Kunjabihari Swain¹, Murthy Cherukuri^1,*, Indu Sekhar Samanta², Bhargav Appasani^3,*, Nicu Bizon^4,5, Mihai Oproescu⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 1993-2015, 2025, DOI:10.32604/cmes.2025.067121 - 26 November 2025

Abstract Transmission line faults pose a significant threat to power system resilience, underscoring the need for accurate and rapid fault identification to facilitate proper resource monitoring, economic loss prevention, and blackout avoidance. Extreme learning machine (ELM) offers a compelling solution for rapid classification, achieving network training in a single epoch. Leveraging the Internet of Things (IoT) and the virtual instrumentation capabilities of LabVIEW, ELM can enable the swift and precise identification of transmission line faults. This paper presents a regularized radial basis function (RBF) ELM-based fault detection and classification system for transmission lines, utilizing a LabVIEW More >

Mujeebu Rehman¹, Qinghua Liu¹, Ali Ghulam², Tariq Ahmad³, Jawad Khan^4,*, Dildar Hussain^5,*, Yeong Hyeon Gu⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.1, pp. 779-805, 2025, DOI:10.32604/cmes.2025.067412 - 30 October 2025

Abstract Identifying druggable proteins, which are capable of binding therapeutic compounds, remains a critical and resource-intensive challenge in drug discovery. To address this, we propose CEL-IDP (Comparison of Ensemble Learning Methods for Identification of Druggable Proteins), a computational framework combining three feature extraction methods Dipeptide Deviation from Expected Mean (DDE), Enhanced Amino Acid Composition (EAAC), and Enhanced Grouped Amino Acid Composition (EGAAC) with ensemble learning strategies (Bagging, Boosting, Stacking) to classify druggable proteins from sequence data. DDE captures dipeptide frequency deviations, EAAC encodes positional amino acid information, and EGAAC groups residues by physicochemical properties to generate… More >

Kaidi Luo¹, Weihuang Cai², Huazhen Liu¹, Yi Zhang², Kailei Pan², Xiaoyi Wang¹, Yuanyuan Liu^1,2*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.2, pp. 1-1, 2025, DOI:10.32604/icces.2025.011866

Abstract As the global prevalence of diabetes continues to rise, chronic diabetic wounds have become an important cause of amputation and death due to their protracted nature. In order to break through the limitations of traditional dressings, this study innovatively constructed a GelMA/HAMA-CS/PCL composite hydrogel-scaffold system containing chitosan based on biomaterials engineering and 3D printing technology. The system provides biomimetic ECM microenvironment through: photocrosslinked hydrogel layer (GelMA/HAMA-CS); Electrostatic spinning PCL film achieves mechanical strengthening and barrier protection. The chitosan component imparts long-term antibacterial activity, and the multi-materials cooperate to promote wound healing. In vitro antibacterial and… More >

Idarous Saleh Said¹, Gilbert Gilibrays Ocen^1,*, Mwase Ali², Alunyu Andrew Egwar¹

Journal of Cyber Security, Vol.7, pp. 359-375, 2025, DOI:10.32604/jcs.2025.066979 - 25 September 2025

Abstract The growing reliance on digital evidence in judicial proceedings has heightened the need for structured, secure, and legally sound frameworks for its collection, preservation, storage, and presentation. In Zanzibar, however, the integration of digital evidence into the court system remains hindered by the absence of standardized procedures and digital infrastructure, undermining the integrity and admissibility of such evidence. This study addresses these challenges by developing a comprehensive Digital Evidence Lifecycle Management Framework (DELM-C) tailored to the operational and legal context of the Zanzibar High Court. The proposed framework aims to streamline digital evidence handling, enhance… More >

Farah Mohammad^1,2,*, Saad Al-Ahmadi^1,3, Jalal Al-Muhtadi^1,3

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 5995-6014, 2025, DOI:10.32604/cmc.2025.063046 - 30 July 2025

