Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (5)
  • Open Access


    CL2ES-KDBC: A Novel Covariance Embedded Selection Based on Kernel Distributed Bayes Classifier for Detection of Cyber-Attacks in IoT Systems

    Talal Albalawi, P. Ganeshkumar*

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3511-3528, 2024, DOI:10.32604/cmc.2024.046396

    Abstract The Internet of Things (IoT) is a growing technology that allows the sharing of data with other devices across wireless networks. Specifically, IoT systems are vulnerable to cyberattacks due to its opennes The proposed work intends to implement a new security framework for detecting the most specific and harmful intrusions in IoT networks. In this framework, a Covariance Linear Learning Embedding Selection (CL2ES) methodology is used at first to extract the features highly associated with the IoT intrusions. Then, the Kernel Distributed Bayes Classifier (KDBC) is created to forecast attacks based on the probability distribution More >

  • Open Access


    MDNN: Predicting Student Engagement via Gaze Direction and Facial Expression in Collaborative Learning

    Yi Chen1,*, Jin Zhou1, Qianting Gao2, Jing Gao1, Wei Zhang3

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 381-401, 2023, DOI:10.32604/cmes.2023.023234

    Abstract Prediction of students’ engagement in a Collaborative Learning setting is essential to improve the quality of learning. Collaborative learning is a strategy of learning through groups or teams. When cooperative learning behavior occurs, each student in the group should participate in teaching activities. Researchers showed that students who are actively involved in a class gain more. Gaze behavior and facial expression are important nonverbal indicators to reveal engagement in collaborative learning environments. Previous studies require the wearing of sensor devices or eye tracker devices, which have cost barriers and technical interference for daily teaching practice. More >

  • Open Access


    Multi-View Multi-Modal Head-Gaze Estimation for Advanced Indoor User Interaction

    Jung-Hwa Kim1, Jin-Woo Jeong2,*

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5107-5132, 2022, DOI:10.32604/cmc.2022.021107

    Abstract Gaze estimation is one of the most promising technologies for supporting indoor monitoring and interaction systems. However, previous gaze estimation techniques generally work only in a controlled laboratory environment because they require a number of high-resolution eye images. This makes them unsuitable for welfare and healthcare facilities with the following challenging characteristics: 1) users’ continuous movements, 2) various lighting conditions, and 3) a limited amount of available data. To address these issues, we introduce a multi-view multi-modal head-gaze estimation system that translates the user’s head orientation into the gaze direction. The proposed system captures the… More >

  • Open Access


    Isomorphic 2D/3D Objects and Saccadic Characteristics in Mental Rotation

    Akanksha Tiwari1, Ram Bilas Pachori1,2, Premjit Khanganba Sanjram1,3,4,*

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 433-450, 2022, DOI:10.32604/cmc.2022.019256

    Abstract Mental rotation (MR) is an important aspect of cognitive processing in gaming since transformation and manipulation of visuospatial information are necessary in order to execute a gaming task. This study provides insights on saccadic characteristics in gaming task performance that involves 2D and 3D isomorphic objects with varying angular disparity. Healthy participants (N =60) performed MR gaming task. Each participant was tested individually in an acoustic treated lab environment. Gaze behavior data of all participants were recorded during task execution and analyzed to find the changes in spatiotemporal characteristics of saccades associated with the variation in angular… More >

  • Open Access


    Eye Gaze Detection Based on Computational Visual Perception and Facial Landmarks

    Debajit Datta1, Pramod Kumar Maurya1, Kathiravan Srinivasan2, Chuan-Yu Chang3,*, Rishav Agarwal1, Ishita Tuteja1, V. Bhavyashri Vedula1

    CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2545-2561, 2021, DOI:10.32604/cmc.2021.015478

    Abstract The pandemic situation in 2020 brought about a ‘digitized new normal’ and created various issues within the current education systems. One of the issues is the monitoring of students during online examination situations. A system to determine the student’s eye gazes during an examination can help to eradicate malpractices. In this work, we track the users’ eye gazes by incorporating twelve facial landmarks around both eyes in conjunction with computer vision and the HAAR classifier. We aim to implement eye gaze detection by considering facial landmarks with two different Convolutional Neural Network (CNN) models, namely More >

Displaying 1-10 on page 1 of 5. Per Page