Mong-Fong Horng^1,#, Thanh-Lam Nguyen^1,#, Thanh-Tuan Nguyen^2,*, Chin-Shiuh Shieh^1,*, Lan-Yuen Guo³, Chen-Fu Hung⁴, Chun-Chih Lo¹

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2025.075064 - 29 January 2026

Abstract The global population is rapidly expanding, driving an increasing demand for intelligent healthcare systems. Artificial intelligence (AI) applications in remote patient monitoring and diagnosis have achieved remarkable progress and are emerging as a major development trend. Among these applications, mouth motion tracking and mouth-state detection represent an important direction, providing valuable support for diagnosing neuromuscular disorders such as dysphagia, Bell’s palsy, and Parkinson’s disease. In this study, we focus on developing a real-time system capable of monitoring and detecting mouth state that can be efficiently deployed on edge devices. The proposed system integrates the Facial… More >

Maddina Dinesh Kumar^1,#, S. U. Mamatha², Khalid Masood³, Nehad Ali Shah^4,#, Se-Jin Yook^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2025.074680 - 29 January 2026

Abstract Fluid dynamic research on rectangular and trapezoidal fins is aimed at increasing heat transfer by means of large surfaces. The trapezoidal cavity form is compared with its thermal and flow performance, and it is revealed that trapezoidal fins tend to be more efficient, particularly when material optimization is critical. Motivated by the increasing need for sustainable energy management, this work analyses the thermal performance of inclined trapezoidal and rectangular porous fins utilising a unique hybrid nanofluid. The effectiveness of nanoparticles in a working fluid is primarily determined by their thermophysical properties; hence, optimising these properties… More >

Sana Shahab¹, Vladimir Simic^2,*, Ashit Kumar Dutta^3,4, Mohd Anjum^5,*, Dragan Pamucar^6,7,8

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2025.073945 - 29 January 2026

Abstract Environmental problems are intensifying due to the rapid growth of the population, industry, and urban infrastructure. This expansion has resulted in increased air and water pollution, intensified urban heat island effects, and greater runoff from parks and other green spaces. Addressing these challenges requires prioritizing green infrastructure and other sustainable urban development strategies. This study introduces a novel Integrated Decision Support System that combines Pythagorean Fuzzy Sets with the Advanced Alternative Ranking Order Method allowing for Two-Step Normalization (AAROM-TN), enhanced by a dual weighting strategy. The weighting approach integrates the Criteria Importance Through Intercriteria Correlation… More >

Amel Ksibi^*, Hatoon Albadah, Ghadah Aldehim, Manel Ayadi

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2025.073533 - 29 January 2026

Abstract Sustainable energy systems will entail a change in the carbon intensity projections, which should be carried out in a proper manner to facilitate the smooth running of the grid and reduce greenhouse emissions. The present article outlines the TransCarbonNet, a novel hybrid deep learning framework with self-attention characteristics added to the bidirectional Long Short-Term Memory (Bi-LSTM) network to forecast the carbon intensity of the grid several days. The proposed temporal fusion model not only learns the local temporal interactions but also the long-term patterns of the carbon emission data; hence, it is able to give… More >

Muhammad Hamzah¹, Muhammad Ramzan^2,*, Abdulrahman A. Almehizia³, Ibrahim Mahariq^4,5,6,7,8,*, Laila A. Al-Essa⁹, Ahmed S. Hassan¹⁰

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2025.070435 - 29 January 2026

Abstract The present investigation inspects the unsteady, incompressible MHD-induced flow of a ternary hybrid nanofluid made of SiO2 (silicon dioxide), ZnO (zinc oxide), and MWCNT (multi-walled carbon nanotubes) suspended in a water-ethylene glycol base fluid between two perforated squeezing Riga plates. This problem is important because it helps us understand the complicated connections between magnetic fields, nanofluid dynamics, and heat transport, all of which are critical for designing thermal management systems. These findings are especially useful for improving the design of innovative cooling technologies in electronics, energy systems, and healthcare applications. No prior study has… More >

