Caiyun Li^1,#, Xiaowen Liu^1,#, Binhui Tang^1,*, Tingting Lu², Daibo Xiao³, Li Chen³

CMC-Computers, Materials & Continua, Vol.89, No.1, 2026, DOI:10.32604/cmc.2026.086522 - 13 August 2026

Abstract Unmanned aerial vehicle (UAV) communication links in low-altitude operations support mission control, status feedback, and data transmission. Abnormal communication states may affect mission continuity and risk response. However, conventional anomaly detection usually determines only whether a communication anomaly exists, making it difficult to support risk-state assessment and alert-threshold decision-making. To address this problem, this paper proposes Risk Stratification and Task-cost-aware Decision via Knowledge Distillation (RSTD-KD), a task-cost-aware UAV communication risk warning approach that integrates risk stratification, probability calibration, and threshold decision-making. RSTD-KD aggregates fine-grained communication records into window-level behavior samples, constructs low-, medium-, and high-risk… More >

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 >

Yasemin Onal^*

CMC-Computers, Materials & Continua, Vol.88, No.3, 2026, DOI:10.32604/cmc.2026.082593 - 23 July 2026

Abstract Photovoltaic (PV) power generation exhibits considerable sensitivity to both weather variability and fluctuations in solar irradiance. Consequently, precise forecasting of PV power is crucial for ensuring grid reliability, load balancing, and the effective functioning of energy markets within a grid-connected solar plant. Conventional forecasting methodologies frequently prove inadequate in accurately capturing the nonlinear and intricate temporal patterns present within PV datasets. To address these shortcomings, this research presents a hybrid short-term PV power forecasting model. This model integrates Neighborhood Component Analysis (NCA) for dimensionality reduction with a Convolutional Neural Network (CNN)-Long Short-Term Memory (LSTM) framework.… More >

HyeSun Chang, Sangjun Lee^*

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.082718 - 15 June 2026

Abstract Accurate identification of heart murmurs from auscultation recordings is essential for early cardiovascular screening and diagnosis. While deep learning offers strong potential for automated heart murmur classification, existing models often exhibit overconfident, incorrect predictions and limited generalization due to dataset bias and class imbalance. To address these challenges, this study proposes a two-stage confidence-regulated learning framework that jointly optimizes feature representation and decision reliability. Rather than focusing solely on improving classification performance, this work emphasizes enhancing prediction reliability through confidence-aware decision-making. The proposed framework integrates supervised contrastive learning (SCL) to strengthen the discriminative structure of… More >

Leonidas Theodorakopoulos, Alexandra Theodoropoulou^*

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.082270 - 15 June 2026

Abstract Auditable autonomy is becoming a practical requirement for deploying large language model (LLM) agents in operational workflows where recommendations can trigger consequential actions. Many autonomy claims remain hard to evaluate because studies emphasize task completion or fluent explanations while underreporting tool privileges, verification conditions, rollback feasibility, and trace completeness. This review develops a decision-making–centered framework that treats autonomy as an auditable engineering property. It introduces a three-plane big data foundation: an evidence plane with provenance and freshness constraints; a decision-trace plane that records retrieval identifiers, tool invocations, intermediate checks, and policy evaluations; and an outcomes More >

Federico Minelli^1,*, Diana D’Agostino¹, Vennapusa Jagadeeswara Reddy², Panagiotis Michailidis^3,4

Energy Engineering, Vol.123, No.6, 2026, DOI:10.32604/ee.2026.074048 - 27 May 2026

Abstract This study investigates the problem of prioritizing rooftop renewable energy (RE) system configurations for a multi-family residential building in Mediterranean climate. The analysis focuses on fixed-tilt photovoltaics (PV), single-axis and dual-axis tracking PV, and small vertical-axis wind turbines (VAWT), each assessed with and without lithium-ion storage. A co-simulation framework is used, coupling EnergyPlus building-HVAC system simulation with PV and wind generation modeling and rule-based battery dispatch to evaluate hourly demand–supply interactions. Three decision criteria are considered for each alternative: total system cost, annual building electric energy demand reduction, and net avoided life-cycle emissions. Stakeholder preferences… More > Graphic Abstract

Linda Naidoo^*, Mariette Coetzee

Journal of Psychology in Africa, Vol.36, No.2, pp. 161-170, 2026, DOI:10.32604/jpa.2026.073305 - 29 April 2026

Abstract This study tested the internal reliability and validity of a 28-item Employee Empowerment scale within a higher education context. A sample of 452 university employees (N = 452) from a South African higher education institution, comprising academics (46%), administrative staff (33%), and professional and managerial staff (21%), participated in the study. The participants were required to complete an employee empowerment questionnaire. The exploratory factor analysis and confirmatory factor analysis identified a three-construct measurement model for employee empowerment: management support, autonomy and decision-making, and access to information and resources. The results revealed that the research instrument More >

Muhammad Mukhtar^1,2, Farizah Yunus¹, Ahmad Shukri Mohd Noor^1,*, Zulfiqar Ali³, Muhammad Junaid^4,*, Mehmood Ahmed⁴

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.076246 - 09 April 2026

Abstract The increasing adoption of 5G cellular networks has introduced significant challenges for network operators. The main challenge lies in the management of seamless handoff (HO), which occurs owing to the rapid expansion of equipment, data, and network complexity. To address this challenge, a model named optimal HO management deep learning neural network (OHMDLNN) is proposed. The model is trained on network activity data, and it uses KPIs (key performance indicators) and system-level parameters to make HO decisions. As demonstrated in the article, OHMDLNN is successful in analyzing the effect and interdependence of KPIs from both… 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 >

Xue Zhang¹, Jie Chen^2,*, Zhihui Zhang³, Dewei Zhang³, Yuejiao Ming³, Xinde Zhang³

Energy Engineering, Vol.123, No.1, 2026, DOI:10.32604/ee.2025.069487 - 27 December 2025

Abstract The integration of wind power and natural gas for hydrogen production forms a Green and Blue Hydrogen Integrated Energy System (GBH-IES), which is a promising cogeneration approach characterized by multi-energy complementarity, flexible dispatch, and efficient utilization. This system can meet the demands for electricity, heat, and hydrogen while demonstrating significant performance in energy supply, energy conversion, economy, and environment (4E). To evaluate the GBH-IES system effectively, a comprehensive performance evaluation index system was constructed from the 4E dimensions. The fuzzy DEMATEL method was used to quantify the causal relationships between indicators, establishing a scientific input-output… More > Graphic Abstract