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  • Open Access

    EDITORIAL

    Introduction to the Special Issue on Mechanics of Composite Materials and Structures

    Jian Xiong1,*, Jinshui Yang2, Hui Li3, Wu Xu4

    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 357-359, 2022, DOI:10.32604/cmes.2022.023418

    Abstract This article has no abstract. More >

  • Open Access

    ARTICLE

    RBMDO Using Gaussian Mixture Model-Based Second-Order Mean-Value Saddlepoint Approximation

    Debiao Meng1,2,3, Shiyuan Yang1, Tao Lin4,5,*, Jiapeng Wang1, Hengfei Yang1, Zhiyuan Lv1

    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 553-568, 2022, DOI:10.32604/cmes.2022.020756

    Abstract Actual engineering systems will be inevitably affected by uncertain factors. Thus, the Reliability-Based Multidisciplinary Design Optimization (RBMDO) has become a hotspot for recent research and application in complex engineering system design. The Second-Order/First-Order Mean-Value Saddlepoint Approximate (SOMVSA/FOMVSA) are two popular reliability analysis strategies that are widely used in RBMDO. However, the SOMVSA method can only be used efficiently when the distribution of input variables is Gaussian distribution, which significantly limits its application. In this study, the Gaussian Mixture Model-based Second-Order Mean-Value Saddlepoint Approximation (GMM-SOMVSA) is introduced to tackle above problem. It is integrated with the Collaborative Optimization (CO) method to… More >

  • Open Access

    ARTICLE

    Dynamical Model to Optimize Student’s Academic Performance

    Evren Hincal, Amna Hashim Alzadjali

    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 393-411, 2022, DOI:10.32604/cmes.2022.019781

    Abstract Excellent student’s academic performance is the uppermost priority and goal of educators and facilitators. The dubious marginal rate between admission and graduation rates unveils the rates of dropout and withdrawal from school. To improve the academic performance of students, we optimize the performance indices to the dynamics describing the academic performance in the form of nonlinear system ODE. We established the uniform boundedness of the model and the existence and uniqueness result. The independence and interdependence equilibria were found to be locally and globally asymptotically stable. The optimal control analysis was carried out, and lastly, numerical simulation was run to… More >

  • Open Access

    ARTICLE

    Mechanical Properties of Soil-Rock Mixture Filling in Fault Zone Based on Mesostructure

    Mei Tao1, Qingwen Ren1,*, Hanbing Bian2, Maosen Cao1, Yun Jia3

    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 681-705, 2022, DOI:10.32604/cmes.2022.019522

    Abstract Soil-rock mixture (SRM) filling in fault zone is an inhomogeneous geomaterial, which is composed of soil and rock block. It controls the deformation and stability of the abutment and dam foundation, and threatens the long-term safety of high arch dams. To study the macroscopic and mesoscopic mechanical properties of SRM, the development of a viable mesoscopic numerical simulation method with a mesoscopic model generation technology, and a reasonable parametric model is crucially desired to overcome the limitations of experimental conditions, specimen dimensions, and experiment fund. To this end, this study presents a mesoscopic numerical method for simulating the mechanical behavior… More >

  • Open Access

    ARTICLE

    Distributed Timestamp Mechanism Based on Verifiable Delay Functions

    Qiang Wu1, Zhaoyang Han2, Ghulam Mohiuddin3, Yongjun Ren1,*

    Computer Systems Science and Engineering, Vol.44, No.2, pp. 1633-1646, 2023, DOI:10.32604/csse.2023.030646

    Abstract In the data communication system, the real-time information interaction of communication device increases the risk of privacy sensitive data being tampered with. Therefore, maintaining data security is one of the most important issues in network data communication. Because the timestamp is the most important way to authenticate data in information interaction, it is very necessary to provide timestamp service in the data communication system. However, the existing centralized timestamp mechanism is difficult to provide credible timestamp service, and users can conspire with timestamping servers to forge timestamps. Therefore, this paper designs a distributed timestamp mechanism based on continuous verifiable delay… More >

  • Open Access

    ARTICLE

    Intelligent Student Mental Health Assessment Model on Learning Management System

    Nasser Ali Aljarallah1,2, Ashit Kumar Dutta3,*, Majed Alsanea4, Abdul Rahaman Wahab Sait5

