The potential for productive use of the digital service LearningApps in teaching foreign languages by Natalia A. Katalkina, Nadezhda V. Bogdanova

“…The purpose of the study is to test the method of productive use by students of higher educational institutions of the LearningApps service in the process of teaching foreign languages. …”
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Tropospheric Ducting: A Comprehensive Review and Machine Learning-Based Classification Advancements by Mohammed Banafaa, Ali Hussein Muqaibel

“…Our findings demonstrate that machine learning models, particularly support vector machines, can effectively classify ducting conditions, offering superior predictive performance compared to other models. …”
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Research on intrusion detection method for edge networks based on federated reinforcement learning by DING Kai, HUANG Yidu, TAO Ming, XIE Renping

Subjects: “…federated reinforcement learning…”
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A Machine Learning Approach for Environmental Assessment on Air Quality and Mitigation Strategy by Chetan Shetty, S. Seema, B. J. Sowmya, Rajesh Nandalike, S. Supreeth, Dayananda P., Rohith S., Vishwanath Y., Rajeev Ranjan, Venugopal Goud

“…In this work, density-based spatial clustering of applications with noise (DBSCAN) is used which is among the widely used clustering algorithms in machine learning. It is not only capable of finding clusters of various sizes and shapes but can also detect outliers. …”
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Why we should revitalize indigenous water harvesting systems: Lessons learned by Musaed Aklan, Charlotte de Fraiture, Laszlo G. Hayde

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Adaptive federated learning secure aggregation scheme based on threshold homomorphic encryption by Zhuo MA, Jiayu JIN, Yilong YANG, Yang LIU, Zuobin YING, Teng LI, Junwei ZHANG

Subjects: “…federated learning…”
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Identification of therapeutic targets for Alzheimer’s Disease Treatment using bioinformatics and machine learning by ZhanQiang Xie, YongLi Situ, Li Deng, Meng Liang, Hang Ding, Zhen Guo, QinYing Xu, Zhu Liang, Zheng Shao

“…This study aimed to identify potential therapeutic targets for the treatment of AD using comprehensive bioinformatics methods and machine learning algorithms. By integrating differential gene expression analysis, weighted gene co-expression network analysis, Mfuzz clustering, single-cell RNA sequencing, and machine learning algorithms including LASSO regression, SVM-RFE, and random forest, five hub genes related to AD, including PLCB1, NDUFAB1, KRAS, ATP2A2, and CALM3 were identified. …”
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Correction to: Welldeveloped spatial reversal learning abilities in harbor seals (Phoca vitulina) by Benedikt Niesterok, Shanie Martin, Lisa Hildebrand, Guido Dehnhardt, Frederike D. Hanke

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Utilization of Project Kind-Er (Engagement in Reading) to Strengthen the Foundation of Learning in Kindergarten by Ma. Benilda Ricaplanca, Mart Albert De Guzman, Christian Bautista

“…This study aimed to determine the effects of introducing one letter per week and another in the subsequent weeks, thereby creating a more engaging learning environment without overwhelming the pupils with two letters at once. …”
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An optimized data analytics pipeline for improving healthcare diagnosis using ensemble learning by Lomat Haider Chowdhury, Shaira Tabassum, Swakkhar Shatabda, Ashir Ahmed

“…Big data and machine learning are already in use to contribute to the healthcare diagnosis sector with the available data which is enormously growing through the digitalization of the system. …”
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Harnessing deep learning to detect bronchiolitis obliterans syndrome from chest CT by Mateusz Koziński, Doruk Oner, Jakub Gwizdała, Catherine Beigelman-Aubry, Pascal Fua, Angela Koutsokera, Alessio Casutt, Argyro Vraka, Michele De Palma, John-David Aubert, Horst Bischof, Christophe von Garnier, Sahand Jamal Rahi, Martin Urschler, Nahal Mansouri

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Machine learning and facial recognition for down syndrome detection: A comprehensive review by Khosro Rezaee

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Deep Learning Approach for Automatic Classification of Ocular and Cardiac Artifacts in MEG Data by Ahmad Hasasneh, Nikolas Kampel, Praveen Sripad, N. Jon Shah, Jürgen Dammers

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The Effectiveness of Android-Based Thematic Learning E-Modules in Increasing Student Motivation by Syaharullah Disa, Sitti Arni, Marnia

Subjects: “…e-module interactive learning…”
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Improving EFL ninth graders’ reading comprehension through thieves learning strategy by Yenny Asmarni, Wisma Yunita, Dedi Sofyan

“…Especially at school, the teachers need to enrich the strategy in teaching and learning process. The objectives of this study were to find out 1) the improvement of students’ reading comprehension of the ninth grade (IXC) of SMPN 13 North Bengkulu, 2) some factors influence the change of students’ reading comprehension at the ninth grade (IX C) of SMPN 13 North Bengkulu. …”
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SEMdag: Fast learning of Directed Acyclic Graphs via node or layer ordering. by Mario Grassi, Barbara Tarantino

“…Recently, industry and academics have paid close attention to DAG structure learning from observable data, and many techniques have been put out to address the problem. …”
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Intelligent System of Somatosensory Music Therapy Information Feedback in Deep Learning Environment by Nan Zhao

“…There is an inaccuracy problem in electrogram judgment, and deep learning has great advantages in signal feature extraction and classification. …”
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Deep Learning-Based Energy Consumption Prediction Model for Green Industrial Parks by Chaoan Lai, Yina Wang, Jianhua Zhu, Xuequan Zhou

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Digital Recruitment Using Intelligent Dialogue Systems Based on Machine Learning Principles by I. N. Kalinouskaya

“…The article suggests the technology of implementation of digital recruiting by Belarusian companies; the method of evaluation of candidates' CVs is given; the method of conducting preliminary interviews with the use of intelligent dialog systems based on the principles of machine learning is given; the example of using the chat-bot in the process of selection and evaluation of candidates is considered; the advantages of digital recruitment over the classical methods of personnel recruitment are specified.…”
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Evaluation of Prediction Performances of Deep Learning Models for the Aerodynamic Characteristics of Flettner Rotors by Seo Janghoon, Park Jung Yoon, Ma Juhwan, Kim Young Bu, Park Dong-Woo

Subjects: “…deep learning model…”
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