Machine-learning prediction for hospital length of stay using a French medico-administrative database by Franck Jaotombo, Vanessa Pauly, Guillaume Fond, Veronica Orleans, Pascal Auquier, Badih Ghattas, Laurent Boyer

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Reinforcement learning for autonomous underwater vehicles (AUVs): navigating challenges in dynamic and energy-constrained environments by Mohab M. Eweda, Karim ElNaggar

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Exploration design for Q-learning-based adaptive linear quadratic optimal regulators under stochastic disturbances by Vina Putri Virgiani, Shiro Masuda

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Adoption of the Creative Process According to the Immersive Method by Sonja Vuk, Tonka Tacol, Janez Vogrinc

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EDITORIAL: ARTIFICIAL INTELLIGENCE AND ITS TRANSFORMATIVE IMPACT ON SCIENTIFIC PUBLISHING by Abubakar Munir

“…Second, the risk of bias in AI algorithms is still an issue because AI algorithms learn from what is already in print form, thus potentially continuing existing biases in publishing materials (5). …”
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Adaptive Energy Management Strategy for Hybrid Electric Vehicles in Dynamic Environments Based on Reinforcement Learning by Shixin Song, Cewei Zhang, Chunyang Qi, Chuanxue Song, Feng Xiao, Liqiang Jin, Fei Teng

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Two-sided Energy Storage Cooperative Scheduling Method for Transmission and Distribution Network Based on Multi-agent Attention-deep Reinforcement Learning by CHEN Shi, ZHU Yujie, LIU Yihong, XU Liuchao, TANG Guodeng

“…The Multi-Agent Attention Noisy Twin Delayed Deep Deterministic Policy Gradient Algorithm (MAAN-TD3) is employed to obtain the optimal solution. …”
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STRATEGIC GOALS AND QUALITATIVE PROGRESS INDICATORS OF THE PROCESS OF NEO-INDUSTRIALISATION OF THE MANUFACTURING INDUSTRY IN UKRAINE by Olha Ilyash, Nataliia Semenchenko, Andrii Sachenko

“…The article shows that the implementation of the strategic and operational goals of the state policy requires the implementation of a set of measures, the main of which is the determination of the priority areas of the state policy in terms of innovative development and the creation of a "core" of new industries, which are prioritized in the development of high-tech entrepreneurship and increased export potential of the processing industry of Ukraine. …”
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USE OF MODERN INFORMATION TECHNOLOGIES TO ENSURE THE COMPETITIVENESS OF REGIONS IN THE CONTEXT OF DECENTRALIZATION OF POWER by Lev Kloba, Solomiya Kloba

“…The main advantages of automation of the educational process in Amalgamated hromada schools are investigated. According to the algorithm, decision-making on the implementation of IT services and evaluating their effectiveness is carried out in 4 stages and formed an algorithm for the use of information technology in Amalgamated hromada to increase competitiveness. …”
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Reactive Power Optimization of a Distribution Network Based on Graph Security Reinforcement Learning by Xu Zhang, Xiaolin Gui, Pei Sun, Xing Li, Yuan Zhang, Xiaoyu Wang, Chaoliang Dang, Xinghua Liu

“…Experiments conducted on real load profiles demonstrated that the proposed method reduced the voltage violation rate to 0%, compared to 4.92% with the Deep Deterministic Policy Gradient (DDPG) algorithm and 5.14% with the Twin Delayed DDPG (TD3) algorithm. …”
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Analysis and Research on Intelligent Logistics Data under Internet of Things and Blockchain by Yige Li

“…Moreover, the open access policy of couriers in the model raises concerns, as the access policy itself constitutes sensitive information, which may result in privacy breaches. …”
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Simulation Study: Trajectory Tracking Control of Parafoil System Based on Deep Reinforcement Learning by Xuepu Zhang

“…Therefore, this paper employs the deep reinforcement learning (DRL) method to train a neural network controller for controlling the parafoil system, based on a modified deterministic version of the distributional soft actor-critic with three refinements (DSACT) algorithm and it is named MC-DSAC-T. The controller of the parafoil system is denoted as a multilayer perceptron (MLP) and the objective function of the policy introduces cumulative discounted rewards of a single episode to improve the stability of the iterative update of the policy, a Monte Carlo (MC) thinking. …”
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Enhancing HVAC Control Systems Using a Steady Soft Actor–Critic Deep Reinforcement Learning Approach by Hongtao Sun, Yushuang Hu, Jinlu Luo, Qiongyu Guo, Jianzhe Zhao

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Quality of care for severe acute malnutrition delivered by community health workers in southern Bangladesh by Chloe Puett, Jennifer Coates, Harold Alderman, Kate Sadler

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Tuberculosis Preventive Treatment (TPT) in India: A Qualitative Review by Jay Patel, Abhishek Sen, Sandeep Rai, Harsh Shah, Nisarg Desai

“…The findings also revealed to create a responsive system that addresses the specific supportive system to ensure treatment adherence and successful outcomes. The integration of TB infection algorithm in existing TB diagnostic and treatment algorithms and comprehensive active case findings could result in positive outcome in reduction of TB, advancing India’s goal of TB elimination.…”
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Rotor angle stability enhancement using DDPG reinforcement agent with Gorilla troops optimized input scaling factors by Ahmed H. Yakout, Ahmed E. B. Abu-Elanien, Hany M. Hasanien

“…Abstract This paper introduces a Reinforcement Learning (RL)-based Power System Stabilizer (PSS) with a Deep Deterministic Policy Gradient (DDPG) algorithm for rotor angle stability. …”
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Automated Pixel Purification for Delineating Pervious and Impervious Surfaces in a City Using Advanced Hyperspectral Imagery Techniques by Payam Sajadi, Mehdi Gholamnia, Stefania Bonafoni, Gerald Mills, Yan-Fang Sang, Zeting Li, Salman Khan, Jiazheng Han, Francesco Pilla

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Challenges and Ethical Considerations in Implementing Assistive Technologies in Healthcare by Eleni Gkiolnta, Debopriyo Roy, George F. Fragulis

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Collaborative Optimization Strategy for Dependent Task Offloading in Vehicular Edge Computing by Xiting Peng, Yandi Zhang, Xiaoyu Zhang, Chaofeng Zhang, Wei Yang

“…The task-offloading problem is modeled as a Markov Decision Process, and an improved twin-delayed deep deterministic policy gradient algorithm, LT-TD3, is introduced to enhance the decision-making process. …”
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Web service and dynamic pricing competition by Ehram Safari, Masoud Babakhani

“…We first develop a time continuous model for competitive pricing of a web service and then we provide some insights about the equilibrium condition of the problem using open-loop differential game and propose an algorithm to obtain the optimal pricing policy for providers. …”
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