A lightweight knowledge graph-driven question answering system for field-based mineral resource survey by Mingguo Wang, Chengbin Wang, Jianguo Chen, Bo Wang, Wei Wang, Xiaogang Ma, Jiangtao Ren, Zichen Li, Yicai Ye, Jiakai Zhang, Yue Wang

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A Survey on Machine Learning Approaches for Personalized Coaching with Human Digital Twins by Harald H. Rietdijk, Patricia Conde-Cespedes, Talko B. Dijkhuis, Hilbrand K. E. Oldenhuis, Maria Trocan

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A Novel Long Short-Term Memory Seq2Seq Model with Chaos-Based Optimization and Attention Mechanism for Enhanced Dam Deformation Prediction by Lei Wang, Jiajun Wang, Dawei Tong, Xiaoling Wang

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Revolutionizing Supply Chain Management With AI: A Path to Efficiency and Sustainability by Kassem Danach, Ali El Dirani, Hassan Rkein

“…Through an in-depth analysis of various AI techniques—such as machine learning, predictive analytics, and optimization algorithms—this study offers novel insights into their applicability in solving complex supply chain problems like demand forecasting, inventory management, and logistics optimization. …”
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Medical Imaging Foundation Models: Paradigm Innovation in Precision Oncology by LIU Zaiyi, ZHAO Zhihe, SHI Zhenwei

“…Based on the research background of artificial intelligence (AI) large-scale models, this article systematically reviews the current research status of medical imaging large-scale models from three key dimensions: the construction of large-scale medical imaging datasets, optimization of large-scale model algorithms, and computational resource requirements. …”
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Algorithms for online fault tolerance server consolidation by Boyu Li, Bin Wu, Meng Shen, Hao Peng, Weisheng Li, Hong Zhang, Jie Gan, Zhihong Tian, Guangquan Xu

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Improving the accuracy and interpretability of neural networks for wind power forecasting by Wenlong Liao, Birgitte Bak-Jensen, Zhe Yang, Gonghao Zhang, Jiannong Fang, Fernando Porté-Agel

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Toward aitiopoietic cognition: bridging the evolutionary divide between biological and machine-learned causal systems by Tomas Veloz

“…Through analyzing convergence pathways including evolutionary algorithms, material intelligence, homeostatic regulation, and multi-scale integration, we propose a research program aimed at bridging this evolutionary divide. …”
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Multi-User Task Offloading Strategy in RIS-Aided Multi-AP Mobile Edge Computing Networks by Wen Zhou, Ling Miao, Dan Deng, Min Hua, Dan Xiang, Chunguo Li

“…In this paper, we consider a reconfigurable intelligent surface (RIS)-aided edge computing-enabled multiuser networks with multiple access points (APs) and investigate the computation offloading strategy of user equipments (UEs). …”
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Image-Based Classification of Freshwater Fish Species to Support Feed Recommendation Using Random Forest by Hindayati Mustafidah, Suwarsito Suwarsito, Rahmat Setiawan, Abdul Karim

“…The findings indicate that the integration of Random Forest with multi-domain image features offers an effective, affordable, and practical solution to support the digital transformation of small and medium scale aquaculture systems through intelligent species recognition and feed guidance…”
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Novel GSIP: GAN-based sperm-inspired pixel imputation for robust energy image reconstruction by Gamal M. Mahmoud, Wael Said, Magdy M. Fadel, Mostafa Elbaz

“…The intelligent sperm motility heuristic navigates the image’s pixel space, identifying the most influential neighboring pixels for accurate imputation. …”
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Machine Learning Techniques Applied to COVID-19 Prediction: A Systematic Literature Review by Yunyun Cheng, Rong Cheng, Ting Xu, Xiuhui Tan, Yanping Bai

“…By establishing a multi-level classification framework that included traditional statistical models (such as ARIMA), ML models (such as SVM), deep learning (DL) models (such as CNN, LSTM), ensemble learning methods (such as AdaBoost), and hybrid models (such as the fusion architecture of intelligent optimization algorithms and neural networks), it revealed that the hybrid modelling strategy effectively improved the prediction accuracy of the model through feature combination optimization and model cascade integration. …”
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Optimizing Artificial Neural Networks Using Mountain Gazelle Optimizer by Muhammed Abdulhamid Karabiyik, Bahaeddin Turkoglu, Tunc Asuroglu

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AI-driven energy management system based on hesitant bipolar complex fuzzy Hamacher power aggregation operators and their applications in MADM by Walid Emam, Hafiz Muhammad Waqas, Tahir Mahmood, Ubaid ur Rehman, Dragan Pamucar

“…Abstract Artificial Intelligence (AI) based energy management systems utilize sophisticated AI algorithms to improve and control the consumption of energy in various sectors, such as power utilities, industrial systems, and smart buildings. …”
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AIPerf: Automated Machine Learning as an AI-HPC Benchmark by Zhixiang Ren, Yongheng Liu, Tianhui Shi, Lei Xie, Yue Zhou, Jidong Zhai, Youhui Zhang, Yunquan Zhang, Wenguang Chen

“…The plethora of complex Artificial Intelligence (AI) algorithms and available High-Performance Computing (HPC) power stimulates the expeditious development of AI components with heterogeneous designs. …”
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Quality monitoring of hybrid welding processes: A comprehensive review by Solomon Habtamu Tessema, Dariusz Bismor

“…Artificial intelligence/Machine learning enables real-time analysis of welding parameters and defect detection, while digital twins offer virtual representations of physical welding processes, facilitating predictive maintenance and optimization. …”
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Challenges of Water Resources Governance under the Impact of Climate Change and Water Transfer by Atabak Jaffari, Ahmad Sharafati, Amin reza Neshat, Seyed abbas Hosseini

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Enhancing Privacy in IoT-Enabled Digital Infrastructure: Evaluating Federated Learning for Intrusion and Fraud Detection by Amogh Deshmukh, Peplluis Esteva de la Rosa, Raul Villamarin Rodriguez, Sandeep Dasari

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From Molecules to Medicines: The Role of AI-Driven Drug Discovery Against Alzheimer’s Disease and Other Neurological Disorders by Mashael A. Alghamdi

“…The discovery of effective therapeutics against Alzheimer’s disease (AD) and other neurological disorders remains a significant challenge. Artificial intelligence (AI) tools are of considerable interest in modern drug discovery processes and, by exploiting machine learning (ML) algorithms and deep learning (DL) tools, as well as data analytics, can expedite the identification of new drug targets and potential lead molecules. …”
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Supply Chain Management Using Evolutionary Algorithms by Skitsko Volodymyr I., Voinikov Mykola Yu.

“…Evolutionary algorithms are part of a broader field in artificial intelligence that is evolutionary computing. …”
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