Deep Learning-Based Diagnosis Algorithm for Alzheimer’s Disease by Zhenhao Jin, Junjie Gong, Minghui Deng, Piaoyi Zheng, Guiping Li

“…Comparative and ablation experiments have validated the proposed classification performance of this method, demonstrating its capability to facilitate an accurate and efficient automated auxiliary diagnosis of AD, offering a deep learning-based solution for it.…”
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Machine learning-based myocardial infarction bibliometric analysis by Ying Fang, Yuedi Wu, Lijuan Gao

“…PurposeThis study analyzed the research trends in machine learning (ML) pertaining to myocardial infarction (MI) from 2008 to 2024, aiming to identify emerging trends and hotspots in the field, providing insights into the future directions of research and development in ML for MI. …”
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USING REINFORCEMENT LEARNING ALGORITHMS FOR UAV FLIGHT OPTIMIZATION by O. Dutsiak, V. Yuzevych

“…In this work, the main attention was focused on the study of a sub-method of machine learning, which is called learning with emphasis, with a view to optimizing the flight of a UAV by optimizing the process of constructing its path. …”
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Comparative Analysis of Machine Learning Algorithms for Antenna Alignments by Mohammad Al Bataineh, Dana I. Abu Abdoun, Mahmoud Al Ahmad

“…In the rapidly evolving field of radio frequency (RF) engineering, precise antenna alignment remains a critical challenge, directly influencing communication performance and reliability. This study presents a comprehensive comparative analysis of three advanced machine learning models—Long Short-Term Memory (LSTM), Convolutional Neural Network (CNN), and Multilayer Perceptron (MLP)—to predict antenna alignments based on S-parameter measurements. …”
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Self-supervised feature learning for acoustic data analysis by Ahmet Pala, Anna Oleynik, Ketil Malde, Nils Olav Handegard

“…The primary objective of this study is to develop an annotation-free deep learning model that extracts acoustic features and improves the representation of acoustic data. …”
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MODEL OF ORGANIZING DISTANCE LEARNING OF ENGLISH BY FUTURE ECONOMISTS by Bykonia Oksana Pavlivna

“…The model of organization of distance teaching of English to cadets of economic specialities which is presented. It contains organizational, educational and control stages and provides a way to manage educational activities during students’ distance learning of English…”
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EEG-Based Attention Classification for Enhanced Learning Experience by Madiha Khalid Syed, Hong Wang, Awais Ahmad Siddiqi, Shahnawaz Qureshi, Mohamed Amin Gouda

“…This paper presents a novel EEG-based learning system designed to enhance the efficiency and effectiveness of studying by dynamically adjusting the difficulty level of learning materials based on real-time attention levels. …”
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Data Poison Detection Schemes for Distributed Machine Learning by Yijin Chen, Yuming Mao, Haoyang Liang, Shui Yu, Yunkai Wei, Supeng Leng

“…Then, for semi-DML, we present an improved data poison detection scheme to provide better learning protection with the aid of the central resource. …”
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Role of Systematic Formative Assessment on Students’ Views of Their Learning by Areiza Restrepo Hugo Nelson

“…<p><span style="font-size: 10.0pt; font-family: ";Verdana";,";sans-serif";; mso-fareast-font-family: ";Times New Roman";; mso-fareast-theme-font: minor-fareast; mso-bidi-font-family: ";Times New Roman";; mso-ansi-language: EN-US; mso-fareast-language: ES-CO; mso-bidi-language: AR-SA;" lang="EN-US">This article presents a partial report of a small qualitative research study that explored the students’ views of their learning during and after the implementation of formative procedures such as self-assessment, feedback, and conferences. …”
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Machine learning prediction of pKa of organic acids by Juda Baikété, Alhadji Malloum, Jeanet Conradie

