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A recommender subsystem construction for calculating the probability of a violation by a locomotive driver using machine-learning algorithms
P. 351–355.
Sidorenko V., Кулагин М. А.
This article describes the issues of analysis and assessment of the human factor for predicting the violation committed by the locomotive driver when driving the electric rolling stock. An intelligent system overview for assessing the likelihood of a violation by a locomotive driver is given. Such a system can generate recommendations depending on previously committed violations. One of the tasks is to reduce the risk of locomotive safety devices malfunctions, which are part of the locomotive electrical equipment. The solution to the problem of predicting the occurrence of possible violations is solved using tools and machine learning algorithms. A model has been built that generates recommendations for the driver based on information about previously committed violations and several static characteristics of the locomotive driver.
In book
Sidorenko V., Кулагин М. А. Varna: IEEE, 2020.
Rozhdestvenskaya E., Abramov R., Журнал социологии и социальной антропологии 2026 Т. 29 № 3 С. 244–274
The article presents an experimental study at the intersection of social anthropology and qualitative sociology. The empirical basis is a corpus of 18 short biographical sketches of collective farm peasant women from the village of Vysheley, Penza Region, created at the end of the Soviet period by school local historians and discovered by one of the authors during a ...
Added: October 7, 2026
Konstantinov A., Elizarova Anastasiya P., Utkin L., Computing, Telecommunications and Control 2026 Vol. 19 No. 1 P. 16–25
Decision trees and their ensemble extensions, such as random forests, are widely used as classification models due to their simplicity and interpretability. However, in many real-world tasks where class labels overlap in the feature space, standard decision trees rely on hard splits that create fragile decision boundaries. In these regions, small perturbations in the input ...
Added: October 2, 2026
Portnoy S., Efremov A., Voloshin A., , in: 2026 Systems of Signal Synchronization, Generating and Processing in Telecommunications (SYNCHROINFO).: Petrozavodsk: IEEE, 2026. P. 1–4.
This paper presents a deep learning-based optimization of a list-decoding algorithm for a concatenated Hamming-Reed-Solomon code transmitted over an AWGN channel with BPSK modulation. The proposed method reformulates early termination of the erasure-pattern list as a weighted regression problem, addressing class imbalance through an asymmetric Weighted Mean Squared Error (WMSE) loss function that penalizes index ...
Added: October 1, 2026
International Joint Conferences on Artificial Intelligence, 2026.
Added: October 1, 2026
Petrovanov I., Sergeev A., Krouk E., , in: 2025 XIХ International Symposium on Problems of Redundancy in Information and Control Systems (Redundancy), 5-7 Nov. 2025.: IEEE, 2025. P. 1–7.
Transport coding is a promising method for reducing message delay in packet-switched networks by adding controlled redundancy at the transport layer. Classical analytical works show that encoding k original packets into n coded packets and reconstructing the message after the first k successful deliveries effectively shifts the latency metric from the maximum to the k-th ...
Added: September 29, 2026
Portnoy S., Efremov A., Кузьмин В. В., В кн.: Распределенные компьютерные и телекоммуникационные сети: управление, вычисление, связь (DCCN-2026): материалы XXIX Международной научной конференции. Россия, Москва, 21–27 сентября 2026 г.: М.: РУДН, 2026..
В работе рассматривается возможность улучшения помехоустойчивости каскадного кода, состоящего из внутреннего кода Хэмминга (4,3) и внешнего кода Рида — Соломона (7,5) над полем GF(8), за счёт дополнительной кор рекции ошибок на основе машинного обучения. Внешний код декодируется списочным алгоритмом с перебором стираний; рассматриваются списки дли ной 5 и 10 комбинаций. Для компенсации потерь помехоустойчивости при ...
Added: September 26, 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, Aleksei Toropov, Alexander Savelev et al., , in: Pattern Recognition. ICPR 2024 International Workshops and Challenges. Kolkata, India, December 1, 2024, Proceedings, Part III. LNCS, volume 15616.: Cham: Springer, 2025. P. 308–320.
This research explores an innovative approach to enhancing the accuracy of detecting small microorganisms in complex microscopic environments. Our study introduces a streamlined, hybrid image pre-processing model specifically designed to address the challenges of identifying diplococci in live microscopy of dynamic samples. By integrating pre-defined filtering techniques with predictive adjustments for optimal applicability, our method ...
Added: September 21, 2026
Cham: Springer, 2020.
Added: September 18, 2026
Sánchez Ansola E., Rosete Suárez A., S. González L. et al., Anales de la Academia de Ciencias de Cuba 2024 Vol. 14 No. 2 Article e1596
Added: September 18, 2026
Lebedev O. B., Левченко Д. Д., Черкасов Р. И., Инженерный вестник Дона 2026 № 2(134) Статья 7
This article analyzes the impact of artificial intelligence (AI) and machine learning technologies on the development and transformation of cyberthreats and the creation of highly effective cyberdefense systems. Key trends in AI evolution are discussed, including data-, model-, application-, and human-centric approaches, and their role in shaping both defensive and offensive capabilities. It is shown ...
Added: September 12, 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
Lebedev O. B., Шмелева А. Г., Гежа Н. С., Информатика и автоматизация (Труды СПИИРАН) 2026 Т. 25 № 3 С. 720–750
This paper describes the development of a neural network model for automated analysis of medical data in electrophysiology based on deep learning methods. The relevance of this work stems from the growing need to improve the objectivity, speed, and accuracy of processing complex spatiotemporal signals, such as ECG or EEG. Convolutional neural networks (CNNs), which ...
Added: September 10, 2026
Вохминцев И. В., Вестник международных организаций: образование, наука, новая экономика 2026 Т. 21 № 2
The EAEU and the CSTO are Russia’s principal regional international organisations. Understanding, assessing, and analysing the foreign-policy positions of the countries that belong to them is a matter of the state’s national interests. This determines the purpose of the study: to identify the level and the form of cohesion in the voting of EAEU and ...
Added: September 7, 2026
Starodubov K., Гвасалия Г. В., Карасев П. И., Нано-био-технологии. Тепло- и электроэнергетика. Математическое моделирование: сборник статей III международной научно-практической конференции (Липецкий государственный технический университет, Липецк, Россия) 2025 С. 219–223
This paper discusses the concept of neural networks, convolutional neural networks, their architecture and their operation principle. The main attention is paid to testing the reliability of storing images of people as embeddings, which are considered to be unrecoverable in the original image. In the course of the research an experiment is carried out: the ...
Added: September 6, 2026
Vyacheslav D. Neverov, Lukyanov A., Andrey V. Krasavin et al., Physical Review B: Condensed Matter and Materials Physics 2026 Vol. 113 No. 2 Article 024515
We develop a neural network approach to solve the self-consistent Bogoliubov-de Gennes equations in strongly disordered s-wave superconductors. The method accurately reproduces inhomogeneous gap distributions and generalizes to system sizes far larger than those used in training. It reduces computational scaling from O(N6 ) to O(N2), enabling quantitative analysis of percolation phenomena and the superconductor-insulator ...
Added: September 5, 2026
Kazun A., Devyatnikov V., Белов М. Д., Вопросы теоретической экономики 2026 Т. 3 № 32 С. 115–135
Как понять, хорош адвокат или нет? В данной статье мы описываем методологию, позволяющую измерять качество юридической помощи через разницу между тем, что предсказывает модель машинного обучения по объективным характеристикам дела, и тем, чем дело закончилось в реальности. Мы исходим из предпосылки, что если у адвоката дела стабильно заканчиваются лучше ожидаемого, то он делает свою работу хорошо. ...
Added: August 28, 2026