Qiang Xiong^*, Jianlong Zhang, Qianwen Song

Journal of Cyber Security, Vol.7, pp. 255-277, 2025, DOI:10.32604/jcs.2025.065625 - 14 July 2025

Abstract In the domain of information security outsourcing, the multi-stage game-theoretic decision-making process, intertwined with moral hazard and dynamic strategy adjustments, significantly impacts the long-term collaboration between the principal (outsourcing enterprise) and the contractor (Managed Security Service Provider—MSSP). This paper conducts a comprehensive analysis of these aspects within information security outsourcing partnerships. A multi-stage game model incorporating moral hazard is constructed to meticulously examine the strategic behaviors and expected revenue fluctuations of both parties across different cooperation stages. Through in-depth model derivation, the impacts of service fees, cooperation-stage progression, and long-term cooperation on expected revenues are… More >

Jingdong Qi^1,#, Fei Zhang^1,#, Xia Zhang^2,*

Congenital Heart Disease, Vol.20, No.3, pp. 383-400, 2025, DOI:10.32604/chd.2025.064790 - 11 July 2025

Abstract Background: Congenital heart disease (CHD) remains a significant global health concern, with considerable heterogeneity across age groups, genders, and regions. Objective: This study aimed to investigate the global epidemiological patterns, inequalities, and socio-demographic determinants of CHD burden from 1990 to 2021 to inform targeted interventions. Methods: This study aimed to investigate the global epidemiological patterns, inequalities, and socio-demographic determinants of CHD burden from 1990 to 2021 to inform targeted interventions. Results: CHD burden increased with age, peaking among individuals aged 70 years and older. This does not reflect new-onset disease, but rather the accumulation of late diagnoses,… More >

Akhila Reddy Yadulla, Mounica Yenugula, Vinay Kumar Kasula^*, Bhargavi Konda, Bala Yashwanth Reddy Thumma

Journal on Internet of Things, Vol.7, pp. 19-48, 2025, DOI:10.32604/jiot.2025.062733 - 11 July 2025

Abstract This study systematically reviews the Internet of Things (IoT) security research based on literature from prominent international cybersecurity conferences over the past five years, including ACM Conference on Computer and Communications Security (ACM CCS), USENIX Security, Network and Distributed System Security Symposium (NDSS), and IEEE Symposium on Security and Privacy (IEEE S&P), along with other high-impact studies. It organizes and analyzes IoT security advancements through the lenses of threats, detection methods, and defense strategies. The foundational architecture of IoT systems is first outlined, followed by categorizing major threats into eight distinct types and analyzing their More >

Komal Rani Narejo¹, Hongying Zan^1,*, Kheem Parkash Dharmani², Orken Mamyrbayev^3,*, Ainur Akhmediyarova⁴, Zhibek Alibiyeva⁴, Janna Alimkulova⁵

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 3407-3429, 2025, DOI:10.32604/cmc.2025.065872 - 03 July 2025

Abstract While automatic image captioning systems have made notable progress in the past few years, generating captions that fully convey sentiment remains a considerable challenge. Although existing models achieve strong performance in visual recognition and factual description, they often fail to account for the emotional context that is naturally present in human-generated captions. To address this gap, we propose the Sentiment-Driven Caption Generator (SDCG), which combines transformer-based visual and textual processing with multi-level fusion. RoBERTa is used for extracting sentiment from textual input, while visual features are handled by the Vision Transformer (ViT). These features are More >

Anees Ara¹, Muhammad Mujahid¹, Amal Al-Rasheed^2,*, Shaha Al-Otaibi², Tanzila Saba¹

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 2717-2731, 2025, DOI:10.32604/cmc.2025.065566 - 03 July 2025

Abstract DeepSeek Chinese artificial intelligence (AI) open-source model, has gained a lot of attention due to its economical training and efficient inference. DeepSeek, a model trained on large-scale reinforcement learning without supervised fine-tuning as a preliminary step, demonstrates remarkable reasoning capabilities of performing a wide range of tasks. DeepSeek is a prominent AI-driven chatbot that assists individuals in learning and enhances responses by generating insightful solutions to inquiries. Users possess divergent viewpoints regarding advanced models like DeepSeek, posting both their merits and shortcomings across several social media platforms. This research presents a new framework for predicting… More >

