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  • Open Access

    ARTICLE

    How Emotion Nurtures Mentality: The Influencing Mechanism of Social-Emotional Competency on the Mental Health of University Students

    Yulei Chen1, Zhaojun Chen1,2, Shichao Wang1, Yang Hang1, Jianpeng Guo1,*

    International Journal of Mental Health Promotion, Vol.26, No.4, pp. 303-315, 2024, DOI:10.32604/ijmhp.2024.046863

    Abstract Social-Emotional Competency (SEC), regarded as a critical psychological resource for individuals to adapt to social environments, is an effective protective factor for students’ mental health, impacting their future success and well-being. Analyzing the impact of SEC on university students’ mental health can offer valuable insights for nurturing talents with healthy psychological and physical development. Based on data from two large-scale surveys of Chinese university students, this study designed two comprehensive Multiple Mediation Models involving SEC, stress, coping strategies, and stress reaction to explore the pathway of emotion nurturing mentality. Study 1 utilized a parallel mediation model to examine the relationships… More >

  • Open Access

    ARTICLE

    Provoking Buying Behaviors Amid Crises: Unfolding the Underlying Mechanisms of Psychological Impairments

    Muhammad Waleed Ayub Ghouri1, Guofeng Wang2, Muhammad Ali Hussain3, Zhisheng Li1,*, Tachia Chin1

    International Journal of Mental Health Promotion, Vol.26, No.4, pp. 279-292, 2024, DOI:10.32604/ijmhp.2024.044759

    Abstract Crises in the past have caused devastating, long-lasting impacts on the global economy. The after-effects always bring some dynamic and rigorous challenges for businesses and governments. Such challenges have always been a point of discussion for scholars. The recent COVID-19 pandemic emaciated the global economy, leaving everyone mired in uncertainty, fear, and psychological impairments. One of the headwind features utilized by consumers during pandemic was panic buying (PB), which must be explored in various contexts for policymakers and practitioners. To address this gap, this study deployed a moderated mediation mechanism, integrating the health belief model (HBM) and competitive arousal theory… More >

  • Open Access

    ARTICLE

    Research on Operation Optimization of Energy Storage Power Station and Integrated Energy Microgrid Alliance Based on Stackelberg Game

    Yu Zhang*, Lianmin Li, Zhongxiang Liu, Yuhu Wu

    Energy Engineering, Vol.121, No.5, pp. 1209-1221, 2024, DOI:10.32604/ee.2024.046141

    Abstract With the development of renewable energy technologies such as photovoltaics and wind power, it has become a research hotspot to improve the consumption rate of new energy and reduce energy costs through the deployment of energy storage. To solve the problem of the interests of different subjects in the operation of the energy storage power stations (ESS) and the integrated energy multi-microgrid alliance (IEMA), this paper proposes the optimization operation method of the energy storage power station and the IEMA based on the Stackelberg game. In the upper layer, ESS optimizes charging and discharging decisions through a dynamic pricing mechanism.… More > Graphic Abstract

    Research on Operation Optimization of Energy Storage Power Station and Integrated Energy Microgrid Alliance Based on Stackelberg Game

  • Open Access

    ARTICLE

    Combo Packet: An Encryption Traffic Classification Method Based on Contextual Information

    Yuancong Chai, Yuefei Zhu*, Wei Lin, Ding Li

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1223-1243, 2024, DOI:10.32604/cmc.2024.049904

    Abstract With the increasing proportion of encrypted traffic in cyberspace, the classification of encrypted traffic has become a core key technology in network supervision. In recent years, many different solutions have emerged in this field. Most methods identify and classify traffic by extracting spatiotemporal characteristics of data flows or byte-level features of packets. However, due to changes in data transmission mediums, such as fiber optics and satellites, temporal features can exhibit significant variations due to changes in communication links and transmission quality. Additionally, partial spatial features can change due to reasons like data reordering and retransmission. Faced with these challenges, identifying… More >

  • Open Access

    ARTICLE

    Big Data Access Control Mechanism Based on Two-Layer Permission Decision Structure

    Aodi Liu, Na Wang*, Xuehui Du, Dibin Shan, Xiangyu Wu, Wenjuan Wang

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1705-1726, 2024, DOI:10.32604/cmc.2024.049011

    Abstract Big data resources are characterized by large scale, wide sources, and strong dynamics. Existing access control mechanisms based on manual policy formulation by security experts suffer from drawbacks such as low policy management efficiency and difficulty in accurately describing the access control policy. To overcome these problems, this paper proposes a big data access control mechanism based on a two-layer permission decision structure. This mechanism extends the attribute-based access control (ABAC) model. Business attributes are introduced in the ABAC model as business constraints between entities. The proposed mechanism implements a two-layer permission decision structure composed of the inherent attributes of… More >

