Computationally Efficient Artifact Suppression for Optical Coherence Tomography Angiography by Wenxin Zhang, Jun Pan, Shiqi Tang, Ning Liu

“…Current artifact suppression methods often require complex algorithms and extensive computation, limiting their practicality. …”
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Merging Multiple System Perspectives: The Key to Effective Inland Shipping Emission-Reduction Policy Design by Solange van der Werff, Fedor Baart, Mark van Koningsveld

“…In this study, we use a new scheme called “event table” to transform big data on vessel trajectories (AIS data) combined with energy-estimating algorithms into shipping-emission outcomes that can be evaluated from multiple perspectives. …”
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Optimization of Adaptive Observation Strategies for Multi-AUVs in Complex Marine Environments Using Deep Reinforcement Learning by Jingjing Zhang, Weidong Zhou, Xiong Deng, Shuo Yang, Chunwang Yang, Hongliang Yin

“…To overcome these challenges, we integrate a Gated Recurrent Unit (GRU) into the D3QN, improving state-space prediction and accelerating reward convergence. …”
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BoneCLIP-XGBoost: A Multimodal Approach for Bone Fracture Diagnosis by Zhihao Su, Yuhuai Zhou, Jianqun Zhou, Hanhua Cao, Huanping Zhang

“…The integration of visual and textual data in medical diagnostics holds significant potential for improving the accuracy and reliability of clinical decision-making. …”
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Entity and Event Recognition Method for Power Grid Fault Handling Plan Based on UIE Framework by Junbo PI, Shixiong QI, Wenduo SUN, Xiansi LOU, Jiandong WO, Yue ZHANG, Tao JIANG, Lianfei SHAN

“…Through verification by the plans of different regional power grid dispatch and control centers, the proposed method has higher entity and event recognition accuracy for fault handling plans than other algorithms. It can accurately identify the fault handling strategies and recovery strategies in the plan, and provide support for the improvement of the regional power grid elasticity in the case of fault.…”
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Does hospital medical staff maintain hospital disaster resilience? by Georgieva Mariya Georgieva, Kostadinov Rostislav Stefanov, Semerdjieva-Filipova Mariya Anastasova

“…Therefore, it is necessary to introduce a specific training program and exercise once a year, which should have a beneficial effect on increasing the preparedness of the medical staff for disasters and improving the operational resilience of the hospital.…”
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A ROS-Based Online System for 3D Gaussian Splatting Optimization: Flexible Frontend Integration and Real-Time Refinement by Li’an Wang, Jian Xu, Xuan An, Yujie Ji, Yuxuan Wu, Zhaoyuan Ma

“…The experimental data shows that compared with the traditional COLMAP-3DGS process, this system reduces the initialization time by 90% and achieves an average PSNR improvement of 1.9 dB on the TUM-RGBD, Tanks and Temples, and KITTI datasets.…”
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AppleLeafNet: a lightweight and efficient deep learning framework for diagnosing apple leaf diseases by Muhammad Umair Ali, Majdi Khalid, Majed Farrash, Hassan Fareed M. Lahza, Amad Zafar, Seong-Han Kim

“…Timely and precise detection is crucial for managing the spread of diseases, thereby improving the production and quality of apples. However, the development of algorithms for analyzing complex leaf images remains a significant challenge. …”
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Machine learning prediction and interpretability analysis of high-risk chest pain: a study from the MIMIC-IV database by Hongyi Chen, Haiyang Song, Hongyu Huang, Xiaojun Fang, Huang Chen, Qingqing Yang, Junyu Zhang, Wenjun Ding, Zheng Gong, Jun Ke

“…Rapid and accurate diagnosis is pivotal for improving patient survival rates.MethodsWe developed a machine learning prediction model using the MIMIC-IV database (n = 14,716 patients, including 1,302 high-risk cases). …”
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Hybrid Automata-Based Control Framework for Real-Time Optimization in Space-Based Solar Power Transmission by Patil Ankita, Ranjan Mritunjay, Deore Kalyani, Sonje Pranjal, Patil Kiran, Patil Rutuja

“…While usual machine learning algorithms may predict the production of energy, they cannot respond sufficiently in real time to alter according to dynamic environmental conditions. …”
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Integrating Remote Sensing and AI for precision Monitoring of Soil and Vegetation Contamination by M. Spiralski, A. Miszczak, G. Siebielec, Ż. Piasecka, R. Trojnacki, P. Kwaśnik, J. Kotlarz, K. A. Kubiak-Siwinska, M. Kacprzak, S. Marciniak, K. A. Rotchimmel, K. P. Beben, J. Szymanski

