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  • Open Access


    Fault Diagnosis Method of Energy Storage Unit of Circuit Breakers Based on EWT-ISSA-BP

    Tengfei Li1, Wenhui Zhang1, Ke Mi1, Qingming Lin1, Shuangwei Zhao2,*, Jiayi Song2

    Energy Engineering, Vol.121, No.7, pp. 1991-2007, 2024, DOI:10.32604/ee.2024.049460

    Abstract Aiming at the problem of energy storage unit failure in the spring operating mechanism of low voltage circuit breakers (LVCBs). A fault diagnosis algorithm based on an improved Sparrow Search Algorithm (ISSA) optimized Backpropagation Neural Network (BPNN) is proposed to improve the operational safety of LVCB. Taking the 1.5kV/4000A/75kA LVCB as an example. According to the current operating characteristics of the energy storage motor, fault characteristics are extracted based on Empirical Wavelet Transform (EWT). Traditional BPNN has problems such as difficulty adjusting network weights and thresholds, being sensitive to initial weights, and quickly falling into More >

  • Open Access


    An Experimental and Numerical Thermal Flow Analysis in a Solar Air Collector with Different Delta Wing Height Ratios

    Ghobad Shafiei Sabet1,*, Ali Sari1, Ahmad Fakhari2,*, Nasrin Afsarimanesh3, Dominic Organ4, Seyed Mehran Hoseini1

    Frontiers in Heat and Mass Transfer, Vol.22, No.2, pp. 491-509, 2024, DOI:10.32604/fhmt.2024.048290

    Abstract This study conducts both numerical and empirical assessments of thermal transfer and fluid flow characteristics in a Solar Air Collector (SAC) using a Delta Wing Vortex Generator (DWVG), and the effects of different height ratios (R = 0.6, 0.8, 1, 1.2 and 1.4) in delta wing vortex generators, which were not considered in the earlier studies, are investigated. Energy and exergy analyses are performed to gain maximum efficiency. The Reynolds number based on the outlet velocity and hydraulic diameter falls between 4400 and 22000, corresponding to the volume flow rate of 5.21–26.07 m/h. It is More >

  • Open Access


    The Influence of Internet Use on Women’s Depression and Its Countermeasures—Empirical Analysis Based on Data from CFPS

    Dengke Xu1, Linlin Shen1, Fangzhong Xu2,*

    International Journal of Mental Health Promotion, Vol.26, No.3, pp. 229-238, 2024, DOI:10.32604/ijmhp.2024.046023

    Abstract Based on China Family Panel Studies (CFPS) 2018 data, the multiple linear regression model is used to analyze the effects of Internet use on women’s depression, and to test the robustness of the regression results. At the same time, the effects of Internet use on mental health of women with different residence, age, marital status and physical health status are analyzed. Then, we can obtain that Internet use has a significant promoting effect on women’s mental health, while the degree of Internet use has a significant inhibitory effect on women’s mental health. In addition, the… More >

  • Open Access


    An Enhanced Ensemble-Based Long Short-Term Memory Approach for Traffic Volume Prediction

    Duy Quang Tran1, Huy Q. Tran2,*, Minh Van Nguyen3

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3585-3602, 2024, DOI:10.32604/cmc.2024.047760

    Abstract With the advancement of artificial intelligence, traffic forecasting is gaining more and more interest in optimizing route planning and enhancing service quality. Traffic volume is an influential parameter for planning and operating traffic structures. This study proposed an improved ensemble-based deep learning method to solve traffic volume prediction problems. A set of optimal hyperparameters is also applied for the suggested approach to improve the performance of the learning process. The fusion of these methodologies aims to harness ensemble empirical mode decomposition’s capacity to discern complex traffic patterns and long short-term memory’s proficiency in learning temporal… More >

  • Open Access


    Computational Verification of Low-Frequency Broadband Noise from Wind Turbine Blades Using Semi-Empirical Methods

    Vasishta Bhargava Nukala*, Chinmaya Prasad Padhy

    Sound & Vibration, Vol.58, pp. 133-150, 2024, DOI:10.32604/sv.2024.047762

    Abstract A significant aerodynamic noise from wind turbines arises when the rotating blades interact with turbulent flows. Though the trailing edge of the blade is an important source of noise at high frequencies, the present work deals with the influence of turbulence distortion on leading edge noise from wind turbine blades which becomes significant in low-frequency regions. Four quasi-empirical methods are studied to verify the accuracy of turbulent inflow noise predicted at low frequencies for a 2 MW horizontal axis wind turbine. Results have shown that all methods exhibited a downward linear trend in noise spectra More >

