Sheng Bi^1,2,*, Jiayan Wang¹, Dong Su¹, Hui Lu¹, Yu Zhang¹

Energy Engineering, Vol.122, No.10, pp. 4135-4151, 2025, DOI:10.32604/ee.2025.066735 - 30 September 2025

Abstract By comparing price plans offered by several retail energy firms, end users with smart meters and controllers may optimize their energy use cost portfolios, due to the growth of deregulated retail power markets. To help smart grid end-users decrease power payment and usage unhappiness, this article suggests a decision system based on reinforcement learning to aid with electricity price plan selection. An enhanced state-based Markov decision process (MDP) without transition probabilities simulates the decision issue. A Kernel approximate-integrated batch Q-learning approach is used to tackle the given issue. Several adjustments to the sampling and data… More >

Erlin Tian¹, Shuai Zhao^2,*, Min Huang², Yushan Pan^3,4, Yihong Wang^3,4, Zuhe Li¹

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 1427-1456, 2025, DOI:10.32604/cmc.2025.066476 - 29 August 2025

Abstract With the increasing importance of multimodal data in emotional expression on social media, mainstream methods for sentiment analysis have shifted from unimodal to multimodal approaches. However, the challenges of extracting high-quality emotional features and achieving effective interaction between different modalities remain two major obstacles in multimodal sentiment analysis. To address these challenges, this paper proposes a Text-Gated Interaction Network with Inter-Sample Commonality Perception (TGICP). Specifically, we utilize a Inter-sample Commonality Perception (ICP) module to extract common features from similar samples within the same modality, and use these common features to enhance the original features of… More >

Darthy Rabecka V^1,*, Britto Pari J¹, Man-Fai Leung^2,*

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 827-853, 2025, DOI:10.32604/cmc.2025.064924 - 29 August 2025

Abstract Techniques in deep learning have significantly boosted the accuracy and productivity of computer vision segmentation tasks. This article offers an intriguing architecture for semantic, instance, and panoptic segmentation using EfficientNet-B7 and Bidirectional Feature Pyramid Networks (Bi-FPN). When implemented in place of the EfficientNet-B5 backbone, EfficientNet-B7 strengthens the model’s feature extraction capabilities and is far more appropriate for real-world applications. By ensuring superior multi-scale feature fusion, Bi-FPN integration enhances the segmentation of complex objects across various urban environments. The design suggested is examined on rigorous datasets, encompassing Cityscapes, Common Objects in Context, KITTI Karlsruhe Institute of… More >

Ling Huang^1,2, Hao Zhang^1,2, Jiwei Mo^1,2, Yuehong Liu^1,2, Qiu Lu^1,2,*, Shuiwang Li^1,2,*

Journal of Information Hiding and Privacy Protection, Vol.7, pp. 45-60, 2025, DOI:10.32604/jihpp.2025.066524 - 31 July 2025

Abstract Rapid advances in computer vision have enabled powerful visual perception systems in areas such as surveillance, autonomous driving, healthcare, and augmented reality. However, these systems often raise serious privacy concerns due to their ability to identify and track individuals without consent. This paper explores the emerging field of identity-hiding visual perception, which aims to protect personal identity within visual data through techniques such as anonymization, obfuscation, and privacy-aware modeling. We provide a system-level overview of current technologies, categorize application scenarios, and analyze major challenges—particularly the trade-off between privacy and utility, technical complexity, and ethical risks. More >

Gracia Cristina Villodres^1,#,*, Federico Salvador-Pérez², José Joaquín Muros¹, Rocío Vizcaíno-Cuenca^3,4,#

International Journal of Mental Health Promotion, Vol.27, No.7, pp. 877-899, 2025, DOI:10.32604/ijmhp.2025.066137 - 31 July 2025

Abstract Background: University students face significant challenges in maintaining healthy physical activity (PA) and dietary habits, and they often fall short of global health recommendations. Psychological factors such as social physique anxiety, body image concerns, and self-objectification may act as barriers to PA engagement, influencing both mental and physical health. The present study constructed a structural equation model (SEM) to examine the relationship between body image-related psychological factors and resistance to PA in university students from southern Spain. Methods: A cross-sectional and correlational study was conducted with 519 university students (74% females, 26% males; Mean age… More >

Yuting He, Zetao Jiang^*

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 5487-5508, 2025, DOI:10.32604/cmc.2025.065169 - 30 July 2025

Abstract Existing Transformer-based image captioning models typically rely on the self-attention mechanism to capture long-range dependencies, which effectively extracts and leverages the global correlation of image features. However, these models still face challenges in effectively capturing local associations. Moreover, since the encoder extracts global and local association features that focus on different semantic information, semantic noise may occur during the decoding stage. To address these issues, we propose the Local Relationship Enhanced Gated Transformer (LREGT). In the encoder part, we introduce the Local Relationship Enhanced Encoder (LREE), whose core component is the Local Relationship Enhanced Module… 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 >

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 >

Wiktoria Staśkiewicz-Bartecka^1,*, Samet Aktaş², Grzegorz Zydek³, Marek Kardas¹, Oskar Kowalski⁴

International Journal of Mental Health Promotion, Vol.27, No.5, pp. 649-665, 2025, DOI:10.32604/ijmhp.2025.064543 - 05 June 2025

Abstract Background: In light of growing concern over eating disorders among young athletes amid cultural and social pressures, this study aimed to assess the prevalence of orthorexia nervosa (ON) risk and evaluate body image perception and its predictive factors among young football players from Poland and Türkiye. Methods: The study involved 171 players aged 15–18 years, recruited from football academies in Poland and Türkiye. The Polish and Turkish versions of the Body-Esteem Scale for Adolescents and Adults (BESAA) were administered to assess body image perception, while the Düsseldorf Orthorexia Scale (DOS) was used to measure ON… More >

Jingcheng Yang¹, Lili Fan², Hongmei Liu^1,*

CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 4725-4740, 2025, DOI:10.32604/cmc.2025.062963 - 19 May 2025

Abstract With the advancement of deep learning in the automotive domain, more and more researchers are focusing on autonomous driving. Among these tasks, free space detection is particularly crucial. Currently, many model-based approaches have achieved autonomous driving on well-structured urban roads, but these efforts primarily focus on urban road environments. In contrast, there are fewer deep learning methods specifically designed for off-road traversable area detection, and their effectiveness is not yet satisfactory. This is because detecting traversable areas in complex outdoor environments poses significant challenges, and current methods often rely on single-image inputs, which do not… More >