Application of Facilitative Learning Model with Photovoice Method in Improving Learning Quality in Youth Education Courses by Sofino, Ririn Gusti, Bayu Pradikto

“…This study aims to improve the quality of learning by implementing a facilitative learning model with the photovoice method. …”
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The impact of a curriculum of the self- learning method to learn some basic skills in football Futsal by رغد جمعة سيد أ.د. هدى عبد السميع

“…The researchers have recommended the use of self- learning method in the process of learning the motor skills because of its significant impact on student learning.   …”
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A Review of Learning-Based Methods for Adaptive Video Streaming Over HTTP by Hala Amer, Mohamed S. Hassan, Mahmoud H. Ismail

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Tracking Learning and Teaching Chains and Their Variations in the Development of Mixed-Methods Methodology by Harri Pitkäniemi

Subjects: “…mixed methods…”
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An Efficient Deep Learning Framework for Revealing the Evolution of Characterization Methods in Nanoscience by Hui-Cong Duan, Long-Xing Lin, Ji-Chun Wang, Tong-Ruo Diao, Sheng-Jie Qiu, Bi-Jun Geng, Jia Shi, Shu Hu, Yang Yang

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Machine Learning Methods for Predicting Cardiovascular Diseases: A Comparative Analysis by Aiym B. Temirbayeva, Arshyn Altybay

“…Future work will explore hyperparameter tuning and ensemble methods to further enhance model performance, providing valuable insights for early diagnosis and treatment of cardiovascular diseases.…”
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A Survey on the Deep Learning-Based Mismatch Removal: Principles and Methods by Shiyu Chen, Cailong Deng, Yong Zhang, Yong Wang, Qixin Zhang, Zhimin Zhou

“…Firstly, these reviews are often embedded within studies that primarily focus on image matching, thereby limiting the detailed and comprehensive analysis of mismatch removal methods. Secondly, reviews of deep learning (DL)-based methods, despite their numerous existence and interconnection, tend to be fragmentary and lack a systematic approach. …”
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Development of digital twin of CNC unit based on machine learning methods by Yu. G. Kabaldin, D. A. Shatagin, M. S. Anosov, A. M. Kuzmishina

“…Machine learning methods valid for the implementation of the above tasks are evaluated. …”
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Machine learning methods for spectrally-resolved imaging analysis in neuro-oncology by T. A. Savelieva, I. D. Romanishkin, A. Ospanov, K. G. Linkov, S. A. Goryajnov, G. V. Pavlova, I. N. Pronin, V. B. Loschenov

“…In this paper, we focus on both the physical foundations of such methods and a very important aspect of their application – machine learning (ML) methods for image processing and tissues’ classification.…”
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Survey on multi-agent reinforcement learning methods from the perspective of population by XIANG Fengtao, LUO Junren, GU Xueqiang, SU Jiongming, ZHANG Wanpeng

“…There were four major categories of population adaptive reinforcement learning methods: transfer learning, course learning, meta learning, and meta game, and typical application scenarios were provided. …”
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Tether Force Estimation Airborne Kite Using Machine Learning Methods by Akarsh Gupta, Yashwant Kashyap, Panagiotis Kosmopoulos

“…This paper explores the potential of Airborne Wind Energy Systems to revolutionize wind energy generation, demonstrating advancements over current methods. Through a series of controlled field experiments and the application of classical machine learning techniques, we achieved significant improvements in tether force estimation. …”
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Deep dive into deep learning methods for cervical cancer detection and classification by Pooja Patre, Dipti Verma

“…This review presents a thorough analysis of deep learning methods utilized for cervical cancer diagnosis, with an emphasis on critical approaches, evaluation metrics, and the ongoing challenges faced in the field. …”
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Supervised methods of machine learning for email classification: a literature survey by Muath AlShaikh, Yasser Alrajeh, Sultan Alamri, Suhib Melhem, Ahmed Abu-Khadrah

“…Notably, supervised methodologies such as support vector machines (SVMs), naive Bayes, decision trees, neural networks, random forests, and deep learning have been exploited for spam filtering. This review delves into issues concerning spam filtering and email classification through supervised machine learning techniques, offering a comprehensive evaluation of strategies, methods, performance indicators, and the benefits and drawbacks of different research. …”
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Recent Advances in Optimization Methods for Machine Learning: A Systematic Review by Xiaodong Liu, Huaizhou Qi, Suisui Jia, Yongjing Guo, Yang Liu

Subjects: “…optimization methods…”
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Machine Learning-Based Methods for the Seismic Damage Classification of RC Buildings by Sung Hei Luk

“…This paper aims to investigate the feasibility of machine learning methods for the vulnerability assessment of buildings and structures. …”
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Indonesian Nursing Educators’ Experiences with Developing Student-Centered Learning Methods by Vigdis Abrahamsen Grøndahl, Kirsti Lauvli Andersen, Ann Karin Helgesen, Asniar Asniar, Randi Martinsen, Riza Septiani, Dharina Baharuddin, Signe Rasch Woersaa, Anna Willman, Liv Berit Olsen

“…The aim of the study was to describe the nurse educators’ experiences with developing student-active methods in nursing education in Indonesia. <b>Methods</b>: This study is part of an Erasmus+ project: Capacity Building in Nursing Education in Indonesia (CABNEI). …”
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METHODS OF DEVELOPING CORRECT PERCEPTION AND ARTICULATION SKILLS IN FOREIGN LANGUAGE LEARNING by Nina L. Goncharova

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COMPARATIVE ANALYSIS OF MACHINE LEARNING METHODS IN CLASSIFYING THE QUALITY OF PALU SHALLOTS by Desy Lusiyanti, Selvy Musdalifah, Agusman Sahari, Iman Al Fajri

“…This study conducts a comparative analysis of various machine learning methods for classifying the quality of Palu shallots based on the Indonesian National Standard (SNI). …”
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Cross-Database Evaluation of Deep Learning Methods for Intrapartum Cardiotocography Classification by Lochana Mendis, Debjyoti Karmakar, Marimuthu Palaniswami, Fiona Brownfoot, Emerson Keenan

“…Efforts to address this issue have focused on data-driven deep-learning methods to detect fetal compromise automatically. …”
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Few-shot Learning in Intelligent Agriculture: A Review of Methods and Applications by Sezai Ercisli, Jingbin Li, Kangle Song, Yi Wang, Huting Wang, Yichen Yuan, Jing Nie, Yang Li

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