Practical use of on-board fuel metering systems of diesel locomotives by K. P. Popov

“…The implementation of algorithms in specialised software designed to process data from onboard systems that allow identifying the indicated influence is relevant only for cases of extreme (by an order of magnitude) difference in the number of switching throttle positions in work shifts.Discussion and conclusion. …”
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Explicit and Implicit Knowledge in Large-Scale Linguistic Data and Digital Footprints from Social Networks by Maria Pilgun

“…This research aims to develop and test algorithms for analyzing both explicit and implicit information in user-generated content and digital interactions. …”
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Machine Learning-Based Intrusion Detection Systems for the Internet of Drones: A Systematic Literature Review by Mostafa Ogab, Sofiane Zaidi, Abdelhabib Bourouis, Carlos T. Calafate

“…From an initial pool of 1,909 records, 62 relevant reports are selected to address the identified research questions. …”
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First study of the RuPatient health information system with optical character recognition of medical records based on machine learning by A. A. Komkov, V. P. Mazaev, S. V. Ryazanova, D. N. Samochatov, E. V. Koshkina, E. V. Bushueva, O. M. Drapkina

“…RuPatient health information system (HIS) is a computer program consisting of a doctor-patient web user interface, which includes algorithms for recognizing medical record text and entering it into the corresponding fields of the system.Aim. …”
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The key genes ME1 and ALDH3A1 involved in glycolysis regulate the lactate pathway and mediate COPD related immune dysregulation by Wenli XIE, Guang ZHOU, Zhitao JING, Shilin QIU

“…Subsequently, key genes involved in glycolysis were identified using the LASSO and SVM-RFE algorithms. After subtyping, GSEA analysis was conducted. …”
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Preparing healthcare leaders of the digital age with an integrative artificial intelligence curriculum: a pilot study by Soo Hwan Park, Roshini Pinto-Powell, Thomas Thesen, Alexander Lindqwister, Joshua Levy, Rachael Chacko, Devina Gonzalez, Connor Bridges, Adam Schwendt, Travis Byrum, Justin Fong, Shahin Shahsavari, Saeed Hassanpour

“…Our study demonstrates that a digital health enrichment elective that runs in parallel to an institution’s preclinical curriculum and embeds AI concepts into relevant clinical topics can enhance students’ confidence in describing the content objectives that pertain to high-level algorithmic understanding, implications, and limitations of the studied models. …”
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Constructing a predictive model for acute mastitis in lactating women based on machine learning by Liujing Zhu, Zuyan Huang, Yan Chen, Guangqiu Li, Liwen Liu

“…This study employed a retrospective case-control study approach and collected relevant data from 369 patients with acute mastitis and 447 healthy controls. …”
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STRATEGIC COMPETENCE AS A GUARANTEE OF PROFESSIONAL ACTIVITY OF A MODERN IT SPECIALIST by Volkova Nataliia, Oliinyk Iryna, Karpova Maryna

“…A strong emphasis is also placed on the following blocks of scientific knowledge: the use of technologies and algorithms of computational intelligence and intelligent data analysis in the tasks of forecasting, analytics, cluster analysis using software tools to support multidimensional data analysis based on DataMining, TextMining, WebMining technologies, mastering system programming languages and methods of developing online programs, performing parallel and distributed calculations, applying numerical methods and algorithms, etc. …”
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Mechanism of baricitinib supports artificial intelligence‐predicted testing in COVID‐19 patients by Justin Stebbing, Venkatesh Krishnan, Stephanie de Bono, Silvia Ottaviani, Giacomo Casalini, Peter J Richardson, Vanessa Monteil, Volker M Lauschke, Ali Mirazimi, Sonia Youhanna, Yee‐Joo Tan, Fausto Baldanti, Antonella Sarasini, Jorge A Ross Terres, Brian J Nickoloff, Richard E Higgs, Guilherme Rocha, Nicole L Byers, Douglas E Schlichting, Ajay Nirula, Anabela Cardoso, Mario Corbellino, the Sacco Baricitinib Study Group

“…Abstract Baricitinib is an oral Janus kinase (JAK)1/JAK2 inhibitor approved for the treatment of rheumatoid arthritis (RA) that was independently predicted, using artificial intelligence (AI) algorithms, to be useful for COVID‐19 infection via proposed anti‐cytokine effects and as an inhibitor of host cell viral propagation. …”
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A New Approach for Quantification of Finger Angles with Applications in Rehabilitation and Medical Assessment by Marius Turnea, Andrei Gheorghita, Irina Duduca, Mariana Rotariu

