BIG DATA и анализ высокого уровня = BIG DATA and Advanced Analytics : сборник научных статей X Международной научно-практической конференции в двух частях, Часть 1 (Республика Беларусь, Минск, 13 марта 2024 года)

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BIG DATA и анализ высокого уровня = BIG DATA and Advanced Analytics : сборник научных статей X Международной научно-практической конференции в двух частях, Часть 1 (Республика Беларусь, Минск, 13 марта 2024 года)

Мн. : БГУИР, 2024.

The collection contains the results of scientific research and development in the field of BIG DATA
and Advanced Analytics for optimizing IT and business solutions, as well as case studies in
the field of medicine, education and ecology.

Использование анализа данных для оптимизации учебного процесса: оценка студентами интересности и полезности деловых игр

Мустафина Н. И., Plaksin M. A., В кн.: BIG DATA и анализ высокого уровня = BIG DATA and Advanced Analytics : сборник научных статей X Международной научно-практической конференции в двух частях, Часть 1 (Республика Беларусь, Минск, 13 марта 2024 года).: Мн.: БГУИР, 2024. С. 457–469.

Added: February 18, 2025

Research target: Computer Science

Language: Russian

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Keywords: big data big data Advanced Analytics Advanced Analytics

BIG DATA и анализ высокого уровня = BIG DATA and Advanced Analytics : сборник научных статей X Международной научно-практической конференции в двух частях, Часть 1 (Республика Беларусь, Минск, 13 марта 2024 года)

Risks and the image of the future in the study of AI technologies prospects

Snegirev A., Sychev S., Futures 2026 Vol. 183 P. 1–22

This study addresses the systemic identification and categorization of risks associated with AI development, arising from tensions between technological evolution and institutional, infrastructural, and economic contexts. Drawing on a constructionist methodology, we interpret technological risks as constitutive elements of expert communities' images of the future. Through in-depth interviews with 100 AI experts, proportionally representing corporate, ...

Added: September 23, 2026

Choosing Between AI Responses: How Valence, Arousal, and Dominance Shape User Preference

Parshakov P., Paklina S., International Journal of Human-Computer Interaction 2026 P. 1–17

This study examines how emotional tone shapes user preference in human–large language model (LLM) interaction. Drawing on the Computers as Social Actors framework, we treat conversational AI as a social communicator whose affective cues influence user judgments. Using large-scale pairwise preference data from LMSYS Chatbot Arena, we model emotional tone through the Valence–Arousal–Dominance framework and ...

Added: September 23, 2026

A Two-Stage Deep Reinforcement Learning Framework for Radio Resource Management and Network Slicing in 5G Heterogeneous Networks

Andrabi U., Wadood E., Ojha S. K. et al., IEEE Access 2026 Vol. 14 P. 103358–103375

The emergence of 5G networks, aimed at accommodating diverse service requirements such as enhanced Mobile Broadband (eMBB), Ultra-Reliable Low-Latency Communication (URLLC), and massive Machine-Type Communication (mMTC), has presented significant challenges in radio resource management and network slicing. In dynamic heterogeneous network systems, traditional heuristics and mathematical programming methods find it challenging to attain scalable multi-objective ...

Added: September 23, 2026

LLM-assisted writing and citation advantage: evidence from scientific publications before and after ChatGPT release

Paklina S., Parshakov P., Elena Rapoport, Scientometrics 2026 P. 1–26

Generative artificial intelligence has become a routine part of academic writing. While much of the debate has focused on questions of integrity and authorship, less attention has been paid to how AI-assisted writing may affect research evaluation itself. This paper asks a straightforward but important question: does the use of LLMs in academic writing change ...

Added: September 23, 2026

Label-Free Quantification in the Crux Toolkit

Kertesz-Farkas A., Acquaye F. L., Journal of Proteome Research 2026 Vol. 25 P. 3764–3768

Ultimately, most tandem mass spectrometry (MS/MS) proteomics experiments aim to not just detect but also quantify the proteins in a given complex sample. Here, we describe an extension to the Crux MS/MS analysis toolkit to enable label-free quantification of peptides. We demonstrate that Crux’s new quantification command, which is modeled after the algorithms implemented in ...

Added: September 23, 2026

Risk Assessment Models for Heated Tobacco Products

Maddalena L., Yildiz B., Del Vecchio Blanco F. et al., Risk Analysis 2026 Vol. 46 No. 4 P. 1–26

Heated tobacco products (HTPs) are marketed as alternatives to conventional cigarettes with a potential reduced risk profile. Yet, their actual impact on cancer and noncancer disease risk remains uncertain and requires rigorous quantitative assessment. In this study, we develop a unified and transparent computational framework for toxicological risk assessment of HTPs, integrating chemical emissions data ...

