Advanced Deep Learning Based Predictive Maintenance of DC Microgrids: Correlative Analysis by M. Y. Arafat, M. J. Hossain, Li Li

“…This study can contribute to the emerging technology for predictive maintenance of MGs and provide significant insights into the modeling and performance of RNN architectures for improving fault detection in MG systems. …”
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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

“…Future research will focus on further improving cross-platform interoperability to expand DT applications in infrastructure management.…”
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A comprehensive review of remote sensing techniques for monitoring Ulva prolifera green tides by Xiaomeng Geng, Xiaomeng Geng, Xiaomeng Geng, Huiru Li, Huiru Li, Le Wang, Weidong Sun, Yize Li

“…Additionally, it identifies the limitations and unresolved challenges in current approaches, such as constraints on data resolution, algorithmic biases, and environmental variability. The potential for integrating multi-source remote sensing data with marine environmental parameters and deep learning techniques is discussed, emphasizing their roles in improving the accuracy and reliability of monitoring and predicting Ulva prolifera green tides. …”
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Optimization of sports injury treatment through artificial intelligence: Methods for effective prevention, diagnosis and rehabilitation by Kimi Milić Marko, Sinanović Šćepan, Jestrović Vladimir

“…The study results indicate substantial improvements in treatment efficiency, reduced recovery time, and increased diagnostic accuracy, directly facilitating a faster return to sporting activities. …”
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Optimizing Natural Image Quality Evaluators for Quality Measurement in CT Scan Denoising by Rudy Gunawan, Yvonne Tran, Jinchuan Zheng, Hung Nguyen, Rifai Chai

“…This evidence indicates a possibility of using the NIQE as a new option in evaluating denoised quality to find improvement or compare the quality between CNN models.…”
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Homework, Households, and Hurdles: The Unexpected Drivers of Student Graduation Perceptions by Daniel Alhassan, Zahra Fatah, Priscilla Mansah Codjoe, Caroline Bena Kuno, Dorcas Ofori-Boateng

“…Among the tested models, random forest provided the best classification performance. …”
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From Code to Life: The AI‐Driven Revolution in Genome Editing by Zhidong Li, Wasi Ullah Khan, Genxiang Bai, Chao Dong, Jungang Wang, Youpeng Zhang, Chong Wang, Hongbin Zhang, Wenyi Wang, Ming Luo, Fei Chen

“…AI‐driven models, such as deep learning‐based predictors and protein language models, enable more accurate sgRNA design, novel Cas protein discovery, and enhanced gene regulatory network analysis. …”
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Recent Advances in Multi-Agent Reinforcement Learning for Intelligent Automation and Control of Water Environment Systems by Lei Jia, Yan Pei

“…It further analyzes the challenges and solutions for improving global cooperative efficiency under practical constraints such as limited resources, system heterogeneity, and unstable communication. …”
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ELEQTRONeX: A GPU-accelerated exascale framework for non-equilibrium quantum transport in nanomaterials by Saurabh S. Sawant, François Léonard, Zhi Yao, Andrew Nonaka

“…By customizing algorithms for GPU multithreading, we achieve significant improvement in computational time, and excellent scaling on up to 512 GPUs and billions of spatial grid cells. …”
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Fruit Detection Methods Based on Deep Learning in Agricultural Planting: A Systematic Literature Review by Xinyu Gong, Qiufeng Wu

“…Based on a comprehensive analysis of existing research, we classify deep learning-based fruit detection models into four application scenarios: few-shot detection (addressing limited data availability and high annotation costs), complex scene detection (resolving issues arising from object occlusion, overlapping, and variable illumination), small-target detection (improving performance on low-resolution and densely clustered objects), and real-time detection (designing lightweight algorithms for faster inference). …”
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Artificial Intelligence in medicine: Potential and Application Possibilities - Comprehensive literature review by Michał Kotowicz, Magdalena Bieniak-Pentchev, Maria Koczkodaj

“…In psychiatry, generative AI models support mental health through personalized interventions and symptom tracking, while in ophthalmology, multimodal learning improves early detection of eye diseases. …”
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Visual recognition of honeybee behavior patterns at the hive entrance. by Tomyslav Sledevič, Artūras Serackis, Dalius Matuzevičius, Darius Plonis, Gabriela Vdoviak

“…This work lays the groundwork for future automated monitoring systems aimed at improving hive health and productivity.…”
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Electricity nowcasting and forecasting efficiency in blockchain-integrated energy trading platforms by Ameni Boumaiza

“…Our methodology integrates real-time nowcasting algorithms and machine learning-based forecasting models to optimize electricity distribution, battery storage utilization, and cost efficiency within the marketplace. …”
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Transforming Farming: A Review of AI-Powered UAV Technologies in Precision Agriculture by Juhi Agrawal, Muhammad Yeasir Arafat

“…In this paper, we present a comprehensive overview of the integration of multispectral, hyperspectral, and thermal sensors mounted on drones with AI-driven algorithms to transform modern farms. Such technologies support crop health monitoring in real time, resource management, and automated decision making, thus improving productivity with considerably reduced resource consumption. …”
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High resolution building facade dataset for facade elements parsingMendeley Data by Shuchang Xu, Fan Wu, Junjie Cheng, Wenzhen Yang

“…This paper introduces a high-resolution building facade dataset—hznu_facade, designed to provide rich data support for urban modeling, digital twin city construction, and facade analysis tasks. …”
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Recent advances in AI-based toxicity prediction for drug discovery by Hyundo Lee, Jisan Kim, Ji-Woon Kim, Yoonji Lee, Yoonji Lee

“…Ongoing advances in databases, algorithms, and computational power have further expanded AI’s role in pharmaceutical research. …”
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Fighting Evaluation Inflation: Concentrated Datasets for Grammatical Error Correction Task by Vladimir Starchenko, Darya Kharlamova, Elizaveta Klykova, Anastasia Shavrina, Aleksey Starchenko, Olga Vinogradova, Olga Lyashevskaya

“…Conclusion: The lower scores registered on concentrated datasets confirm that they provide a way for future improvement of GEC models. The dataset can be used for further studies focusing on distant-context-sensitive GEC. …”
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Clustering and classification of early knee osteoarthritis using machine-learning analysis of step-up and down test kinematics in recreational table tennis players by Ui-jae Hwang, Kyu Sung Chung, Sung-min Ha

“…Louvain clustering identified four distinct kinematic profiles with varying proportions of EOA (ranging from 41.2% to 70.7%). Supervised learning models achieved high performance in classifying EOA status, with Random Forest, gradient boosting, and decision tree algorithms achieving 100% classification accuracy (AUC = 1.000) on the test dataset. …”
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Advancing named entity recognition in interprofessional collaboration and education by Rui Zhang, Yifeng Shan, MengZhe Zhen

“…ASOS complements this by employing real-time feedback loops, conflict resolution algorithms, and resource reallocation strategies to iteratively refine contributions and interactions.ResultsExperimental evaluations demonstrate significant improvements in entity recognition accuracy, conflict mitigation, and overall collaboration efficiency compared to baseline methods.DiscussionThis study advances the theoretical and practical applications of NER in IPC, ensuring scalability and adaptability to complex, real-world scenarios.…”
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Prediction and optimization of hardness in AlSi10Mg alloy produced by laser powder bed fusion using statistical and machine learning approaches by İnayet Burcu Toprak

“…This study highlights the importance of integrating Machine Learning and statistical analysis methods for the effective modeling and optimization of LPBF processes. The findings contribute significantly to the literature and serve as a valuable reference for future research aimed at improving LPBF process efficiency and performance.…”
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