Xunguang Yan^1,2, Wenrui Wang¹, Fanglin Lu¹, Hongyong Fan³, Bo Wu¹, Jianfeng Yu^1,*

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 1439-1458, 2025, DOI:10.32604/cmc.2024.057797 - 03 January 2025

Abstract To maintain the reliability of power systems, routine inspections using drones equipped with advanced object detection algorithms are essential for preempting power-related issues. The increasing resolution of drone-captured images has posed a challenge for traditional target detection methods, especially in identifying small objects in high-resolution images. This study presents an enhanced object detection algorithm based on the Faster Region-based Convolutional Neural Network (Faster R-CNN) framework, specifically tailored for detecting small-scale electrical components like insulators, shock hammers, and screws in transmission line. The algorithm features an improved backbone network for Faster R-CNN, which significantly boosts the More >

Jing Li¹, Minghui Li^2,*, Guanghuan Xie³

Psycho-Oncologie, Vol.18, No.4, pp. 249-255, 2024, DOI:10.32604/po.2024.056994 - 04 December 2024

Abstract This study reviews the historical development, current applications, and multifaceted impacts of religious psychological coping on the physical and mental health of cancer patients. As a method for coping with life’s pressures through religious beliefs or activities, religious psychological coping has been proven to alleviate the negative emotions of cancer patients and enhance their spiritual well-being and quality of life (QOL). Research indicates that religious faith can alleviate the physical symptoms of cancer patients, extend survival time, reduce the fear of death, assist in coping with treatment side effects, and improve self-efficacy and overall quality More >

Xiao Luo^1,3, Hao Zhu^1,2,*, Zhenli Zhang^1,2

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2667-2687, 2024, DOI:10.32604/cmc.2024.047988 - 27 February 2024

Abstract Road traffic safety can decrease when drivers drive in a low-visibility environment. The application of visual perception technology to detect vehicles and pedestrians in infrared images proves to be an effective means of reducing the risk of accidents. To tackle the challenges posed by the low recognition accuracy and the substantial computational burden associated with current infrared pedestrian-vehicle detection methods, an infrared pedestrian-vehicle detection method A proposal is presented, based on an enhanced version of You Only Look Once version 5 (YOLOv5). First, A head specifically designed for detecting small targets has been integrated into… More >

Van-Son Huynh¹, Thanh-Thao Ly¹, My-Tien Nguyen-Thi^1,*, Xuan Thanh Kieu Nguyen², Gallayaporn Nantachai^3,4, Vinh-Long Tran-Chi¹

International Journal of Mental Health Promotion, Vol.25, No.9, pp. 1019-1031, 2023, DOI:10.32604/ijmhp.2023.029235 - 10 August 2023

Abstract Religion is one of the social entities that has had a significant impact on the pandemic. The study’s goals are to investigate the relationship between well-being and fear of COVID-19, as well as to test whether religious beliefs mediate the effect of wellbeing on fear of COVID-19. The sample comprised of 433 participants in Vietnam. Independent Sample t-Test, One-way ANOVA, mediation analysis were used to analyze the data. In the levels of well-being, individuals who engage in religious services daily have higher levels than those hardly and never attend, and people from the age of 18 More >

Abdullah S. AL-Malaise AL-Ghamdi^1,2,3, Sultanah M. Alshammari^3,4, Mahmoud Ragab^3,5,6,*

Computer Systems Science and Engineering, Vol.46, No.2, pp. 1863-1877, 2023, DOI:10.32604/csse.2023.035869 - 09 February 2023

Abstract Notwithstanding the religious intention of billions of devotees, the religious mass gathering increased major public health concerns since it likely became a huge super spreading event for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Most attendees ignored preventive measures, namely maintaining physical distance, practising hand hygiene, and wearing facemasks. Wearing a face mask in public areas protects people from spreading COVID-19. Artificial intelligence (AI) based on deep learning (DL) and machine learning (ML) could assist in fighting covid-19 in several ways. This study introduces a new deep learning-based Face Mask Detection in Religious Mass… More >

Shynar Mussiraliyeva¹, Batyrkhan Omarov^1,*, Paul Yoo^1,2, Milana Bolatbek¹

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 915-934, 2022, DOI:10.32604/cmc.2022.019189 - 07 September 2021

Abstract In this research paper, we propose a corpus for the task of detecting religious extremism in social networks and open sources and compare various machine learning algorithms for the binary classification problem using a previously created corpus, thereby checking whether it is possible to detect extremist messages in the Kazakh language. To do this, the authors trained models using six classic machine-learning algorithms such as Support Vector Machine, Decision Tree, Random Forest, K Nearest Neighbors, Naive Bayes, and Logistic Regression. To increase the accuracy of detecting extremist texts, we used various characteristics such as Statistical More >