A Review of Applicable Technologies, Routing Protocols, Requirements, and Architecture for Disaster Area Networks by Mohammad M. Alsayyed, Selvakumar Manickam, Eka Ratri Noor Wulandari, I. Dewa Made Widia, Shankar Karuppayah

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Artificial Intelligence for DC Arc Fault Detection in Photovoltaic Systems: A Comprehensive Review by Kamal Chandra Paul, Disnebio Waldmann, Chen Chen, Yao Wang, Tiefu Zhao

“…Key challenges are discussed, along with future directions such as hybrid models, transfer learning, and implementation in resource-constrained edge devices. …”
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Lightweight Vision Transformer for Frame-Level Ergonomic Posture Classification in Industrial Workflows by Luca Cruciata, Salvatore Contino, Marianna Ciccarelli, Roberto Pirrone, Leonardo Mostarda, Alessandra Papetti, Marco Piangerelli

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Denoising of Heart Sounds Using Lightweight FCNs and Spectrograms With and Without Context by Declan Duggan, Andriy Temko, Volodymyr Sarana, Andreea Factor, Emanuel Popovici

“…This work is a step towards a real-time deep learning-based denoiser for use with a digital stethoscope.…”
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Health Modeling — An Innovative Educational Program for the General Medicine Specialty by M. M. Litvinova, M. S. Khamidulina, T. M. Litvinova, Yu. A. Lutokhina, E. N. Dudnik, N. V. Kireeva, K. V. Ivashkin, B. A. Volel

“…Aim: to present the principles and distinctive features of the innovative educational program “Health Modeling” for the General Medicine specialty, aimed at refocusing medical training toward proactive health preservation and disease prevention.Key points. …”
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Wearable IoT (w-IoT) artificial intelligence (AI) solution for sustainable smart-healthcare by Gurdeep Singh

“…Smart technologies, specifically wearables are cutting edge innovation of design science with an emerging Artificial Intelligence (AI) capability for sustainable healthcare. …”
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Wheat Powdery Mildew Severity Classification Based on an Improved ResNet34 Model by Meilin Li, Yufeng Guo, Wei Guo, Hongbo Qiao, Lei Shi, Yang Liu, Guang Zheng, Hui Zhang, Qiang Wang

“…Among the most prevalent global wheat diseases, powdery mildew—caused by fungal infection—poses a significant threat to crop yield and quality, making early and accurate detection crucial for effective management. In this study, we present QY-SE-MResNet34, a deep learning-based classification model that builds upon ResNet34 to perform multi-class classification of wheat leaf images and assess powdery mildew severity at the single-leaf level. …”
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Ai-powered digital twin in the industrial IoT by Željko Bolbotinović, Saša D. Milić, Žarko Janda, Dragan Vukmirović

“…According to DT needs and hierarchical data processing, as well as edge, fog, and cloud computing, the paper presents state-of-the-art ML models and algorithms. …”
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GPT-4off: On-Board Traversability Probability Estimation for Off-Road Driving via GPT Knowledge Distillation by Nahyeong Kim, Seongkyu Choi, Sun Choi, Yejun Lee, Youngjae Cheong, Jhonghyun An

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Editorial Preview by Su-Cheng Haw

“…Additionally, this edition presents a captivating collection of 7 papers curated by our Thematic Editor, Dr. …”
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WirelessNet: An Efficient Radio Access Network Model Based on Heterogeneous Graph Neural Networks by Jose Perdomo, M. A. Gutierrez-Estevez, Chan Zhou, Jose F. Monserrat

“…WirelessNet represents network nodes and the underlying wireless phenomena between them as nodes and edges of different type in a heterogeneous graph. …”
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From 6G to <i>SeaX-G</i>: Integrated 6G TN/NTN for AI-Assisted Maritime Communications—Architecture, Enablers, and Optimization Problems by Anastasios Giannopoulos, Panagiotis Gkonis, Alexandros Kalafatelis, Nikolaos Nomikos, Sotirios Spantideas, Panagiotis Trakadas, Theodoros Syriopoulos

