Kai Xie¹, Shaoqing Yuan², Dayun Zou¹, Jinran Wang^1,*, Genjun Chen¹, Ciwei Gao³, Yinghao Cao¹

Energy Engineering, Vol.123, No.2, 2026, DOI:10.32604/ee.2025.070733 - 27 January 2026

Abstract The construction of spot electricity markets plays a pivotal role in power system reforms, where market clearing systems profoundly influence market efficiency and security. Current clearing systems predominantly adopt a single-system architecture, with research focusing primarily on accelerating solution algorithms through techniques such as high-efficiency parallel solvers and staggered decomposition of mixed-integer programming models. Notably absent are systematic studies evaluating the adaptability of primary-backup clearing systems in contingency scenarios—a critical gap given redundant systems’ expanding applications in operational environments. This paper proposes a comprehensive evaluation framework for analyzing dual-system adaptability, demonstrated through an in-depth case… More >

Xuhui Lou¹, Xu Hou², Jie Wang³, Xiaobao Tian^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.34, No.1, pp. 1-1, 2025, DOI:10.32604/icces.2025.011045

Abstract Grain boundaries (GBs) are transitional, defective, and anisotropic interfaces between adjacent grains with different orientations. However, most models assume that the GB is an isotropic dielectric determined by itself and lacks formation information; these assumptions hinder the theoretical investigation of the effect GBs have on polycrystalline ferroelectrics at the mesoscopic scale. Here, a novel GB model based on the formation mechanism is established for ferroelectric polycrystals. It has been found that the Curie-Weiss temperature range, elastic coefficient, and permittivity of GBs are related to the orientation of adjacent grains and the polarization state. The shielding More >

Muflih Alhazmi¹, Waqar Ul Hassan², Saba Shaheen³, Mohammed M. A. Almazah⁴, Azmat Ullah Khan Niazi^3,*, Nafisa A. Albasheir⁵, Ameni Gargouri⁶, Naveed Iqbal⁷

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 1903-1940, 2025, DOI:10.32604/cmes.2025.072973 - 26 November 2025

Abstract This paper proposes a model-based control framework for vehicle platooning systems with second-order nonlinear dynamics operating over switching signed networks, time-varying delays, and deception attacks. The study includes two configurations: a leaderless structure using Finite-Time Non-Singular Terminal Bipartite Consensus (FNTBC) and Fixed-Time Bipartite Consensus (FXTBC), and a leader—follower structure ensuring structural balance and robustness against deceptive signals. In the leaderless model, a bipartite controller based on impulsive control theory, gauge transformation, and Markovian switching Lyapunov functions ensures mean-square stability and coordination under deception attacks and communication delays. The FNTBC achieves finite-time convergence depending on initial More >

Hansam Cho¹, Seokho Moon¹, Sunhyeok Hwang¹, Seoung Bum Kim^1,*, Younghoon Kim^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 1941-1967, 2025, DOI:10.32604/cmes.2025.072455 - 26 November 2025

Abstract Accurately determining when and what to remanufacture is essential for maximizing the lifecycle value of industrial equipment. However, existing approaches face three significant limitations: (1) reliance on predefined mathematical models that often fail to capture equipment-specific degradation, (2) offline optimization methods that assume access to future data, and (3) the absence of component-level guidance. To address these challenges, we propose a data-driven framework for component-level decision-making. The framework leverages streaming sensor data to predict the remaining useful life (RUL) without relying on mathematical models, employs an online optimization algorithm suitable for practical settings, and, through More >

Maysaa Al-Qurashi¹, Ayesha Siddiqa², Shazia Karim³, Yu-Ming Chu^4,5,*, Saima Rashid^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 2057-2129, 2025, DOI:10.32604/cmes.2025.071629 - 26 November 2025

Abstract Chikungunya is a mosquito-borne viral infection caused by the chikungunya virus (CHIKV). It is characterized by acute onset of high fever, severe polyarthralgia, myalgia, headache, and maculopapular rash. The virus is rapidly spreading and may establish in new regions where competent mosquito vectors are present. This research analyzes the regulatory dynamics of a stochastic differential equation (SDE) model describing the transmission of the CHIKV, incorporating seasonal variations, immunization efforts, and environmental fluctuations modeled through Poisson random measure noise under demographic heterogeneity. The model guarantees the existence of a global positive solution and demonstrates periodic dynamics… More >

