Gaeul Kim¹, Dohoon Kim^2,*

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.078931 - 08 May 2026

Abstract Manned-Unmanned Teaming (MUM-T) is an operational system where manned and unmanned systems perform missions through a collaboration interface, expanding beyond defense into civilian domains. The core of MUM-T lies in the organic interaction between manned and unmanned systems. The Collaboration Interface enabling this interaction becomes a primary target for cyber attacks due to its reliance on wireless networks. Compromising the reliability of the collaboration interface goes beyond simple communication failures; it directly leads to mission failure and aircraft safety issues. Therefore, systematic threat analysis and assessment tailored to this specific domain are essential. This study… More >

Ali S. Alghamdi^*

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.1, 2026, DOI:10.32604/cmes.2026.079763 - 27 April 2026

Abstract The integration of wind-based DG introduces significant variability and uncertainty into the operation of distribution networks, which complicates the planning and decision-making process. This paper presents a dual-objective stochastic optimization framework for the optimal allocation of wind DG, considering dynamic network reconfiguration across multiple loading conditions. Probabilistic modeling of wind speed is integrated using the Weibull distribution and the associated wind power uncertainty is discretized through a scenario-based point estimation method. Variability in load is accounted for by considering multiple loading levels, and the integrated uncertainty space is constructed as the Cartesian product of wind… More >

Nai-Wei Lo¹, Cheng-I Lin², Chih-Chieh Chang^3,*, Chi-Yang Chang⁴, Tran Thi Luu Ly¹

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.1, 2026, DOI:10.32604/cmes.2026.077316 - 27 April 2026

Abstract The growing frequency of malicious attacks on Internet of Things (IoT) devices has rendered conventional approaches with static label-dependent risk assessment models obsolete, especially when coping with unknown and continuously evolving threats. To mitigate these challenges, a novel dynamic trust evaluation framework approach is proposed in this work. The proposed framework utilized unsupervised learning and zero-knowledge proofs to assess device risks in complex environments adaptively, with an accuracy rate of 98.96% for normal clustering and 95.39% for anomalies. K-means clustering algorithm is leveraged to distinguish risk patterns with an additional Decision Tree classification algorithm to More >

Safaa M. Ali¹, Ranj S. Abdullah², Hussain H. Al-Kayiem³, Ali M. Tukkee^4,5,*

Energy Engineering, Vol.123, No.5, 2026, DOI:10.32604/ee.2026.076252 - 27 April 2026

Abstract Energy supply and ventilation for isolated offices in rural areas are strongly recommended to be powered by renewable or standalone energy systems under the concept of net-zero-energy building (netZEB). A rooftop solar chimney is one of the adopted methods for space ventilation to improve thermal comfort. This approach has not been investigated under forced convection to support the netZEB. The objective of the current work is to experimentally assess the effectiveness of natural and forced ventilation methods for a prototype net-zero-energy office with a rooftop solar chimney. The prototype is a low-cost office constructed in… More > Graphic Abstract

Junwei Zhang¹, Pei Liu¹, Huihang Li¹, Guokang Huang¹, Bozheng Yuan¹, Wenjing Wei¹, Xiaoshun Zhang^2,*

Energy Engineering, Vol.123, No.5, 2026, DOI:10.32604/ee.2025.072462 - 27 April 2026

Abstract Addressing global climate challenges necessitates urgent low carbon transitions in high energy consuming enterprises (HECEs). This study proposes a comprehensive framework to assess their carbon reduction potential (CRP) by integrating electricity usage behavior analysis and dynamic carbon emission factor (DCEF) prediction. HECEs are classified into “electricity reduction” and “electricity transfer” categories based on load characteristics, enabling tailored optimization strategies. The framework employs machine learning to predict DCEFs, capturing real time variations in grid carbon intensity. A low carbon optimization model is then formulated to minimize emissions while adhering to production requirements and grid constraints, solved… More > Graphic Abstract

