Yu Li, Mingxiao Li, Dongyang Ou^*, Junjie Guo, Fangyuan Pan

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 893-909, 2024, DOI:10.32604/cmes.2023.031350

Abstract With the rapid development of mobile Internet, spatial crowdsourcing has become more and more popular. Spatial crowdsourcing consists of many different types of applications, such as spatial crowd-sensing services. In terms of spatial crowd-sensing, it collects and analyzes traffic sensing data from clients like vehicles and traffic lights to construct intelligent traffic prediction models. Besides collecting sensing data, spatial crowdsourcing also includes spatial delivery services like DiDi and Uber. Appropriate task assignment and worker selection dominate the service quality for spatial crowdsourcing applications. Previous research conducted task assignments via traditional matching approaches or using simple network models. However, advanced mining… More > Graphic Abstract

Tamilvizhi Thanarajan¹, Youseef Alotaibi², Surendran Rajendran^3,*, Krishnaraj Nagappan⁴

CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1995-2013, 2023, DOI:10.32604/cmc.2023.039644

Abstract Autism spectrum disorder (ASD) can be defined as a neurodevelopmental condition or illness that can disturb kids who have heterogeneous characteristics, like changes in behavior, social disabilities, and difficulty communicating with others. Eye tracking (ET) has become a useful method to detect ASD. One vital aspect of moral erudition is the aptitude to have common visual attention. The eye-tracking approach offers valuable data regarding the visual behavior of children for accurate and early detection. Eye-tracking data can offer insightful information about the behavior and thought processes of people with ASD, but it is important to be aware of its limitations… More >

Adel Hafeezallah¹, Ahlam Al-Dhamari^2,3,*, Syed Abd Rahman Abu-Bakar²

Computer Systems Science and Engineering, Vol.47, No.1, pp. 593-611, 2023, DOI:10.32604/csse.2023.039479

Abstract Visual motion segmentation (VMS) is an important and key part of many intelligent crowd systems. It can be used to figure out the flow behavior through a crowd and to spot unusual life-threatening incidents like crowd stampedes and crashes, which pose a serious risk to public safety and have resulted in numerous fatalities over the past few decades. Trajectory clustering has become one of the most popular methods in VMS. However, complex data, such as a large number of samples and parameters, makes it difficult for trajectory clustering to work well with accurate motion segmentation results. This study introduces a… More >

G. Rajasekaran^1,*, J. Raja Sekar²

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2399-2412, 2023, DOI:10.32604/iasc.2023.029119

Abstract Abnormal behavior detection is challenging and one of the growing research areas in computer vision. The main aim of this research work is to focus on panic and escape behavior detections that occur during unexpected/uncertain events. In this work, Pyramidal Lucas Kanade algorithm is optimized using EMEHOs to achieve the objective. First stage, OPLKT-EMEHOs algorithm is used to generate the optical flow from MIIs. Second stage, the MIIs optical flow is applied as input to 3 layer CNN for detect the abnormal crowd behavior. University of Minnesota (UMN) dataset is used to evaluate the proposed system. The experimental result shows… More >

Shinjin Kang¹, Soo Kyun Kim^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 219-237, 2022, DOI:10.32604/cmes.2022.018413

Abstract This paper proposes a methodology for using multi-modal data in gameplay to detect outlier behavior. The proposed methodology collects, synchronizes, and quantifies time-series data from webcams, mouses, and keyboards. Facial expressions are varied on a one-dimensional pleasure axis, and changes in expression in the mouth and eye areas are detected separately. Furthermore, the keyboard and mouse input frequencies are tracked to determine the interaction intensity of users. Then, we apply a dynamic time warp algorithm to detect outlier behavior. The detected outlier behavior graph patterns were the play patterns that the game designer did not intend or play patterns that… More >

Yu Xue^1,2,*, Jiafeng Qin¹, Shoubao Su², Adam Slowik³

Computer Systems Science and Engineering, Vol.39, No.2, pp. 211-219, 2021, DOI:10.32604/csse.2021.016693

Abstract Recently, online learning platforms have proven to help people gain knowledge more conveniently. Since the outbreak of COVID-19 in 2020, online learning has become a mainstream mode, as many schools have adopted its format. The platforms are able to capture substantial data relating to the students’ learning activities, which could be analyzed to determine relationships between learning behaviors and study habits. As such, an intelligent analysis method is needed to process efficiently this high volume of information. Clustering is an effect data mining method which discover data distribution and hidden characteristic from uncharacterized online learning data. This study proposes a… More >

Shinjin Kang¹, Soo Kyun Kim^2,*

CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3725-3736, 2021, DOI:10.32604/cmc.2021.016828

Abstract In this study, we propose a low-cost system that can detect the space outlier utilization of residents in an indoor environment. We focus on the users’ app usage to analyze unusual behavior, especially in indoor spaces. This is reflected in the behavioral analysis in that the frequency of using smartphones in personal spaces has recently increased. Our system facilitates autonomous data collection from mobile app logs and Google app servers and generates a high-dimensional dataset that can detect outlier behaviors. The density-based spatial clustering of applications with noise (DBSCAN) algorithm was applied for effective singular movement analysis. To analyze high-level… More >

Shinjin Kang¹, Taiwoo Park^2,*

Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 205-214, 2020, DOI:10.31209/2019.100000141

Abstract This paper describes an outlier detection system based on a multimodal physiology data clustering algorithm in a PC gaming environment. The goal of this system is to provide information on a game player’s abnormal behavior with a bio-signal analysis. Using this information, the game platform can easily identify players with abnormal behavior in specific events. To do this, we propose a mouse device that measures the wearer's skin conductivity, temperature, and motion. We also suggest a Dynamic Time Warping (DTW) based clustering algorithm. The developed system examines the biometric information of 50 players in a bullet dodge game. This paper… More >

Ling Wu¹, Haoxue Liu², Tong Zhu², Yueqi Hu³

Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 633-642, 2018, DOI:10.31209/2018.100000030

Abstract The objective of the current study was to examine how experienced and inexperienced driver behaviour changed (including heart rate and longitudinal speeds) when approaching and exiting highway tunnels. Simultaneously, the NARX neural network was used to predict real-time speed with the heart rate regarded as the input variable. The results indicated that familiarity with the experimental route did decrease drivers’ mental stress but resulted in higher speed. The proposed NARX model could predict synchronous speed with high accuracy. These results of the present study concern how to establish the automated driver model in the simulation environment. More >

Yongping Yu¹, Lihui Chen¹, Shaopeng Zheng¹, Baihui Zeng¹, Weipeng Sun^{2, ∗}

CMES-Computer Modeling in Engineering & Sciences, Vol.123, No.1, pp. 185-200, 2020, DOI:10.32604/cmes.2020.07997

Abstract This paper is focused on the post-buckling behavior of the fixed laminated composite beams with effects of axial compression force and the shear deformation. The analytical solutions are established for the original control equations (that is not simplified) by applying the Maclaurin series expansion, Chebyshev polynomials, the harmonic balance method and the Newton’s method. The validity of the present method is verified via comparing the analytical approximate solutions with the numerical ones which are obtained by the shooting method. The present third analytical approximate solutions can give excellent agreement with the numerical solutions for a wide range of the deformation… More >