Guglielmo D’Amico^1,*, Edoardo Lui², Filippo Petroni¹

CMES-Computer Modeling in Engineering & Sciences, Vol.148, No.1, 2026, DOI:10.32604/cmes.2026.082608 - 27 July 2026

Abstract This paper develops an operational framework for short-horizon risk management in multistate stochastic systems, with application to wind farm performance. We focus on instantaneous mobility-based indicators derived from finite-state continuous-time Markov chains, which capture the local propensity of a system to transition between states. Unlike classical reliability and availability measures, these indicators provide a dynamic description of system behavior. The indicators are interpreted as policy signals to support decision-making under budget constraints. We introduce a state-conditional expected short-horizon loss, representing non-production risk, and use it to evaluate ranking-based intervention strategies. The framework is applied to More >

Zhongjian Ling, Yongou Zhang^*, Yifan Li, Xianzhong Wang

CMES-Computer Modeling in Engineering & Sciences, Vol.148, No.1, 2026, DOI:10.32604/cmes.2026.082363 - 27 July 2026

Abstract Due to the complex and dynamic nature of multi-phase interfaces, accurately capturing interface evolution remains one of the key challenges in multi-phase flow simulations, particularly in modeling bubble rising. In this study, a fully Lagrangian method is developed by using the Generalized Finite Difference (GFD) scheme, which we refer to as Finite Difference Particle Method (FDPM), and the Continuum Surface Force (CSF) model to simulate bubble dynamics. In this framework, the fluid is represented by particles, and all partial differential terms in the Navier–Stokes equations are discretized into symmetric linear systems using the GFD scheme.… More > Graphic Abstract

Mahander Kumar¹, Lal Khan^2,*, Mohammad Zubair Khan^3,*, Ibrahim Aljubayri⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.148, No.1, 2026, DOI:10.32604/cmes.2026.081699 - 27 July 2026

Abstract Aspect-Based Sentiment Analysis (ABSA) is a fundamental Natural Language Processing (NLP) task that aims to determine fine-grained sentiment polarity toward specific aspects mentioned in text. With the emergence of Large Language Models (LLMs) and transformer-based architectures, significant improvements have been achieved in contextual representation learning for sentiment analysis. However, existing LLM-inspired and transformer-based ABSA frameworks often suffer from inadequate aspect-context alignment, redundant feature integration, limited interpretability, and insufficient coordination between contextual and sequential modeling components. To address these challenges, this paper proposes two hybrid architectures, namely HABSA and AAC-HABSA, centered on a novel Adaptive Aspect… More > Graphic Abstract

Karthick Raghunath K. M.¹, Manjula V.¹, Mahesh T. R.¹, Surbhi B. Khan^2,3,*, Ahmed Alyahya^4,*, Shakila Basheer⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.148, No.1, 2026, DOI:10.32604/cmes.2026.081429 - 27 July 2026

Abstract In general, medical biometric datasets, with the essential unique behavioral and physical traits for personalized healthcare, shape the patient identification process, but the tendency towards transparency and fairness is still far away. Most of the existing methods fail to integrate the latest mathematical techniques rigorously with the deep learning models, which eventually makes such models undesirable due to their lack of interpretability and potential bias. As such, in this study, a novel Contour Integrated Transparent Augmented Deep Learning (CITADL) methodology is introduced to bridge this gap. In this study, a structured framework, namely CITADL, combines… More >

AL-Wesabi Ibrahim¹, Hassan M. Hussein Farh^2,*, Jiazhu Xu^1,*, Mohamad A. Alawad², Ahmed Alqurashi³, Abdullrahman A. Al-Shamma’a²

CMES-Computer Modeling in Engineering & Sciences, Vol.148, No.1, 2026, DOI:10.32604/cmes.2026.081371 - 27 July 2026

Abstract Load frequency control (LFC) in interconnected power systems has always been a challenging task in the presence of uncertainty and variability in the power systems arising primarily due to the integration of renewable energy sources and the impact of electric vehicles on the power system. Although various PI/PID and other advanced control strategies have been employed for LFC in power systems, the existing methods have shown some limitations in terms of dynamic flexibility and robustness in the presence of nonlinearities and couplings in the power systems. Moreover, the optimization methods employed for the tuning of… More >

