Serial visual reversal learning in captive black-handed spider monkeys, Ateles geoffroyi by Jules Dorschner, Laura Teresa Hernandez Salazar, Matthias Laska

“…We found that the spider monkeys quickly learned to reliably discriminate between two simultaneously presented visual stimuli, that they succeeded in a visual reversal learning task, and that they displayed an increase in learning speed across consecutive reversals, suggesting that they are capable of serial reversal learning-set formation with visual cues. …”
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Rprot-Vec: a deep learning approach for fast protein structure similarity calculation by Yichuan Zhang, Wen Zhang

“…Thus, there is a need for sequence-based methods capable of inferring structural similarity efficiently and at scale. Result We present Rprot-Vec (Rapid Protein Vector), a deep learning model that predicts protein structural similarity and performs homology detection using only primary sequence data. …”
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Identification of exosome-related genes in NSCLC via integrated bioinformatics and machine learning analysis by Zhenjie Sun, Tianyu Du, Guosheng Yang, Yinghuan Sun, Xuyang Xiao

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Hybrid Supervised and Reinforcement Learning for Motion-Sickness-Aware Path Tracking in Autonomous Vehicles by Yukang Lv, Yi Chen, Ziguo Chen, Yuze Fan, Yongchao Tao, Rui Zhao, Fei Gao

“…However, as AD applications divert occupants’ attention to non-driving activities at varying degrees, MS in self-driving vehicles has been significantly exacerbated. This study presents a novel framework, the Hybrid Supervised–Reinforcement Learning (HSRL), designed to reduce passenger discomfort while achieving high-precision tracking performance with computational efficiency. …”
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COVID-19 World Vaccine Adverse Reactions Based on Machine Learning Clustering Algorithm by Lozan M. Abdulrahman, Adnan Mohsin Abdulazeez, Dathar A. Hasan

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Online Learning of Stabilizing Controllers Using Noisy Input-Output Data and Prior Knowledge by Nariman Niknejad, Farnaz Adib Yaghmaie, Hamidreza Modares

“…This paper presents online prior-knowledge-based data-driven approaches for verifying stability and learning a stabilizing dynamic controller for linear stochastic input-output systems. …”
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Impact of Channel and System Parameters on Performance Evaluation of Frequency Extrapolation Using Machine Learning by Michael Neuman, Daoud Burghal, Andreas F. Molisch

“…Over the past years, various machine learning (ML) techniques have been proposed for this goal, but their effectiveness is usually evaluated only for a limited number of examples. …”
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Risk factors associated with children learning disorders at school: a socio-medical problem. by Beatriz Sabina Roméu, Zenaida María Saéz, Margarita Roméu Escobar

“…Study group: 42 children presenting learning difficulties as to their teacher´s opinion. …”
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A Machine Learning Framework for Student Retention Policy Development: A Case Study by Sidika Hoca, Nazife Dimililer

“…Early identification of students at risk of dropout is crucial for proactive and preventive intervention. This study presents a machine learning framework for predicting and visualizing students at risk of dropping out. …”
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Enhancing professional development for Third Space roles: reflections on the added value of Learning Circles by Linde Moriau, Réka Matolay, Emma McKenna, Andrea Toarniczky, Judit Gáspár, Márta Frigyik, Catherine Bates

“…Learning Circles were implemented as a core component of professional development programmes, aiming to foster quality integration of Community Engaged Research and Learning (CERL) in academic practice. …”
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Sound event detection by intermittency ratio criterium and source classification by deep learning techniques by Vidaña-Vila Ester, Brambilla Giovanni, Alsina-Pagès Rosa Ma

“…Urban environments are characterized by a complex interplay of various sound sources, which significantly influence the overall soundscape quality. This study presents a methodology that combines the intermittency ratio (IR) metric for acoustic event detection with deep learning (DL) techniques for the classification of sound sources associated with these events. …”
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Enhanced group relation learning via aligned attention masking for fashion product captioning by Yuhao Tang, Dong Ye, Fei Tao, Guodong Du

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Choice of machine learning models for predicting the development of psychological disorders in people with hypothireosis and hyperthireosis by Нурал Гулієв

“…A more detailed analysis of its development will be presented in the following articles. A mathematical description of the chosen forecasting method is provided, which includes potential ways of implementation and steps for building an algorithm for one of these methods. …”
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Influenza virus genotype to phenotype predictions through machine learning: a systematic review by Laura K. Borkenhagen, Martin W. Allen, Jonathan A. Runstadler

“…Methods and Results: We present a systematic review of English literature published through 15 April 2021 of studies employing machine learning methods to generate predictions of influenza A virus phenotypes from genomic or proteomic input. …”
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Development of data driven machine learning models for the prediction and design of pyrimidine corrosion inhibitors by Aeshah H. Alamri, N. Alhazmi

“…In the present work, machine learning algorithms were utilized to develop predictive models for fifty-four (54) pyrimidines derivatives whose experimentally determined inhibition efficiencies data as corrosion inhibitors for carbon steel in hydrochloric acid medium are available in the literature utilizing the partial least square regression (PLS) and the random forest (RF). …”
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A Review of Machine Learning-Based Routing Protocols for Wireless Sensor Network Lifetime by Abhay R. Gaidhani, Amol D. Potgantwar

“…Machine learning is the process of acting without human involvement or reprogramming in order to learn from experiences. …”
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Reported Challenges in Deep Learning-Based Human Pose Estimation: A Systematic Review by Nagwa R. Fisal, Ahmed Fathalla, Dina A. Elmanakhly, Ahmad Salah

“…Human Pose Estimation (HPE) is the technique of precisely estimating the locations of human joints in images and videos. Deep learning has been frequently applied recently to improve HPE performance. …”
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Predicting congenital syphilis cases: A performance evaluation of different machine learning models. by Igor Vitor Teixeira, Morgana Thalita da Silva Leite, Flávio Leandro de Morais Melo, Élisson da Silva Rocha, Sara Sadok, Ana Sofia Pessoa da Costa Carrarine, Marília Santana, Cristina Pinheiro Rodrigues, Ana Maria de Lima Oliveira, Keduly Vieira Gadelha, Cleber Matos de Morais, Judith Kelner, Patricia Takako Endo

“…In light of this situation, machine learning techniques have been explored to assess the incidence of syphilis and contribute to the epidemiological surveillance in this scenario.…”
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A feature explainability-based deep learning technique for diabetic foot ulcer identification by Pramod Singh Rathore, Abhishek Kumar, Amita Nandal, Arvind Dhaka, Arpit Kumar Sharma

“…Artificial intelligence (AI), particularly through deep learning, has revolutionized DFU diagnosis and treatment. …”
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Robust Drone Video Analysis for Occluded Urban Traffic Monitoring Based on Deep Learning by Carlos Gellida-Coutino, Reyes Rios-Cabrera, Alan Maldonado-Ramirez, Anand Sanchez-Orta

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