Toward Greener Matrix Operations by Lossless Compressed Formats by Francesco Tosoni, Philip Bille, Valerio Brunacci, Alessio de de Angelis, Paolo Ferragina, Giovanni Manzini

“…Moreover, our experiments reveal that while data parallelism can improve execution speed and energy efficiency, optimizing both simultaneously poses interesting challenges. …”
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Preclinical Cognitive Markers of Alzheimer Disease and Early Diagnosis Using Virtual Reality and Artificial Intelligence: Literature Review by María de la Paz Scribano Parada, Fátima González Palau, Sonia Valladares Rodríguez, Mariano Rincon, Maria José Rico Barroeta, Marta García Rodriguez, Yolanda Bueno Aguado, Ana Herrero Blanco, Estela Díaz-López, Margarita Bachiller Mayoral, Raquel Losada Durán

“…Executive functions precede memory decline, while processing speed is a significant correlate. …”
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Harnessing AI forward and backward chaining with telemetry data for enhanced diagnostics and prognostics of smart devices by Muhammad Shoaib Farooq, Rizwan Pervez Mir, Atif Alvi, Kilian Tutusaus, Eduardo Garcia Villena, Fadwa Alrowais, Hanen Karamti, Imran Ashraf

“…This study proposes a novel AI-driven framework that integrates forward chaining and backward chaining algorithms to analyze telemetry data from IoT devices. …”
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Investigating the Use of Electrooculography Sensors to Detect Stress During Working Activities by Alessandra Papetti, Marianna Ciccarelli, Andrea Manni, Andrea Caroppo, Gabriele Rescio

“…To tackle work-related stress in the evolving landscape of Industry 5.0, organizations need to prioritize employee well-being through a comprehensive strategy. While electrocardiograms (ECGs) and electrodermal activity (EDA) are widely adopted physiological measures for monitoring work-related stress, electrooculography (EOG) remains underexplored in this context. …”
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Engineering Synthetic Microbial Communities: Diversity and Applications in Soil for Plant Resilience by Arneeb Tariq, Shengzhi Guo, Fozia Farhat, Xihui Shen

“…Artificial intelligence-driven models can predict complex microbial interactions, while machine learning algorithms can analyze vast datasets to identify key microbial taxa and their functions. …”
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DRBO—A Regional Scale Simulator Calibration Framework Based on Day-to-Day Dynamic Routing and Bayesian Optimization by Xuan Jiang, Yibo Zhao, Chonghe Jiang, Junzhe Cao, Alexander Skabardonis, Alex Kurzhanskiy, Raja Sengupta

“…The prior dynamic imitates how vehicles propagate as time flows while the latter one reveals how vehicles choose their route according to their own information. …”
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An AI-Based Framework for Characterizing the Atmospheric Fate of Air Pollutants Within Diverse Environmental Settings by Nataša Radić, Mirjana Perišić, Gordana Jovanović, Timea Bezdan, Svetlana Stanišić, Nenad Stanić, Andreja Stojić

“…This study introduces a novel artificial intelligence (AI) modeling framework that combines machine learning algorithms optimized through metaheuristics with explainable AI to capture complex interactions among pollutant concentrations, meteorological data, and socio-economic indicators. …”
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Spatial Simulation and Optimization of Cropping Structure Under Climate and Land Use Change Conditions Considering Synergistic Economic Benefits and Carbon Reduction in Crop Growth... by Mo Li, Haiyan Li, Zhaoqiang Zhou, Yingshan Chen, Yijia Wang, Tianxiao Li, Qiang Fu

“…This approach is based on climate change conditions and it accurately simulates future land use changes and crop growth processes, establishes a carbon emission intensity optimization model, and generates a spatial planting structure optimization and regulation scheme based on intelligent optimization algorithms under changing scenarios. The results of the model application show that the planting structure option in the future scenario can increase economic benefit by up to 14.8% compared to the current scenario while simultaneously reducing total greenhouse gas emissions by 6.77%. …”
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Digital twin-driven method for determining wind force coefficients of a bridge deck section by Hao-Yang Li, You-Lin Xu, Hai-Li Liao, Lin Huang, Qi Wang

“…The sectional model of the bridge deck tested in a wind tunnel is taken as a physical model, while its virtual model is established using CFD simulation. …”
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Multi-Attitude Hybrid Network for Remote Sensing Hyperspectral Images Super-Resolution by Chi Chen, Yunhan Sun, Xueyan Hu, Ning Zhang, Hao Feng, Zheng Li, Yongcheng Wang

