Erdinç Uslan^1,*, Emin Ulugergerli²

Revue Internationale de Géomatique, Vol.35, pp. 31-51, 2026, DOI:10.32604/rig.2026.075081 - 05 February 2026

Abstract Climate classification systems are essential tools for analyzing regional climatic behavior, assessing long-term aridity patterns, and evaluating the impacts of climate change on water resources and ecosystem resilience. This study introduces a new Climate Classification Method based on uniform and unitless variables, referred to as the U2 Climate Classification (U2CC). The proposed U2 Index was designed to overcome structural limitations of the classical De Martonne (1942) and Erinç (1949) indices, which rely on raw precipitation–temperature ratios and are sensitive to extreme values, particularly subzero temperatures. The U2 methodology consisted of two key steps: (i) normalization… More >

Hussain H. Al-Kayiem^1,*, Safaa M. Ali², Sundus S. Al-Azawiey³, Raed A. Jessam³

Energy Engineering, Vol.123, No.2, 2026, DOI:10.32604/ee.2025.073303 - 27 January 2026

Abstract Gas Turbines are among the most important energy systems for aviation and thermal-based power generation. The performance of gas turbine intakes with S-shaped diffusers is vulnerable to flow separation, reversal flow, and pressure distortion, mainly in aggressive S-shaped diffusers. Several methods, including vortex generators and energy promoters, have been proposed and investigated both experimentally and numerically. This paper compiles a review of experimental investigations that have been performed and reported to mitigate flow separation and restore system performance. The operational principles, classifications, design geometries, and performance parameters of S-shaped diffusers are presented to facilitate the… More > Graphic Abstract

Tao Zhang^1,*, Hailun Wang¹, Tianyue Wang¹, Tian Tian²

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072696 - 12 January 2026

Abstract The critical components of gas turbines suffer from prolonged exposure to factors such as thermal oxidation, mechanical wear, and airflow disturbances during prolonged operation. These conditions can lead to a series of issues, including mechanical faults, air path malfunctions, and combustion irregularities. Traditional model-based approaches face inherent limitations due to their inability to handle nonlinear problems, natural factors, measurement uncertainties, fault coupling, and implementation challenges. The development of artificial intelligence algorithms has provided an effective solution to these issues, sparking extensive research into data-driven fault diagnosis methodologies. The review mechanism involved searching IEEE Xplore, ScienceDirect,… 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

Shaojie Min¹, Yaxiao Luo¹, Kebing Liu¹, Qingyuan Gong², Yang Chen^1,*

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-23, 2026, DOI:10.32604/cmc.2025.073175 - 09 December 2025

Abstract User identity linkage (UIL) across online social networks seeks to match accounts belonging to the same real-world individual. This cross-platform mapping enables accurate user modeling but also raises serious privacy risks. Over the past decade, the research community has developed a wide range of UIL methods, from structural embeddings to multimodal fusion architectures. However, corresponding adversarial and defensive approaches remain fragmented and comparatively understudied. In this survey, we provide a unified overview of both mapping and anti-mapping methods for UIL. We categorize representative mapping models by learning paradigm and data modality, and systematically compare them… More >

Abdullah Alourani¹, Mehtab Alam^2,*, Ashraf Ali³, Ihtiram Raza Khan⁴, Chandra Kanta Samal²

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-32, 2026, DOI:10.32604/cmc.2025.070161 - 10 November 2025

Abstract The evolution of cities into digitally managed environments requires computational systems that can operate in real time while supporting predictive and adaptive infrastructure management. Earlier approaches have often advanced one dimension—such as Internet of Things (IoT)-based data acquisition, Artificial Intelligence (AI)-driven analytics, or digital twin visualization—without fully integrating these strands into a single operational loop. As a result, many existing solutions encounter bottlenecks in responsiveness, interoperability, and scalability, while also leaving concerns about data privacy unresolved. This research introduces a hybrid AI–IoT–Digital Twin framework that combines continuous sensing, distributed intelligence, and simulation-based decision support. The… More >

Ameer Hamza, Robertas Damaševičius^*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-41, 2026, DOI:10.32604/cmc.2025.069721 - 10 November 2025

Abstract This systematic review aims to comprehensively examine and compare deep learning methods for brain tumor segmentation and classification using MRI and other imaging modalities, focusing on recent trends from 2022 to 2025. The primary objective is to evaluate methodological advancements, model performance, dataset usage, and existing challenges in developing clinically robust AI systems. We included peer-reviewed journal articles and high-impact conference papers published between 2022 and 2025, written in English, that proposed or evaluated deep learning methods for brain tumor segmentation and/or classification. Excluded were non-open-access publications, books, and non-English articles. A structured search was… More >

Ravita Chahar, Ashutosh Kumar Dubey^*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-65, 2026, DOI:10.32604/cmc.2025.066990 - 10 November 2025

Abstract Objective: The increasing global prevalence of mental health disorders highlights the urgent need for the development of innovative diagnostic methods. Conditions such as anxiety, depression, stress, bipolar disorder (BD), and autism spectrum disorder (ASD) frequently arise from the complex interplay of demographic, biological, and socioeconomic factors, resulting in aggravated symptoms. This review investigates machine intelligence approaches for the early detection and prediction of mental health conditions. Methods: The preferred reporting items for systematic reviews and meta-analyses (PRISMA) framework was employed to conduct a systematic review and analysis covering the period 2018 to 2025. The potential… More >

Tianyu Zhao¹, Xiaoli Zhao², Kenny S. L. Cheah^3,*, Ye Zhang³

International Journal of Mental Health Promotion, Vol.27, No.12, pp. 2023-2038, 2025, DOI:10.32604/ijmhp.2025.071322 - 31 December 2025

Abstract Background: Despite access to university counseling services, many students underutilize them due to cultural stigma, language barriers, and perceived irrelevance. As a result, ChatGPT has emerged as an informal, always-available support system. This study investigates how international PhD students in Malaysia navigate loneliness, mental well-being, and social disconnection through interactions with Generative AI (mainly ChatGPT. Methods: Using a mixed-methods design, the study surveyed 155 international doctoral students and analyzed quantitative responses across four dimensions: loneliness, well-being (WHO-5), perceived social support, and AI-facilitated emotional support. Additionally, open-ended responses were examined using Latent Dirichlet Allocation (LDA) to identify… More >

Yang Liu¹, Biao Chen¹, Xin Liu², Chenxi Luo², Shihui Xiao^2,*

Frontiers in Heat and Mass Transfer, Vol.23, No.6, pp. 2127-2146, 2025, DOI:10.32604/fhmt.2025.070973 - 31 December 2025

Abstract This study evaluated corn kernel drying performance and quality changes using hot air drying (HAD) and infrared drying (ID) across temperatures ranging from 55°C to 80°C. Optimal drying parameters were determined by using the entropy weight method, with drying time, specific energy consumption, damage rate, fatty acids, starch, polyphenols, and flavonoids as indicators. Results demonstrated that ID significantly outperformed HAD, achieving drying times up to 20% shorter and reducing specific energy consumption and kernel damage by up to 79.3% and 66.7%, respectively, while also better preserving quality attributes. Both methods exhibited drying profiles characterized by More >