    Computer Systems Science and Engineering, Vol.44, No.2, pp. 1853-1868, 2023, DOI:10.32604/csse.2023.028755

    Abstract A learning management system (LMS) is a software or web based application, commonly utilized for planning, designing, and assessing a particular learning procedure. Generally, the LMS offers a method of creating and delivering content to the instructor, monitoring students’ involvement, and validating their outcomes. Since mental health issues become common among studies in higher education globally, it is needed to properly determine it to improve mental stability. This article develops a new seven spot lady bird feature selection with optimal sparse autoencoder (SSLBFS-OSAE) model to assess students’ mental health on LMS. The major aim of the SSLBFS-OSAE model is to… More >

  • Open Access

    ARTICLE

    An Ordinal Multi-Dimensional Classification (OMDC) for Predictive Maintenance

    Pelin Yildirim Taser*

    Computer Systems Science and Engineering, Vol.44, No.2, pp. 1499-1516, 2023, DOI:10.32604/csse.2023.028083

    Abstract Predictive Maintenance is a type of condition-based maintenance that assesses the equipment's states and estimates its failure probability and when maintenance should be performed. Although machine learning techniques have been frequently implemented in this area, the existing studies disregard to the natural order between the target attribute values of the historical sensor data. Thus, these methods cause losing the inherent order of the data that positively affects the prediction performances. To deal with this problem, a novel approach, named Ordinal Multi-dimensional Classification (OMDC), is proposed for estimating the conditions of a hydraulic system's four components by taking into the natural… More >

  • Open Access

    ARTICLE

    Rider Optimization Algorithm Based Optimal Cloud Server Selection in E-Learning

    R. Soundhara Raja Pandian*, C. Christopher Columbus

    Computer Systems Science and Engineering, Vol.44, No.2, pp. 1749-1762, 2023, DOI:10.32604/csse.2023.028014

    Abstract Currently, e-learning is one of the most prevalent educational methods because of its need in today’s world. Virtual classrooms and web-based learning are becoming the new method of teaching remotely. The students experience a lack of access to resources commonly the educational material. In remote locations, educational institutions face significant challenges in accessing various web-based materials due to bandwidth and network infrastructure limitations. The objective of this study is to demonstrate an optimization and queueing technique for allocating optimal servers and slots for users to access cloud-based e-learning applications. The proposed method provides the optimization and queueing algorithm for multi-server… More >

  • Open Access

    ARTICLE

    Optimal Deep Convolutional Neural Network with Pose Estimation for Human Activity Recognition

    S. Nandagopal1,*, G. Karthy2, A. Sheryl Oliver3, M. Subha4

    Computer Systems Science and Engineering, Vol.44, No.2, pp. 1719-1733, 2023, DOI:10.32604/csse.2023.028003

    Abstract Human Action Recognition (HAR) and pose estimation from videos have gained significant attention among research communities due to its application in several areas namely intelligent surveillance, human robot interaction, robot vision, etc. Though considerable improvements have been made in recent days, design of an effective and accurate action recognition model is yet a difficult process owing to the existence of different obstacles such as variations in camera angle, occlusion, background, movement speed, and so on. From the literature, it is observed that hard to deal with the temporal dimension in the action recognition process. Convolutional neural network (CNN) models could… More >

  • Open Access

    ARTICLE

    Deep Learning Enabled Social Media Recommendation Based on User Comments

    K. Saraswathi1,*, V. Mohanraj2, Y. Suresh2, J. Senthilkumar2

    Computer Systems Science and Engineering, Vol.44, No.2, pp. 1691-1702, 2023, DOI:10.32604/csse.2023.027987

    Abstract Nowadays, review systems have been developed with social media Recommendation systems (RS). Although research on RS social media is increasing year by year, the comprehensive literature review and classification of this RS research is limited and needs to be improved. The previous method did not find any user reviews within a time, so it gets poor accuracy and doesn’t filter the irrelevant comments efficiently. The Recursive Neural Network-based Trust Recommender System (RNN-TRS) is proposed to overcome this method’s problem. So it is efficient to analyse the trust comment and remove the irrelevant sentence appropriately. The first step is to collect… More >

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