Sheeba Razzaq^1,*, Majid Iqbal Khan²

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 5377-5398, 2025, DOI:10.32604/cmc.2025.068539 - 23 October 2025

Abstract Multi-Object Tracking (MOT) represents a fundamental but computationally demanding task in computer vision, with particular challenges arising in occluded and densely populated environments. While contemporary tracking systems have demonstrated considerable progress, persistent limitations—notably frequent occlusion-induced identity switches and tracking inaccuracies—continue to impede reliable real-world deployment. This work introduces an advanced tracking framework that enhances association robustness through a two-stage matching paradigm combining spatial and appearance features. Proposed framework employs: (1) a Height Modulated and Scale Adaptive Spatial Intersection-over-Union (HMSIoU) metric for improved spatial correspondence estimation across variable object scales and partial occlusions; (2) a feature More >

Tianzhe Jiao, Yuming Chen, Xiaoyue Feng, Chaopeng Guo, Jie Song^*

CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 2681-2700, 2025, DOI:10.32604/cmc.2025.069235 - 23 September 2025

Abstract Visible-infrared object detection leverages the day-night stable object perception capability of infrared images to enhance detection robustness in low-light environments by fusing the complementary information of visible and infrared images. However, the inherent differences in the imaging mechanisms of visible and infrared modalities make effective cross-modal fusion challenging. Furthermore, constrained by the physical characteristics of sensors and thermal diffusion effects, infrared images generally suffer from blurred object contours and missing details, making it difficult to extract object features effectively. To address these issues, we propose an infrared-visible image fusion network that realizes multimodal information fusion… More >

Yuqian Huang¹, Luyi Chen², Zilun Peng¹, Lin Cui^1,*

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 6015-6034, 2025, DOI:10.32604/cmc.2025.066717 - 30 July 2025

Abstract Persistent flows are defined as network flows that persist over multiple time intervals and continue to exhibit activity over extended periods, which are critical for identifying long-term behaviors and subtle security threats. Programmable switches provide line-rate packet processing to meet the requirements of high-speed network environments, yet they are fundamentally limited in computational and memory resources. Accurate and memory-efficient persistent flow detection on programmable switches is therefore essential. However, existing approaches often rely on fixed-window sketches or multiple sketches instances, which either suffer from insufficient temporal precision or incur substantial memory overhead, making them ineffective… More >

Rachana Poongodan¹, Dayanand Lal Narayan², Deepika Gadakatte Lokeshwarappa³, Hirald Dwaraka Praveena⁴, Dae-Ki Kang^5,*

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 5751-5772, 2025, DOI:10.32604/cmc.2025.066314 - 30 July 2025

Abstract In recent decades, brain tumors have emerged as a serious neurological disorder that often leads to death. Hence, Brain Tumor Segmentation (BTS) is significant to enable the visualization, classification, and delineation of tumor regions in Magnetic Resonance Imaging (MRI). However, BTS remains a challenging task because of noise, non-uniform object texture, diverse image content and clustered objects. To address these challenges, a novel model is implemented in this research. The key objective of this research is to improve segmentation accuracy and generalization in BTS by incorporating Switchable Normalization into Faster R-CNN, which effectively captures the… More >

Vafa Mirzaei, Mohammad Bameri, Peyman Moradweysi, Mohammad Mohammadi Aghdam^*

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.3, pp. 2811-2832, 2025, DOI:10.32604/cmes.2025.065318 - 30 June 2025

Abstract The precise computation of nanoelectromechanical switches’ (NEMS) multi-physical interactions requires advanced numerical models and is a crucial part of the development of micro- and nano-systems. This paper presents a novel compound numerical method to study the instability of a functionally graded (FG) beam-type NEMS, considering surface elasticity effects as stated by Gurtin-Murdoch theory in an Euler-Bernoulli beam. The presented method is based on a combination of the Method of Adjoints (MoA) together with the Bézier-based multi-step technique. By utilizing the MoA, a boundary value problem (BVP) is turned into an initial value problem (IVP). The… More > Graphic Abstract