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  • Open Access

    ARTICLE

    Perceived Social Support and Symptoms of Depression and Anxiety among Chinese Adolescents: A Moderated Chain Mediation Model

    Le-Qing Jin1, Chen-Wei Pan1, Chun-Hua Zhao2, Dan-Lin Li1, Yi-Bo Wu3,*, Tian-Yang Zhang1,4,*

    International Journal of Mental Health Promotion, Vol.27, No.1, pp. 29-40, 2025, DOI:10.32604/ijmhp.2025.057962 - 31 January 2025

    Abstract Background: Although previous studies indicate that perceived social support might be associated with adolescent psychological problems, the specific mechanism has not been thoroughly discussed. Based on theoretical and empirical research on problematic Internet use (PIU) and sleep quality, this study explored whether they play a mediating role between perceived social support and symptoms of depression and anxiety among adolescents. Furthermore, we investigated whether these relationships varied by place of residence. Methods: A sample of 2115 Chinese adolescents was included, and analyzed data related to perceived social support, PIU, sleep quality, symptoms of depression and anxiety,… More >

  • Open Access

    ARTICLE

    The Association between Problematic Internet Use, Resilience, and Fatigue in First-Year Medical College Students in China: A Moderated Mediation Model

    Xiumei Chen1,2, Xiaobing Lu3,*, Yufu Ning1, Lifeng Wang1, Jeffrey H. Gamble4, Xianhe Chen5, Xingyong Jiang6, I-Hua Chen7,*, Peijin Lin8

    International Journal of Mental Health Promotion, Vol.27, No.1, pp. 51-63, 2025, DOI:10.32604/ijmhp.2024.057750 - 31 January 2025

    Abstract Background: Resilience is crucial for medical college students to thrive in the highly stressful environment of medical education. However, the prevalence of problematic internet use (PIU) in this population may negatively impact their resilience. This study investigated the influence of problematic online gaming (PG) and problematic social media use (PSMU) on the resilience of medical college students in China. Methods: A sample of 5075 first-year medical college students from four Chinese universities was studied. PG served as the independent variable, resilience as the dependent variable, fatigue as the mediator, and PSMU as the moderator. Structural… More >

  • Open Access

    ARTICLE

    Internet of Things Software Engineering Model Validation Using Knowledge-Based Semantic Learning

    Mahmood Alsaadi, Mohammed E. Seno*, Mohammed I. Khalaf

    Intelligent Automation & Soft Computing, Vol.40, pp. 29-52, 2025, DOI:10.32604/iasc.2024.060390 - 10 January 2025

    Abstract The agility of Internet of Things (IoT) software engineering is benchmarked based on its systematic insights for wide application support infrastructure developments. Such developments are focused on reducing the interfacing complexity with heterogeneous devices through applications. To handle the interfacing complexity problem, this article introduces a Semantic Interfacing Obscuration Model (SIOM) for IoT software-engineered platforms. The interfacing obscuration between heterogeneous devices and application interfaces from the testing to real-time validations is accounted for in this model. Based on the level of obscuration between the infrastructure hardware to the end-user software, the modifications through device replacement, More >

  • Open Access

    ARTICLE

    Enhancing Vehicle Overtaking System via LoRa-Enabled Vehicular Communication Approach

    Kwang Chee Seng, Siti Fatimah Abdul Razak*, Sumendra Yogarayan

    Computer Systems Science and Engineering, Vol.49, pp. 239-258, 2025, DOI:10.32604/csse.2024.056582 - 10 January 2025

    Abstract Vehicle overtaking poses significant risks and leads to injuries and losses on Malaysia’s roads. In most scenarios, insufficient and untimely information available to drivers for accessing road conditions and their surrounding environment is the primary factor that causes these incidents. To address these issues, a comprehensive system is required to provide real-time assistance to drivers. Building upon our previous research on a LoRa-based lane change decision-aid system, this study proposes an enhanced Vehicle Overtaking System (VOS). This system utilizes long-range (LoRa) communication for reliable real-time data exchange between vehicles (V2V) and the cloud (V2C). By More >

  • Open Access

    ARTICLE

    Energy-Efficient Internet of Things-Based Wireless Sensor Network for Autonomous Data Validation for Environmental Monitoring

    Tabassum Kanwal1, Saif Ur Rehman1,*, Azhar Imran2, Haitham A. Mahmoud3

    Computer Systems Science and Engineering, Vol.49, pp. 185-212, 2025, DOI:10.32604/csse.2024.056535 - 10 January 2025

