Automated violence monitoring system for real-time fistfight detection using deep learning-based temporal action localization by Baolong Qi, Baoyuan Wu, Bailing Sun

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Harnessing Artificial Intelligence and Machine Learning for Identifying Quantitative Trait Loci (QTL) Associated with Seed Quality Traits in Crops by My Abdelmajid Kassem

“…This review presents an integrated overview of AI/ML applications in QTL mapping and seed trait prediction, highlighting key methodologies such as LASSO regression, Random Forest, Gradient Boosting, ElasticNet, and deep learning techniques including convolutional neural networks (CNNs) and graph neural networks (GNNs). …”
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Hierarchical Sensing Framework for Polymer Degradation Monitoring: A Physics-Constrained Reinforcement Learning Framework for Programmable Material Discovery by Xiaoyu Hu, Xiuyuan Zhao, Wenhe Liu

“…Our method combines three key innovations: (1) a dual-channel sensing architecture that fuses spectroscopic signatures from Graph Isomorphism Networks with temporal degradation patterns captured by transformer-based models, enabling comprehensive molecular state detection across multiple scales; (2) a physics-constrained policy network that ensures sensor measurements adhere to thermodynamic principles while optimizing the exploration of degradation pathways; and (3) a hierarchical signal processing system that balances multiple sensing modalities through adaptive weighting schemes learned from experimental feedback. …”
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Design of a TSR-based project learning strategy for biochemistry undergraduate teaching and research labs: a case study by Camille R. Reaux, Shelby A. Meche, Jordan M. Grider, Soundharya Dhanabal, Tarikul I. Milon, Feng Chen, Wu Xu

“…The uniqueness of the method benefits students’ learning of big data and computational methods. Specifically, students learn (i) how to search proteins of interest from the PDB archive, (ii) basic supercomputer skills, (iii) how to prepare datasets, (iv) how to perform protein structure and sequence analyses, (v) how to interpret the results, visualize protein structures and make graphs. …”
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Integration of Information and Communication Technologies (ICT) on Pupils’ Learning of English in Selected Schools in Buyanja Town Council, Rukungiri District. by Arinaitwe, Frankline

“…Data from quantitative and qualitative research was then analysed and presented in form of tables and graphs. Conclusions, recommendations suggestions for further research studies were finally made.…”
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A computational framework for IoT security integrating deep learning-based semantic algorithms for real-time threat response by Ripal Ranpara, Shobhit K. Patel, Om Prakash Kumar, Fahad Ahmed Al-Zahrani

“…This research paper presents a hybrid deep learning and semantic reasoning framework that enhances threat intelligence and autonomous response. …”
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Predictive value of machine learning for the progression of gestational diabetes mellitus to type 2 diabetes: a systematic review and meta-analysis by Meng Zhao, Zhixin Yao, Yan Zhang, Lidan Ma, Wenquan Pang, Shuyin Ma, Yijun Xu, Lili Wei

“…The risk of bias was assessed through the prediction model risk of bias assessment tool and a graph was drawn accordingly. The meta-analysis was performed using Stata15.0. …”
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A Trust Based Anomaly Detection Scheme Using a Hybrid Deep Learning Model for IoT Routing Attacks Mitigation by Khatereh Ahmadi, Reza Javidan

“…Several security solutions have been proposed to address routing attacks detection in RPL–based IoT, most of which are based on machine learning techniques, intrusion detection systems and trust-based approaches. …”
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Convolutional transform learning based fusion framework for scale invariant long term target detection and tracking in unmanned aerial vehicles by Fatma S. Alrayes, Nazir Ahmad, Asma Alshuhail, Menwa Alshammeri, Ali Alqazzaz, Hassan Alkhiri, Jehad Saad Alqurni, Yahia Said

“…Therefore, this study develops a novel long-term target detection and tracking model for unmanned aerial vehicles using a deep fusion-based convolutional transform learning (LTTDT–UAVDFCTL) model. The LTTDT–UAVDFCTL model presents a new model to improve the robustness and accuracy of target tracking and detection in scale-variant environments. …”
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Investigation of comparative machine learning models in effluent dephenolization process onto H3PO4-anchored corn cob by Chijioke Elijah Onu, Joseph Tagbo Nwabanne, Ositadimma Chamberline Iheanocho, Paschal Enyinnaya Ohale, Chiamaka Peace Onu, Marcel Ikenna Ejimofor, Suraj Kumar Bhagat, Christian O. Asadu, Christopher C. Obi, Chidiogo Ezekwem

