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News
November 10, 2026
Physicists Train AI to Optimise Particle Beams in Accelerators
Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science and the Budker Institute of Nuclear Physics at the Siberian Branch of the Russian Academy of Sciences have developed RLABC (Reinforcement Learning for Accelerator Beamline Control), a framework that uses reinforcement learning to identify optimal settings for a particle accelerator. In a computer simulation, RLABC optimised the accelerator's parameters to achieve a particle transmission rate of 70%. The study has been published in Computer Physics Communications.
November 9, 2026
'Organ-on-a-Chip Technology Could Eliminate the Need for Animal Testing'
The Laboratory of Molecular Physiology at the HSE Faculty of Biology and Biotechnology investigates how molecular regulators known as microRNAs control gene expression and contribute to the development of diseases, including cancer, viral and inflammatory conditions, and pregnancy complications. At HSE University, researchers develop organ-on-a-chip models: miniature devices containing living cells that mimic the functions of human organs, such as the placenta and intestines. These models help researchers understand how diseases develop and how drugs affect them. HSE News Service spoke with Evgeny Knyazev, Head of the Laboratory.
November 9, 2026
Flattened Terrain Models Underestimate Vehicle-to-Vehicle Communication Outages
Researchers at HSE MIEM have shown that widely used simulators of vehicle-to-vehicle communication significantly overestimate its reliability because they assume flat terrain. When terrain features, bridges, and tunnels are taken into account, the outage rate on a mountain serpentine road rises from 21% to 30%, on an overpass from 20% to 33%, and in a tunnel from 0% to 80%. The results have been published in Future Transportation.

 

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Анализ информации в инвестиционно-инновационной деятельности на основе технологий интеллектуальных агентов

Качество. Инновации. Образование. 2007. № 8. С. 17–21.
Makarov S.

A problem of difficulties of large amount of innovation project analysis and ways of solving the problem are described in the article. Disadvantages of existing information retrieval systems and advantages of multiagent technology systems, as well as classifications, tasks and mechanisms of intellectual agents are pointed out.

