Ruigang Zhang^1,*, Qihui Yan², Jialiang Wang¹, Hao Wang¹, Jie Sun², Junjiao Shi²

Energy Engineering, Vol.122, No.9, pp. 3609-3624, 2025, DOI:10.32604/ee.2025.066880 - 26 August 2025

Abstract As the core facility of offshore wind power systems, the structural safety of offshore booster stations directly impacts the stable operation of entire wind farms. With the global energy transition toward green and low-carbon goals, offshore wind power has emerged as a key renewable energy source, yet its booster stations face harsh marine environments, including persistent wave impacts, salt spray corrosion, and equipment-induced vibrations. Traditional monitoring methods relying on manual inspections and single-dimensional sensors suffer from critical limitations: low efficiency, poor real-time performance, and inability to capture millinewton-level stress fluctuations that signal early structural fatigue.… More >

Nikolai A. Magnitskii^*

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.7, pp. 1529-1544, 2025, DOI:10.32604/fdmp.2025.067021 - 31 July 2025

Abstract This paper presents both analytical and numerical studies of the conservative Sawada–Kotera equation and its dissipative generalization, equations known for their soliton solutions and rich chaotic dynamics. These models offer valuable insights into nonlinear wave propagation, with applications in fluid dynamics and materials science, including systems such as liquid crystals and ferrofluids. It is shown that the conservative Sawada–Kotera equation supports traveling wave solutions corresponding to elliptic limit cycles, as well as two- and three-dimensional invariant tori surrounding these cycles in the associated ordinary differential equation (ODE) system. For the dissipative generalized Sawada–Kotera equation, chaotic 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 >

Bing Wei, Yubin Li, Yi Wu^*, Ming Zhong, Ning Luo

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 4773-4804, 2025, DOI:10.32604/cmc.2025.065090 - 30 July 2025

Abstract Metadata prefetching and data placement play a critical role in enhancing access performance for file systems operating over wide-area networks. However, developing effective strategies for metadata prefetching in environments with concurrent workloads and for data placement across distributed networks remains a significant challenge. This study introduces novel and efficient methodologies for metadata prefetching and data placement, leveraging fine-grained control of prefetching strategies and variable-sized data fragment writing to optimize the I/O bandwidth of distributed file systems. The proposed metadata prefetching technique employs dynamic workload analysis to identify dominant workload patterns and adaptively refines prefetching policies, More >

Mingyang Zhao^1,2,*, Xiaojun Li^1,3, Miao Li^1,2, Bangbang Mu^1,2

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 2827-2846, 2025, DOI:10.32604/cmc.2025.065251 - 03 July 2025

Abstract The control of gas extraction in coal mines relies on the effectiveness of gas extraction. The main method of gas extraction is to drive drill pipes into the coal seam through a drilling rig and use technologies such as hydraulic fracturing to pre-extract gas in the drill holes. Therefore, the real-time detection of the drill pipe status is closely related to the effectiveness of gas extraction. To achieve fast and accurate identification of drill pipes, we propose FSS-YOLO, which is a lightweight drill pipe detection method based on YOLOv8n-obb. This method first introduces the FasterBlock… More >

Siti Ramadhani^1,2, Lestari Handayani², Theam Foo Ng³, Sumayyah Dzulkifly¹, Roziana Ariffin^4,5, Haldi Budiman⁶, Shir Li Wang^1,7,*

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.3, pp. 2711-2765, 2025, DOI:10.32604/cmes.2025.062709 - 30 June 2025

Abstract In recent years, feature selection (FS) optimization of high-dimensional gene expression data has become one of the most promising approaches for cancer prediction and classification. This work reviews FS and classification methods that utilize evolutionary algorithms (EAs) for gene expression profiles in cancer or medical applications based on research motivations, challenges, and recommendations. Relevant studies were retrieved from four major academic databases–IEEE, Scopus, Springer, and ScienceDirect–using the keywords ‘cancer classification’, ‘optimization’, ‘FS’, and ‘gene expression profile’. A total of 67 papers were finally selected with key advancements identified as follows: (1) The majority of papers… More > Graphic Abstract

Ali Hamid Farea^1,*, Iman Askerzade^1,2, Omar H. Alhazmi³, Savaş Takan⁴

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 1457-1484, 2025, DOI:10.32604/cmc.2025.064872 - 09 June 2025

Abstract Feature selection (FS) is a pivotal pre-processing step in developing data-driven models, influencing reliability, performance and optimization. Although existing FS techniques can yield high-performance metrics for certain models, they do not invariably guarantee the extraction of the most critical or impactful features. Prior literature underscores the significance of equitable FS practices and has proposed diverse methodologies for the identification of appropriate features. However, the challenge of discerning the most relevant and influential features persists, particularly in the context of the exponential growth and heterogeneity of big data—a challenge that is increasingly salient in modern artificial… More >

Mingliang Deng¹, Zhao Zhang^1,*, Hongyan Zhou², Xuebo Chen²

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 1189-1202, 2025, DOI:10.32604/cmc.2025.064509 - 09 June 2025

Abstract To fully explore the potential features contained in power load data, an innovative short-term power load forecasting method that integrates data mining and deep learning techniques is proposed. Firstly, a density peak fast search algorithm optimized by time series weighting factors is used to cluster and analyze load data, accurately dividing subsets of data into different categories. Secondly, introducing convolutional block attention mechanism into the bidirectional gated recurrent unit (BiGRU) structure significantly enhances its ability to extract key features. On this basis, in order to make the model more accurately adapt to the dynamic changes… More >

Xuan Wu¹, Yafei Song¹, Xiaodan Wang^1,*, Peng Wang¹, Qian Xiang²

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 1279-1305, 2025, DOI:10.32604/cmc.2025.064471 - 09 June 2025

Abstract With the growth of the Internet of Things (IoT) comes a flood of malicious traffic in the IoT, intensifying the challenges of network security. Traditional models operate with independent layers, limiting their effectiveness in addressing these challenges. To address this issue, we propose a cross-layer cooperative Feature Subset-Based Malicious Traffic Detection (FSMMTD) model for detecting malicious traffic. Our approach begins by applying an enhanced random forest method to adaptively filter and retain highly discriminative first-layer features. These processed features are then input into an improved state-space model that integrates the strengths of recurrent neural networks… More >

Yiming Zhou¹, Jinhua Zhang^2,3, Kai Long^2,*, Ayesha Saeed², Yutang Chen², Rongrong Geng², Tao Tao⁴, Xiaohui Guo¹

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.2, pp. 1743-1761, 2025, DOI:10.32604/cmes.2025.063034 - 30 May 2025

Abstract The jacket structure and transition piece comprise the supporting structure of a bottom-fixed offshore wind turbine (OWT) connected to the steel tower, which determines the overall structural dynamic performance of the entire OWT. Ideally, optimal performance can be realized by effectively coordinating two components, notwithstanding their separate design processes. In pursuit of this objective, this paper proposes a concurrent design methodology for the jacket structure and transition piece by exploiting topology optimization (TO). The TO for a three-legged jacket foundation is formulated by minimizing static compliance. In contrast to conventional TO, two separated volume fractions… More >