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Subject
News
September 11, 2026
How to Assess Students Knowledge in the Age of AI
A researcher at HSE University has proposed a flowchart to help lecturers decide how to assess students who use artificial intelligence. It shows where the use of AI should be restricted and where it can be incorporated into the learning process. The article has been published in IT Professional.
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.

 

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Моделирование и стабилизация нерегулярного механизма ценообразования на сети локальных рынков

Дифференциальные уравнения и процессы управления. 2023. № 4. С. 53–66.
Alexeeva T., Кузнецов Н. В., Мокаев Т. Н., Посудин К. М.

The accuracy of forecasting the expected values of economic indicators under conditions of irregular dynamics has a key role in taking optimal management decision-making. This current and complex task can be effectively solved using modern methods based on artificial intelligence, the wide introduction of which into the economy is aimed at by the Federal project "Artificial Intelligence". We show the effectiveness of combining artificial intelligence and classical methods of mathematical control to detect irregular dynamics in the pricing mechanism and stabilize the revealed irregular mode through a small control action using a pricing model in the market of short-term goods as an example.

Research target: Mathematics Economics and Management
Language: Russian
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Keywords: искусственный интеллектхаосchaosнелинейная динамикаnonlinear dynamicspricing modelмодель ценообразованияunstable periodic orbitHenon mapОтображение Энонестабильная периодическая орбита deep machine learning artificial intelligenceглубокое машинное обучение
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The integration of data-driven and knowledge-driven approaches in generative geospatial modelling (GGM) is often hindered by their mathematical incompatibilities. Here, we propose a geometric algebra (GA)-based framework that employs a unified multi-vector representation to fuse heterogeneous data and diverse knowledge. The framework facilitates structured reasoning and hypothesis generation through a task-adaptable, five-stage cycle: representation, reasoning, ...
Added: August 13, 2026
Cambodia's Policy on the Artificial Intelligence: Determinants, Directions, Interim Outcomes
Kanaev E., Southeast Asia: Actual Problems of Development 2026 Vol. 1 No. 1(70) P. 153–163
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Added: July 30, 2026
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