Qiang Zhang¹, Shuo Feng¹, Shanxiong Chen², Teng Wan¹, Ying Qi^1,*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-22, 2026, DOI:10.32604/cmc.2025.068247 - 10 November 2025

Abstract Human motion modeling is a core technology in computer animation, game development, and human-computer interaction. In particular, generating natural and coherent in-between motion using only the initial and terminal frames remains a fundamental yet unresolved challenge. Existing methods typically rely on dense keyframe inputs or complex prior structures, making it difficult to balance motion quality and plausibility under conditions such as sparse constraints, long-term dependencies, and diverse motion styles. To address this, we propose a motion generation framework based on a frequency-domain diffusion model, which aims to better model complex motion distributions and enhance generation… More >

Harith Iman Othman Kalam¹, Ainon Nisa Othman^1,*, Mohamad Hezri Razali^1,*, Pauziyah Mohammad Salim¹, Akhbaaruddin Abd Hamid²

Revue Internationale de Géomatique, Vol.34, pp. 973-985, 2025, DOI:10.32604/RIG.2025.071917 - 24 December 2025

Abstract Ground Penetrating Radar (GPR) is a widely used method that is non-destructive for underground or subsurface detection. It is used in various fields and has proved to be reliable and effective. This research focuses on detecting the presence of air cavities using GPR and analyzing the radargram output based on the compactness of soil and different frequencies. The compactness is used to illustrate the presence of cavities underground artificially. The research examines how variations in the compactness of soil affect the radargram response in showing the presence of cavities using different frequencies. Experimental results demonstrate More >

Shuxin Tan¹, Wei Yan², Lei Zhao¹, Xianglin Zhang^3,*, Ziqiang Man², Yu Lu², Teng Liu², Gaoyue Zhong², Weiqun Liu², Linjun Shi³

Energy Engineering, Vol.122, No.12, pp. 5175-5197, 2025, DOI:10.32604/ee.2025.068692 - 27 November 2025

Abstract The integration of large-scale renewable energy introduces frequency instability challenges due to inherent intermittency. While doubly-fed pumped storage units (DFPSUs) offer frequency regulation potential in pumping mode, conventional strategies fail to address hydraulic-mechanical coupling dynamics and operational constraints, limiting their effectiveness. This paper presents an innovative primary frequency control strategy for double-fed pumped storage units (DFPSUs) operating in pumping mode, integrating an adaptive parameter calculation method. This method is constrained by operational speed and power limits, addressing key performance factors. A dynamic model that incorporates the reversible pump-turbine characteristics is developed to translate frequency deviations… More >

Bin Zhang¹, En-Cheng Liou^2,*, Yi-Chih Tung³, Muhammad Usman^2,4, Chiung-An Chen^2,4, Chao-Shun Yang^2,4

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 2551-2571, 2025, DOI:10.32604/cmes.2025.072471 - 26 November 2025

Abstract Indoor localization is a fundamental requirement for future 6G Intelligent Sensing and Communication (ISAC) systems, enabling precise navigation in environments where Global Positioning System (GPS) signals are unavailable. Existing methods, such as map-based navigation or site-specific fingerprinting, often require intensive data collection and lack generalization capability across different buildings, thereby limiting scalability. This study proposes a cross-site, map-free indoor localization framework that uses low-frequency sub-1 GHz radio signals and a Transformer-based neural network for robust positioning without prior environmental knowledge. The Transformer’s self-attention mechanisms allow it to capture spatial correlations among anchor nodes, facilitating accurate… More >

Mudasir Ali¹, Muhammad Faheem Mushtaq², Urooj Akram², Nagwan Abdel Samee^3,*, Mona M. Jamjoom⁴, Imran Ashraf^5,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 1863-1901, 2025, DOI:10.32604/cmes.2025.070389 - 26 November 2025

Abstract Differentiating between regular and abnormal noises in machine-generated sounds is a crucial but difficult problem. For accurate audio signal classification, suitable and efficient techniques are needed, particularly machine learning approaches for automated classification. Due to the dynamic and diverse representative characteristics of audio data, the probability of achieving high classification accuracy is relatively low and requires further research efforts. This study proposes an ensemble model based on the LeNet and hierarchical attention mechanism (HAM) models with MFCC features to enhance the models’ capacity to handle bias. Additionally, CNNs, bidirectional LSTM (BiLSTM), CRNN, LSTM, capsule network More >

