Do our students learn to treat patients? A necessary approach due to the social significance of a problem by Luis Alberto Corona Martínez

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Data-Driven Machine-Learning Model in District Heating System for Heat Load Prediction: A Comparison Study by Fisnik Dalipi, Sule Yildirim Yayilgan, Alemayehu Gebremedhin

“…We present our data-driven supervised machine-learning (ML) model to predict heat load for buildings in a district heating system (DHS). …”
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A comparative study on different machine learning approaches with periodic items for the forecasting of GPS satellites clock bias by Longjiang Song, Jiahao Liu, Leilei Wang, Ziyi Wang, Yibo Yuan

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A Q-Learning-Based Parameters Adaptive Algorithm for Formation Tracking Control of Multi-Mobile Robot Systems by Chen Zhang, Wen Qin, Ming-Can Fan, Ting Wang, Mou-Quan Shen

“…Then an adaptive method of sliding mode control parameters optimized by Q-learning scheme is employed, which can avoid the complex parameter tuning process. …”
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EXPERIENCES OF UNDERGRADUATE NURSING STUDENTS LEARNING PSYCHOMOTOR SKILLS DURING THE COVID-19 PANDEMIC: A QUALITATIVE STUDY by Bahar Çiftçi, Muruvvet Demiral-uzan, Güzel Nur Yıldız

“…ABSTRACT Objective: This study aimed to examine the experiences of nursing students learning psychomotor skills during the COVID-19 pandemic, the problems they experienced in this process, and their feelings and needs. …”
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A feature extraction method for hydrofoil attached cavitation based on deep learning image semantic segmentation algorithm by Yingyuan Liu, Yizhi Wang, Kang An

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COVID-19 and Emergency Migration to Remote Teaching in a Public University in the Maldives: Challenges, Solutions, and Lessons Learned by Dheeba Moosa, Visama Hassan

“…Challenges included internet, technology, student support, learning, and evaluation. The lecturers learned new skills during the pandemic, which was a positive outcome. …”
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Sustainable foam glass property prediction using machine learning: A comprehensive comparison of predictive methods and techniques by Mohamed Abdellatief, Leong Sing Wong, Norashidah Md Din, Ali Najah Ahmed, Abba Musa Hassan, Zainah Ibrahim, G. Murali, Kim Hung Mo, Ahmed El-Shafie

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Event-Trigger Reinforcement Learning-Based Coordinate Control of Modular Unmanned System via Nonzero-Sum Game by Yebao Liu, Tianjiao An, Jianguo Chen, Luyang Zhong, Yuhan Qian

Subjects: “…reinforcement learning…”
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Reinforcement learning based recovery flight control for flapping-wing micro-aerial vehicles under extreme attitudes by Yang Yu, Qiang Lu, Botao Zhang

“…This article deals with the recovery flight problem of flapping-wing micro-aerial vehicles under extreme attitude by using a reinforcement learning approach. First, the reinforcement learning-based control policy is proposed to enable the flapping-wing micro-aerial vehicles to be recovery flight rapidly and keep the angular acceleration as small as possible. …”
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Identification of blood plasma protein ratios for distinguishing Alzheimer's disease from healthy controls using machine learning by Ali Safi, Elisa Giunti, Omar Melikechi, Weiming Xia, Noureddine Melikechi

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Corrigendum to “Plant MicroRNA Prediction by Supervised Machine Learning Using C5.0 Decision Trees” by Philip H. Williams, Rodney P. Eyles, Georg Weiller

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Enhancing undrained shear strength prediction: a robust hybrid machine learning approach with naïve Bayes modeling by Chen Fang, Ying Li, Yang Shi

“…This paper presents a novel methodology for the USS prediction in soft clays using machine learning techniques, and particularly it highlights the attention on the following five important input variables: pre-consolidation stress (PS), vertical effective stress (VES), liquid limit (LL), plastic limit (PL), and natural water content (W). …”
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Identifying human activities causing water pollution based on microbial community sequencing and source classifier machine learning by Zhangmu Jing, Yi Zhang, Xiaoling Liu, Qingqian Li, Yanji Hao, Yeqing Li, Hongjie Gao

Subjects: “…Source classifier machine learning…”
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Predicting Risk through Artificial Intelligence Based on Machine Learning Algorithms: A Case of Pakistani Nonfinancial Firms by Shamsa Khalid, Muhammad Anees Khan, M.S. Mazliham, Muhammad Mansoor Alam, Nida Aman, Muhammad Tanvir Taj, Rija Zaka, Muhammad Jehangir

“…So, in this study, we used financial ratios for accurate risk assessment and for the automation of corporate risk management by developing machine learning algorithms using techniques, namely, random forest, decision tree, naïve Bayes, and KNN. …”
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Goal and shot prediction in ball possessions in FIFA Women’s World Cup 2023: a machine learning approach by Iyán Iván-Baragaño, Antonio Ardá, José L. Losada, Rubén Maneiro

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Reinforcement Learning-Based Resource Allocation Scheme of NR-V2X Sidelink for Joint Communication and Sensing by Zihan Li, Ping Wang, Yamin Shen, Song Li

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The classification of absence seizures using power-to-power cross-frequency coupling analysis with a deep learning network by A.V. Medvedev, B. Lehmann

“…New artificial intelligence methods such as deep learning neural networks can provide powerful tools for automated analysis of EEG. …”
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Vehicle Turn Pattern Counting and Short Term Forecasting Using Deep Learning for Urban Traffic Management System by Sundarakrishnan Narayanan, Sohan Varier, Tarun Bhupathi, Manaswini Simhadri Kavali, Mohana, P. Ramakanth Kumar, K. Sreelakshmi

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Retracted: Evaluation of High-Quality Development of Shaanxi’s Economy Based on Digital Economy Based on Machine Learning Algorithm by International Transactions on Electrical Energy Systems

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