Harnessing ICT for English Language Learning in Indonesia: Challenges and Opportunities by Aditya P. Nugraha, Fajar Duriat, Rusdayanti Rusdayanti

“…During the COVID-19 pandemic, online learning became mandatory, leading to the use of various apps, tools, and teaching methods to ensure the learning process continued. …”
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About the Usage of the Augmented Reality Technology in Mathematics and Physics Learning by Yu. Yu. Dyulicheva

“…The purpose of the work is the investigation of the modern approaches to augmented reality usage in mathematics and physics learning and the development of mobile application with graphical tips in the augmented reality mode for solving the dynamics typical problems.Materials and methods. …”
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DTC-m6Am: A Framework for Recognizing N6,2′-O-dimethyladenosine Sites in Unbalanced Classification Patterns Based on DenseNet and Attention Mechanisms by Hui Huang, Fenglin Zhou, Jianhua Jia, Huachun Zhang

“…Methods: Our proposed DTC-m6Am model first represents RNA sequences by One-Hot coding to capture base-based features and provide structured inputs for subsequent deep learning models. …”
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The features of Chinese students’ integration into the learning environment of Russian universities by M. A. Galaguzova, A. V. Shvetsova, Wei Zhang

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Specifics of the Algorithmic Prescriptions in the Learning Process of the Gymnastics Exercises’ Techniques by Victor BUFTEA

“…Namely, the sequence of the planned actions makes up the scheme of the program, carried out in a logical order, scientifically based and strictly established. Based on the algorithmization follows the execution or the methodical application of the program and its evaluation, focused on the reverse connection. …”
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Motivation and Parental Supervision Improve Indonesian Language Learning Outcomes by Muhammad Agus Halim, Ni Wayan Rati

“…Based on the results of the large test of influence together on learning motivation and parental supervision on learning outcomes. …”
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Theories and cognitive models of postnonclassical learning in natural science education by Suriya Irekovna Gilmanshina, Lyudmila Vladimirovna Moiseeva, Inna Nikolaevna Pushkareva, Sergey Borisov Ignatov, Iskander Rafailevich Gilmanshin

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Augmented reality in science learning: A systematic literature review by Z. Zufahmi, Fatchur Rohman, Murni Sapta Sari

“…Augmented Reality has been widely implemented at various levels of education and makes a positive contribution to learning. The positive impact of using AR can improve visualization, motivation, learning experience, and student personnel in science learning. …”
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Children who screen positive for autism at 2.5 years and receive early intervention: a prospective naturalistic 2-year outcome study by Spjut Jansson B, Miniscalco C, Westerlund J, Kantzer A, Fernell E, Gillberg C

“…The following interventions were available: a comprehensive intervention based on Applied Behavior Analysis – Intensive Learning (IL) – in two settings, which included home- and preschool-based (IL Regular) and only home-based (IL Modified) and eclectic interventions.Results: There was considerable variability in terms of outcome, but intervention group status was not associated with any of the chosen outcome variables. …”
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Social-emotional learning in physical education classes at elementary schools by Mahmood Sindiani, Hadas Brodie Schroeder, Ayelet Dunsky

“…It underscores the importance of creating a positive and emotionally supportive learning environment, contributing significantly to students’ holistic development. …”
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Micro-Location Temperature Prediction Leveraging Deep Learning Approaches by Amadej Krepek, Iztok Fister, Iztok Fister

“…As a result, these events have been addressed by artificial intelligence methods more and more frequently. In line with this, the paper focuses on searching for predicting the air temperature in a particular Slovenian micro-location by using a weather prediction model Maximus based on a long-short term memory neural network learned by the long-term, lower-resolution dataset CERRA. …”
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Learning a Mid-Level Representation for Multiview Action Recognition by Cuiwei Liu, Zhaokui Li, Xiangbin Shi, Chong Du

“…To this end, we propose a learning framework based on multitask random forest to exploit a discriminative mid-level representation for videos from multiple cameras. …”
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Heterogeneity-aware device selection for efficient federated edge learning by Yiran Shi, Jieyan Nie, Xingwei Li, Hui Li

“…Federated learning (FL) combined with mobile edge computing (FEEL) provides an end-to-edge synergetic learning approach to allow end devices to participate in machine learning model training parallelly while ensuring user privacy is maintained. …”
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Incorporation of XAI and Deep Learning in Biomedical Imaging: A Review by Sushil K. Singh, Bal Virdee, Saurabh Aggarwal, Abhilash Maroju

“…Concerns about liability in autonomous car accidents are comparable to those associated with deep learning applications in medical imaging. Errors such as false positives and false negatives can negatively affect patients' health. …”
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Applications of machine learning in decision analysis for dose management for dofetilide. by Andrew E Levy, Minakshi Biswas, Rachel Weber, Khaldoun Tarakji, Mina Chung, Peter A Noseworthy, Christopher Newton-Cheh, Michael A Rosenberg

“…Principal component analysis and cluster analysis identified 8 clusters as a reasonable data reduction method. These 8 clusters were then used to define patient states in a tabular reinforcement learning model trained on 80% of dosing decisions. …”
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The Establishment and Evaluation Model of the Thematic Deep-Learning Teaching Module by Kai-Chao Yao, Li-Chiou Hsu, Jiunn-Shiou Fang, Yi-Jung Chen, Zhou-Kai Guo

“…Students’ affective attitudes toward the four dimensions of teaching material and equipment, cognitive development, skills performance, and self-exploration were positive. Feedback revealed that students who participated in the teaching experiment responded positively on all levels of the affective scale, indicating increased motivation and willingness to continue learning. …”
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Collaborative Writing Learning in Inquiry to Improve Critical Thinking Skills by Nurul Shofiah, Zulmy Faqihuddin Putera, Sripit Widiastuti

“…One effective approach to mastering academic writing is through inquiry-based collaborative learning. Hence, this study endeavors to delineate the procedures involved and gauge students' perceptions of inquiry-based collaborative writing in enhancing critical thinking skills within the Indonesian language curriculum. …”
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Calibration of Electron Microscopes Through Deep Learning and Bayesian Optimization by Jilles S. van Hulst, Roy A. C. van Zuijlen, Narges Javaheri, Maurits Diephuis, Duarte J. Antunes, W. P. M. H. Heemels

“…The method uses deep learning to interpret the high-dimensional image, also called the Ronchigram, produced by the STEM, providing a quality index that quantifies the distance of the current image from its calibrated state. …”
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Machine Learning Predictive Models for Survival in Patients with Brain Stroke by Solmaz Norouzi, Samira Ahmadi, Shayeste Alinia, Farshid Farzipoor, Azadeh Shahsavari, Ebrahim Hajizadeh, Mohammad Asghari Jafarabadi

“…The best-performing model was selected based on diagnostic performance metrics: specificity, sensitivity, precision, accuracy, area under the receiver operating characteristic curve (AUC), positive likelihood ratio, negative likelihood ratio, and negative predictive value. …”
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Few-Shot Learning With Prototypical Networks for Improved Memory Forensics by Muhammad Fahad Malik, Ammara Gul, Ayesha Saadia, Faeiz M. Alserhani

“…As the first application of prototypical networks to the Dumpware10 dataset (to the best of authors knowledge), our findings highlight the potential of few-shot learning for memory forensics-based malware detection, opening new avenues for research in this domain. …”
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