“…Extensive experiments demonstrate that our method achieves optimal reconstruction results compared to other state-of-the-art algorithms while effectively reducing the computational complexity.…”
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A Novel Self-Attention-Enabled Weighted Ensemble-Based Convolutional Neural Network Framework for Distributed Denial of Service Attack Classification by Shravan Venkatraman, S. Kanthimathi, K. S. Jayasankar, T. Pranay Jiljith, R. Jashwanth

“…Each model extracts features at multiple scales, while self-attention mechanisms enhance feature integration and relevance. …”
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Spatiotemporal Trends and Zoning Geospatial Assessment in China’s Offshore Mariculture (2018–2022) by Zewen Mo, Yulin Chen, Xuan Zhang, Zhipan Wang, Qingling Zhang

“…This study utilizes high-resolution remote sensing data (2017–2023) and advanced ConvNeXt V2 algorithms to quantitatively analyze the spatiotemporal dynamics of offshore mariculture and explore its spatial distribution in relation to marine functional zoning policies. …”
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Applications of fault-tolerant control system in the design of wind turbine generation systems: A comprehensive review and future prospects by Arslan Ahmed Amin, Muhammad Irfan, Turki Alsuwian, Saifur Rahman, Ansa Mubarak, Saba Waseem

“…Wind Turbine Generation Systems (WTGS) are widely acknowledged as a key pillar of the renewable power generation sector, while availability and efficiency are among the main issues, particularly those related to faults within systems that reduce performance and increase maintenance costs. …”
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Designing an Intelligent Scoring System for Crediting Manufacturers and Importers of Goods in Industry 4.0 by Mohsin Ali, Abdul Razaque, Joon Yoo, Uskenbayeva Raissa Kabievna, Aiman Moldagulova, Satybaldiyeva Ryskhan, Kalpeyeva Zhuldyz, Aizhan Kassymova

“…The decentralized and unchangeable ledger of the Blockchain technology significantly reduces the risk of fraud while maintaining real-time transaction recording. …”
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A GNSS–Cellular Network Hybridization Strategy for Robust Positioning by María Jesús Jiménez-Martínez, Mónica Zabala Haro, Ángel Martín Furonés, Ana Anquela Julián

“…The results show that, while hybridization enhances positioning, the 4G-only solution often performs in terms of vertical accuracy. …”
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MobNas ensembled model for breast cancer prediction by Tariq Shahzad, Sheikh Muhammad Saqib, Tehseen Mazhar, Muhammad Iqbal, Ahmad Almogren, Yazeed Yasin Ghadi, Mamoon M. Saeed, Habib Hamam

“…Abstract Breast cancer poses a real and immense threat to humankind, thus a need to develop a way of diagnosing this devastating disease early, accurately, and in a simpler manner. Thus, while substantial progress has been made in developing machine learning algorithms, deep learning, and transfer learning models, issues with diagnostic accuracy and minimizing diagnostic errors persist. …”
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High-accuracy combustible gas cloud imaging system using YOLO-plume classification network by Jiani Zhou, Yang Liu, Yong Zhang, Haotian Hu, Zenan Leng, Feng Sun, Chen Chen

“…Due to the irregular shape and ambiguous boundary of the gas, traditional motion detection algorithms are difficult to adapt to the changes in the gas movement state with the environment, resulting in an increased probability of false alarms. …”
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Scalable Semantic Adaptive Communication for Task Requirements in WSNs by Hong Yang, Xiaoqing Zhu, Jia Yang, Ji Li, Linbo Qing, Xiaohai He, Pingyu Wang

“…The experimental results show that the proposed SSAC is more robust than traditional and other semantic communication algorithms in image classification tasks, and achieves scalable compression rates without sacrificing classification performance, while improving the bandwidth utilization of the communication system.…”
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Predictive modelling employing machine learning, convolutional neural networks (CNNs), and smartphone RGB images for non-destructive biomass estimation of pearl millet (Pennisetum... by Faten Dhawi, Abdul Ghafoor, Norah Almousa, Sakinah Ali, Sara Alqanbar

“…XGBoost achieved the highest accuracy (R2 = 0.98, RMSE = 0.26) with a comprehensive feature set, while CNN-based models also showed strong predictive ability. …”
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Deep Reinforcement Learning of Mobile Robot Navigation in Dynamic Environment: A Review by Yingjie Zhu, Wan Zuha Wan Hasan, Hafiz Rashidi Harun Ramli, Nor Mohd Haziq Norsahperi, Muhamad Saufi Mohd Kassim, Yiduo Yao

“…Through a comparative analysis of classical DRL algorithms, this study highlights their advantages and limitations in handling real-time navigation tasks under dynamic environmental conditions. …”
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