The Influence of Power Relations on Teenagers’ Learning Process in an EFL Class by Yolima Forero-Rocha, Luis Fernando Gómez-Rodríguez

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(EFL) Learners’ Perspectives on Vocabulary Learning through Reading and Listening by Sara Jamal Mohammed Faraj

“…It was also found that there is no significant difference between both genders and age groups in vocabulary learning.…”
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Methodological Aspects of Learning of Work with a Multi-user Database by V. Oskerko, Z. Punchik

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Psychometrics of an Elo-based large-scale online learning system by Hanke Vermeiren, Joost Kruis, Maria Bolsinova, Han L.J. van der Maas, Abe D. Hofman

“…This method proves to be highly advantageous in online learning environments. Computerized adaptive practice (CAP) endeavors to present learners with items that are well-suited to their individual ability levels, with the ultimate goal of enhancing motivation and optimizing learning outcomes. …”
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The Impact of Online Learning System on Students Affected with Stroke Disease by Sobia Wassan, Chen Xi, Tian Shen, Kamal Gulati, Kinza Ibraheem, Rana M. Amir Latif Rajpoot

“…Neuroimaging investigates SD’s impact on attention, working memory, mood, and hippocampal learning. We analyzed how this data enriches our mechanistic understanding of these alterations and the clinical illnesses linked with sleep disruption. …”
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Driver Lane-Changing Behavior Prediction Based on Deep Learning by Cheng Wei, Fei Hui, Asad J. Khattak

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Application of Rotating Machinery Fault Diagnosis Based on Deep Learning by Wei Cui, Guoying Meng, Aiming Wang, Xinge Zhang, Jun Ding

“…After a brief review of early fault diagnosis methods, this paper focuses on the method models that are widely used in deep learning: deep belief networks (DBN), autoencoders (AE), convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), and transfer learning methods are summarized from the two aspects of principle and application in the field of fault diagnosis of rotating machinery. …”
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Feature Extraction and Classification of Music Content Based on Deep Learning by Qianqiu Shi, Young Chun Ko

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Analysis of the Application of Deep Learning in Model Reconstruction of Ancient Buildings by Zhihong Wang, Hao Xiong

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Balanced coarse-to-fine federated learning for noisy heterogeneous clients by Longfei Han, Ying Zhai, Yanan Jia, Qiang Cai, Haisheng Li, Xiankai Huang

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Editorial: Affirmation? How to Learn to Live with ‘The Others’ Through Design by Enrique Nieto Fernández, Ester Gisbert Alemany

“…We will meet with disobedient ants, cultural management, invasive plants, ancestral knowledges, unstable amphibians, women’s communities, changing climates, Indigenous peoples, environments, and publics that—all together—design a ‘we’ that is always in formation, affecting the places where we work, the studios where we design, the classrooms where we learn, or the epistemologies from which we articulate our relationship with otherness. …”
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Meta Learning Strategies for Comparative and Efficient Adaptation to Financial Datasets by Kubra Noor, Ubaida Fatima

Subjects: “…Meta-learning techniques…”
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Blood cancer prediction model based on deep learning technique by Amr I. Shehta, Mona Nasr, Alaa El Din M. El Ghazali

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Deep Transfer Learning for Biology Cross-Domain Image Classification by Chunfeng Guo, Bin Wei, Kun Yu

“…Inspired by the analysis of previous studies, the effect of biology cross-domain image classification in transfer learning is proposed. In this work, the multiple transfer learning scheme is designed to exploit deep transfer learning on several biology image datasets from different domains. …”
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Implementation of Arabic Online Learning at Post-Pandemic of Covid 19 by Aceng Rahmat, Mohammad Sarip, Khambali Khambali, Mohammed Alghali Khalil Yusuf

Subjects: “…Arabic Language Learning…”
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Learning models innovation in industrial revolution 4.0 era by Metsa Fajrianti Kusumah Suwandi, Muhammad Alfat

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Learning tasks as an assessment tool of competencies in organization of pedagogical practice by O. P. Kazakova

Subjects: “…learning task…”
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Machine Learning Model for Processing Aerospace Images of the Earthʼs Surface by T. F. Starovoitova, I. A. Starovoitov

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Predicting the thickness of shallow landslides in Switzerland using machine learning by C. Schaller, C. Schaller, L. Dorren, M. Schwarz, C. Moos, A. C. Seijmonsbergen, E. E. van Loon

“…We tested three machine learning (ML) models based on random forest (RF) models, generalised additive models (GAMs), and linear regression models (LMs). …”
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Scalable Multilabel Learning Based on Feature and Label Dimensionality Reduction by Jaesung Lee, Dae-Won Kim

“…In this study, we propose an efficient multilabel feature selection method to achieve scalable multilabel learning when the number of labels is large. The empirical experiments on several multilabel datasets show that the multilabel learning process can be boosted without deteriorating the discriminating power of the multilabel classifier.…”
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