“…The study opens new perspectives for the development of advanced data processing algorithms, including the integration of deep learning neural networks for modelling and optimizing joint movements…”
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A Hierarchical and Self-Evolving Digital Twin (HSE-DT) Method for Multi-Faceted Battery Situation Awareness Realisation by Kai Zhao, Ying Liu, Yue Zhou, Wenlong Ming, Jianzhong Wu

“…Simulations indicate that the values of root mean square error (RMSE) for state of charge (SOC) and state of health (SOH) are lower compared to other algorithms, being less than 0.9% and 0.8%, respectively. …”
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Reinforcement learning for vehicle-to-grid: A review by Hongbin Xie, Ge Song, Zhuoran Shi, Jingyuan Zhang, Zhenjia Lin, Qing Yu, Hongdi Fu, Xuan Song, Haoran Zhang

“…Through this systematic review of reinforcement learning applications in Vehicle-to-Grid, the paper aims to provide relevant references for subsequent studies.…”
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Innovative Approaches to Sustainable Urban Planning: Analysing Current Trends by Meruyert Baidrakhmanova, Gani Karabayev, Seimur Mamedov

“…The study includes a comprehensive review of relevant international research, along with examples of practical implementations of the findings. …”
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Computational Strategy for Analyzing Effective Properties of Random Composites—Part I: Conductivity by Vladimir Mityushev, Piotr Drygaś, Simon Gluzman, Nurlan Nauryzbayev, Karlygash Nurtazina

“…Even minor changes to Random Sequential Addition algorithms lead to different formulas for the effective constants. …”
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Efficient text-to-video retrieval via multi-modal multi-tagger derived pre-screening by Yingjia Xu, Mengxia Wu, Zixin Guo, Min Cao, Mang Ye, Jorma Laaksonen

“…In this work, we present a plug-and-play multi-modal multi-tagger-driven pre-screening framework, which pre-screens a substantial number of videos before applying any TVR algorithms, thereby efficiently reducing the search space of videos. …”
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Status of research on prediction models for severity in confirmed Covid-19 patients by Maicel Eugenio Monzón-Pérez, Lizet Sánchez-Valdés, Elizabeth Rieche-Gómez, Agustín Lage-Dávila

“…Objective: To describe the sources, authors, documents and key issues that are part of the research front; identify which models, outcome variables, predictors and algorithms have been relevant; and identify to what extent the available models could meet the quality attributes and what characteristics they must have to be applicable to the Cuban context. …”
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Clinical Recommendations on Emergency Medical Care Rendering to Children with Acute Intoxication by A. A. Baranov, S. F. Bagnenko, L. S. Namazova-Baranova, Y. S. Alexandrovich, K. V. Pshenisnov, E. A. Alexeyeva, L. R. Selimzyanova

“…Acute accidental intoxication appears to be especially relevant for pediatric practice. Drugs, various chemicals frequently used in everyday life and in farming, as well as animal poisons, including snake poisons, may have a toxic effect on children. …”
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CLUMM: Contrastive Learning for Unobtrusive Motion Monitoring by Pius Gyamenah, Hari Iyer, Heejin Jeong, Shenghan Guo

“…Additionally, these cameras frequently capture irrelevant environmental information, which can hinder the performance of deep learning algorithms. To address these limitations, this paper introduces a novel framework that leverages a contrastive learning approach to learn rich representations from raw images without the need for manual labeling. …”
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Artificial intelligence model in the cognitive and learning activities of university subjects by N. Abishev, R. Ramazanov, M. Abaideldanova, K. Chesnokova, A. Baizhumayeva

“…The authors design this model using algorithms–sets of rules that enable programs to make decisions, recognize patterns, and generate predictions based on input data relevant to the learning and cognitive processes of university subjects. …”
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The OpenLAM Challenges: LAM Crystal Philately competition by Anyang Peng, Xinzijian Liu, Ming-Yu Guo, Linfeng Zhang, Han Wang

“…Since 2022, the Deep Potential team has been actively pretraining LAMs and launched the OpenLAM Initiative, which advocates for creating a community-driven platform aimed at accelerating the development of open-source foundation models by sharing curated datasets, algorithms, and relevant workflows. As part of the OpenLAM Initiative, the OpenLAM Challenges are competitions designed to benchmark atomic modeling methods, encourage community collaboration, and accelerate advances in machine learning-driven scientific discovery. …”
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