Yang Li¹, Jiangping Xu^1,*, Yun Liu¹, Wen Zhong^2,*, Fei Wang³

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 461-483, 2024, DOI:10.32604/cmes.2024.046467

Abstract In this research, we present the pure open multi-processing (OpenMP), pure message passing interface (MPI), and hybrid MPI/OpenMP parallel solvers within the dynamic explicit central difference algorithm for the coining process to address the challenge of capturing fine relief features of approximately 50 microns. Achieving such precision demands the utilization of at least 7 million tetrahedron elements, surpassing the capabilities of traditional serial programs previously developed. To mitigate data races when calculating internal forces, intermediate arrays are introduced within the OpenMP directive. This helps ensure proper synchronization and avoid conflicts during parallel execution. Additionally, in the MPI implementation, the coins… More > Graphic Abstract

Dengke Xu¹, Linlin Shen¹, Fangzhong Xu^2,*

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 study found that women’s age,… More >

GAURAV AGARWAL

Journal of Polymer Materials, Vol.39, No.3-4, pp. 255-267, 2022, DOI:10.32381/JPM.2022.39.3-4.6

Abstract Studies were conducted to observe the effect of fracture toughness and damping response on fabric reinforced epoxy polymer composites. The samples of glass fabric, kevlar fabric and carbon fabric having 15wt%, 25wt%, 35wt%, 45wt% and 55wt % fabric content were prepared and tested following ASTM standards. Fracture toughness, peak load and increase in energy absorption are determined for the fabric-epoxy composites. Effect of temperature on storage modulus, loss modulus and tan delta values for various percentages of fabric epoxy composites are noticed and corresponding damping response behaviour is determined. The results revealed that reduction in strength at higher percentage of… More >

Duy Quang Tran¹, Huy Q. Tran^2,*, 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 relationships. Firstly, a dataset for… More >

Rajesh Kumar Panda, B.V.S.S.S. Prasad^*

Frontiers in Heat and Mass Transfer, Vol.2, No.1, pp. 1-10, 2011, DOI:10.5098/hmt.v2.1.3008

Abstract Conjugate heat transfer from a flat circular disk is investigated both computationally and experimentally with a constant heat flux imposed on its bottom surface and a shower head of air jets impinging on the top surface. The shower head consists of a central jet surrounded by four neighboring perimeter jets. Measured temperature data at twelve locations within the plate are compared with the conjugate heat transfer result obtained at the same locations computationally by Shear Stress Transport (SST) κ-ω turbulence model. The spacing to orifice diameter ratio (H/d = 1 to 4), the jet Reynolds number (7115 to 10674) and… More >

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 for a given mean wind… More >

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, capitalizing on the ambiguities present… More >

Tao Xu^1,*, Fangqiang Zuo¹, Kai Zheng^2,*

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 the relationship between parental educational… More >

Shahad Alzahrani¹, Hatim Alsuwat², Emad Alsuwat^3,*

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 utilizes latent variables to quantify… More >

Wei Zhou¹, Xincong Jiang^2,*, Chuan Qin²

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 2069-2093, 2024, DOI:10.32604/cmes.2023.043248

Abstract Edge devices, due to their limited computational and storage resources, often require the use of compilers for program optimization. Therefore, ensuring the security and reliability of these compilers is of paramount importance in the emerging field of edge AI. One widely used testing method for this purpose is fuzz testing, which detects bugs by inputting random test cases into the target program. However, this process consumes significant time and resources. To improve the efficiency of compiler fuzz testing, it is common practice to utilize test case prioritization techniques. Some researchers use machine learning to predict the code coverage of test… More >