“…Finally, we propose a set of resource optimization scenarios, including dynamic spectrum allocation, energy-efficient communications and edge offloading in MCNs, and discuss how AI/ML and learning-based methods can offer scalable, adaptive solutions. …”
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Navigating the evolution: a comprehensive review of sustainable finance in mergers and acquisitions [version 1; peer review: 2 approved] by Kishan Jee, Debdas Rakshit, Sabyasachi Mondal, Satish Chandra Tiwari

“…Conclusions and implications of key findings Machine learning and big data analytics may help scholars get a more thorough grasp of the historical and present significance of sustainability in M&A. …”
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UAV Hyperspectral Remote Sensing Image Classification: A Systematic Review by Zhen Zhang, Lehao Huang, Qingwang Wang, Linhuan Jiang, Yemao Qi, Shunyuan Wang, Tao Shen, Bo-Hui Tang, Yanfeng Gu

“…This article provides an in-depth and systematic review of UAV HSI classification techniques, systematically examining the evolution from traditional machine learning approaches, such as sparse coding, compressed sensing, and kernel methods, to cutting-edge deep learning frameworks, including convolutional neural networks, Transformer models, recurrent neural networks, graph convolutional networks, generative adversarial networks, and hybrid models. …”
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Novel algorithm for multifocus image fusion: integration of convolutional neural network and partial differential equation by Gargi J Trivedi, Rajesh Sanghvi

“…This paper presents a novel method for Multifocus image fusion that combines anisotropic diffusion PDE filtering and convolutional neural network (CNN) feature extraction. …”
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APT Adversarial Defence Mechanism for Industrial IoT Enabled Cyber-Physical System by Safdar Hussain Javed, Maaz Bin Ahmad, Muhammad Asif, Waseem Akram, Khalid Mahmood, Ashok Kumar Das, Sachin Shetty

“…This approach utilizes masked self-attentional layers to address the limitations of prior Deep Learning (DL) methods that rely on convolutions. Two datasets, the DAPT2020 malware, and Edge I-IoT datasets are used to evaluate the approach, and it attains the highest detection accuracy of 96.97&#x0025; and 95.97&#x0025;, with prediction time of 20.56 seconds and 21.65 seconds, respectively. …”
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Quantum-Inspired Multi-Scale Object Detection in UAV Imagery: Advancing Ultra-Small Object Accuracy and Efficiency for Real-Time Applications by Muhammad Muzammul, Muhammad Assam, Ayman Qahmash

“…Ultra-small object detection in UAV imagery presents significant challenges due to scale variation, environmental complexity, and computational constraints. …”
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An IoT Framework for the Detection of Lung Cancer Using a Decision Support System by Ahamd Habboush, Bassam Elzaghmouri, Binod Kumar Pattanayak, Pravat Kumar Rautaray

“…Cutting-edge machine learning models were leveraged, including Support Vector Machines (SVM), Naïve Bayes Multinomial (NBM), KNN, PART (Partial Rule-based Tree), and Random Forest (RF), to improve the precision of our forecasts. …”
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Explainable artificial intelligence for sustainable urban water systems engineering by Shofia Saghya Infant, Sundaram Vickram, A Saravanan, C M Mathan Muthu, Devarajan Yuarajan

“…Explainable Artificial Intelligence (XAI) has potential for revolutionary improvements in operational efficiency, resilience, and decision-making in the engineering of sustainable urban water systems. Presenting cutting-edge approaches in XAI (such as SHAP (Shapley Additive Explanations), LIME (Local Interpretable Model-agnostic Explanations), and counterfactual analysis), this review defines the evolution of explainability approaches specifically for hydrological modelling, demand prediction, and leak detection. …”
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Deep LBLS: Accelerated Sky Region Segmentation Using Hybrid Deep CNNs and Lattice Boltzmann Level-Set Model by Fatema A. Albalooshi, M. R. Qader, Yasser Ismail, Wael Elmedany, Hesham Al-Ammal, Muttukrishnan Rajarajan, Vijayan K. Asari

“…However, sky region segmentation poses significant challenges due to complex backgrounds, varying lighting conditions, and the absence of clear edges and textures. In this paper, we present a new hybrid fast segmentation technique for the sky region that learns from object components to achieve rapid and effective segmentation while preserving precise details of the sky region. …”
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