Enhancing e-learning through AI: advanced techniques for optimizing student performance by Rund Mahafdah, Seifeddine Bouallegue, Ridha Bouallegue

“…AI algorithms, known for their cognitive ability and capacity to learn, adapt, and make decisions, are employed to analyze and forecast student performance, thereby improving educational quality and outcomes. …”
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Subtypes detection of papillary thyroid cancer from methylation assay via Deep Neural Network by Andrea Colacino, Andrea Soricelli, Michele Ceccarelli, Ornella Affinito, Monica Franzese

“…When applied to the thyroid independent dataset, the proposed Neural Net architecture successfully discriminates tumor versus normal samples (AUC = 0.91 +/- 0.05) and follicular versus classical PTC subtypes (AUC = 0.80 +/- 0.05), outperforming traditional machine learning algorithms. Conclusions: In conclusion, the study highlights the effectiveness of CNNs in the methylation based classification of thyroid tumors and their subtypes, demonstrating its ability to capture subtle epigenetic differences with minimal preprocessing.This versatility makes the model adaptable for classifying other tumor types. …”
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A Data-Driven Model for the Energy and Economic Assessment of Building Renovations by Giuseppe Piras, Francesco Muzi, Zahra Ziran

“…This research aims to identify the main factors influencing the energy consumption of buildings by analyzing a large database of building characteristics using machine learning algorithms. Based on the parameters that the analysis shows to have the greatest impact, the average cost of energy retrofitting measures will be used to elaborate a cost–benefit analysis model and the economic payback time for each measure, individually or in combination. …”
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Application of a Hybrid Model for Data Analysis in Hydroponic Systems by Kuanysh Bakirov, Jamalbek Tussupov, Akhmet Tussupov, Ibraheem Shayea, Aruzhan Shoman

“…Maintaining precise microclimate control is essential, as even minor deviations can significantly affect the yield and product quality, but traditional monitoring methods fail to adapt promptly to changing conditions. To overcome this limitation, an automated monitoring system integrating machine learning methods XGBoost 3.0.0, principal component analysis (PCA), and fuzzy logic was developed. …”
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Advances in impact force identification: A comprehensive review of techniques and mathematical innovations by Hamed Kalhori, Shabnam Tashakori, Ben Halkon, Mehrisadat Makki Alamdari, Bing Li, Morteza Saberi

“…Notable emerging directions include hybrid physics-informed machine learning frameworks, domain adaptation and transfer learning to alleviate data dependency, and incremental learning paradigms suited for real-time deployment. …”
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A Resting ECG Screening Protocol Improved with Artificial Intelligence for the Early Detection of Cardiovascular Risk in Athletes by Luiza Camelia Nechita, Dana Tutunaru, Aurel Nechita, Andreea Elena Voipan, Daniel Voipan, Anca Mirela Ionescu, Teodora Simina Drăgoiu, Carmina Liana Musat

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Evaluating a Procedural Content Orchestrator Gameplay Data and Classifying User Profiles by Leonardo Tórtoro Pereira, T. Yuji Teoi, Claudio Fabiano Motta Toledo

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K-LM: Knowledge Augmenting in Language Models Within the Scholarly Domain by Vivek Kumar, Diego Reforgiato Recupero, Rim Helaoui, Daniele Riboni

“…The use of superior algorithms and complex architectures in language models have successfully imparted human-like abilities to machines for specific tasks. …”
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AI-powered approaches for enhancing remote sensing-based water contamination detection in ecological systems by Li Yang, Zhang Ziwen, Xinhao Lin, Junmiao Hei, Yixiao Wang, Ang Zhang

“…Recent advancements in artificial intelligence (AI) offer promising solutions to enhance water contamination detection, particularly by leveraging machine learning algorithms and sensor networks for continuous monitoring.MethodsThis paper presents a novel AI-powered approach for improving water contamination detection, which incorporates real-time data processing and predictive modeling to identify contamination events and optimize response strategies. …”
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Toward Efficient Hierarchical Federated Learning Design Over Multi-Hop Wireless Communications Networks by Tu Viet Nguyen, Nhan Duc Ho, Hieu Thien Hoang, Cuong Danh Do, Kok-Seng Wong