Abstract Malware continues to pose a significant threat to cybersecurity, with new advanced infections that go beyond traditional detection. Limitations in existing systems include high false-positive rates, slow system response times, and inability to respond quickly to new malware forms. To overcome these challenges, this paper proposes OMD-RAS: Implementing Malware Detection in an Optimized Way through Real-Time and Adaptive Security as an extensive approach, hoping to get good results towards better malware threat detection and remediation. The significant steps in the model are data collection followed by comprehensive preprocessing consisting of feature engineering and normalization. Static… More >

Lieping Zhang^1,2, Hao Ma¹, Jiancheng Huang³, Cui Zhang^4,*, Xiaolin Gao²

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 2245-2265, 2025, DOI:10.32604/cmc.2025.061519 - 16 April 2025

Abstract Detecting individuals wearing safety helmets in complex environments faces several challenges. These factors include limited detection accuracy and frequent missed or false detections. Additionally, existing algorithms often have excessive parameter counts, complex network structures, and high computational demands. These challenges make it difficult to deploy such models efficiently on resource-constrained devices like embedded systems. Aiming at this problem, this research proposes an optimized and lightweight solution called FGP-YOLOv8, an improved version of YOLOv8n. The YOLOv8 backbone network is replaced with the FasterNet model to reduce parameters and computational demands while local convolution layers are added.… More >

Yu Zhang, Daoyu Zhang^*, Tiezhou Wu

Energy Engineering, Vol.122, No.1, pp. 203-220, 2025, DOI:10.32604/ee.2024.056244 - 27 December 2024

Abstract Precisely estimating the state of health (SOH) of lithium-ion batteries is essential for battery management systems (BMS), as it plays a key role in ensuring the safe and reliable operation of battery systems. However, current SOH estimation methods often overlook the valuable temperature information that can effectively characterize battery aging during capacity degradation. Additionally, the Elman neural network, which is commonly employed for SOH estimation, exhibits several drawbacks, including slow training speed, a tendency to become trapped in local minima, and the initialization of weights and thresholds using pseudo-random numbers, leading to unstable model performance.… More >

Chein-Shan Liu, Chung-Lun Kuo^*

Digital Engineering and Digital Twin, Vol.2, pp. 145-167, 2024, DOI:10.32604/dedt.2024.042804 - 31 December 2024

Abstract A new concept of projective solution is introduced for the second-order linear partial differential equations (PDEs) endowed with constant coefficients. In terms of a projective variable the PDE is transformed to a second-order ordinary differential equation (ODE) with constant coefficients at the first time. The characteristic form appears as the coefficient preceding the second-order derivative term. Depending on the characteristic form and coefficients we can derive various parameters-dependent particular solutions, which can be adopted as the bases to expand the solution. The Helmholtz and wave equations are solved by the projection method. We project the… More >

Anyu Xu¹, Yonghang Sun², Heow Pueh Lee^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.31, No.2, pp. 1-1, 2024, DOI:10.32604/icces.2024.010894

Abstract A pentagon plate-shaped metamaterial with resonators inside is designed, and both sides are covered with PVC membranes. The components are designed with sloped exterior walls and can form a regular dodecahedron metacage. The effect of the single component is based on the vibration of the membranes, when the size of two membranes has the same size, the transmission loss appears to be significant around 900 Hz and have another peak around 1400 Hz. When use twelve components to form a regular dodecahedron metacage, with a diameter of less than half a meter, a measurement of… More >

Yuxuan Zhao^1,2,*, Bo Wang¹, Shu Wang¹, Wenjun Xu², Gang Ma²

Energy Engineering, Vol.121, No.12, pp. 3711-3733, 2024, DOI:10.32604/ee.2024.054032 - 22 November 2024

Abstract The output of photovoltaic power stations is significantly affected by environmental factors, leading to intermittent and fluctuating power generation. With the increasing frequency of extreme weather events due to global warming, photovoltaic power stations may experience drastic reductions in power generation or even complete shutdowns during such conditions. The integration of these stations on a large scale into the power grid could potentially pose challenges to system stability. To address this issue, in this study, we propose a network architecture based on VMD-KELM for predicting the power output of photovoltaic power plants during severe weather… More >