Advancing cardiovascular care through actionable AI innovation by Giuseppe Biondi-Zoccai, Arjun Mahajan, Dylan Powell, Mariangela Peruzzi, Roberto Carnevale, Giacomo Frati

“…Indeed, offline RL refers to a class of ML algorithms that learn optimal decision-making policies from a fixed dataset of previously collected experiences—such as electronic health records or registries—without the need for active, real-time interaction with the clinical environment. …”
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Enhancing healthcare AI stability with edge computing and machine learning for extubation prediction by Kuo-Yang Huang, Ying-Lin Hsu, Che-Liang Chung, Huang-Chi Chen, Ming-Hwarng Horng, Ching-Hsiung Lin, Ching-Sen Liu, Jia-Lang Xu

“…Given the pivotal role of ventilators, accurately predicting extubation outcomes is essential to optimize patient care. This study presents an edge computing-based framework that incorporates machine learning algorithms to predict ventilator extubation success using real-time data collected directly from ventilators. …”
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Integrated Method of Future Capacity and RUL Prediction for Lithium‐Ion Batteries Based on CEEMD‐Transformer‐LSTM Model by Wangyang Hu, Chaolong Zhang, Laijin Luo, Shanhe Jiang

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ATKB-PID: an adaptive control method for micro tension under complex hot rolling conditions by Xinkai Xu, Xiangrong Song, Zheng Qi

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Computed tomography-based radiomic features combined with clinical parameters for predicting post-infectious bronchiolitis obliterans in children with adenovirus pneumonia: a retro... by Li Zhang, Ling He, Guangli Zhang, Xiaoyin Tian, Haoru Wang, Fang Wang, Xin Chen, Yinglan Zheng, Man Li, Yang Li, Zhengxiu Luo

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An accurate model to predict drilling fluid density at wellbore conditions by Mohammad Ali Ahmadi, Seyed Reza Shadizadeh, Kalpit Shah, Alireza Bahadori

“…Based on the statistical criteria the PSO-ANN model has reasonable performance in comparison with other intelligent methods used in this study. Therefore, the PSO-ANN model can be employed reliably to estimate the drilling fluid density (g/cm3) at HPHT condition. …”
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Machine learning of automatic hierarchical multi-label classification method for identifying metal failure mechanisms by Ruitong Han, Chang-Bo Liu, Wanting Sun, Shuai Yu, Haoran Zheng, Lin Deng

“…It is anticipated that the optimization and extension of HFFNet-2d are conducive in diverse material systems and application scenarios to accelerate the intelligent process of material development and failure analysis, ultimately supporting the design of reliable and high-performance engineering materials.…”
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Non-intrusive Load Identification Method Based on the Online Self-organizing Incremental Neural Network—Non-intrusive load identification method based on the online self-organizing... by Zhengwei HU, Zhihong WANG, Ruixin CHANG, Zhiyuan XIE, Wangbin CAO

“…With the development of intelligent electronic technology, the accurate identification of electrical load usage will have extensive user demands in the field of smart electricity. …”
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Research on Book Recommendation Integrating Book Category Features and User Attribute Information by Yan Chen, Eric Blancaflor, Mideth Abisado

“…The research verifies the necessity of attribute information to capture users’ personalized needs, and provides theoretical and practical reference for the optimization of intelligent book recommendation system.…”
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Computer Vision-Based Robotic System Framework for the Real-Time Identification and Grasping of Oysters by Hao-Ran Qu, Jue Wang, Lang-Rui Lei, Wen-Hao Su

“…This study addresses the labor-intensive and safety-critical challenges of manual oyster processing by innovating an advanced robotic intelligent sorting system. Central to this system is the integration of a high-resolution vision module, dual operational controllers, and the collaborative AUBO-i3 robot, all harmonized through a sophisticated Robot Operating System (ROS) framework. …”
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Review on Key Technologies for Autonomous Navigation in Field Agricultural Machinery by Hongxuan Wu, Xinzhong Wang, Xuegeng Chen, Yafei Zhang, Yaowen Zhang

“…Autonomous navigation technology plays a crucial role in advancing smart agriculture by enhancing operational efficiency, optimizing resource utilization, and reducing labor dependency. …”
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Enhancing action recognition in educational settings using AI-driven information systems for public health monitoring by Changchun Lu, Han Ruijuan

“…IntroductionThe integration of Artificial Intelligence (AI) into educational environments is revolutionizing action recognition, offering a transformative opportunity to enhance public health monitoring. …”
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Efficient Resource Allocation and UAV Deployment in STAR-RIS and UAV-Relay Assisted Public Safety Networks for Video Transmission by Naveed Khan, Ayaz Ahmad, Abdulmalik Alwarafy, Munam Ali Shah, Abderrahmane Lakas, Muhammad Moazam Azeem

“…This optimization is subject to several constraints. The formulated optimization problem is non-convex, posing a challenge in solving it. …”
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Emerging Trends in the Integrating Remote Sensing and Machine Learning for Groundwater Resources Management: A Bibliometric Study by Abolfazl Akbarpour, Moein Tosan, Raziyeh Shamshirgaran

“…The integration of multi-source remote sensing data (including data from new-generation satellites and aerial platforms) with advanced artificial intelligence algorithms (such as deep neural networks, physics-informed models, and reinforcement learning methods) is expected to become a central focus for leading researchers in hydrology, water resources, and machine learning engineering. …”
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Battery swapping scheduling for electric vehicles: a non-cooperative game approach by Yu Zhang, Tao Han, Wei He, Jianhua Xia, Lichao Cui, Zuofu Ma, Shiwei Liu

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Experimental observation of the critical conditions and establishment of bifurcation set equation for chip flow angle catastrophe in transverse turning by Longjun Luo, Liangshan Xiong, Shaonan Zhang, Baoyi Zhu, Hongliang Yang

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YOLOv8 forestry pest recognition based on improved re-parametric convolution by Lina Zhang, Shengpeng Yu, Bo Yang, Shuai Zhao, Ziyi Huang, Zhiyin Yang, Helong Yu

“…This advancement holds positive implications for agroforestry ecology and supports the broader goals of intelligent and sustainable development. Future work could explore further optimization techniques and the application of this model to other domains requiring lightweight and accurate detection systems.…”
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A Study of Mixed Non-Motorized Traffic Flow Characteristics and Capacity Based on Multi-Source Video Data by Guobin Gu, Xin Sun, Benxiao Lou, Xiang Wang, Bingheng Yang, Jianqiu Chen, Dan Zhou, Shiqian Huang, Qingwei Hu, Chun Bao

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A Near-Infrared Imaging System for Robotic Venous Blood Collection by Zhikang Yang, Mao Shi, Yassine Gharbi, Qian Qi, Huan Shen, Gaojian Tao, Wu Xu, Wenqi Lyu, Aihong Ji

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Outlier Traffic Flow Detection and Pattern Analysis Under Unplanned Disruptions: A Low-Rank Robust Decomposition Model by Zhipeng Duan

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