Two-stage deep reinforcement learning method for agile optical satellite scheduling problem by Zheng Liu, Wei Xiong, Zhuoya Jia, Chi Han

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Memory-driven deep-reinforcement learning for autonomous robot navigation in partially observable environments by Estrella Montero, Nabih Pico, Mitra Ghergherehchi, Ho Seung Song

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Use of Active Learning to Design Wind Tunnel Runs for Unsteady Cavity Pressure Measurements by Ankur Srivastava, Andrew J. Meade

“…In this work, the feasibility of an active machine learning technique to design wind tunnel runs using proxy data is tested. …”
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Deep Reinforcemnet Learning for Robust Beamforming in Integrated Sensing, Communication and Power Transmission Systems by Chenfei Xie, Yue Xiu, Songjie Yang, Qilong Miao, Lu Chen, Yong Gao, Zhongpei Zhang

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Distance Learning For Military Doctors in Crisis Situations: The DILEMMA Cross-Sectional Study Results by Nataliia Sydorova, Valerii Savytskyi, Taras Kuts

“… Distance learning for medical personnel, although convenient in times of crisis (pandemics, military operations), can be a problem in terms of the limited practical component of such training. …”
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Detection of mite infested saffron plants using aerial imaging and machine learning classifier by Hossein Sahabi, Jalal Baradaran-Motie

“… Aim of study: To evaluate and develop a machine learning code that uses aerial images in visible and near infrared (NIR) spectra to detect mite-infested Saffron (Crocus sativus L.) plants through processing the spectral indices to classify healthy and diseased plants. …”
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Project-based learning as a means of forming leadership qualities in senior preschool children by G. Vatamaniuk, T. Tetiana

“…The aim of the study was to find an answer to the question of how project-based learning contributes to the development of leadership qualities in older preschool children. …”
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Fault Detection in Induction Machines Using Learning Models and Fourier Spectrum Image Analysis by Kevin Barrera-Llanga, Jordi Burriel-Valencia, Angel Sapena-Bano, Javier Martinez-Roman

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Language Interference in Arabic Learning: A Case Study of Islamic Boarding Schools in Indonesia by Muhamad Solehudin, Yusuf Arisandi

Subjects: “…arabic learning…”
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Physical unclonable in-memory computing for simultaneous protecting private data and deep learning models by Wenshuo Yue, Kai Wu, Zhiyuan Li, Juchen Zhou, Zeyu Wang, Teng Zhang, Yuxiang Yang, Lintao Ye, Yongqin Wu, Weihai Bu, Shaozhi Wang, Xiaodong He, Xiaobing Yan, Yaoyu Tao, Bonan Yan, Ru Huang, Yuchao Yang

“…It potentially serves as the hardware infrastructure for edge devices in federated learning or other systems.…”
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Deep Learning Algorithms for Traffic Forecasting: A Comprehensive Review and Comparison with Classical Ones by Shahriar Afandizadeh, Saeid Abdolahi, Hamid Mirzahossein

“…This paper aims to comprehensively review deep learning algorithms and classical models employed in traffic forecasting. …”
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Lithium-Ion Battery State of Health Degradation Prediction Using Deep Learning Approaches by Talal Alharbi, Muhammad Umair, Abdulelah Alharbi

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User Interface Designs of an Educational Mobile Application: A Study of Qiraat Teaching and Learning by Zulkifly Mohd Zaki, Syahidatul Fitriah Ishak, Khairul Anuar Mohamad

“…One of the major highlights from the participants is that the application can be used as a supplementary teaching and learning tool for people who wish to learn Qiraat anytime and anywhere. …”
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Predicting Flight Trajectory in Convective Weather through Boosted Spatiotemporal Deep Learning Ensemble by Xi Zhu, Ke Zhang, Zhuxi Zhang, Lifei Tan

“…To address this problem, we propose a boosted spatiotemporal deep learning ensemble for mining the law of how convective weather affects flight trajectory stretching. …”
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A Machine Learning Model for Predicting Prognosis in HCC Patients With Diabetes After TACE by Wu L, Chen L, Zhang L, Liu Y, Ouyang D, Wu W, Lei Y, Han P, Zhao H, Zheng C

“…Therefore, this study aimed to establish and validate a machine learning-based explainable prediction model of prognosis in patients with HCC and T2DM undergoing transarterial chemoembolization (TACE).Patients and Methods: The prediction model was developed using data from the derivation cohort comprising patients from three medical centers, followed by external validation utilizing patient data extracted from another center. …”
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Sentiment analysis of the Hamas-Israel war on YouTube comments using deep learning by Ashagrew Liyih, Shegaw Anagaw, Minichel Yibeyin, Yitayal Tehone

Subjects: “…Deep learning approach…”
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Why and how should we simulate platform trials? Learnings from EU-PEARL by Elias Laurin Meyer, Tobias Mielke, Marta Bofill Roig, Michaela Maria Freitag, Peter Jacko, Pavla Krotka, Peter Mesenbrink, Tom Parke, Sonja Zehetmayer, Dario Zocholl, Franz König

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EFFICACY AND ADAPTATION OF E-LEARNING IN INDIAN HIGHER EDUCATION INSTITUTIONS DURING COVID-19 by Jayashree Saha, Papori Baruah

Subjects: “…E-learning…”
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Mixed-Effects Modeling of Neurofeedback Self-Regulation Performance: Moderators for Learning in Children with ADHD by Agnieszka Zuberer, Franziska Minder, Daniel Brandeis, Renate Drechsler

“…However, it is unclear to what extent children learn to regulate their brain activity and in what way NF learning may be affected by subject- and treatment-related factors. …”
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Airport Arrival Flow Prediction considering Meteorological Factors Based on Deep-Learning Methods by Zhao Yang, Yifan Wang, Jie Li, Liming Liu, Jiyang Ma, Yi Zhong

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