Decentralized Coordination of Temperature Control in Multiarea Premises by Maria Yukhymchuk, Volodymyr Dubovoi, Viacheslav Kovtun

“…The proposed coordination algorithms make it possible to optimize the operating modes of the system automatically when its structure and/or settings are changed. …”
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The role of artificial intelligence in enhancing disaster preparedness and trauma care by Mohamad Sorani

“…Furthermore, ethical considerations such as data privacy, algorithmic bias, and equitable access are crucial to ensuring that AI-driven solutions are implemented responsibly and inclusively.This review also explores future directions for AI, including the development of sophisticated predictive models, autonomous systems for high-risk tasks, immersive training programs utilizing virtual and augmented reality, and global collaboration aimed at standardizing AI tools and practices. …”
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Robust EEG Characteristics for Predicting Neurological Recovery from Coma After Cardiac Arrest by Meitong Zhu, Meng Xu, Meng Gao, Rui Yu, Guangyu Bin

“…By integrating machine learning (ML) algorithms, such as Gradient Boosting Models and Support Vector Machines, with SHAP-based feature visualization, robust screening methods were applied to ensure the reliability of predictions. …”
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Towards representation learning of radar altimeter waveforms for sea ice surface classification by L. Happ, L. Happ, S. Patil, S. Hendricks, R. Fellegara, L. Kaleschke, A. Gerndt, A. Gerndt

“…Moreover, machine learning models for sea ice classification often depend on supervised training, which is vulnerable to uncertainties in labeled data, especially in polar regions. …”
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Workload Forecasting Methods in Cloud Environments: An Overview by Samah Aziz, Manar Kashmoola

“…We explore more sophisticated approaches like algorithms for deep learning (DL) and machine learning (ML) in addition to more conventional approaches like analysis of time series and models of regression. …”
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Intelligent gear decision method for vehicle automatic transmission system based on data mining by Yong Wang, Jianfeng Zeng, Pengfei Du, Huachao Xu

“…Subsequently, dynamic programming algorithms are employed to optimize intelligent gear decisions. …”
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Cervical cancer demystified: exploring epidemiology, risk factors, screening, treatment modalities, preventive measures, and the role of artificial intelligence by N. Mohammad, M. Khan, M. Maqsood, A. H. K. Naseeb

“…AI-driven technologies, including deep learning algorithms and machine learning models, are emerging as valuable tools in cervical cancer detection, risk assessment, and treatment planning. …”
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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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Forecasting motion trajectories of elbow and knee joints during infant crawling based on long–short-term memory (LSTM) networks by Jieyi Mo, Qiliang Xiong, Ying Chen, Yuan Liu, Xiaoying Wu, Nong Xiao, Wensheng Hou

“…It experimentally explores how different input and output time-frames affect prediction accuracy and sets the stage for future research focused on optimizing models and developing effective control strategies to improve assistive crawling devices.…”
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Tumor tissue-of-origin classification using miRNA-mRNA-lncRNA interaction networks and machine learning methods by Ankita Lawarde, Ankita Lawarde, Masuma Khatun, Prakash Lingasamy, Prakash Lingasamy, Andres Salumets, Andres Salumets, Andres Salumets, Vijayachitra Modhukur, Vijayachitra Modhukur

“…Using transcriptomic profiles from 14 cancer types in The Cancer Genome Atlas (TCGA), we constructed co-expression networks and applied multiple feature selection techniques including recursive feature elimination (RFE), random forest (RF), Boruta, and linear discriminant analysis (LDA) to identify a minimal yet informative subset of miRNA features. Ensemble ML algorithms were trained and validated with stratified five-fold cross-validation for robust performance assessment across class distributions.ResultsOur models achieved an overall 99% classification accuracy, distinguishing 14 cancer types with high robustness and generalizability. …”
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Postmarketing safety evaluation of pemetrexed using FAERS and JADER databases by Luo Lv, Xiangyang Wu, Yubo Ren, Yuli Guo, Haixiong Wang, Xiaofang Li

“…Continuous pharmacovigilance is essential to optimize its clinical use and improve patient safety.…”
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Label semantics and image features aware remote sensing sample retrieval from multi-source datasets for AI-enabled remote sensing monitoring by XingTao Ren, XingTao Ren, Yan Ma, YiXin Zhou, YiXin Zhou

“…Future work may focus on further optimizing the retrieval algorithms and expanding the range of supported data platforms to enhance the robustness and scalability of the system.…”
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