Sex Differences in Intelligence on the WISC: A Meta-Analysis on Children with Specific Learning Disabilities by Lorenzo Esposito, David Giofrè

“…In this framework, the present study aims to investigate, through a meta-analytical approach, whether there are sex differences in the profiles emerging from the WISC battery in children with a Specific Learning Disability. …”
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Identifying the Support of Human Resource Specialists to Facilitate the Learning of Education Workers in Hormozgan Province by Ahad Ameri, Mohammadnoor Rahmani, Leila Khajehpour

“…Objective: Education staff professional development is a comprehensive, focused and supportive approach designed to promote education staff for growth. The aim of the present study was to identify the support of human resource specialists in facilitating the learning of education workers in Hormozgan province. …”
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Enhancing cardiac disease detection via a fusion of machine learning and medical imaging by Tao Yu, KeYue Chen

“…Abstract Cardiovascular illnesses continue to be a predominant cause of mortality globally, underscoring the necessity for prompt and precise diagnosis to mitigate consequences and healthcare expenditures. This work presents a complete hybrid methodology that integrates machine learning techniques with medical image analysis to improve the identification of cardiovascular diseases. …”
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Reviewing the Impact of Generative AI on ‎Language Learning and Teaching: A Synthesis of Potentials and Pitfalls by Hewa Fouad Ali, Zahra Abdulmutalib Muhammed

“…The study presents the common ‎characteristics of GenAI ‎pertaining to the aspects of education. …”
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ESTABLISHING A METHODOLOGY FOR BENCHMARKING SPEECH SYNTHESIS FOR COMPUTER-ASSISTED LANGUAGE LEARNING (CALL) by Zöe Handley, Marie-Josée Hamel

“…Despite the new possibilities that speech synthesis brings about, few Computer-Assisted Language Learning (CALL) applications integrating speech synthesis have found their way onto the market. …”
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RSS Tracking Control for AVs Under Bayesian-Network-Based Intelligent Learning Scheme by Kun Zhang, Kezhen Han, Nanbin Zhao

“…Therefore, developing intelligent control strategies that can accurately predict the behavior of surrounding vehicles and make corresponding adjustments is crucial. This paper presents an intelligent driving control scheme for autonomous vehicles (AVs) based on a responsibility-sensitive safety (RSS) tracking control mechanism within a Bayesian network intelligent learning framework. …”
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Federated Learning Framework for Real-Time Activity and Context Monitoring Using Edge Devices by Rania A. Alharbey, Faisal Jamil

“…With the increasing need for effective elderly care solutions, this paper presents a novel federated learning-based system that uses smartphones as edge devices to monitor and enhance elderly care in real-time. …”
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A robust deep learning approach for glasses detection in non‐standard facial images by Saddam Bekhet, Hussein Alahmer

“…In addition, the obtained performance is even worse on real‐world (non‐standard) images, especially when compared to recent achievements in other computer vision research areas. In this paper, we present a robust deep learning approach for glasses detection from selfie photos full/partial frontal body non‐standard images captured in real‐life uncontrolled environments that do not utilize any facial landmarks. …”
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Advances and Challenges in Deep Learning for Automated Welding Defect Detection: A Technical Survey by Abdulrahim Mohammed, Muhammad Hussain

“…Automated welding defect detection has emerged as a pivotal aspect of quality assurance in high-stakes industries such as aerospace, oil and gas, and construction. This paper presents a comprehensive review of state-of-the-art Deep Learning (DL) models tailored for welding defect detection, segmentation, and classification, emphasizing technical advancements and persistent challenges. …”
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Ethiopian Traffic Sign Recognition Using Customized Convolutional Neural Networks and Transfer Learning by Amlakie Aschale Alemu, Misganaw Aguate Widneh

“…Optimizer, batch size, learning rate, and epoch are among the tuned training hyperparameters. …”
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Deep-learning-assisted reconfigurable metasurface antenna for real-time holographic beam steering by Ma Hyunjun, Kim Jin-Soo, Choe Jong-Ho, Park Q-Han

“…Suitable states for the generation of the desired patterns can be identified using iteration, but this is very slow and needs to be done for each far-field pattern. Here, we present a deep-learning-based method for the control of a metasurface antenna with point dipole elements that vary in their state using dipole polarizability. …”
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Creating interpretable deep learning models to identify species using environmental DNA sequences by Samuel Waggoner, Jon Donnelly, Rose Gurung, Laura Jackson, Chaofan Chen

“…As a result, ecologists have begun using the DNA that animals naturally leave behind in water or soil (called environmental DNA, or eDNA) to identify the species present in an environment. Recent work has shown that when used to identify species, convolutional neural networks (CNNs) can be as much as 150 times faster than ObiTools, a traditional method that does not use deep learning. …”
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Multistage deep learning methods for automating radiographic sharp score prediction in rheumatoid arthritis by Hajar Moradmand, Lei Ren

“…This study proposes a multistage deep learning model to predict the Overall Sharp Score (OSS) from hand X-ray images. …”
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Developing E-Commerce Skills Using Micro-Learning Reflecting Egypt's Vision 2030 by Amr Toony Ali AL-kardousei

“…Such skills have created many job opportunities, reduced unemployment rates, doubled productivity rates, and played a vital role for its users in development field. micro-learning plays an crucial role in teaching and learning, as it has turned from prolonged learning to micro-learning, in which learning content is presented in small units as needed, and applying what is learned in small focused steps i.e., focused learning (3-5 minutes) per unit focusing on a single specific performance goal and followed by one or two short activities. …”
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Performance evaluation of machine learning based voting classifier system for human activity recognition by Sonika Jindal, Monika Sachdeva, Alok K. S. Kushwaha

“…These machine learning classifiers are ensembled by analyzing the best performers among them. …”
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Playing it right: Empirical validation of the Gamertype scale for game-based learning in higher education by Joel Manuel Prieto Andreu, Pablo Moreno Ger

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Foreign Language Learning and Identity Reconstruction: Learners’ Understanding of the Intersections of the Self, the Other and Power by Seyyed Hatam Tamimi Sa’d

“…The present qualitative study sought to explore the relationship between English language learning and identity reconstruction from the view - points of Iranian language learners. …”
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The Tradition of Indigenous People as a Learning Material of Social Science at Senior High School by Usmaedi Usmaedi, Bunyamin Maftuh, Hamdan Hamdan, Siti Nurbayani K, Puji Siswanto

“…These traditions of indigenous people in Kasepuhan adat Cibadak Warungbanten can be used as materials or sources of social science learning. Therefore, Social Science teachers should think creatively in presenting teaching materials for Social Science subjects at schools. …”
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A systematic literature review and taxonomy proposition of machine learning techniques in smart manufacturing by Frederico de Oliveira Santos, Ivanete Schneider Hahn

“…This study presents a novel taxonomy that identifies 85 specific machine-learning techniques used in smart manufacturing. …”
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Identifying Challenges and Opportunities in the Implementation of Mobile Learning in Physical Education: A Literature Review by Raehang, La Ode Adhi Virama, Dewangga Yudhistira

“…The findings indicate that mobile learning presents both challenges and opportunities in physical education. …”
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