Divya Ramesh, Sriram Venkatachalam^*

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2025.069854 - 29 January 2026

Abstract A hybrid model combining Fully Non-Linear Potential Flow Theory (FNPT) based on the Finite Element Method (FEM) and the Unified Navier-Stokes equation, using the 3D Improved Meshless Local Petrov Galerkin method with Rankine Source (IMLPG_R), is developed to study wave interactions with a porous layer. In previous studies, the above formulations are applied to wave interaction with fixed cylindrical structures. The present study extends this framework by integrating a unified governing equation within the hybrid modeling approach to capture the dynamics of wave interaction with porous media. The porous layers are employed to replicate the… More >

Haokai Xie¹, Yi Lu¹, Xiaojun Ni¹, Yilei Gu¹, Sihao Fu^2,*, Wenyao Ye³, Zheren Zhang², Zheng Xu²

Energy Engineering, Vol.123, No.2, 2026, DOI:10.32604/ee.2025.070934 - 27 January 2026

Abstract With the rapid development of large-scale offshore wind farms, efficient and reliable power transmission systems are urgently needed. Hybrid high-voltage direct current (HVDC) configurations combining a diode rectifier unit (DRU) and a modular multilevel converter (MMC) have emerged as a promising solution, offering advantages in cost-effectiveness and control capability. However, the uncontrollable nature of the DRU poses significant challenges for system stability under offshore AC fault conditions, particularly due to its inability to provide fault current or voltage support. This paper investigates the offshore AC fault characteristics and fault ride-through (FRT) strategy of a hybrid… More >

Miriam Di Matteo^*, Domiziana Vespasiano, Gianluigi Lo Basso, Costanza Vittoria Fiorini, Andrea Vallati

Energy Engineering, Vol.123, No.2, 2026, DOI:10.32604/ee.2025.064353 - 27 January 2026

Abstract Decarbonising the building sector, particularly residential heating, represents a critical challenge for achieving carbon-neutral energy systems. Efficient solutions must integrate both technological performance and renewable energy sources while considering operational constraints of existing systems. This study investigates a hybrid heating system combining a natural gas boiler (NGB) with an air-to-water heat pump (AWHP), evaluated through a combination of laboratory experiments and dynamic modelling. A prototype developed in the Electrical and Energy Engineering Laboratory enabled the characterization of both heat generators, the collection of experimental data, and the calibration of a MATLAB/Simulink model, including emissions and… More >

Jeongeun Ryu¹, Riyeong Kim², Soomin Lee¹, Sumin Kim¹, Hyunwoo Choi^1,2, Seongmin Kim^1,2,*

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.074871 - 12 January 2026

Abstract As containerized environments become increasingly prevalent in cloud-native infrastructures, the need for effective monitoring and detection of malicious behaviors has become critical. Malicious containers pose significant risks by exploiting shared host resources, enabling privilege escalation, or launching large-scale attacks such as cryptomining and botnet activities. Therefore, developing accurate and efficient detection mechanisms is essential for ensuring the security and stability of containerized systems. To this end, we propose a hybrid detection framework that leverages the extended Berkeley Packet Filter (eBPF) to monitor container activities directly within the Linux kernel. The framework simultaneously collects flow-based network… More >

Girish Hariharan¹, Vinyas¹, Gowrishankar Mandya Chennegowda¹, Nitesh Kumar¹, Shiva Kumar¹, Deepak Doreswamy², Subraya Krishna Bhat^1,*

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.073772 - 12 January 2026

Abstract This study presents a framework involving statistical modeling and machine learning to accurately predict and optimize the mechanical and damping properties of hybrid granite–epoxy (G–E) composites reinforced with cast iron (CI) filler particles. Hybrid G–E composite with added cast iron (CI) filler particles enhances stiffness, strength, and vibration damping, offering enhanced performance for vibration-sensitive engineering applications. Unlike conventional approaches, this work simultaneously employs Artificial Neural Networks (ANN) for high-accuracy property prediction and Response Surface Methodology (RSM) for in-depth analysis of factor interactions and optimization. A total of 24 experimental test data sets of varying input… More >