  • Open Access


    An Empirical Study on the Effectiveness of Adversarial Examples in Malware Detection

    Younghoon Ban, Myeonghyun Kim, Haehyun Cho*

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3535-3563, 2024, DOI:10.32604/cmes.2023.046658

    Abstract Antivirus vendors and the research community employ Machine Learning (ML) or Deep Learning (DL)-based static analysis techniques for efficient identification of new threats, given the continual emergence of novel malware variants. On the other hand, numerous researchers have reported that Adversarial Examples (AEs), generated by manipulating previously detected malware, can successfully evade ML/DL-based classifiers. Commercial antivirus systems, in particular, have been identified as vulnerable to such AEs. This paper firstly focuses on conducting black-box attacks to circumvent ML/DL-based malware classifiers. Our attack method utilizes seven different perturbations, including Overlay Append, Section Append, and Break Checksum,… More >

  • Open Access


    Parental Educational Expectations, Academic Pressure, and Adolescent Mental Health: An Empirical Study Based on CEPS Survey Data

    Tao Xu1,*, Fangqiang Zuo1, Kai Zheng2,*

    International Journal of Mental Health Promotion, Vol.26, No.2, pp. 93-103, 2024, DOI:10.32604/ijmhp.2023.043226

    Abstract Background: This study aimed to investigate the relationship between parental educational expectations and adolescent mental health problems, with academic pressure as a moderating variable. Methods: This study was based on the baseline data of the China Education Panel Survey, which was collected within one school year during 2013–2014. It included 19,958 samples from seventh and ninth graders, who ranged from 11 to 18 years old. After removing missing values and conducting relevant data processing, the effective sample size for analysis was 16344. The OLS (Ordinary Least Squares) multiple linear regression analysis was used to examine… More >

  • Open Access


    Evaluating the Efficacy of Latent Variables in Mitigating Data Poisoning Attacks in the Context of Bayesian Networks: An Empirical Study

    Shahad Alzahrani1, Hatim Alsuwat2, Emad Alsuwat3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1635-1654, 2024, DOI:10.32604/cmes.2023.044718

    Abstract Bayesian networks are a powerful class of graphical decision models used to represent causal relationships among variables. However, the reliability and integrity of learned Bayesian network models are highly dependent on the quality of incoming data streams. One of the primary challenges with Bayesian networks is their vulnerability to adversarial data poisoning attacks, wherein malicious data is injected into the training dataset to negatively influence the Bayesian network models and impair their performance. In this research paper, we propose an efficient framework for detecting data poisoning attacks against Bayesian network structure learning algorithms. Our framework… More >

  • Open Access


    Developing Transparent IDS for VANETs Using LIME and SHAP: An Empirical Study

    Fayaz Hassan1,*, Jianguo Yu1, Zafi Sherhan Syed2, Arif Hussain Magsi3, Nadeem Ahmed4

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3185-3208, 2023, DOI:10.32604/cmc.2023.044650

    Abstract Vehicular Ad-hoc Networks (VANETs) are mobile ad-hoc networks that use vehicles as nodes to create a wireless network. Whereas VANETs offer many advantages over traditional transportation networks, ensuring security in VANETs remains a significant challenge due to the potential for malicious attacks. This study addresses the critical issue of security in VANETs by introducing an intelligent Intrusion Detection System (IDS) that merges Machine Learning (ML)–based attack detection with Explainable AI (XAI) explanations. This study ML pipeline involves utilizing correlation-based feature selection followed by a Random Forest (RF) classifier that achieves a classification accuracy of 100%… More >

  • Open Access


    Empirical Analysis of Neural Networks-Based Models for Phishing Website Classification Using Diverse Datasets

    Shoaib Khan, Bilal Khan, Saifullah Jan*, Subhan Ullah, Aiman

    Journal of Cyber Security, Vol.5, pp. 47-66, 2023, DOI:10.32604/jcs.2023.045579

    Abstract Phishing attacks pose a significant security threat by masquerading as trustworthy entities to steal sensitive information, a problem that persists despite user awareness. This study addresses the pressing issue of phishing attacks on websites and assesses the performance of three prominent Machine Learning (ML) models—Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Long Short-Term Memory (LSTM)—utilizing authentic datasets sourced from Kaggle and Mendeley repositories. Extensive experimentation and analysis reveal that the CNN model achieves a better accuracy of 98%. On the other hand, LSTM shows the lowest accuracy of 96%. These findings underscore the More >

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