Md. Fahmid-Ul-Alam Juboraj¹, Fahmid Al Farid^2,3, Mahe Zabin⁴, Jia Uddin⁵, Muhammad Iqbal Hossain^1,*, Sarina Mansor^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.148, No.1, 2026, DOI:10.32604/cmes.2026.081254 - 27 July 2026

Abstract The integration of Internet of Things (IoT) technologies in agriculture enables precision farming but introduces significant cybersecurity vulnerabilities. This paper presents FICNet (Feature Integrated Convolutional Network), a lightweight deep learning architecture for intrusion detection in agricultural IoT environments. Evaluated on the Farm-Flow AG-IoT security dataset, FICNet achieves 100% binary classification accuracy and 81.25% multiclass accuracy (macro F1: 80.43%, precision: 91.26%, ROC-AUC: 96.78%) across 8 traffic categories. A multi-dimensional component analysis confirms the contribution of each architectural component: multi-scale convolutions provide 5.3% noise robustness advantage, squeeze-and-excitation attention controls per-class detection trade-offs, and the full architecture achieves More >

Zhongxue Li^1,*, Yu Peng¹, Jin Xu², Loc Vu-Quoc³, Bassam A. Izzuddin⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.148, No.1, 2026, DOI:10.32604/cmes.2026.081240 - 27 July 2026

Abstract This paper proposes a computational theory for multibody dynamics based on a novel co-rotational formulation of a four-node quadrilateral shell element, designed to address nonlinear dynamic problems in flexible multibody systems undergoing arbitrarily large displacements and rotations. To circumvent the numerical inefficiency caused by the asymmetric tangent stiffness matrix in conventional co-rotational approaches, an incrementally additive vectorial rotational variable is introduced, which ensures the symmetry of the element’s tangent stiffness matrix in both global and local coordinate systems. The adoption of this vectorial rotational variable substantially improves computational efficiency and numerical stability. Hamilton’s principle is… More >

Manal Ghannam¹, Bilgen Kaymakamzade^1,2, Muhammad Farman^1,3,4, Kottakkaran Sooppy Nisar^5,*, Mohammed Altaf Ahmed⁶

CMES-Computer Modeling in Engineering & Sciences, Vol.148, No.1, 2026, DOI:10.32604/cmes.2026.081075 - 27 July 2026

Abstract In Vitro Fertilization (IVF) has been a major medical advancement in the field of fertility treatment. It has helped millions of individuals and couples overcome infertility by providing a workable option. It involves removing eggs from the ovaries of a female, fertilizing those eggs with male sperm in a monitored lab condition. In this work, we developed a new model to show the success of In Vitro Fertilization rates in women through a fractional-order compartmental modeling framework by using real data. The developed model is analyzed statistically, and the biological feasibility of the model. The Lipschitz condition,… More >

Malika Abid¹, Mohammed Kamel Benkaddour¹, Mohamed Benouis², Amine Khaldi¹, Monalisa Sahu³, Aditya Kumar Sahu^4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.148, No.1, 2026, DOI:10.32604/cmes.2026.081055 - 27 July 2026

Abstract Federated Learning (FL) is a cutting-edge method in the medical imaging field that allows hospitals to collaboratively build models without revealing patient data. Nevertheless, FL is still vulnerable to numerous security and privacy issues, including, but not limited to, data poisoning, Byzantine attacks, and inference attacks. The existing literature has only partly dealt with this topic by focusing either on particular threats or on mitigation strategies, thus leaving the overall comprehension of the problems and their solutions in medical imaging as inadequate. The main threats to FL are systematically classified in this systematic review, with… More >

Teng Long¹, Leyu Wang^2,*, James D. Lee³, Cing-Dao Kan²

CMES-Computer Modeling in Engineering & Sciences, Vol.148, No.1, 2026, DOI:10.32604/cmes.2026.080866 - 27 July 2026

Abstract Titanium alloy Ti-6Al-4V has been widely applied in many industries, for example, aerospace, marine, automotive, and biomedical engineering systems, where accurate characterization of plastic deformation is important for evaluating material performance and potential failure under severe loading conditions. This material shows nonlinear plasticity and tension–compression asymmetry, which makes the strain hardening characterization important for computational failure analysis and crashworthiness-related simulations. However, conventional strain hardening models and parameter identification methods often rely on linear or extrapolation-based assumptions and are sensitive to initial guesses due to the non-convex nature of the optimization problem. In this study, a More >