“…Thus, accurate prediction of pKa values is crucial for understanding and modulating the acidity and basicity of organic molecules, with applications in drug discovery, materials science, and environmental chemistry. Here, we present four tree-based machine learning models for pKa prediction of organic molecules. …”
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A Deep Learning Biomimetic Milky Way Compass by Yiting Tao, Michael Lucas, Asanka Perera, Samuel Teague, Timothy McIntyre, Titilayo Ogunwa, Eric Warrant, Javaan Chahl

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Prediction of induction motor faults using machine learning by Ademola Abdulkareem, Tochukwu Anyim, Olawale Popoola, John Abubakar, Agbetuyi Ayoade

“…Unplanned downtime in industrial sectors presents significant challenges, impacting both production efficiency and profitability. …”
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Strategy for teaching and learning in L2: about the student

“…Jannie Roos presents various learning techniques that promote learner autonomy. …”
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Android Technology in Interactive Learning for Multimedia Animation Courses by Army Trilidia Devega, Hilda Herasmus, Sabtu Sabtu, Ambiyar Ambiyar, Remon Lapisa, Larisang Larisang

“…Interactive learning media is a tool used to deliver learning content by presenting concepts in an engaging manner that can stimulate interest and participation in learning activities to achieve objectives. …”
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Lightweight Deep Learning Model for Fire Classification in Tunnels by Shakhnoza Muksimova, Sabina Umirzakova, Jushkin Baltayev, Young-Im Cho

“…Tunnel fires pose a severe threat to human safety and infrastructure, necessitating the development of advanced and efficient fire detection systems. This paper presents a novel lightweight deep learning (DL) model specifically designed for real-time fire classification in tunnel environments. …”
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Deep learning for automated encrustation detection in sewer inspection by Wasiu Yusuf, Hafiz Alaka, Mubashir Ahmad, Wusu Godoyon, Saheed Ajayi, Luqman Olalekan Toriola-Coker, Abdullahi Ahmed

“…While prior research has primarily addressed common sewer defect like crack, root intrusion, and infiltration among others, the challenge of encrustation—the formation of hard deposits within sewer systems—has received less attention. This study presents a pioneering deep-learning approach to detect encrustation in sewers by leveraging survey videos from 14 different sewers in the United Kingdom. …”
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STUDENTS’ CRITICAL THINKING ABILITY IN INTEGRATED LEARNING MODEL by Putri Dwi Sundari, Parno Parno, Sentot Kusairi

“…The results show that the students’ critical thinking skill in the temperature and heat materials increased after following the peer instruction integrated 5E learning cycle. The students have been able to build basic skills, provide simple explanations, organize strategies and tactics, make further explanations and are still unable to make conclusions from the physics problems presented KEMAMPUAN BERPIKIR KRITIS SISWA DALAMMODEL PEMBELAJARAN TERINTEGRASI Abstrak Penelitian ini bertujuan menganalisis kemampuan berpikir kritis siswa pada model siklus belajar 5E terintegrasi peer instruction dalam materi suhu dan kalor. …”
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Machine learning for discrimination of phase‐change chalcogenide glasses by Qundao Xu, Meng Xu, Siqi Tang, Shaojie Yuan, Ming Xu, Wei Zhang, Xian‐Bin Li, Zhongrui Wang, Xiangshui Miao, Chengliang Wang, Matthias Wuttig

“…To tackle this challenge, we present a machine learning (ML) approach to separate electronic phase‐change materials (ePCMs) from other chalcogenides, based upon subtle differences in the short‐range order inside the glassy phase. …”
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Transformative Learning for Controversial History of G 30 S/PKI by Yudi Hartono, Khoirul Huda

“…In learning, the concept of transformative learning that is directed at historical didactics based on academic history is needed. …”
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Model of Organization of Distance Learning for Students of Architectural Specialties by E. A. Dyachkova

“…The article also presents an analysis of scientific literature, the purpose of which is to generalize knowledge in the field of distance learning and professional training in relation to architectural education. …”
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