Kexin Jiang^1,2, Yong Fan², Liang Wen¹, Zhigang Xie¹, Enzhi Dong¹, Bo Zhu¹, Zhonghua Cheng^1,*

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.077392 - 09 April 2026

Abstract With the growing deployment of unmanned aerial vehicles (UAVs), reliable engine health state assessment (HSA) requires methods that are interpretable, auditable, and transferable under noisy data and varying operating conditions. This paper proposes an AHP-enhanced, data-driven HSA framework that builds a unified health vector from four indicators—remaining useful life (RUL) health, absolute state, relative degradation, and condition health. Indicator weights are derived using AHP with consistency checking, and the resulting continuous health index is mapped through nonlinear stretching and four-level thresholds to produce actionable health grades. Experiments on the NASA CMAPSS benchmark (FD001) evaluate conventional More >

Hitesh Mohapatra^*

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.076726 - 09 April 2026

Abstract This review examines current approaches to real-time decision-making and task optimization in Internet of Things systems through the application of machine learning models deployed at the network edge. Existing literature shows that edge-based distributed intelligence reduces cloud dependency. It addresses transmission latency, device energy use, and bandwidth limits. Recent optimization strategies employ dynamic task offloading mechanisms to determine optimal workload placement across local devices and edge servers without centralized coordination. Empirical findings from the literature indicate performance improvements with latency reductions of approximately 32.8% and energy efficiency gains of 27.4% compared to conventional cloud-centric models.… More >

Chao Guo¹, Chao Deng², Xing Bai³, Ziyuan Fan⁴, Jintao Li², Yuan Ren^2,*

Structural Durability & Health Monitoring, Vol.20, No.2, 2026, DOI:10.32604/sdhm.2025.075363 - 31 March 2026

Abstract Hangers play a crucial role in transferring loads in suspension bridges, yet their condition often deteriorates faster than expected due to corrosion and fatigue effects. Premature hanger failure poses serious risks to bridge safety and results in significant economic loss due to frequent replacement and traffic interruption. To address these challenges, this study proposes an integrated framework to evaluate the life-cycle safety and operational cost of bridge hangers. Traffic data obtained from Weigh-in-Motion (WIM) systems are used to simulate dynamic hanger responses. A wire-to-hanger deterioration model is then employed to capture the time-dependent interaction between… More >

Ehsan Momeni¹, Mohammad Dehghannezhad¹, Fereydoon Omidinasab¹, Danial Jahed Armaghani^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.3, 2026, DOI:10.32604/cmes.2026.077300 - 30 March 2026

Abstract In the last decade, the importance of sustainable construction and artificial intelligence (AI) in civil engineering has been underlined in many studies. Numerous studies highlighted the superiority of AI techniques over simple and mathematical regression analyses, which suffer from relatively poor generalization and an inability to capture highly non-linear relationships among inputs and output(s) parameters. In this study, to evaluate the compressive strength of concrete with glass powder (GP) and recycled aggregates, 600 concrete samples were tested in the laboratory, and their results were evaluated. For intelligent assessment of concrete compressive strength (CCS), the study… More >

Belén Rovira^1,*, Aude Chabrelie¹, Sauro Bianchi², Frédéric Pichelin¹

Journal of Renewable Materials, Vol.14, No.3, 2026, DOI:10.32604/jrm.2025.02025-0173 - 25 March 2026

Abstract The construction sector is facing significant challenges in transitioning to a defossilised system. While wood-based products have considerable potential, reliance on adhesives derived from fossil fuels poses significant sustainability concerns. Tannin-based adhesives present a compelling bio-based alternative, offering advantageous bonding properties with the potential to reduce toxicity, minimise fossil resource use, and enhance end-of-life scenarios. Despite extensive research demonstrating the technical potential of tannin-based adhesives, industrial adoption remains limited—partly due to the paucity of studies addressing their environmental impacts. The present study investigates the use of tannin-based adhesives in the production of interior-grade plywood, employing… More >