“…The future of the study will be focused on the multi-temporal analyses, improving prediction accuracy and dataset and environmental risk mapping. …”
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Optimizing solar energy utilization in facilities using machine learning-based scheduling techniques: A case study by Hussam J. Khasawneh, Waseem M. Al-Khatib, Zaid A. Ghazal, Ahmad M. Al-Hadi, Zaid M. Arabiyat, Osama Habahbeh

“…This study introduces an approach to improving the utilization of solar energy in facilities by integrating advanced machine learning (ML) techniques into solar power scheduling. …”
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Reinforcement Learning for Autonomous Process Control in Industry 4.0: Advantages and Challenges by Nuria Nievas, Adela Pagès-Bernaus, Francesc Bonada, Lluís Echeverria, Xavier Domingo

“…The analysis focuses on application types, problem modeling, training algorithms, validation methods, and deployment statuses. …”
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Smart grid stability prediction using Adaptive Aquila Optimizer and ensemble stacked BiLSTM by Safwan Mahmood Al-Selwi, Mohd Fadzil Hassan, Said Jadid Abdulkadir, Mohammed Gamal Ragab, Alawi Alqushaibi, Ebrahim Hamid Sumiea

“…Results: Multiple rounds of empirical experiments using different sets of optimizers and configurations, supported by the visualization capabilities of TensorBoard, demonstrate significant improvements in the performance of the AAO-BiLSTM model. …”
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Strategies and Challenges for Unmanned Aerial Vehicle-Based Continuous Inspection and Predictive Maintenance of Solar Modules by Ghulam E. Mustafa Abro, Amjad Ali, Sufyan Ali Memon, Tayab Din Memon, Faheem Khan

“…This study emphasizes the significance of early defect identification on solar farm efficiency and delineates a strategy for improving the reliability and cost-effectiveness of photovoltaic module inspections via UAV technology.…”
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A Hybrid Automata-Driven Machine Learning Framework for Real-Time Energy Optimization in Smart Buildings by Rikame Rajashri, Ranjan Mritunjay Kr., Jadhav Monali, Wankhede Shrushti, Bankar Sakshi, Bachhav Pranjal

“…The intended hybrid solution effectively improves forecasting efficiency, enhances energy efficiency, and facilitates smart scheduling of energy-driven systems. …”
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Instruments for assessing healthcare professionals’ knowledge, attitudes and practices regarding deprescribing: a scoping review protocol by Luciane Cruz Lopes, Jardel Corrêa de Oliveira, Luis Phillipe Nagem Lopes, Mariana Del Grossi Moura, Ana Carolina Figueiredo Modesto, Laís Lessa Neiva Pantuzza

“…Objective To map instruments for assessing healthcare professionals’ knowledge, attitudes and practices regarding deprescribing.Introduction Deprescribing is essential for improving patient outcomes by managing polypharmacy, reducing fall risks and decreasing medication costs. …”
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BLE phase-based ranging: accuracy and capability under strong Wi-Fi interference by Igor Kravets, Nazarii Kotliar, Oleksandr Karpin, Andriy Luchechko

“…In the case of long-distance ranging, ignoring interfered frequencies improves the situation dramatically, but this results in worse resolution and sometimes may identify the distance incorrectly due to false peaks.…”
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Artificial Intelligence in IVF Laboratories: Elevating Outcomes Through Precision and Efficiency by Yaling Hew, Duygu Kutuk, Tuba Duzcu, Yagmur Ergun, Murat Basar

“…Through an in-depth examination of current case studies, advancements, and future directions, this manuscript highlights how AI can revolutionize IVF by standardizing processes, improving patient outcomes, and advancing the precision of reproductive medicine. …”
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Automatic Ladle Tracking with Object Detection and OCR in Steel Melting Shops by Kabil Murugan, Mahinas Senthilmurugan, Venbha V. Senthilkumar, Harshita Velusamy, Karthiga Sekar, Vasanthan Buvanesan, Manikandan Venugopal

“…The results demonstrate that vision-based automated ladle tracking is feasible in steel plants, improving operational efficiency, ensuring safety, and minimizing human intervention.…”
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