Research target: Computer Science
Priority areas: business informatics
Language: Russian
Full text
Keywords: project analysisinformation retrieval systemsintellectual agentsинформационно-поисковые системыанализ проектовинтеллектуальные агентысредства обработки и поиска информациипрограммная реализация интеллектуальных систембанки данных
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Impact of 5G NR-V2X Message Losses on Connected Vehicle Warning Functions
Физулин А. В., Stepanyants V., Amerikanov A. et al., FUTURE TRANSPORTATION 2026 Vol. 6 No. 6 Article 264
Cooperative warning functions depend on whether V2X information becomes available in time to influence vehicle control. This article presents an event-based co-simulation framework coupling SUMO, ns-3 (ms-van3t), 5G-LENA NR sidelink and application records, with Sionna RT enabled for the intersection scenario. In 140 emergency-vehicle-warning runs, reducing mean packet reception ratio (PRR) from 0.9412 to 0.0675 ...
Added: November 12, 2026
Structural model of decision support system for sustainable development of oil and gas companies
Stoianova A. D., Trofimets V. Y., Matrokhina K. V., International Journal of Engineering, Transactions A: Basics 2025 Vol. 38 No. 4 P. 701–709
The article considers the issue of managerial decision-making in an oil and gas company, which is related to the class of multi-criteria choice problems. To improve the validity of decisions in the context of companies’ sustainable development it is proposed to implement a Decision Support System (DSS). A brief review of the existing methods of ...
Added: November 10, 2026
EdFitter: a hybrid course recommendation system using large language models
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Educational institutions face increasing pressure to adapt their curricula to the rapidly evolving demands of the job market, and recommender systems can be important tools to guide students in selecting courses that align with their career goals. We present EdFitter, a hybrid course recommendation system that combines pretrained text embeddings for retrieval with large language ...
Added: November 10, 2026
Assessing density equilibration in confined Liquid–Liquid interfaces
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Equilibration is often assumed rather than tested in molecular dynamics studies of confined liquid–liquid interfaces, even though different physical properties may relax on different time scales. In this work, equilibration is examined using an automated truncation method based on the marginal standard error rule. Interfacial geometry, wetting behaviour, and density-related properties are analysed for liquid–liquid ...
Added: November 10, 2026
Influence of nuclear quantum effects on metastable states of warm dense hydrogen
Lukyanchuk V., Norman G., Kondratyuk N. et al., Scientific Reports 2026 Vol. 16 No. 1 Article 16435
Previously, it has been effectively shown that nuclear quantum effects (NQE) considerably influence the prediction of the warm dense hydrogen phase diagram. Here, we study the influence of NQE on the parameters of the conducting state formation in warm dense hydrogen using path integral molecular dynamics (PIMD) within the framework of the finite temperature density ...
Added: November 10, 2026
Machine Learning and Knowledge Discovery in Databases. Research Track and Applied Data Science Track. European Conference, ECML PKDD 2026, Naples, Italy, September 7–11, 2026, Proceedings
Springer, 2027.
This volume is Part VIII of the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2026, held in Naples, Italy, September 7–11, 2026. It contains 40 papers from the Research Track and the Applied Data Science Track and is published as volume 16948 of Lecture Notes in ...
Added: November 9, 2026
Artificial Intelligence for Software Engineering (AI4SE): A Review of Capabilities, Evaluation, and Verification Challenges
Avdoshin S.M., Pesotskaya E.Y., Proceedings of the Institute for System Programming of the RAS 2026 Vol. 38 No. 6, part 2 P. 133–146
Artificial intelligence has significantly reshaped contemporary software engineering practice, changing how software systems are designed, implemented, tested, and maintained. Recent advances in large language models and AI-assisted development tools have expanded the role of AI from supporting isolated tasks to participating in multiple stages of the software lifecycle. In many development settings, software is now created from high-level specifications ...
Added: November 8, 2026
MFL-ScrollNet: Recurrent Sliding-Window Detection for Panoramic Pipeline Magnetic Flux Leakage Images
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Abstract Automated interpretation of magnetic flux leakage (MFL) data is central to condition assessment of long-distance oil and gas pipelines. Yet, full-resolution panoramas are difficult to process without either suppressing small anomalies through resizing or fragmenting elongated objects at sliding-window boundaries. We propose MFL-ScrollNet, a recurrent sliding-window detector that formulates panoramic analysis as an ordered sequence ...
Added: November 8, 2026
Proceedings 2026 IEEE International Conference on Joint Cloud Computing JCC 2026
IEEE Computer Society (Conference Publishing Services, CPS), 2026.
Added: November 7, 2026
Detecting the undetectable: benchmarking AI-generated text
Sergey Avdoshin, Elena Pesotskaya, Saleh H. et al., Procedia Computer Science 2026 Vol. 292 P. 1332–1341
The rapid development of generative large language models (LLMs) has intensified the need for reliable methods capable of distinguishing AI-generated text from human writing, especially in academic and professional settings. This paper presents the results of a systematic benchmarking study evaluating the performance and limitations of contemporary LLM-text detectors applied to Russian-language academic content. We introduce ...
Added: November 7, 2026
PrimeKV: Preserving critical KV cache without attention scores for long-context inference
Zhang Z., Ilvovsky D., Neurocomputing 2027 Vol. 710
Efficient management of the Key-Value (KV) cache is essential for deploying large language models (LLMs) in long-context scenarios, where memory requirements often exceed the capacity of resource-constrained hardware. Many existing training-free compression algorithms typically rely on attention-driven heuristics, but exhibit two key limitations. First, they require explicit attention score computation, which is difficult to reconcile ...
Added: November 5, 2026
A Multimodal Framework for Aphasia Severity Classification in Russian
Kolmogorova A., Ekaterina Yavshitz, Margolina A. et al., Association for Computational Linguistics, 2026.
Automatic classification of aphasia severity presents persistent challenges, particularly for languages with limited clinical speech re sources such as Russian. This paper explores a multimodal approach to severity estimation that combines acoustic and semantic representa tions of pathological speech. Acoustic features are extracted using pretrained Wav2Vec 2.0 models, while semantic information is obtained from the ...
