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Нейросетевая система прогнозирования результатов сезона итальянской футбольной лиги "Серия А"
Вестник Пермского университета. Серия: Математика. Механика. Информатика. 2023. № 1(60). С. 84–92.
Бутина Д., Yasnitsky L.
The article describes the development of neural network system for predicting the Italian football Lega Serie A season results. To select the initial set, thematic sites containing complete statistics on the necessary characteristics were used. The system based on cost characteristics has 12 input parameters. The average testing error of this system was 3 %. The system allows to evaluate the performance of a football team in a season within the ranking from 1 to 5 positions, where 1 is 1–4 places and entry into the Champions League, and 5 is the team leaving the league. The significance of the input parameters is revealed. The influence of input parameters on the result is also shown.
Language:
Russian
Joulitov A.K., Lomazova I.A., Proceedings of the Institute for System Programming of the RAS 2026 Vol. 38 No. 4(2) P. 215–224
In process mining, DFG (Directly-Follows Graph) models are popular due to their simplicity and clarity. However, if a process is acyclic but contains concurrent events, standard algorithms for discovering DFG models can generate "fake" cycles that do not actually exist in the event log. These cycles hinder the analysis of information processes, significantly reducing the ...
Added: September 24, 2026
Добрина Д. Н., Nesterenko A., Прикладная дискретная математика. Приложение 2026 № 19 С. 151–159
Работа содержит результаты формального анализа криптографических механизмов, входящих в состав проекта методических рекомендаций «Защищенный универсальный протокол передачи данных и управления микросхемой интеллектуальной карты» (протокол SECUNDA). Получена формальная модель и перечень трудноразрешимых математических задач, трудоёмкостью решения которых можно оценить стойкость используемых криптографических механизмов. ...
Added: September 24, 2026
I.I. Sergeev, I.A. Lomazova, Modeling and Analysis of Information Systems 2026 Vol. 33 No. 3 P. 394–419
Object-centric process mining has emerged as a powerful paradigm for analyzing event data involving multiple interacting business objects. Existing discovery techniques often rely on object-centric Petri nets with fixed arc multiplicities, limiting their ability to represent parametric resource consumption and production patterns and to capture quantitative dependencies between interacting object types. In this paper, we ...
Added: September 24, 2026
Ivan Bulychev, Savchenko A., AI 2026 Vol. 7 No. 9 Article 380
Recent advances in large language model (LLM) agents have shown promise for autonomous decision-making in recommender systems. However, existing approaches suffer from two fundamental limitations: flat agent memories that conflate different information modalities and prohibitive computational costs that prevent scaling beyond a few hundred users. We propose Hybrid-GraphRAG, a recommender system that integrates hierarchical agent ...
Added: September 24, 2026
Marinin N., Getman A., В кн.: Труды Института системного программирования РАНЧ. 2. Т. 38. Вып. 4.: ИСП РАН, 2026.
This paper investigates a method for detecting DNS tunnels in network traffic using a neural network.
To achieve this, an analysis of current detection approaches was conducted, and a dataset for neural network
training was prepared. The proposed model takes as input a sequence of characters extracted from DNS
responses. The trained model demonstrated an F1-score close to ...
Added: September 23, 2026
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
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
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
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
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
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
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
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
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
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
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
Singapore: Springer, 2025.
Added: September 21, 2026
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
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
Marinin N., Getman A., Труды Института системного программирования РАН 2026 Т. 38 № 4 С. 123–142
This paper investigates a method for detecting DNS tunnels in network traffic using a neural network.
To achieve this, an analysis of current detection approaches was conducted, and a dataset for neural network
training was prepared. The proposed model takes as input a sequence of characters extracted from DNS
responses. The trained model demonstrated an F1-score close to ...
Added: September 11, 2026
Karacharovskiy V., Ларина У. С., Резмерица А. А., Социологические исследования 2026 № 7 С. 60–75
Based on the neural network approach, the decomposition of the index of social mood in Russia for the period 2004-2024 was carried out and their dynamics for this period was modeled. The following issues are discussed: (a) the nature of the social mood' shocks in Russia, based on their connection with the concepts of politics ...
Added: May 14, 2026
Антонов Н. С., Сахарова Г. М., Stadnik N., Электронный научный журнал "Социальные аспекты здоровья населения" 2025 Т. 71 № S3 Статья 13
Significance. A sedentary lifestyle is one of the four most important risk factors for developing non-communicable diseases. Regular physical activity can prevent from 4 million to 5 million deaths annually worldwide.
Purpose. To study the prevalence of a sufficient level of daily physical activity and its three components among the adult population, men and women, in ...
Added: April 9, 2026
Pakshin P., Legal Issues in the Digital Age 2026 Vol. 7 No. 1 P. 32–48
Artificial intelligence plays a significant role in automation, minimizing human intervention in fields such as medicine, art, and law. Despite the historically close relationship between art and technology, generative AI has expanded the potential for creative activity. A significant catalyst for this process has been the proliferation of pre-trained AI systems, which have accelerated the ...
Added: March 31, 2026
Bagrov A. N., V. A. Gordin, Svetlova N. A. et al., Russian Meteorology and Hydrology 2026 Vol. 51 No. 1 P. 33–40
A technology for operational complex forecasting (postprocessing)1 of squall wind gusts at the points of weather station location in described. The technology was implemented at the Hydrometeorological Research Center of Russia. It uses the results of forecasts of several forecast models and the complex forecast of average wind. The tests have shown an increase in ...
Added: February 17, 2026