Added: September 22, 2026

Segmentation of the Iris and Pupil of the Human Eye in Images from an Infrared Camera

Aleksei Samarin, Alexander Savelev, Aleksei Toropov et al., Pattern Recognition and Image Analysis 2024 Vol. 34 No. 3 P. 855–862

Tasks related to the automation of medical data processing are becoming more urgent. Particular attention is paid to systems for monitoring and analyzing human physiological parameters. Such systems often use specialized sensors to capture biomedical images, such as infrared cameras. This article describes our study of the problem of segmenting the eye pupil and iris ...

Added: September 21, 2026

A Model Based on Universal Filters for Image Color Correction

Aleksei Samarin, Nazarenko A., Alexander Savelev et al., Pattern Recognition and Image Analysis 2024 Vol. 34 No. 3 P. 844–854

Improving image quality is becoming an increasingly popular task, especially when working with mobile devices. One common approach to image enhancement is the use of convolutional neural networks. However, to achieve good results, such networks must be large enough, otherwise there is a risk of unwanted artifacts. In addition, large convolutional neural networks require significant ...

Added: September 21, 2026

Streptococci Recognition in Microscope Images Using Taxonomy-based Visual Features

Aleksei Samarin, Alexander Savelev, Aleksei Toropov et al., Optical Memory and Neural Networks (Information Optics) 2024 Vol. 33 P. 424–434

This study explores the development of classifiers for microbial images, specifically focusing on streptococci captured via microscopy of live samples. Our approach uses AutoML-based techniques and automates the creation and analysis of feature spaces to produce optimal descriptors for classifying these microscopic images. This technique leverages interpretable taxonomic features based on the external geometric attributes ...

Added: September 21, 2026

Specialized Image Descriptors Adaptation for Polyp Recognition over Endoscopic Images

Aleksei Samarin, Aleksei Toropov, Alexander Savelev et al., Pattern Recognition and Image Analysis 2024 Vol. 34 No. 4 P. 1053–1060

This paper presents a novel approach to classification in biomedical imaging, specifically targeting polyp recognition in video endoscopy snapshots. Our method leverages specialized image descriptors to enhance the accuracy and robustness of polyp recognition. By employing these specialized descriptors, we address the challenges inherent in analyzing biomedical images from open datasets. Our approach not only ...

Added: September 21, 2026

Lightweight Image Preprocessing Model for Improving Microorganism Detection in Microscopic Scenes

Самарин А. В., Торопов А. Г., Савельев А. Г. et al., Pattern Recognition and Image Analysis 2024 Vol. 34 No. 4 P. 1044–1052

This paper presents a study aimed at improving the detection quality of small-sized microorganisms under challenging microscopic conditions through the application of a lightweight combined image preprocessing model. We focused on the task of detecting diplococci in images obtained through dynamic sample microscopy. The proposed approach employs predefined filters for image preprocessing, combined with the ...

Added: September 21, 2026

Advancements in Signal, Image and Video Processing

Singapore: Springer Singapore, 2025.

Added: September 21, 2026

Interpretable Lazy Classification with Interval Pattern Structures and Local Interval Explanations

Tomat A., Sergei O. Kuznetsov, International Journal of Approximate Reasoning 2026 Vol. 197 Article 109754

Interval Pattern Structures (IPS) provide a natural way to represent local, human-readable explanations for predictions on numerical data through vectors of intervals interpreted as axis-parallel hyper-rectangles. In this paper, we develop and evaluate an IPS-based k-nearest neighbors classifier, IPS-KNN, that explains each prediction through a single local interval description rather than through the aggregation of ...

Added: September 21, 2026

IDAP++: Advancing Divergence-Based Pruning via Filter-Level and Layer-Level Optimization

Aleksei Samarin, Nazarenko A., Kotenko E. et al., / Series arXiv "math". 2025. No. 2511.20141.

This paper presents a novel approach to neural network compression that addresses redundancy at both the filter and architectural levels through a unified framework grounded in information flow analysis. Building on the concept of tensor flow divergence, which quantifies how information is transformed across network layers, we develop a two-stage optimization process. The first stage ...

Added: September 21, 2026

Modernized Nonlocal Blocks for Infrared Camera Image Segmentation of the Human Eye

Aleksei Samarin, Alexander Savelev, Aleksei Toropov et al., Pattern Recognition and Image Analysis 2025 Vol. 35 No. 2 P. 169–178

This study explores the incorporation of specialized self-attention mechanisms into deep learning architectures, with a particular emphasis on segmenting human iris and pupil regions in infrared images. In this work, we present some modified versions of nonlocal blocks designed to enhance self-attentive properties while addressing the distinct characteristics of infrared imaging data. By applying these customized ...