Tianyuan Qi¹, Junpeng Zhao^1,2,*, Chunjie Wang^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.1, pp. 127-151, 2025, DOI:10.32604/cmes.2025.070769 - 30 October 2025

Abstract A major bottleneck in large-scale eigenfrequency topology optimization is the repeated solution of the generalized eigenvalue problem. This work presents an efficient graphics processing unit (GPU) solver for three-dimensional (3D) topology optimization that maximizes the fundamental eigenfrequency. The Successive Iteration of Analysis and Design (SIAD) framework is employed to avoid solving a full eigenproblem at every iteration. The sequential approximation of the eigenpairs is solved by the GPU-accelerated multigrid-preconditioned conjugate gradient (MGPCG) method to efficiently improve the eigenvectors along with the topological evolution. The cluster-mean approach is adopted to address the non-differentiability issue caused by… More > Graphic Abstract

Yumeng Kong^*, Xuesong Guo, Yifei Wang

International Journal of Mental Health Promotion, Vol.27, No.10, pp. 1577-1594, 2025, DOI:10.32604/ijmhp.2025.069985 - 31 October 2025

Abstract Background: Anxiety and depression are prevalent among university students, calling for effective non-pharmacological interventions. Tai Chi shows potential in reducing these symptoms, but research on its effects at different frequencies in younger populations is limited. This study compared the impacts of high-(5 sessions/week), medium-(3 sessions/week), and low-frequency (2 sessions/week) 24-form Tai Chi on college students’ anxiety/depression, versus a control group. Methods: A randomized controlled trial (RCT) included 120 university students with mild-to-moderate anxiety/depression, randomly assigned to 4 groups (30 each). The 8-week intervention used the Self-Rating Anxiety Scale (SAS) and Self-Rating Depression Scale (SDS) for… More >

He Wang, Shiqiang Li^*, Yiqi Liu, Jing Bian

Energy Engineering, Vol.122, No.11, pp. 4497-4521, 2025, DOI:10.32604/ee.2025.065244 - 27 October 2025

Abstract With the evolution of DC distribution networks from traditional radial topologies to more complex multi-branch structures, the number of measurement points supporting synchronous communication remains relatively limited. This poses challenges for conventional fault distance estimation methods, which are often tailored to simple topologies and are thus difficult to apply to large-scale, multi-node DC networks. To address this, a fault distance estimation method based on sparse measurement of high-frequency electrical quantities is proposed in this paper. First, a preliminary fault line identification model based on compressed sensing is constructed to effectively narrow the fault search range… More >

Nur Sabrina Jamal, Nabilah Naharudin^*

Revue Internationale de Géomatique, Vol.34, pp. 751-776, 2025, DOI:10.32604/rig.2025.071091 - 17 October 2025

Abstract Multicriteria Decision Analysis (MCDA) has been integrated with GIS modelling by many studies to aid the decision-making process. This integration enhances modelling by incorporating spatial relationships and using advanced techniques, including the combination of Frequency Ratio (FR) and Analytical Hierarchical Process (AHP), also known as FR-AHP. Although methods like Two-Steps Floating Catchment Area (2SFCA), AHP, and FR are widely applied in measuring accessibility, they have limitations in terms of threshold sensitivity and subjectivity. Hence, this study used FR-AHP, which combines the data-driven strength of FR and the structured decision-making technique of AHP to provide a… More >

Fan Chen^*, Tianhui Zhang, Man Wang, Zhiheng Zhuang, Qiang Zhang, Zihan Ma

Energy Engineering, Vol.122, No.10, pp. 4099-4120, 2025, DOI:10.32604/ee.2025.069346 - 30 September 2025

Abstract The configuration of a hybrid energy storage system (HESS) plays a pivotal role in mitigating wind power fluctuations and enabling primary frequency regulation, thereby enhancing the active power support capability of wind power integration systems. However, most existing studies on HESS capacity configuration overlook the self-recovery control of the state of charge (SOC), creating challenges in sustaining capacity during long-term operation. This omission can impair frequency regulation performance, increase capacity requirements, and shorten battery lifespan. To address these challenges, this study proposes a bi-level planning–operation capacity configuration model that explicitly incorporates SOC self-recovery control. In… More >