“…Federated learning (FL) has recently received considerable attention and is becoming a popular machine learning (ML) framework that allows clients to train machine learning models in a decentralized fashion without sharing any private dataset. …”
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A novel integrated TDLAVOA-XGBoost model for tool wear prediction in lathe and milling operations by Zhongyuan Che, Chong Peng, Chi Wang, Jikun Wang

“…This study proposes an integrated model for tool wear prediction in CNC machining that combines improved algorithms with XGBoost. …”
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AI generations: from AI 1.0 to AI 4.0 by Jiahao Wu, Hengxu You, Jing Du

“…Building on these developments, the proposed AI 4.0 puts forward the bold vision of self-directed AI capable of setting its own goals, orchestrating complex training regimens, and possibly exhibiting elements of machine consciousness. This paper traces the historical foundations of AI across roughly 70 years, mapping how changes in technological bottlenecks from algorithmic innovation to high-performance computing to specialized data have stimulated each generational leap. …”
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Bridge Digital Twin for Practical Bridge Operation and Maintenance by Integrating GIS and BIM by Yan Gao, Guanyu Xiong, Ziyu Hu, Chengzhang Chai, Haijiang Li

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Advanced Leaf Classification Using Multi-Layer Perceptron for Smart Crop Management by Sara Mumtaz, Mohammed Alshehri, Yahya AlQahtani, Abdulmonem Alshahrani, Bayan Alabdullah, Haifa F. Alhasson, Hui Liu

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From Neural Networks to Emotional Networks: A Systematic Review of EEG-Based Emotion Recognition in Cognitive Neuroscience and Real-World Applications by Evgenia Gkintoni, Anthimos Aroutzidis, Hera Antonopoulou, Constantinos Halkiopoulos

“…Discussion: These challenges include developing adaptive, real-time processing algorithms, integrating EEG with other inputs like facial expressions and physiological sensors, and a need for standardized protocols for emotion elicitation and classification. …”
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Multi-Trait Phenotypic Analysis and Biomass Estimation of Lettuce Cultivars Based on SFM-MVS by Tiezhu Li, Yixue Zhang, Lian Hu, Yiqiu Zhao, Zongyao Cai, Tingting Yu, Xiaodong Zhang

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Revolutionizing Water Quality Monitoring with Artificial Intelligence: A Systematic Review by Mahmoud Saleh Al-Khafaji, Layth Abdulameer, Muthanna M. A. AL-Shammari, Najah M. L. Al Maimuri, Anmar Dulaimi, Dhiya Al‑Jumeily

“…This systematic review addresses these gaps by evaluating the transformative role of artificial intelligence (AI) in revolutionizing monitoring practices through two novel mechanisms: (1) enhanced multivariate data fidelity via Internet of Things (IoT)-sensor networks and satellite remote sensing, and (2) predictive modeling precision using machine learning (ML) algorithms. By synthesizing 1,032 studies (2011–2025), we demonstrate that AI-driven systems achieve 94% accuracy in prediction and reduce field sampling costs by 60% through Landsat 8 satellite integration. …”
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A multi‐objective feature optimization strategy for developing high‐entropy alloys with optimal strength and ductility by Yan Zhang, Shewei Xin, Wei Zhou, Xiao Wang, Yangyang Xu, Yanjing Su

“…This multi‐objective feature optimization strategy is adaptable to other material systems, offering a pathway to improve machine learning performance and accelerate materials discovery.…”
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Inheritance and protection of intangible cultural heritage in drama category based on AI human–computer interaction and digital technology by Jingjing Ren

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An Optimal Internet of Things-Driven Intelligent Decision-Making System for Real-Time Fishpond Water Quality Monitoring and Species Survival by Saima Kanwal, Muhammad Abdullah, Sahil Kumar, Saqib Arshad, Muhammad Shahroz, Dawei Zhang, Dileep Kumar

“…Smart fish farming faces critical challenges in achieving comprehensive automation, real-time decision-making, and adaptability to diverse environmental conditions and multi-species aquaculture. …”
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