Added: November 4, 2026
Findings of the Association for Computational Linguistics: EMNLP 2026
Association for Computational Linguistics, 2026.
Findings of the Association for Computational Linguistics: EMNLP 2026 ...
Added: November 3, 2026
PULSE: Psychological Characteristics Unified Learning via Speech-based Estimation
Abdulkhadirov T., Ryumina E., Ryumin D. et al., Expert Systems with Applications 2026 Vol. 334 P. 1–29
Assessing human psychological characteristics from speech requires models that can jointly capture affective states, expressive behavior, and relatively stable personality traits. However, most existing speech-based frameworks address isolated tasks and use separate task-specific models. This leads to model proliferation and complicates inference in real-world intelligent systems. Unified models are also difficult to develop because few ...
Added: November 3, 2026
Interpretable GNN with Stable Concepts as Neurons
Kuznetsov S., CEUR Workshop Proceedings 2026 Vol. Vol-4247 P. 27–32
A method for constructing interpretable graph neural networks based on an ordered subsets of "interesting" formal concepts is proposed. Interestingness indices for selecting concepts are compared, namely frequency (extent size) and Δ-stability. The experimental results demonstrate that Δ-stability provides superior performance of the generated networks at the inference stage. ...
Added: November 2, 2026
О длине адаптивной различающей последовательности для семейства наблюдаемых автоматов
Бурдонов И. Б., Evtushenko N. V., Косачев А. С., Труды Института системного программирования РАН 2025 Т. 37 № 6-1 С. 7–20
В статье исследуется длина адаптивной различающей последовательности для семейства инициальных полностью определенных наблюдаемых, возможно, недетерминированных автоматов. Приводится верхняя оценка длины такой последовательности и показывается ее достижимость. Обсуждается, каким образом полученные результаты можно применить при построении адаптивных диагностических тестов на основе конечно-автоматной модели. ...
Added: October 31, 2026
К организации системы запросов в распределенной сети с кластерами диаметра не больше 2
Бурдонов И. Б., Evtushenko N. V., Косачев А. С. et al., Труды Института системного программирования РАН 2026 Т. 38 № 4-1 С. 7–24
В статье усовершенствуется предложенная в предыдущей статье авторов модель кластеризованной распределённой сети с опросом, соответствующая сервис-ориентированной архитектуре. Целью опроса является нахождение ближайшего узла, готового оказать требуемую услугу (сервис) как можно раньше. Предлагаемые алгоритмы обеспечивают достижимость узлов, отсутствие дублирования сообщений, и обмен сообщениями с найденным узлом по кратчайшему пути. Кластеризованность сети означает, что в графе сети ...
Added: October 31, 2026
Идентификация финального состояния в автоматах с таймаутами
Твардовский А. С., Бурдонов И. Б., Evtushenko N. V., Труды Института системного программирования РАН 2026 Т. 38 № 4-2 С. 7–22
В статье вводятся понятия установочной и синхронизирующей последовательностей для конечных автоматов с временными ограничениями и таймаутами. Такие последовательности широко используются для идентификации финального состояния исследуемого автомата как при синтезе тестов на основе формальных моделей, так и при обучении конечно-автоматных моделей. Метод синтеза установочных и синхронизирующих последовательностей основан на использовании конечно-автоматной абстракции временного автомата, поскольку методы ...
Added: October 31, 2026
К организации системы запросов в распределенной сети с кластерами-кликами
Бурдонов И. Б., Evtushenko N. V., Косачев А. С. et al., Труды Института системного программирования РАН 2026 Т. 38 № 3-1 С. 7–32
В статье предложена модель кластеризованной распределённой сети для обработки запросов. В такой сети узлы являются вычислительными единицами, и каждый узел может запросить ту или иную услугу, которая может быть оказана каким-то другим, но заранее неизвестным, узлом сети. Для этого осуществляется опрос сети аналогичный поиску в ширину для того, чтобы найти ближайший узел с необходимыми свойствами. ...
Added: October 31, 2026
Кластеризация услуг распределенной системы, в которой хосты могут выполнять функцию коммутации сообщений
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Статья является продолжением предыдущей статьи авторов, в которой строится абстрактная модель распределенной сети, содержащей только хосты и коммутаторы. Хосты предлагают пользователям пакеты определенных услуг (сервисов), сообщения (запросы) между хостами пересылаются через промежуточные узлы по правилам коммутации, и настройка узлов определяет множество путей от хоста к хосту, по которым будут пересылаться пакеты. Ситуация моделируется с использованием ...
Added: October 30, 2026
Оценка моделей LLM по степени готовности решать задачи управления в области ESG
Storchevoy M., Mylnikov L., Чернышев В. В. et al., / SSRN. Серия "Working Papers". 2025.
Внимание к охране природы принимает все большую значимость для бизнеса с одной стороны в связи с ужесточением в природоохранном законодательстве, а с другой в связи с использованием ESG рейтингов при принятии решений о коммерческой деятельности компаний. Составление рейтинга LLM систем, способных оказывать консультационные услуги в области природоохраны и ESG, позволяет осуществить выбор такой системы для ...
Added: September 18, 2025
Causal Estimands for Policy Evaluation and Beyond
Sokolov B., / Series OSF "SocArXiv". 2025.
This paper reviews various estimands used in modern scientific and applied research to operationalize causal inquiries within the Rubin Causal Model framework. I first introduce the most widely utilized average treatment effects, such as ATE, ATT, and ATC. I then describe their popular extensions, including those targeting local and conditional treatment effects; causal interactions and mediation; effects ...
Added: May 6, 2025
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Nowadays, there is an accelerated development of technology, which requires more rapid collection of science and technology data to track the dynamics of change, monitor results and identify promising areas of development. Systematic structure of existing and developing areas of research and technology is impossible without detailed classifications of the scientific and technological sphere. These ...
Added: March 26, 2025
Cultural characteristics of Digital Ecosystem Product Teams and Operational Efficiency
Ovanesova Y., Moshiashvili M. M., Типсина Н. О., / Series "Working Papers". 2021.
The purpose of this article is to analyze and evaluate the cultural characteristics of the digital ecosystem product teams leaders and operational efficiency. Using binary choice models (the main conclusions were made on the basis of logit regressions), has been found a significant negative relationship between the probability of achieving business goals by a team ...
Added: February 17, 2025
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