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  • 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 >

  • Open Access

    ARTICLE

    Study on Real-Time Heart Rate Detection Based on Multi-People

    Qiuyu Hu1, Wu Zeng1,*, Yi Sheng1, Jian Xu1, Weihua Ou2, Ruochen Tan3

    Computer Systems Science and Engineering, Vol.44, No.2, pp. 1397-1408, 2023, DOI:10.32604/csse.2023.027980

    Abstract Heart rate is an important vital characteristic which indicates physical and mental health status. Typically heart rate measurement instruments require direct contact with the skin which is time-consuming and costly. Therefore, the study of non-contact heart rate measurement methods is of great importance. Based on the principles of photoelectric volumetric tracing, we use a computer device and camera to capture facial images, accurately detect face regions, and to detect multiple facial images using a multi-target tracking algorithm. Then after the regional segmentation of the facial image, the signal acquisition of the region of interest is further resolved. Finally, frequency detection… More >

  • Open Access

    ARTICLE

    Deep-BERT: Transfer Learning for Classifying Multilingual Offensive Texts on Social Media

    Md. Anwar Hussen Wadud1, M. F. Mridha1, Jungpil Shin2,*, Kamruddin Nur3, Aloke Kumar Saha4

    Computer Systems Science and Engineering, Vol.44, No.2, pp. 1775-1791, 2023, DOI:10.32604/csse.2023.027841

    Abstract Offensive messages on social media, have recently been frequently used to harass and criticize people. In recent studies, many promising algorithms have been developed to identify offensive texts. Most algorithms analyze text in a unidirectional manner, where a bidirectional method can maximize performance results and capture semantic and contextual information in sentences. In addition, there are many separate models for identifying offensive texts based on monolingual and multilingual, but there are a few models that can detect both monolingual and multilingual-based offensive texts. In this study, a detection system has been developed for both monolingual and multilingual offensive texts by… More >

  • Open Access

    ARTICLE

    An Optimized Deep-Learning-Based Low Power Approximate Multiplier Design

    M. Usharani1,*, B. Sakthivel2, S. Gayathri Priya3, T. Nagalakshmi4, J. Shirisha5

    Computer Systems Science and Engineering, Vol.44, No.2, pp. 1647-1657, 2023, DOI:10.32604/csse.2023.027744

    Abstract Approximate computing is a popular field for low power consumption that is used in several applications like image processing, video processing, multimedia and data mining. This Approximate computing is majorly performed with an arithmetic circuit particular with a multiplier. The multiplier is the most essential element used for approximate computing where the power consumption is majorly based on its performance. There are several researchers are worked on the approximate multiplier for power reduction for a few decades, but the design of low power approximate multiplier is not so easy. This seems a bigger challenge for digital industries to design an… More >

  • Open Access

    ARTICLE

    An Optimized Transfer Learning Model Based Kidney Stone Classification

    S. Devi Mahalakshmi*

    Computer Systems Science and Engineering, Vol.44, No.2, pp. 1387-1395, 2023, DOI:10.32604/csse.2023.027610

    Abstract The kidney is an important organ of humans to purify the blood. The healthy function of the kidney is always essential to balance the salt, potassium and pH levels in the blood. Recently, the failure of kidneys happens easily to human beings due to their lifestyle, eating habits and diabetes diseases. Early prediction of kidney stones is compulsory for timely treatment. Image processing-based diagnosis approaches provide a greater success rate than other detection approaches. In this work, proposed a kidney stone classification method based on optimized Transfer Learning(TL). The Deep Convolutional Neural Network (DCNN) models of DenseNet169, MobileNetv2 and GoogleNet… More >

  • Open Access

    ARTICLE

    Fuzzy Fruit Fly Optimized Node Quality-Based Clustering Algorithm for Network Load Balancing

    P. Rahul1,*, N. Kanthimathi1, B. Kaarthick2, M. Leeban Moses1

    Computer Systems Science and Engineering, Vol.44, No.2, pp. 1583-1600, 2023, DOI:10.32604/csse.2023.027424

    Abstract Recently, the fundamental problem with Hybrid Mobile Ad-hoc Networks (H-MANETs) is to find a suitable and secure way of balancing the load through Internet gateways. Moreover, the selection of the gateway and overload of the network results in packet loss and Delay (DL). For optimal performance, it is important to load balance between different gateways. As a result, a stable load balancing procedure is implemented, which selects gateways based on Fuzzy Logic (FL) and increases the efficiency of the network. In this case, since gateways are selected based on the number of nodes, the Energy Consumption (EC) was high. This… More >

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