Learning quality-guided multi-layer features for classifying visual types with ball sports application by Xin Huang, Tengsheng Liu, Yue Yu

“…This highlights the need for precise X-ray image analysis in the medical and imaging fields. In this study, we present an advanced perceptual deep learning framework that extracts key features from large X-ray datasets, mimicking human visual perception. …”
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Digital teachers and parallel education: A paradigm shift in teaching and learning after ChatGPT by WANG Fei-Yue

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Multimedia Related Vocabulary Learning Strategies among English as a Foreign Language Algerian Students by Adela Talbi spouse Hassani

“… The focus in the present paper is on the evolution of students' behaviour in terms of Vocabulary Learning Strategies use from Year 1 to Year 3, with special focus on the type of strategies that might be conductive to larger vocabulary size.  …”
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Iterative Dissipativity of Partial Difference Equation Dynamics in Open-Loop Iterative Learning Control Mode by Tengfei Xiao

“…Finally, a thermal process and a numeric example are presented to illustrate the effectiveness of the proposed iteratively dissipative learning control approach.…”
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Research on knowledge concept extraction method based on few-shot learning and chain-of-thought prompting by SHE Linlin, XIONG Longyang, LU Xuesong

“…In view of the above challenges, a method based on few-shot learning and chain-of-thought prompting for knowledge concept extraction was proposed, utilizing open-source large language models. …”
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Deep Learning with Convolutional Neural Networks: A Compact Holistic Tutorial with Focus on Supervised Regression by Yansel Gonzalez Tejeda, Helmut A. Mayer

“…In this tutorial, we present a compact and holistic discussion of Deep Learning with a focus on Convolutional Neural Networks (CNNs) and supervised regression. …”
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MuToN Quantifies Binding Affinity Changes upon Protein Mutations by Geometric Deep Learning by Pengpai Li, Zhi‐Ping Liu

“…Despite significant efforts to create accurate computational models, predicting how mutations affect affinity remains challenging due to the complexity of the biological mechanisms involved. In the present work, a geometric deep learning framework called MuToN is introduced for quantifying protein binding affinity change upon residue mutations. …”
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A Novel Approach to Android Malware Intrusion Detection Using Zero-Shot Learning GANs by Syed Atir Raza Shirazi, Mehwish Shaikh

“…The study highlights the importance of adopting advanced machine learning techniques such as zero-shot learning GANs to enhance the effectiveness of intrusion detection systems in cybersecurity. …”
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Competing with Media Richness: Cognitive and Psychological Endowment Effects as the Fundamentally Pervasive Perspective of Learning Performance by Sumiyana Sumiyana, Muhammad Adlin Saputra

“…This research presents its novelty through learning attachment behaviour due to supremely personal psychological and cognitive endowment effects. …”
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The Role of the School Counselor in Diagnosing the Aggressive Behavior and Learning Disabilities: A Case Study in Algeria by Mhamel Imad Eddine

“…Thus, the researcher carried out a theoretical reading of this tool and used the clinical method by presenting a practical model of observation to diagnose the psychological and educational issues in the school milieu. …”
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Research on knowledge concept extraction method based on few-shot learning and chain-of-thought prompting by SHE Linlin, XIONG Longyang, LU Xuesong

“…In view of the above challenges, a method based on few-shot learning and chain-of-thought prompting for knowledge concept extraction was proposed, utilizing open-source large language models. …”
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An Unequal Clustering and Multi-Hop Routing Protocol Based on Fuzzy Logic and Q-Learning in WSNs by Zhen Wang, Jin Duan

“…To overcome this challenge and enhance network lifespan, this study presents FQ-UCR, a hybrid approach that merges unequal clustering based on fuzzy logic (FL) with routing optimized through Q-learning. …”
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Credit card fraud Detection using Feature select method and improved machine learning algorithm by Mohammed AL-Hammadi

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The Survey on Students’ Satisfaction Degree towards Online Learning during Covid-19 Pandemic Condition by Taufik, Fiptar Abdi Alam

“…The present study aimed at describing the satisfaction level of the university students in online learning at STKIP Muhammadiyah Barru during the Covid-19 pandemic situation. …”
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Automated mold defects classification in paintings: A comparison of machine learning and rule-based techniques. by Hilman Nordin, Bushroa Abdul Razak, Norrima Mokhtar, Mohd Fadzil Jamaludin, Adeel Mehmood

“…Mold defects pose a significant risk to the preservation of valuable fine art paintings, typically arising from fungal growth in humid environments. This paper presents a novel approach for detecting and categorizing mold defects in fine art paintings. …”
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Machine Learning Enables Real‐Time Proactive Quality Control: A Proof‐Of‐Concept Study by T. Honda, A. Yamazaki

“…This study presents proof‐of‐concept using a low‐dimensional dynamical system. …”
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A novel machine learning based framework for developing composite digital biomarkers of disease progression by Song Zhai, Andy Liaw, Judong Shen, Yuting Xu, Vladimir Svetnik, James J. FitzGerald, James J. FitzGerald, Chrystalina A. Antoniades, Dan Holder, Marissa F. Dockendorf, Jie Ren, Richard Baumgartner

“…However, the complexity of DHT datasets and the potential to derive numerous digital features that were not previously possible to measure pose challenges, including in selection of the most important digital features and construction of composite digital biomarkers.MethodsWe present a comprehensive machine learning based framework to construct composite digital biomarkers for progression tracking. …”
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Early Diagnosis of Autism: A Review of Video-Based Motion Analysis and Deep Learning Techniques by Ziqian Yang, Yuyao Zhang, Jiachuan Ning, Xin Wang, Zhihui Wu

“…The paper provides a systematic review of video-based motion analysis and deep learning (DL) techniques for early diagnosis of ASD. …”
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A novel deep learning technique for multi classify Alzheimer disease: hyperparameter optimization technique by A. S. Elmotelb, Fayroz F. Sherif, A. S. Abohamama, A. S. Abohamama, Mahmoud Fakhr, Amr M. Abdelatif

“…To address issues with limited data and computing resources, this work presents a novel deep-learning method based on using a newly proposed hyperparameter optimization method to identify the hyperparameters of ResNet152V2 model for classifying the phases of AD more accurately. …”
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Spectroscopy-Based Methods and Supervised Machine Learning Applications for Milk Chemical Analysis in Dairy Ruminants by Aikaterini-Artemis Agiomavriti, Maria P. Nikolopoulou, Thomas Bartzanas, Nikos Chorianopoulos, Konstantinos Demestichas, Athanasios I. Gelasakis

“…The objectives of the current review were (i) to describe the most widely applied spectroscopy-based and supervised machine learning methods utilized for the evaluation of milk components, origin, technological properties, adulterants, and drug residues, (ii) to present and compare the performance and adaptability of these methods and their most efficient combinations, providing insights into the strengths, weaknesses, opportunities, and challenges of the most promising ones regarding the capacity to be applied in milk quality monitoring systems both at the point-of-care and beyond, and (iii) to discuss their applicability and future perspectives for the integration of these methods in milk data analysis and decision support systems across the milk value-chain.…”
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