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News
September 9, 2026
‘Balkan Hospitality Opens Doors: Studying Dialects on the Verge of Extinction
You cannot study spoken dialects from books. Instead, you need to go to a village, seek out its elders, and earn the trust of local residents before you can record hours of spontaneous stories. This is how Natalia Muravleva, Associate Professor at the Faculty of Humanities, conducts her research. Her internship in Serbia continued her long-standing study of dialects spoken by Macedonian settlers. In this interview, she discusses how diaspora cultural centres help researchers reach informants, why native speakers need to be interviewed only in their own language (otherwise, as she puts it, they may 'break'), and how a single field season helped her finalise her monograph. She also shares warm memories of autumn in Belgrade and of colleagues with whom grammar can be discussed in three languages at once.
September 9, 2026
Scientists Train Neural Network to Generate Process Plans from 3D Models
Researchers at the HSE FCS AI and Digital Science Institute have developed CAD2TechSpec, a framework that converts 3D models of mechanical parts into machining process plans—step-by-step instructions for machine tools. The solution aims to reduce the time required for the design and preparation of technical process documentation in mechanical engineering, aircraft manufacturing, and other high-tech industries. The study findings have been published in PeerJ Computer Science.
September 7, 2026
Biologists Discover 'Molecular Fingerprint' of Preeclampsia
Researchers at HSE University employed a new method to model hypoxia in placental cells during pregnancies complicated by preeclampsia and identified molecular markers of tissue hypoxia. Since hypoxia is one of the key mechanisms underlying preeclampsia, these findings are important for a more accurate and timely diagnosis of the disease and for the development of effective treatment methods. The paper has been published in Placenta.

 

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Data Science and Algorithms in Systems: Proceedings of 6th Computational Methods in Systems and Software 2022, Vol. 2

Vol. 2. Book 597. Issue 1. Cham : Springer, 2023.
Under the general editorship: R. Silhavy, P. Silhavy, Z. Prokopova

This book offers real-world data science and algorithm design topics linked to systems and software engineering. Furthermore, articles describing unique techniques in data science, algorithm design, and systems and software engineering are featured.

This book is the second part of the refereed proceedings of the 6th Computational Methods in Systems and Software 2022 (CoMeSySo 2022). The CoMeSySo 2022 conference, which is being hosted online, is breaking down barriers. CoMeSySo 2022 aims to provide a worldwide venue for debate of the most recent high-quality research findings.

Chapters
An Empirical Study on Price Determinants of the Primary Real Estate Market
Rutskiy V., Videnin S., Azizam S. H. et al., , in: Data Science and Algorithms in Systems: Proceedings of 6th Computational Methods in Systems and Software 2022, Vol. 2Vol. 2. Book 597. Issue 1.: Cham: Springer, 2023. P. 587–599.
The paper is devoted to the study of price determinant in the primary residential real estate market at the municipal level on the example of the residential real estate market in the city of Krasnoyarsk. This is one of the major economic centers of the East Siberian region of Russia. The authors show the applicability ...
Added: January 25, 2023
Research target: Computer Science
Language: English
DOI
Text on another site
Keywords: Software EngineeringSoftware Engineering ApplicationsInformatics
Data Science and Algorithms in Systems: Proceedings of 6th Computational Methods in Systems and Software 2022, Vol. 2
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The EAEU and the CSTO are Russia’s principal regional international organisations. Understanding, assessing, and analysing the foreign-policy positions of the countries that belong to them is a matter of the state’s national interests. This determines the purpose of the study: to identify the level and the form of cohesion in the voting of EAEU and ...
Added: September 7, 2026
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Oil Spill Segmentation in SAR Data Using ViT-UNet: Performance and Practical Insights
Зуенко Д. О., Trofimova E., Хайдарова И., IEEE Access 2026 Vol. 14 P. 121339–121357
Oil spill segmentation in Synthetic Aperture Radar (SAR) images is limited by noisy annotations in publicly available datasets and by architectural choices that interact with label quality in opposing directions. First, we introduce a manually refined version of the Deep-SAR Oil Spill (SOS) dataset, in which 36.25% of masks are corrected for false positives, missed ...
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Scalable machine learning approach to disordered s-wave superconductors
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Proceedings of the 42nd Conference on Uncertainty in Artificial Intelligence (UAI), PMLR Volume 337, 17-21 August 2026, KIT, Amsterdam, the Netherlands
Proceedings of Machine Learning Research , 2026.
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A unified frequency-domain framework for tilted slice localization and ischemic stroke detection
Khodadoust J., Kulikova S., Khodadoust F., Biomedical Signal Processing and Control 2027 Vol. 129 P. 111284–111284
Acute ischemic stroke (AIS) analysis from two-dimensional (2D) clinical imaging is hindered by uncontrolled slice tilt and geometric inconsistencies that violate the assumptions of pose-agnostic deep learning (DL) models. This paper proposes a unified geometry-aware, frequency-domain framework for tilted slice localization and ischemic stroke segmentation that explicitly decouples pose estimation from lesion analysis. The method ...
Added: September 2, 2026
Proceedings of the 2026 Fourth International Conference on Distributed Computing and High Performance Computing (DCHPC)
IEEE, 2026.
On behalf of the Organizing Committee, it is my great pleasure to extend a warm welcome to all participants of the Fourth International IEEE Conference on Distributed Computing and High-Performance Computing (DCHPC 2026), held in Tehran from May 10–11, 2026. This conference is jointly organized by the School of Computer Science at the Institute for Research in Fundamental Sciences (IPM) ...
Added: September 2, 2026
Discrete Markowitz Portfolio Optimization with Open-Source Classical and Quantum-Inspired Solvers: A Cross-Market Walk-Forward Study
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The cardinality-constrained Markowitz problem is NP-hard and traditionally solved with commercial MIQP solvers. Following the 2022 export restrictions that rendered both commercial MIQP software and cloud quantum platforms (IBM Quantum, D-Wave Leap) inaccessible from the Russian Federation, practitioners require open-source alternatives. This paper systematically compares three solver families for the discrete mean-variance problem: two open-source ...
Added: August 27, 2026
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Added: August 27, 2026
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