Dingwen Wang, Ming Zhao^*

Journal of Cyber Security, Vol.2, No.2, pp. 63-68, 2020, DOI:10.32604/jcs.2020.07229

Abstract Mobile crowdsensing is a new paradigm with powerful performance for data collection through a large number of smart devices. It is essential to obtain high quality data in crowdsensing campaign. Most of the existing specs ignore users’ diversity, focus on solving complicated optimization problem, and consider devices as instances of intelligent software agents which can make reasonable choices on behalf of users. Thus, the efficiency and quality of contributed data cannot be preserved simultaneously. In this paper, we propose a new scheme for improving the quality of contributed data, which recommends tasks to users based on calculated score that jointly… More >

Joseph J. Knadler¹, Daniel J. Penny¹, Tyler H. Harris², Gary D. Webb³, Antonio G. Cabrera^1,4, William B. Kyle¹

Congenital Heart Disease, Vol.13, No.5, pp. 794-798, 2018, DOI:10.1111/chd.12669

Abstract Objective: The growing body of medical literature in pediatric cardiology has made it increasingly difficult for individual providers to stay abreast of the most current, meaningful articles to help guide practice. Crowdsourcing represents a collaborative process of obtaining information from a large group of individuals, typically from an online or web‐based community, and could serve a potential mechanism to pool indi‐ vidual efforts to combat this issue. This study aimed to utilize crowdsourcing as a novel way to generate a list of the most relevant, current publications in congenital heart disease, utilizing input from an international group of professionals in… More >

Shuyu Li¹, Guozheng Zhang^{1, *}

CMC-Computers, Materials & Continua, Vol.63, No.1, pp. 223-241, 2020, DOI:10.32604/cmc.2020.07499

Abstract With the popularity of sensor-rich mobile devices, mobile crowdsensing (MCS) has emerged as an effective method for data collection and processing. However, MCS platform usually need workers’ precise locations for optimal task execution and collect sensing data from workers, which raises severe concerns of privacy leakage. Trying to preserve workers’ location and sensing data from the untrusted MCS platform, a differentially private data aggregation method based on worker partition and location obfuscation (DP-DAWL method) is proposed in the paper. DP-DAWL method firstly use an improved K-means algorithm to divide workers into groups and assign different privacy budget to the group… More >

Jinlin Wang¹, Xing Wang^{1, *}, Yuchen Yang¹, Hongli Zhang¹, Binxing Fang¹

CMC-Computers, Materials & Continua, Vol.62, No.3, pp. 1053-1075, 2020, DOI:10.32604/cmc.2020.08675

Abstract Web information system (WIS) is frequently-used and indispensable in daily social life. WIS provides information services in many scenarios, such as electronic commerce, communities, and edutainment. Data cleaning plays an essential role in various WIS scenarios to improve the quality of data service. In this paper, we present a review of the state-of-the-art methods for data cleaning in WIS. According to the characteristics of data cleaning, we extract the critical elements of WIS, such as interactive objects, application scenarios, and core technology, to classify the existing works. Then, after elaborating and analyzing each category, we summarize the descriptions and challenges… More >

Ning Cao^1,2, Shengfang Li¹, Keyong Shen¹, Sheng Bin³, Gengxin Sun^3,*, Dongjie Zhu⁴, Xiuli Han⁵, Guangsheng Cao⁵, Abraham Campbell⁶

CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 227-241, 2019, DOI:10.32604/cmc.2019.06125

Abstract Monitoring, understanding and predicting Origin-destination (OD) flows in a city is an important problem for city planning and human activity. Taxi-GPS traces, acted as one kind of typical crowd sensed data, it can be used to mine the semantics of OD flows. In this paper, we firstly construct and analyze a complex network of OD flows based on large-scale GPS taxi traces of a city in China. The spatiotemporal analysis for the OD flows complex network showed that there were distinctive patterns in OD flows. Then based on a novel complex network model, a semantics mining method of OD flows… More >

Zhenqiu Xiao^1,*, Bin Yang², Desy Tjahjadi³

CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1141-1154, 2019, DOI:10.32604/cmc.2019.05638

Abstract Crowd counting is a challenging task in crowded scenes due to heavy occlusions, appearance variations and perspective distortions. Current crowd counting methods typically operate on an image patch level with overlaps, then sum over the patches to get the final count. In this paper we describe a real-time pedestrian counting framework based on a two-stage human detection algorithm. Existing works with overhead cameras is mainly based on visual tracking, and their robustness is rather limited. On the other hand, some works, which focus on improving the performances, are too complicated to be realistic. By adopting a line sampling process, a… More >

Tiejun Wang¹, Tao Wu^1,*, Amir Homayoon Ashrafzadeh², Jia He¹

CMC-Computers, Materials & Continua, Vol.57, No.1, pp. 81-96, 2018, DOI:10.32604/cmc.2018.03259

Abstract Crowdsourcing is widely used in various fields to collect goods and services from large participants. Evaluating teaching quality by collecting feedback from experts or students after class is not only delayed but also not accurate. In this paper, we present a crowdsourcing-based framework to evaluate teaching quality in the classroom using a weighted average operator to aggregate information from students’ questionnaires described by linguistic 2-tuple terms. Then we define crowd grade based on similarity degree to distinguish contribution from different students and minimize the abnormal students’ impact on the evaluation. The crowd grade would be updated at the end of… More >