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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Prediction of Myocardial Infarction Based on Non-ECG Sleep Data Combined With Domain Knowledge by Changyun Li, Yonghan Zhao, Qihui Mo, Zhibing Wang, Xi Xu

“…Multiple features related to HR and RR were extracted and integrated with clinical features; four algorithms&#x2014;MLP, SVM, XGBoost, and CNN&#x2014;were employed for model construction. …”
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AC-YOLO: A lightweight ship detection model for SAR images based on YOLO11. by Rui He, Dezhi Han, Xiang Shen, Bing Han, Zhongdai Wu, Xiaohu Huang

“…However, existing SAR ship detection algorithms encounter two major challenges: limited detection accuracy and high computational cost, primarily due to the wide range of target scales, indistinct contour features, and complex background interference. …”
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Risk-Adjusted Deep Reinforcement Learning for Portfolio Optimization: A Multi-reward Approach by Himanshu Choudhary, Arishi Orra, Kartik Sahoo, Manoj Thakur

“…Recent advances in portfolio optimization have shown promising capabilities of deep reinforcement learning algorithms to dynamically allocate funds across various potential assets to meet the objectives of prospective investors. …”
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Explainable Recommender Systems Through Reinforcement Learning and Knowledge Distillation on Knowledge Graphs by Alexandra Vultureanu-Albişi, Ionuţ Murareţu, Costin Bădică

“…To optimize recommendations while ensuring sustainability and transparency, the proposed method integrates reinforcement learning with graph-based representations of career trajectories. …”
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Machine Learning Unveils the Impacts of Key Elements and Their Interaction on the Ambient-Temperature Tensile Properties of Cast Titanium Aluminides Employing SHAP Analysis by Shiqiu Liu, Li Liang

“…Comparative analysis of three algorithms within the training dataset proved the random forest regression (RFR) as the optimal modeling approach. …”
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Monitoring of vegetation chlorophyll content in photovoltaic areas using UAV-mounted multispectral imaging by Ming Li, Weiyi Wang, Haoran Li, Zekun Yang, Jianjun Li

“…In this study, the vegetation within a photovoltaic power plant served as the research subject, and multispectral images were acquired using unmanned aerial vehicles, while in situ chlorophyll measurements were obtained through ground-based sampling at multiple time points. …”
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Artificial intelligence in pancreatic intraductal papillary mucinous neoplasm imaging: A systematic review. by Muhammad Ibtsaam Qadir, Jackson A Baril, Michele T Yip-Schneider, Duane Schonlau, Thi Thanh Thoa Tran, C Max Schmidt, Fiona R Kolbinger

“…Based on the Fukuoka and Kyoto international consensus guidelines, the current clinical management of intraductal papillary mucinous neoplasm (IPMN) largely depends on imaging features. While these criteria are highly sensitive in detecting high-risk IPMN, they lack specificity, resulting in surgical overtreatment. …”
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