    Abstract This study presents an energy-efficient Internet of Things (IoT)-based wireless sensor network (WSN) framework for autonomous data validation in remote environmental monitoring. We address two critical challenges in WSNs: ensuring data reliability and optimizing energy consumption. Our novel approach integrates an artificial neural network (ANN)-based multi-fault detection algorithm with an energy-efficient IoT-WSN architecture. The proposed ANN model is designed to simultaneously detect multiple fault types, including spike faults, stuck-at faults, outliers, and out-of-range faults. We collected sensor data at 5-minute intervals over three months, using temperature and humidity sensors. The ANN was trained on 70%… More >

  • Open Access

    ARTICLE

    5DGWO-GAN: A Novel Five-Dimensional Gray Wolf Optimizer for Generative Adversarial Network-Enabled Intrusion Detection in IoT Systems

    Sarvenaz Sadat Khatami1, Mehrdad Shoeibi2, Anita Ershadi Oskouei3, Diego Martín4,*, Maral Keramat Dashliboroun5

    CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 881-911, 2025, DOI:10.32604/cmc.2024.059999 - 03 January 2025

    Abstract The Internet of Things (IoT) is integral to modern infrastructure, enabling connectivity among a wide range of devices from home automation to industrial control systems. With the exponential increase in data generated by these interconnected devices, robust anomaly detection mechanisms are essential. Anomaly detection in this dynamic environment necessitates methods that can accurately distinguish between normal and anomalous behavior by learning intricate patterns. This paper presents a novel approach utilizing generative adversarial networks (GANs) for anomaly detection in IoT systems. However, optimizing GANs involves tuning hyper-parameters such as learning rate, batch size, and optimization algorithms,… More >

  • Open Access

    ARTICLE

    A Support Vector Machine (SVM) Model for Privacy Recommending Data Processing Model (PRDPM) in Internet of Vehicles

    Ali Alqarni*

    CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 389-406, 2025, DOI:10.32604/cmc.2024.059238 - 03 January 2025

    Abstract Open networks and heterogeneous services in the Internet of Vehicles (IoV) can lead to security and privacy challenges. One key requirement for such systems is the preservation of user privacy, ensuring a seamless experience in driving, navigation, and communication. These privacy needs are influenced by various factors, such as data collected at different intervals, trip durations, and user interactions. To address this, the paper proposes a Support Vector Machine (SVM) model designed to process large amounts of aggregated data and recommend privacy-preserving measures. The model analyzes data based on user demands and interactions with service More >

  • Open Access

    REVIEW

    The Internet of Things under Federated Learning: A Review of the Latest Advances and Applications

    Jinlong Wang1,2,*, Zhenyu Liu1, Xingtao Yang1, Min Li1, Zhihan Lyu3

    CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 1-39, 2025, DOI:10.32604/cmc.2024.058926 - 03 January 2025

    Abstract With the rapid development of artificial intelligence, the Internet of Things (IoT) can deploy various machine learning algorithms for network and application management. In the IoT environment, many sensors and devices generate massive data, but data security and privacy protection have become a serious challenge. Federated learning (FL) can achieve many intelligent IoT applications by training models on local devices and allowing AI training on distributed IoT devices without data sharing. This review aims to deeply explore the combination of FL and the IoT, and analyze the application of federated learning in the IoT from More >

  • Open Access

    ARTICLE

    LoRa Sense: Sensing and Optimization of LoRa Link Behavior Using Path-Loss Models in Open-Cast Mines

    Bhanu Pratap Reddy Bhavanam, Prashanth Ragam*

    CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.1, pp. 425-466, 2025, DOI:10.32604/cmes.2024.052355 - 17 December 2024

    Abstract The Internet of Things (IoT) has orchestrated various domains in numerous applications, contributing significantly to the growth of the smart world, even in regions with low literacy rates, boosting socio-economic development. This study provides valuable insights into optimizing wireless communication, paving the way for a more connected and productive future in the mining industry. The IoT revolution is advancing across industries, but harsh geometric environments, including open-pit mines, pose unique challenges for reliable communication. The advent of IoT in the mining industry has significantly improved communication for critical operations through the use of Radio Frequency… More >

  • Open Access

    ARTICLE

    An Asynchronous Data Transmission Policy for Task Offloading in Edge-Computing Enabled Ultra-Dense IoT

    Dayong Wang1,*, Kamalrulnizam Bin Abu Bakar1, Babangida Isyaku2, Liping Lei3

    CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 4465-4483, 2024, DOI:10.32604/cmc.2024.059616 - 19 December 2024

    Abstract In recent years, task offloading and its scheduling optimization have emerged as widely discussed and significant topics. The multi-objective optimization problems inherent in this domain, particularly those related to resource allocation, have been extensively investigated. However, existing studies predominantly focus on matching suitable computational resources for task offloading requests, often overlooking the optimization of the task data transmission process. This inefficiency in data transmission leads to delays in the arrival of task data at computational nodes within the edge network, resulting in increased service times due to elevated network transmission latencies and idle computational resources.… More >

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