Research result. Information technologies

Liquid neural networks (LNNs) are a class of continuous machine learning models in which the evolution of a hidden state is described by a system of ...

VALIDITY ASSESSMENT OF PUBLIC MRI DATASETS FOR NEURO-ONCOLOGICAL ABNORMALITY DETECTION: UNCOVERING CRITICAL DATA QUALITY ISSUES

Yasser Nizamli, Anton Yuryevich Filatov, Weaam Fadel, Yulia Alexandrovna Shichkina

The reliability of machine learning models in high-stakes applications like brain tumor diagnosis depends critically on the quality of training data. This paper presents a forensic ...

OPTIMIZATION OF A HYBRID SEARCH ALGORITHM IN TEXT CORPUSA BASED ON MULTI-LEVEL RELEVANCE METRICS

Tatyana Mikhailovna Levina, Yaroslav Vadimovich Belyakov

The relevance of this research stems from the exponential growth of unstructured text data and the increasing demands on the speed and relevance of its processing ...

APPLYING MACHINE LEARNING TECHNIQUES TO THE DEVELOPMENT OF ASSISTIVE INTELLIGENT SYSTEM FOR THE HEARING IMPAIRED

Yana Gennadievna Velikaya, Arsenii Eduardovich Medvedev, Pavel Vladimirovich Vassiliev, Vladimir Mikhailovich Mikhelev

The paper proposes an intelligent assistive system for Deaf and Hard-of-Hearing users designed to transform acoustic information into a visually accessible form. The study is motivated by the ...

INVESTIGATION OF A STOCK PRICE FORECASTING METHOD BASED ON EUCLIDEAN DISTANCE

Yuri Gennadievich Chashin, Alexey Alexandrovich Shiryaev

This article examines a stock price forecasting method based on Euclidean distance. It discusses the widespread use of Euclidean distance in science, specifically exploring its applications ...

INNOVATIVE METHODS A ND LINGUISTIC APPROACHES OF AI FOR OVERCOMING PSYCHOLOGICAL TRAUMA

Kristina Sergeevna Ivashko

The relevance of implementing intelligent computing platforms in psychiatry and clinical psychology is dictated by the urgent need to improve existing diagnostic and therapeutic strategies, especially ...

OPTIMIZATION OF HYPERPARAMETERS OF MACHINE LEARNING MODELS BASED ON EVOLUTIONARY ALGORITHMS AND SURROGATE MODELING

Evgeny Andreevich Zaripov, Sergey Alexandrovich Lazarenko

Relevance. Building high-precision predictive models in modern intelligent systems requires automating the search for optimal hyperparameters. Traditional optimization methods demonstrate low efficiency in high-dimensional spaces and with significant ...

DECISION SUPPORT SYSTEM FOR RESPONDING TO INFORMATION SECURITY THREATS

Данил Сергеевич Чмыхало, Andrey Ravilevich Gazizov, Olga Leonidovna Legonko

In today's increasingly digitalized world, ensuring information security for enterprises and organizations across various business types and industries is becoming an increasingly pressing issue, requiring advanced threat detection ...

MAPPING THE SCHOLARLY LANDSCAPE: A BIBLIOMETRIC ANALYSIS OF AI AND EMERGING TECHNOLOGIES ON ARXIV

Boris Nikolaevich Chigarev

Artificial intelligence and emerging technologies are boosting research efficiency and global competitiveness, transforming industries. They also raise important social and ethical governance issues that require evidence-based policy decisions. This ...

APPROACHES TO DETECTING ANOMALOUS HUMAN BEHAVIOR BASED ON IMAGES FROM CCTV CAMERAS

Anastasia Ilyinichna Kolesnikova, Oleg Olegovich Basov

This paper presents a review of approaches to the automatic detection of anomalous human behavior from surveillance video recordings. The relevance of the study is обусловлена the diversity ...

EXPERT SYSTEM FOR INFORMATION SECURITY EVENT ANALYSIS

Daniil Anatolyevich Potienko, Andrey Ravilevich Gazizov, Olga Leonidovna Legonko

This article explores the development of a hybrid expert system for analyzing information security events, aimed at automating threat detection in network traffic. Given the growing volume of data ...

CONSTRUCTING MULTI-DOMAIN KNOWLEDGE SYSTEMS BASED ON MULTI-LAYER KNOWLEDGE GRAPHS

Vadim Konstantinovich Pimeshkov

Knowledge systems enable the representation and application of structured information to solve a wide variety of problems. The development and application of modern knowledge systems inevitably encounter heterogeneous ...

ARCHITECTURE OF A DECISION SUPPORT SYSTEM FOR MICROGRID DEVELOPMENT

Aleksandr Sergeevich Vendin

This article examines the architecture of a design decision support system (DSS) for microgrid development. Microgrid use stems from the need to power autonomous facilities located remote from ...

SYSTEM ARCHITECTURE FOR ASR OF AGGLUTINATIVE LOW-RESOURCE LANGUAGES

Olga Viktorovna Timchenko, Darya Konstantinovna Alekseeva, Zalina Khamidbievna Abregova, Valeriya Andreevna Grechko

The relevance of the research is driven by the need to overcome the digital divide, which is particularly acute for low-resource languages. While speakers of widely spoken languages ...

ANALYSIS OF PROSODIC PARAMETERS OF EMOTIONALLY COLORED SPEECH

Tatiana Nikolaevna Balabanova, Alexander Sergeevich Belov, Alexander Sergeevich Pashkov, Evgeny Mikhailovich Mamatov

This paper presents a study of prosodic parameters of emotionally colored speech in the Russian language. The aim of the study is to identify the most informative acoustic ...

USING THEMATIC CLUSTERING IN MULTIMODAL DATA TO SEARCH FOR IMPLICIT CONNECTIONS AND TRENDS IN THESAURUS DEVELOPMENT

Vladimir Alexandrovich Yurchak

With the development of artificial intelligence and machine learning, it has become possible to use hierarchical probabilistic models in the field of natural language processing. Probabilistic or "thematic ...

QUANTIZATION METHOD FOR DETECTION NEURAL NETWORKS ON EMBEDDED SYSTEMS

Danila Stanislavovich Khrupin, Valeriy Alekseevich Shaptsev

Model quantization is a key method for deploying high-performance neural network object detectors on resource-constrained devices. However, standard quantization approaches, such as PTQ, QAT, and even mixed-precision methods, ...

SYSTEM-OBJECT MODELING AS A TOOL FOR VERIFICATION AND OPTIMIZATION OF THE QUALITY CONTROL SYSTEM IN A PRODUCTION LINE (CASE STUDY OF «DENTALCAST 50 TYPE 4» PRODUCT)

Pavel Andreevich Buzov, Alexander Gennadievich Zhikharev, Elena Viktorovna Malkush, Andrey Vladimirovich Kuznetsov

Relevance. In the context of industrial digital transformation and increasing demands for economic efficiency and product quality, methods enabling in-depth analysis and optimization of production systems are becoming ...

NEURAL NETWORKS IN THE TASK OF RECOGNIZING CREDIT CARD FRAUD