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

“…The research results can be used while developing basic educational programs of teacher education. …”
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An Empirical Comparison of Machine Learning and Deep Learning Models for Automated Fake News Detection by Yexin Tian, Shuo Xu, Yuchen Cao, Zhongyan Wang, Zijing Wei

“…Our results show that transformer-based models, especially ALBERT, achieve state-of-the-art performance (macro F1 up to 0.99) with rich context, while classical ensembles remain viable for constrained settings. …”
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Behavioral economics: science or exoticism? by I. N. Drogobytsky

“…While studying economics as a science and an active sphere of human activity, scientists aim to give consistency to their knowledge, ensure that they are adequate and constructive. …”
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The comparison of distance metrics in descriptor matching methods utilised in TLS-SfM point cloud registration by Markiewicz Jakub

“…Descriptor matching in SfM-TLS typically employs the L2 norm to measure Euclidean distances between features, valued for its simplicity and compatibility with algorithms like SIFT. This study investigates the influence of various distance metrics on descriptor matching during the correspondence search stage of SfM-TLS. …”
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Artificial intelligence: protection and defence of human rights (ethical aspect) by Yu. M. Zhornokui

“…Work should focus on developing an ethical framework for artificial intelligence systems that prioritises transparency, fairness and accountability, while minimising potential negative impacts on human rights.…”
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Automated Microservices Identification Through Business Process Analysis: A Semantic-Driven Clustering Approach by Idris Oumoussa, Rajaa Saidi

“…The rise of microservice architectures has further evolved software development practices, building upon the foundation established by web services in breaking down monolithic systems, while offering more finely detailed, coherent, and loosely interconnected services. …”
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A Machine Learning Framework for Student Retention Policy Development: A Case Study by Sidika Hoca, Nazife Dimililer

“…This study presents a machine learning framework for predicting and visualizing students at risk of dropping out. While most previous work relies on wide-ranging data from numerous sources such as surveys, enrolment, and learning management systems, making the process complex and time-consuming, the current study uses minimal data that are readily available in any registration system. …”
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SpaceRL — A reinforcement learning-based knowledge graph driver by Miguel Bermudo, Daniel Ayala, Inma Hernández, David Ruiz, Miguel Toro

“…The generation of such agents is a complex task, even more so for a non-expert user.SpaceRL is meant to overcome these limitations by providing a flexible set of tools designed with a wide variety of customization options, in order to adapt to different users’ needs, while also including a variety of state-of-the-art RL algorithms and several embedding models that can be combined to optimize the agents performance. …”
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Gamification Elements in the Process of Ukrainian Language Training of Pedagogy Specialists by Iryna Humeniuk

“…The necessity of improving the methodology of teaching the language to students of different age groups while taking into account the main educational trends and public demand has been substantiated. …”
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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

“…Food contaminants, including harmful microbes, pesticide residues, heavy metals and illegal additives, pose significant public health risks. While traditional detection methods are effective, they are often slow and require complex equipment, which limits their application in real-time monitoring and rapid response. …”
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Method of 128-position quadrature amplitude-polarization manipulation by P. E. Korneev

“…The techniques based on the use of algorithms for processing special types of signals are the most promising to this date. …”
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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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Quantification of health by scaling similarity judgments. by Alexander M M Arons, Paul F M Krabbe

“…The correlation between the metric scales ranged from 0.73 to 0.95, while the non-metric scales ranged from 0.76 to 1.00, indicating strong to near perfect associations. …”
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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

“…In addition, LGG immune cell infiltration was viewed using CIBERSORT and ssGSEA algorithms and correlation analysis was done with cuproptosis-related genes. …”
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Stability analysis of semi-submersible floating wind turbines based on gyro-turbine coupled dynamics model by Wancheng Wang, Hao Li, Yihang Yang, Kai Sheng, Lijing Chen

“…Based on this model, an innovative PSO-optimized fuzzy control strategy is proposed, utilizing intelligent particle swarm optimization algorithms to adjust controller parameters for optimal performance under various environmental conditions. …”
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Description of route dependencies for computer-based railway signalling systems by Michał Grzybowski, Jakub Młyńczak, Lucyna Sokołowska

“…In addition, during research algorithms for automatic verification of conflicting route exclusion correctness have been designed, which allows for reduction of effort required for verification of conflicting route exclusion function. …”
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Identity-Based Provable Data Possession with Designated Verifier from Lattices for Cloud Computing by Mengdi Zhao, Huiyan Chen

“…Theoretical analysis confirms that the scheme achieves security guarantees while maintaining practical feasibility. Furthermore, simulation-based experiments show that for a 1 MB file and lattice dimension of <i>n</i> = 128, the computation times for core algorithms such as <b>TagGen</b>, <b>GenProof</b>, and <b>CheckProof</b> are approximately 20.76 s, 13.75 s, and 3.33 s, respectively. …”
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Contrastive Disentangled Variational Autoencoder for Collaborative Filtering by Woo-Seong Yun, Seong-Min Kang, Yoon-Sik Cho

“…Consequently, our model improves the predictive performance by effectively learning the representations toward salient latent features while excluding the effects from popularity. The proposed contrastive disentanglement framework is generic and thus adaptable to VAE-based recommender algorithms. …”
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Energy Demand Forecasting Scenarios for Buildings Using Six AI Models by Khaled M. Salem, Francisco J. Rey-Martínez, A. O. Elgharib, Javier M. Rey-Hernández

“…This research addresses a significant gap in energy demand forecasting across three building types by comparing six machine learning algorithms: Artificial Neural Networks, Random Forest, XGBoost, Radial Basis Function Network, Autoencoder, and Decision Trees. …”
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Evaluation of the Compliance of Urban Functions in Sofia City with the 15-minute City Concept by D. Petrova-Antonova, B. Monticelli, S. Ilieva

“…Existing studies predominantly rely on either survey-based assessments or algorithmic approaches, often overlooking the integration of both methods and the micro-scale walkability factors that impact accessibility.…”
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