TEACHER EDUCATION AND FEATURES OF THE CONTEMPORARY EDUCATIONAL CONTEXT by Irina G. Zakharova

“…The importance of the teacher’s role in the ICT context creation achieving adequate quality of education is proved.Scientific novelty and practical significance. The research results can be used while developing basic educational programs of teacher education. …”
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A longitudinal study of interplay between student engagement and self-regulation by Sami Heikkinen, Mohammed Saqr, Jonna Malmberg, Matti Tedre

“…The findings demonstrate that both engagement and self-regulation skills can develop over time with appropriate support, suggesting opportunities for adaptive intervention throughout the course. This research provides actionable insights for developing targeted support strategies, including early warning systems for at-risk students and personalized scaffolding approaches based on students' behavioural patterns. …”
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Deep convolutional neural network (DCNN)-based model for pneumonia detection using chest x-ray images by S. I. Ele, U. R. Alo, H. F. Nweke, A. H. Okemiri, E. O. Uche-Nwachi

“…This study focuses on developing and implementing a machine learning model tailored specifically for medical diagnosis, leveraging advancements in computer vision and deep learning algorithms. This research aims to design an efficient and accurate model capable of classifying medical images into distinct categories, enabling automated diagnosis and identification of various ailments and conditions. …”
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Techno-economic optimization of hybrid renewable systems for sustainable energy solutions by Kanaga Bharathi N, Manoharan Abirami, Devi Vighneshwari, Manoharan Hariprasath

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Pharmacoeconomic analysis of conservative strategy for the treatment of patients with diabetic foot syndrome in Moscow by Marina Fedorovna Kalashnikova, Nadezhda Viktorovna Maksimova, Ivan Ivanovich Dedov

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Current application, possibilities, and challenges of artificial intelligence in the management of rheumatoid arthritis, axial spondyloarthritis, and psoriatic arthritis by Emre Bilgin

“…Advances in AI, mainly in machine learning and deep learning, have significantly influenced medical research and clinical practice over the past decades by offering precisions in data understanding and treatment approaches. …”
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FedDL: personalized federated deep learning for enhanced detection and classification of diabetic retinopathy by Dasari Bhulakshmi, Dharmendra Singh Rajput

“…We are proposing federated deep learning (FedDL) in FL, a research paradigm that allows for collective training of DL models without exposing clinical information. …”
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A novel approach for breast cancer detection using a Nesterov accelerated adam optimizer with an attention mechanism by Abeer Saber, Tamer Emara, Samar Elbedwehy, Esraa Hassan

“…Abstract Image-based automatic breast tumor detection has become a significant research focus, driven by recent advancements in machine learning (ML) algorithms. …”
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Calibration of Integrated Low-Cost Environmental Sensors for Urban Air Temperature Based on Machine Learning by Fang Nan, Chao Zeng, Huanfeng Shen, Liupeng Lin

“…Multiple linear regression (MLR) and light gradient boosting machine (LightGBM) algorithms were employed for calibration, with leave-one-out cross-validation (LOOCV) being used for model evaluation. …”
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A Comparative Analysis of Machine Learning Techniques for Predicting the Performance of Microchannel Gas Coolers in CO₂ Automotive Air-Conditioning Systems by Shehryar Ishaque, Naveed Ullah, Man-Hoe Kim

“…This paper explores the application of machine learning (ML) algorithms to predict the thermohydraulic performance of MCGCs in automotive air-conditioning systems. …”
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Predicting tuberculosis drug properties using extended energy based topological indices via a python driven QSPR approach by Kiran Naz, Hafiz Muhammad Bilal, Muhammad Kamran Siddiqui, Sarfraz Ahmad, Mustafa Ahmed Ali

“…All the calculations are done using Python, and the rigorous algorithmic implementation in the form of matrix formulation and computation of the eigenvalue is also given for reproducibility. …”
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METHOD OF CLASTERIZATION OF VESSELS ROUTES IN THE SYSTEM OFCOVERING THE SITUATION AT SEA by Valentin Y. Mazur, Oleh V. Borovyk, Roman V. Rachok

“…Directions of further research is the formation of a methodology for risk assessment based on the analysis of spatial anomalies of vessel traffic.…”
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A Machine Learning Framework for Student Retention Policy Development: A Case Study by Sidika Hoca, Nazife Dimililer

“…Unlike most similar research, the proposed framework provides a comprehensive system that not only identifies students at risk of dropout but also groups them into meaningful clusters, enabling tailored policy generation for each cluster through digital technologies. …”
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Specificity and Areas of Usage of Cardiovascular Prediction Models Among Athletes—State-of-the-art Review by Tomasz Chomiuk, Przemysław Kasiak, Artur Mamcarz, Daniel Śliż

“…Indirect prediction algorithms are feasible and easy-to-apply methods of individual cardiovascular disease risk estimation. …”
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Au-Ag Bimetallic Nanoparticles for Surface-Enhanced Raman Scattering (SERS) Detection of Food Contaminants: A Review by Pengpeng Yu, Chaoping Shen, Xifeng Yin, Junhui Cheng, Chao Liu, Ziting Yu

“…Surface-enhanced Raman scattering (SERS) technology has gained widespread use in related research due to its hypersensitivity, non-destructibility and molecular fingerprinting capabilities. …”
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InCrowd-VI: A Realistic Visual–Inertial Dataset for Evaluating Simultaneous Localization and Mapping in Indoor Pedestrian-Rich Spaces for Human Navigation by Marziyeh Bamdad, Hans-Peter Hutter, Alireza Darvishy

“…The evaluation of state-of-the-art visual odometry (VO) and SLAM algorithms on InCrowd-VI revealed severe performance limitations in these realistic scenarios. …”
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Novel Cuproptosis-Related Gene Signature for Precise Identification of High-Risk Populations in Low-Grade Gliomas by Ping Chen, Hailing Han, Xuejie Wang, Bing Wang, Zhanfeng Wang

“…The purpose of this research is to establish a predictive model for cuproptosis-related genes in order to recognise LGG populations at high risk. …”
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Intelligent SDN to enhance security in IoT networks by Safi Ibrahim, Aya M. Youssef, Mahmoud Shoman, Sanaa Taha

“…This study employs multiclassification algorithms to precisely detect and categorise diverse security threats in SDN. …”
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Influenza virus genotype to phenotype predictions through machine learning: a systematic review by Laura K. Borkenhagen, Martin W. Allen, Jonathan A. Runstadler

“…Machine learning techniques have demonstrated promise in addressing this critical need for other pathogens because the underlying algorithms are especially well equipped to uncover complex patterns in large datasets and produce generalizable predictions for new data. …”
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Development of data driven machine learning models for the prediction and design of pyrimidine corrosion inhibitors by Aeshah H. Alamri, N. Alhazmi

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