  • Open Access

    ARTICLE

    A Novel Foreign Object Detection Method in Transmission Lines Based on Improved YOLOv8n

    Yakui Liu1,2,3,*, Xing Jiang1, Ruikang Xu1, Yihao Cui1, Chenhui Yu1, Jingqi Yang1, Jishuai Zhou1

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1263-1279, 2024, DOI:10.32604/cmc.2024.048864

    Abstract The rapid pace of urban development has resulted in the widespread presence of construction equipment and increasingly complex conditions in transmission corridors. These conditions pose a serious threat to the safe operation of the power grid. Machine vision technology, particularly object recognition technology, has been widely employed to identify foreign objects in transmission line images. Despite its wide application, the technique faces limitations due to the complex environmental background and other auxiliary factors. To address these challenges, this study introduces an improved YOLOv8n. The traditional stepwise convolution and pooling layers are replaced with a spatial-depth convolution (SPD-Conv) module, aiming to… More >

  • Open Access

    ARTICLE

    Efficient Unsupervised Image Stitching Using Attention Mechanism with Deep Homography Estimation

    Chunbin Qin*, Xiaotian Ran

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1319-1334, 2024, DOI:10.32604/cmc.2024.048850

    Abstract Traditional feature-based image stitching techniques often encounter obstacles when dealing with images lacking unique attributes or suffering from quality degradation. The scarcity of annotated datasets in real-life scenes severely undermines the reliability of supervised learning methods in image stitching. Furthermore, existing deep learning architectures designed for image stitching are often too bulky to be deployed on mobile and peripheral computing devices. To address these challenges, this study proposes a novel unsupervised image stitching method based on the YOLOv8 (You Only Look Once version 8) framework that introduces deep homography networks and attention mechanisms. The methodology is partitioned into three distinct… More >

  • Open Access

    ARTICLE

    A Study on Enhancing Chip Detection Efficiency Using the Lightweight Van-YOLOv8 Network

    Meng Huang, Honglei Wei*, Xianyi Zhai

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 531-547, 2024, DOI:10.32604/cmc.2024.048510

    Abstract In pursuit of cost-effective manufacturing, enterprises are increasingly adopting the practice of utilizing recycled semiconductor chips. To ensure consistent chip orientation during packaging, a circular marker on the front side is employed for pin alignment following successful functional testing. However, recycled chips often exhibit substantial surface wear, and the identification of the relatively small marker proves challenging. Moreover, the complexity of generic target detection algorithms hampers seamless deployment. Addressing these issues, this paper introduces a lightweight YOLOv8s-based network tailored for detecting markings on recycled chips, termed Van-YOLOv8. Initially, to alleviate the influence of diminutive, low-resolution markings on the precision of… More >

  • Open Access

    ARTICLE

    Mobile Crowdsourcing Task Allocation Based on Dynamic Self-Attention GANs

    Kai Wei1, Song Yu2, Qingxian Pan1,*

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 607-622, 2024, DOI:10.32604/cmc.2024.048240

    Abstract Crowdsourcing technology is widely recognized for its effectiveness in task scheduling and resource allocation. While traditional methods for task allocation can help reduce costs and improve efficiency, they may encounter challenges when dealing with abnormal data flow nodes, leading to decreased allocation accuracy and efficiency. To address these issues, this study proposes a novel two-part invalid detection task allocation framework. In the first step, an anomaly detection model is developed using a dynamic self-attentive GAN to identify anomalous data. Compared to the baseline method, the model achieves an approximately 4% increase in the F1 value on the public dataset. In… More >

  • Open Access

    ARTICLE

    A Layered Energy-Efficient Multi-Node Scheduling Mechanism for Large-Scale WSN

    Xue Zhao, Shaojun Tao, Hongying Tang, Jiang Wang*, Baoqing Li*

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1335-1351, 2024, DOI:10.32604/cmc.2024.047996

    Abstract In recent years, target tracking has been considered one of the most important applications of wireless sensor network (WSN). Optimizing target tracking performance and prolonging network lifetime are two equally critical objectives in this scenario. The existing mechanisms still have weaknesses in balancing the two demands. The proposed heuristic multi-node collaborative scheduling mechanism (HMNCS) comprises cluster head (CH) election, pre-selection, and task set selection mechanisms, where the latter two kinds of selections form a two-layer selection mechanism. The CH election innovatively introduces the movement trend of the target and establishes a scoring mechanism to determine the optimal CH, which can… More >

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