Muhammad Farooq Siddique¹, Saif Ullah¹, Jong-Myon Kim^1,2,*

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 3577-3603, 2025, DOI:10.32604/cmc.2025.065326 - 03 July 2025

Abstract Centrifugal Pumps (CPs) are critical machine components in many industries, and their efficient operation and reliable Fault Diagnosis (FD) are essential for minimizing downtime and maintenance costs. This paper introduces a novel FD method to improve both the accuracy and reliability of detecting potential faults in such pumps. The proposed method combines Wavelet Coherent Analysis (WCA) and Stockwell Transform (S-transform) scalograms with Sobel and non-local means filters, effectively capturing complex fault signatures from vibration signals. Using Convolutional Neural Network (CNN) for feature extraction, the method transforms these scalograms into image inputs, enabling the recognition of More >

Jitendra Kumar Samriya¹, Virendra Singh², Gourav Bathla³, Meena Malik⁴, Varsha Arya^5,6, Wadee Alhalabi⁷, Brij B. Gupta^8,9,10,11,*

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 3893-3910, 2025, DOI:10.32604/cmc.2025.063242 - 03 July 2025

Abstract The integration of the Internet of Things (IoT) into healthcare systems improves patient care, boosts operational efficiency, and contributes to cost-effective healthcare delivery. However, overcoming several associated challenges, such as data security, interoperability, and ethical concerns, is crucial to realizing the full potential of IoT in healthcare. Real-time anomaly detection plays a key role in protecting patient data and maintaining device integrity amidst the additional security risks posed by interconnected systems. In this context, this paper presents a novel method for healthcare data privacy analysis. The technique is based on the identification of anomalies in… More >

Liang Mu¹, Yurui Kang¹, Zixu Yan¹, Guangyu Zhu^2,*

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 2495-2512, 2025, DOI:10.32604/cmc.2025.063208 - 03 July 2025

Abstract The accurate prediction and analysis of emergencies in Urban Rail Transit Systems (URTS) are essential for the development of effective early warning and prevention mechanisms. This study presents an integrated perception model designed to predict emergencies and analyze their causes based on historical unstructured emergency data. To address issues related to data structuredness and missing values, we employed label encoding and an Elastic Net Regularization-based Generative Adversarial Interpolation Network (ER-GAIN) for data structuring and imputation. Additionally, to mitigate the impact of imbalanced data on the predictive performance of emergencies, we introduced an Adaptive Boosting Ensemble… More >

Zhimei Cai^1,2,*, Faridah Mydin Kutty^1,*, Muhammad Syawal Amran¹

International Journal of Mental Health Promotion, Vol.27, No.6, pp. 753-769, 2025, DOI:10.32604/ijmhp.2025.064983 - 30 June 2025

Abstract Background: considering the significant issue of learning burnout among university students, it is essential to investigate the connection between mindfulness and learning burnout. This systematic review and meta-analysis sought to thoroughly examine the direct and indirect relationships between mindfulness and learning burnout. Methods: a comprehensive literature search was conducted in Scopus, Google Scholar, and Web of Science databases until 07 July 2024. A comprehensive literature review analysis of 19 articles was included, which identified three dimensions of learning burnout: emotions, behaviors, and outcomes, determined the indirect and direct relationships between mindfulness and learning burnout, and… More >

Lin Luo^1,2,*, Junfeng Yuan¹, Yanling Wang¹, Rui Zhu¹, Huilin Xu¹, Siyuan Bi¹, Zhongge Zhang¹

International Journal of Mental Health Promotion, Vol.27, No.6, pp. 863-876, 2025, DOI:10.32604/ijmhp.2025.064385 - 30 June 2025

Abstract Objectives: Social Network Addiction (SNA) is becoming increasingly prevalent among college students; however, there remains a lack of consensus regarding the measurement tools and their optimal cutoff score. This study aims to validate the 21-item Social Network Addiction Scale-Chinese (SNAS-C) in its Chinese version and to determine its optimal cutoff score for identifying potential SNA cases within the college student population. Methods: A cross-sectional survey was conducted, recruiting 3387 college students. Latent profile analysis (LPA) and receiver operating characteristic (ROC) curve analysis were employed to establish the optimal cutoff score for the validated 21-item SNAS-C. Results:… More >