Added: September 21, 2026

Non-Contrast Brain CT Images Segmentation Enhancement: Lightweight Pre-Processing Model for Ultra-Early Ischemic Lesion Recognition and Segmentation

Aleksei Samarin, Alexander Savelev, Aleksei Toropov et al., Journal of Imaging 2025 Vol. 11 No. 10 Article 359

Timely identification and accurate delineation of ultra-early ischemic stroke lesions in non-contrast computed tomography (CT) scans of the human brain are of paramount importance for prompt medical intervention and improved patient outcomes. In this study, we propose a deep learning-driven methodology specifically designed for segmenting ultra-early ischemic regions, with a particular emphasis on both the ...

Added: September 21, 2026

Pattern Recognition. ICPR 2024 International Workshops and Challenges

Springer, Cham, 2025.

Added: September 21, 2026

Automation of Multi-Class Microscopy Image Classification Based on the Microorganisms Taxonomic Features Extraction

Aleksei Samarin, Alexander Savelev, Aleksei Toropov et al., Journal of Imaging 2025 Vol. 11 No. 6 P. 1–20

This study presents a unified low-parameter approach to multi-class classification of microorganisms (micrococci, diplococci, streptococci, and bacilli) based on automated machine learning. The method is designed to produce interpretable taxonomic descriptors through analysis of the external geometric characteristics of microorganisms, including cell shape, colony organization, and dynamic behavior in unfixed microscopic scenes. A key advantage ...

Added: September 21, 2026

Балканские войны 1912–1913 гг. в современных национальных СМИ Сербии как символ единения балканских народов

Мулина А. А., В кн.: Балканские войны 1912–1913 гг.: далекие предпосылки и долгое эхо.: М.: Институт славяноведения РАН, 2024. С. 287–297.

В данной статье рассматривается вопрос отражения событий 1912–1913 гг. в национальных СМИ Сербии в 2012–2013 и 2022–2023 гг. Опираясь на «большие данные», полученные из сервиса Google, а также на материалы качественной газеты «Политика», автор анализирует особенности освещения эпизодов Балканских войн, а также запросы пользователей интернета на территории Сербии по темам, связанным с событиями 1912–1913 гг. ...

Added: April 21, 2026

Президентские выборы в Турецкой Республике в информационном пространстве стран Балканского полуострова: медиагеографический анализ

Мулина А. А., Якова Т. С., Вестник Российского университета дружбы народов. Серия: Литературоведение, журналистика 2025 Т. 30 № 1 С. 161–171

The article presents the results of a study of the information space of the Balkan states conducted during the presidential elections in Turkey (2023): the authors referred to this period as one of the most striking political events in the country over the past five years. The purpose of the proposed work is to identify ...

Added: April 21, 2026

Политические эффекты государственных цифровых платформ и сервисов в автократиях

Balayan A. A., Томин Л. В., Публичная политика 2023 Т. 7 № 1-2 С. 108–117

The paper is devoted to the study of certain aspects of the digitalization of public administration in autocracies, primarily government platforms and digital services. The analysis of the political effects of government platforms and services is carried out in the broader context of the study of new cybernetic mode of governance that complement/transform the disciplinary ...

Added: March 31, 2026

Цифровое общество: теоретическая модель и российская действительность

Smirnov A., Мониторинг общественного мнения: Экономические и социальные перемены 2021 № 1 С. 129–153

The article considers a theoretical model of digital society based on four concepts: super-connectivity, platformisation, datafication, and algorithmic governance. The model describes how the digitalisation of society deepens: from the transfer of individual practices and social interactions to a new social order based on big data. Analysis of panel data from the 2003–2018 longitudinal survey ...

Added: March 18, 2026

Прогнозирование миграционных процессов методами цифровой демографии

Smirnov A., Экономика региона 2022 Т. 18 № 1 С. 133–145

The nature and intensity of migration processes are constantly changing. Demographic statistics are not suitable for obtaining up-to-date information and making timely decisions in the field of demographic and social policy. Thus, digital demography is becoming increasingly important, as this area of population research uses new methods and data sources resulting from the Internet expansion ...

Added: March 18, 2026

Improving guest satisfaction by identifying hotel service micro-elements failures through Deep Learning of online reviews

Kazakov S., Cuesta-Valiño P., Butkovskaya V. et al., Cuadernos de Gestion 2025 Vol. 25 No. 1 P. 71–88

This study provides an in-depth examination of often-overlooked hotel service micro-elements within the broader spectrum of hospitality services, with the aim of improving service delivery and enhancing guest satisfaction. To achieve this, we develop a methodological framework that integrates: (a) VADER text-based sentiment analysis, (b) a robust logistic regression procedure to identify the specific hotel ...

Added: February 28, 2026