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Application of Artificial Intelligence Large Language Model in Power Equipment Operation and Maintenance by Xiaohong Chen, Wenrun Fu, Chaoming Liu, Zehong Liu, Junpeng Li, Zhiliang Hu, Dongbin Hu

“…To address these challenges, this study combines knowledge graph retrieval-augmented generation, multimodal alignment, fine-tuning and continuous learning, and other big model application optimization techniques to construct an AI-LLM power equipment maintenance system. …”
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Collective variables of neural networks: empirical time evolution and scaling laws by Samuel Tovey, Sven Krippendorf , Michael Spannowsky, Konstantin Nikolaou, Christian Holm

“…This work presents a novel framework for understanding learning dynamics and scaling relations in neural networks. …”
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Flood Classification and Improved Loss Function by Combining Deep Learning Models to Improve Water Level Prediction in a Small Mountain Watershed by Rukai Wang, Ximin Yuan, Fuchang Tian, Minghui Liu, Xiujie Wang, Xiaobin Li, Minrui Wu

“…ABSTRACT Floods are major natural disasters that present considerable challenges to socioeconomic and ecological systems. …”
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Hybrid high-performance computing enhanced machine learning framework for nano-thermal conductivity in MWNT-oil-based solar cooking systems by Nischal P. Mungle, Sumit Kumar, Dnyaneshwar M. Mate, Sham H. Mankar, Tejas R. Patil, Hirkani Padwad, Niteen T. Kakade, Nilesh Shelke, Haytham F. Isleem, Vikrant S. Vairagade

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Design of an intelligent AI-based multi-layer optimization framework for grid-tied solar PV-fuel cell hybrid energy systems by Prashant Nene, Dolly Thankachan

“…FL-DEO stands for Federated Learning-Based Distributed Optimization. GNNHSCO is Graph Neural Networks Power Router. …”
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Peculiarities of the pedagogical situation at the training of bachelors on the direction 08.03.01 «Construction» on the example of discipline of specialization by Nelli I. Taraseeva

“…For the efficient operation of the system “lecturer” – “student” it is necessary to have highly qualified lecturers and modern material and technical equipment for the educational process.The goal of this work is to perform the analysis of the current teaching situation; on the example of the profile discipline to develop a learning algorithm and its implementation in accordance with the laws of the didactics of Bachelors in 08.01.03 construction direction “Highways”.Materials and methods: the methods of research consist in studying the basics of Didactics (learning theory) with positions of interdisciplinary areas of knowledge, such as general theory and graph sys tems, familiarizing with the functioning laws of the learning process, pedagogical technologies of domestic and foreign researchers. …”
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Aspect-Based Sentiment Analysis: A Comprehensive Review and Open Research Challenges by Waqas Ahmad, Hikmat Ullah Khan, Fawaz Khaled Alarfaj, Mohammed Alreshoodi

“…In this review study, we first focus on two diverse research tasks, aspect extraction, and aspect sentiment analysis and then we present a comprehensive review of existing studies in various classifications such as lexicon-based, graph data, topic models, machine learning, and deep learning. …”
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Integrating artificial Intelligence-Based metaheuristic optimization with Machine learning to enhance Nanomaterial-Containing latent heat thermal energy storage systems by Ali Basem, Hanaa Kadhim Abdulaali, As’ad Alizadeh, Pradeep Kumar Singh, Komal Parashar, Ali E. Anqi, Husam Rajab, Pancham Cajla, H. Maleki

“…Progress in artificial intelligence and machine learning has significantly improved the capability to accurately predict the properties of nano-enhanced phase change materials (NePCMs). …”
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Dual-stream detection and segmentation framework for vision based unmanned ground vehicle pothole perception on unstructured roads by Chenyuan He, He Yang, Zhouyu Zhang, Hai Wang, Yingfeng Cai, Long Chen, Can Zhong, Yiqun Zhang

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iDILI-MT: identifying drug-induced liver injury compounds with a multi-head Transformer by Wanrong Zheng, Fobao Lai

“…Evaluated on a curated set of 1,919 small-molecule compounds, iDILI-MT outperformed traditional machine-learning classifiers and state-of-the-art graph neural networks, achieving a mean area under the receiver-operating-characteristic curve (AUC-ROC) of 0.8499, area under the precision-recall curve (AUC-PR) of 0.8905, and F1 score of 0.8173 across ten trials. …”
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