			2017-07-02	
J	Suh, CH; Tan, VYF; Zhao, RB				Suh, Changho; Tan, Vincent Y. F.; Zhao, Renbo			Adversarial Top-K Ranking	IEEE TRANSACTIONS ON INFORMATION THEORY			English	Article; Proceedings Paper	Information Theory and Applications Workshop	JAN 31-FEB 05, 2016	La Jolla, CA			Adversarial population; Bradley-Terry-Luce model; crowdsourcing; minimax optimality; sample complexity; top-K ranking; tensor decompositions	LATENT VARIABLE MODELS	We study the top-K ranking problem where the goal is to recover the set of top-K ranked items out of a large collection of items based on partially revealed preferences. We consider an adversarial crowdsourced setting where there are two population sets, and pairwise comparison samples drawn from one of the populations follow the standard Bradley-Terry-Luce model (i.e., the chance of item i beating item j is proportional to the relative score of item i to item j), while in the other population, the corresponding chance is inversely proportional to the relative score. When the relative size of the two populations is known, we characterize the minimax limit on the sample size required (up to a constant) for reliably identifying the top-K items, and demonstrate how it scales with the relative size. Moreover, by leveraging a tensor decomposition method for disambiguating mixture distributions, we extend our result to the more realistic scenario, in which the relative population size is unknown, thus establishing an upper bound on the fundamental limit of the sample size for recovering the top-K set.	[Suh, Changho] Korea Adv Inst Sci & Technol, Sch Elect Engn, Taejon 305701, South Korea; [Tan, Vincent Y. F.; Zhao, Renbo] Natl Univ Singapore, Dept Elect & Comp Engn, Singapore 117583, Singapore; [Tan, Vincent Y. F.; Zhao, Renbo] NUS, Dept Math, Singapore 119076, Singapore; [Zhao, Renbo] NUS, Dept Ind & Syst Engn, Singapore 117576, Singapore	Suh, CH (reprint author), Korea Adv Inst Sci & Technol, Sch Elect Engn, Taejon 305701, South Korea.	chsuh@kaist.ac.kr; vtan@nus.edu.sg; elezren@nus.edu.sg		Tan, Vincent/0000-0002-5008-4527	National Research Foundation of Korea within MSIP through the Korean Government [2015R1C1A1A02036561]; National University of Singapore (NUS) through the NUS Young Investigator Award [R-263-000-B37-133]; MoE AcRF Tier 1 Grant [R-263-000-C12-112]	Manuscript received February 15, 2016; revised October 11, 2016; accepted January 23, 2017. Date of publication January 26, 2017; date of current version March 15, 2017. C. Suh was supported by the National Research Foundation of Korea within MSIP through the Korean Government under Grant 2015R1C1A1A02036561. V. Y. F. Tan and R. Zhao were supported in part by the National University of Singapore (NUS) through the NUS Young Investigator Award under Award R-263-000-B37-133 and in part by MoE AcRF Tier 1 Grant under Grant R-263-000-C12-112. This paper was presented at the 2016 Information Theory and Applications Workshop.	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J	Bujari, A; Ciman, M; Gaggi, O; Palazzi, CE				Bujari, Armir; Ciman, Matteo; Gaggi, Ombretta; Palazzi, Claudio E.			Using gamification to discover cultural heritage locations from geo-tagged photos	PERSONAL AND UBIQUITOUS COMPUTING			English	Article						Cultural heritage; Gamification; Geolocalization; Knowledge discovery		Many enchanting cultural heritage locations are hidden from tourists, especially when considering countries full of historic attractions. Tourists tend to consider only mainstream monuments and towns, neglecting wonderful little jewels along their travel itinerary. However, this is generally not their fault, as travelers cannot be aware of all the surrounding beauties when visiting a new region. To this aim, we discuss and analyze here PhotoTrip, an interactive tool able to autonomously recommend charming, even if not mainstream, cultural heritage locations along travel itineraries. PhotoTrip is able to identify these points of interest by gathering pictures and related information from Flickr and Wikipedia and then provide the user with suggestions and recommendations. An important technical challenge for this kind of services is the ability to provide only the most relevant pictures among the many available for any considered itinerary. To this aim, we have exploited social networks, crowdsourcing and gamification to involve users in the process of improving the response quality of our system.	[Bujari, Armir; Gaggi, Ombretta; Palazzi, Claudio E.] Univ Padua, Dept Math, Padua, Italy; [Ciman, Matteo] Univ Geneva, Qual Life Grp, Geneva, Switzerland	Gaggi, O (reprint author), Univ Padua, Dept Math, Padua, Italy.	abujari@math.unipd.it; Matteo.Ciman@unige.ch; gaggi@math.unipd.it; cpalazzi@math.unipd.it			Universit degli Studi di Padova [PRAT CPDA137314, PRAT CPDA151221]	The authors would like to thank Michele Torresin and Dario De Giovanni for their technical help during the development of the system and those who took part to the user tests. This work has been partially funded by the Universit degli Studi di Padova, through the Projects PRAT CPDA137314 and PRAT CPDA151221.	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J	Raad, E; Chbeir, R; Dipanda, A; Raad, EJ				Raad, Elie; Chbeir, Richard; Dipanda, Albert; Raad, Eliana J.			Automatic rule generation using crowdsourcing for better relationship type discovery	PERVASIVE AND MOBILE COMPUTING			English	Article						Relationship discovery; Crowdsourcing; Knowledge acquisition; Rule extraction; Link mining; Social networks	SOCIAL NETWORK; EXTRACTION; PRIVACY; PHOTOS; WEB	With the increasing popularity of information sharing and the growing number of social network users, relationship management is one of the key challenges which arise in the context of social networks. One particular relationship management task aims at identifying relationship types that are relevant between social network users and their contacts. Manually identifying relationship types is one possible solution, however it is a time-consuming and tedious task that requires constant maintenance. In this paper, we present a rule-based approach that sets the focus on published photos as a valuable source to identify relationship types. Our approach automatically generates relevant relationship discovery rules based on a crowdsourcing methodology that constructs useful photo datasets. Knowledge is first retrieved from these datasets and then used to create relationship discovery rules. The obtained set of rules is extended using a number of predefined common sense rules and then personalized using a rule mining algorithm. Experimental results demonstrate the correctness and the efficiency of the generated sets of rules to identify relationship types. (C) 2016 Elsevier B.V. All rights reserved.	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