PROJECT BASED LEARNING FOR CREATING THE 21ST CENTURY ENGINEER by Julia N. Ziyatdinova, Phillip Albert Sanger

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Enhancing augmented reality with machine learning for hands-on origami training by Mikołaj Łysakowski, Jakub Gapsa, Chenxu Lyu, Thomas Bohné, Sławomir Konrad Tadeja, Piotr Skrzypczyński, Piotr Skrzypczyński

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IS TRANSLANGUAGING LEGITIMATE IN ENGLISH LEARNING?: STUDENTS’ PERSPECTIVES FROM INDONESIA by Surya Asra, Rahmiati Rahmiati, Prima Nucifera, Fadlia Fadlia, Aina Mawaddah

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Similarity Measure Learning in Closed-Form Solution for Image Classification by Jing Chen, Yuan Yan Tang, C. L. Philip Chen, Bin Fang, Zhaowei Shang, Yuewei Lin

“…However, similarity learning has been paid less attention in learning problems. …”
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STRATEGIES OF EDUCATIONAL INSTITUTIONS IN BUILDING LEARNING INDEPENDENCE OF CHILDREN WITH DISABILITY by Annisa Arrumaisyah Daulay, Randi Saputra, Birrul Walidaini

Subjects: “…independence of learning…”
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Assessment of using transfer learning with different classifiers in hypodontia diagnosis by Tansel Uyar, Didem Sakaryalı Uyar

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Radiogenomics and machine learning predict oncogenic signaling pathways in glioblastoma by Abdul Basit Ahanger, Syed Wajid Aalam, Tariq Ahmad Masoodi, Asma Shah, Meraj Alam Khan, Ajaz A. Bhat, Assif Assad, Muzafar Ahmad Macha, Muzafar Rasool Bhat

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A Tristage Adaptive Biased Learning for Artificial Bee Colony by Qiaoyong Jiang, Yueqi Ma, Yanyan Lin, Jianan Cui, Xinjia Liu, Yali Wu, Lei Wang

“…To overcome this limit, an effective framework with tristage adaptive biased learning is proposed for existing ABCs (TABL + ABCs). …”
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Using Factor Decomposition Machine Learning Method to Music Recommendation by Dapeng Sun

“…On the other hand, we learn from item-based CF, which ensures that the candidate set covers user preference. …”
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Duolingo in English education: Evidence-based perspectives on learning outcomes by F. Fitriani

Subjects: “…mobile-assisted language learning…”
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Prediction of Mg Alloy Corrosion Based on Machine Learning Models by Zhenxin Lu, Shujing Si, Keying He, Yang Ren, Shuo Li, Shuman Zhang, Yi Fu, Qi Jia, Heng Bo Jiang, Haiying Song, Mailing Hao

“…The RF algorithm offered the most accurate predictions than the other three machine learning algorithms. The input effects on corrosion potential have been investigated. …”
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Effects of project-based learning on EFL learners' writing performance. by Abebaw Andargie, Dawit Amogne, Ebabu Tefera

“…Accordingly, this study aimed to investigate the impact of project-based learning on EFL learners' writing performance. It sought to determine whether and to what extent project-based learning could enhance writing skills in an EFL context. …”
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Evaluation of learning English with the illuminative model in the Fun English program by Risa Ginting

Subjects: “…learning evaluation…”
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Deep Learning for Automatic Recognition of Magnetic Type in Sunspot Groups by Yuanhui Fang, Yanmei Cui, Xianzhi Ao

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Comparative analysis of deep learning models for crack detection in buildings by S. Siva Rama Krishnan, M. K. Nalla Karuppan, Adil O. Khadidos, Alaa O. Khadidos, Shitharth Selvarajan, Saarthak Tandon, Balamurugan Balusamy

“…We also train and validate several deep learning models to classify brickwork images as either cracked or normal. …”
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Retracted: Cleanup Sketched Drawings: Deep Learning-Based Model by Applied Bionics and Biomechanics

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An Incremental Learning Ensemble Strategy for Industrial Process Soft Sensors by Huixin Tian, Minwei Shuai, Kun Li, Xiao Peng

“…The ability to handle large amounts of data incrementally and efficiently is indispensable for modern machine learning (ML) algorithms. According to the characteristics of industrial production process, we address an ILES (incremental learning ensemble strategy) that incorporates incremental learning to extract information efficiently from constantly incoming data. …”
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Explainable Machine Learning-Based Prediction Model for Diabetic Nephropathy by Jing-Mei Yin, Yang Li, Jun-Tang Xue, Guo-Wei Zong, Zhong-Ze Fang, Lang Zou

“…We compare four machine learning algorithms, including extreme gradient boosting (XGB), random forest, decision tree, and logistic regression, by AUC-ROC curves, decision curves, and calibration curves. …”
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Research on the Application of Deep Learning Methods in the Field of Image Classification by Peng Yuhui

“…The application of deep learning methods such as Convolutional Neural Network, Recurrent Neural Networks and Long Short-Term Memory in image classification is also discussed. …”
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Review on Deep Learning and Neural Network Implementation for Emotions Recognition by Renas Rajab Asaad

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