DYNAMICS OF THE INTEREST FOR LEARNING FOREIGN LANGUAGE IN UNIVERSITY STUDENTS by N. Naydenova, K. Katsarova

“…The disclosure of the change in the attitude towards the foreign language as a result of the conducted training and the dynamics of the individual motives of the students are important guidelines for improving the quality of the foreign language training. The aim of the presented research is to follow the dynamics of interest in learning a foreign language among university students. …”
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Students' perceptions of autonomy in the context of their experiences in remote learning by Wioletta Kwiatkowska, Agata Ćwiek

“…The aim of this article is to present the possibilities and limitations associated with the autonomy of remote learners. …”
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Federated Learning for Privacy-Preserving Employee Performance Analytics by Jay Barach

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Make or buy strategy for Machine Learning Operations – MLOps by DIEGO NOGARE, ISMAR F. SILVEIRA, RENATO BANZAI, MAÍNA C. ALEXANDRE

“…Additionally, qualitative and quantitative reviews of MLFlow, Airflow, Kubeflow, Databricks, Dataiku, H2O, Amazon AWS, Microsoft Azure, and Google GCP tools are presented, which facilitate the life-cycle management of machine learning models. …”
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Machine Learning and Neural Networks for IT-Diagnostics of Neurological Diseases by U. A. Vishniakou, Y. W. Xia, Ch. Y. Yu

“…The article considers machine learning methods and neural networks for diagnosing neurological diseases (Alzheimer’s and Parkinson’s diseases) in patients based on voice analysis. …”
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AISLEX: Approximate individual sample learning entropy with JAX by Ondrej Budik, Milan Novak, Florian Sobieczky, Ivo Bukovsky

“…We present AISLEX, an online anomaly detection module based on the Learning Entropy algorithm, a novel machine learning-based information measure that quantifies the learning effort of neural networks. …”
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An overview of the activation functions used in deep learning algorithms by Mete Çelik, Kemal Adem, Serhat Kılıçarslan

“…In this study, we present an overview of common and current activation functions used in deep learning algorithms. …”
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Wind power prediction using stacking and transfer learning by Xu Cheng, Yu Cao, Zhiyuan Song, Chenguang Zhang

“…Abstract As countries focus more on renewable energy, especially wind power, predicting wind power output accurately is crucial for managing power grids and saving costs. This paper presents a new method for ultra-short-term wind power prediction using a combination of Stacking and Transfer Learning. …”
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An Interactive Approach to Learning and Teaching in Visual Arts Education by Zlata Tomljenović

“…The present research focuses on modernising the approach to learning and teaching the visual arts in teaching practice, as well as examining the performance of an interactive approach to learning and teaching in visual arts classes with the use of a combination of general and specific (visual arts) teaching methods. …”
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Identification of learning mechanisms in a wild meerkat population. by Will Hoppitt, Jamie Samson, Kevin N Laland, Alex Thornton

“…We deployed it to analyse learning in groups of wild meerkats (Suricata suricatta) presented with a novel foraging apparatus. …”
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Machine learning for improved density functional theory thermodynamics by Sergei I. Simak, Erna K. Delczeg-Czirjak, Olle Eriksson

“…Abstract The predictive accuracy of density functional theory (DFT) for alloy formation enthalpies is often limited by intrinsic energy resolution errors, particularly in ternary phase stability calculations. In this work, we present a machine learning (ML) approach to systematically correct these errors, improving the reliability of first-principles predictions. …”
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<i>Democracy Otherwise</i>: Learning From the South by Tanja Winkler

“…Democracy otherwise—which is grounded in decoloniality and its accompanying epistemologies of the South—provides urban and regional planners with an opportunity to learn from the diverse democratic practices emerging in the Global South, practices that are deliberately delinked from the state and capitalism. …”
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The dynamics of motor learning through the formation of internal models. by Camilla Pierella, Maura Casadio, Ferdinando A Mussa-Ivaldi, Sara A Solla

“…Noise is not only present but necessary for the convergence of learning through the minimization of the difference between actual and predicted outcomes.…”
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Language, Gender Bias and Identity in Arabic Language Learning by Qushayyi Akbar Editia, Zakiah Muftie Daradjah, Shofil Fikri

“…This research aims to determine the relationship between language, gender bias and identity in Arabic language learning. Language and gender cannot be separated in a context, as aspects of language, including structure, word use, and communication conventions, can play a role in forming and reproducing gender norms, including in Arabic language learning. …”
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STRATEGIES TO ENHANCE BUSINESS GROWTH THROUGH ENTREPRENEURIAL LEARNING by Prety Diawati

“… This study examines the effects of work experience, self-efficacy, and access to finance on business growth, with entrepreneurial learning as a mediating variable. It employs a quantitative approach with SEM-PLS methodology. …”
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Enhancing Sports Team Management Through Machine Learning by Ling Zhang, Yifan An

“…However, research on machine learning in football has primarily focused on prediction. …”
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Survey on Deep Learning-Based Marine Object Detection by Ruolan Zhang, Shaoxi Li, Guanfeng Ji, Xiuping Zhao, Jing Li, Mingyang Pan

“…Therefore, high-performance deep learning-based algorithms and high-quality marine-related datasets need to be summarized. …”
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Classification of Music Structural Functions using Deep Learning by Dina A. AbdulQader, Piotr Bilski

“…The following paper presents a novel approach to MSA that aims to predict labels for structural music segments (such as verse or chorus), thereby it would enhance any MSA-based applications. …”
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Automatic wildfire monitoring system based on deep learning by Yingshu Peng, Yi Wang

“…Firstly, visual saliency areas in motion images are extracted to improve detection efficiency. Secondly, transfer learning techniques are employed to improve the generalization performance of the constructed deep learning classification model. …”
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Statistical mechanics and machine learning of the α-Rényi ensemble by Andrew Jreissaty, Juan Carrasquilla

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