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Parameter Estimation of Combinational Circuits Using Machine Learning Methods
P. 937–942.
Попова Т. И., Масленикова А. С., В кн.: Компьютерная лингвистика и интеллектуальные технологии: По материалам ежегодной международной конференции «Диалог». Выпуск 24.Issue 24.: M.: Max press, 2026. С. 420–428.
This study focuses on developing and comparing methods for automatic annotation of speech formulas in a corpus of Russian internet comments. Speech formulas are a class of multiword expressions that convey emotional reactions in dialogue. The research material consisted of a corpus of 10,000 comments (157,261 tokens) collected from five Telegram channels. Dictionary-based formal search ...
Added: June 29, 2026
Новиков Р. С., Novopashin M., Pozin B., Programming and Computer Software 2026 Vol. 52 No. 1 P. 28 – 38
Added: June 26, 2026
Korotayev A., Chernomorchenko I., Медведев И. А., Восток. Афро-азиатские общества: история и современность 2026 № 3 С. 117–130
This study employs machine learning methods to rank factors contributing to large-scale armed and unarmed destabilization across Asian and African countries. Analysis reveals that African nations demonstrate greater vulnerability to armed destabilization (up to full-scale civil wars), whereas Asian countries are more prone to less violent unarmed forms (mass antigovernment demonstrations, riots, general strikes and ...
Added: June 21, 2026
Butorova A., Bobakov V., Sergeev A. et al., European Physical Journal: Special Topics 2026 P. 1–19
This paper presents a review of artificial intelligence (AI) methods for failure prediction in data center cooling systems, with a focus on the integration of digital twins (DTs), physics-informed learning, and graph-based models. Positioned within complex network science, this review addresses a limitation of conventional graph approaches—their reliance on pairwise connectivity—whereas real-world failures often arise ...
Added: June 10, 2026
Untila K., Tasenko O., В кн.: Современная лингвистика: ключ к диалогу. Труды и материалы IV Казанского международного лингвистического саммита.Т. 1: СОВРЕМЕННАЯ ЛИНГВИСТИКА: КЛЮЧ К ДИАЛОГУ.: Каз.: Издательство Казанского университета, 2024. С. 221–224.
Шизофрения – это хроническое психическое расстройство, которое выражается как комбинация психотических симптомов – таких как галлюцинации, бред и дезорганизация когнитивных функций. У многих пациентов с диагнозом шизофрения обнаруживаются нарушения речи.
Для исследования были отобраны рассказы об истории из жизни из корпуса 3D. В качестве личных историй были собраны ответы на вопросы «Какой самый лучший или запоминающийся ...
Added: June 8, 2026
Seul: PMLR, 2026.
Added: June 4, 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
Avdoshin S. M., Pesotskaya E. Y., Информационные технологии 2026 Т. 32 № 4 С. 185–194
With the rapid advancement of artificial intelligence, and deep learning in particular, models have emerged that are capable of delivering highly accurate predictions. However, the internal logic of such models remains difficult to interpret—an issue of critical importance, especially in domains where the correctness of an algorithm directly affects high-stakes decision-making. One promising avenue for ...
Added: May 8, 2026
Vasilev A., Kapitanov A., Roman Solovyev et al., PeerJ Computer Science 2026 Vol. 12 Article 3724
This article introduces MinMAE, a novel activation calibration method for Post-Training Quantization (PTQ) that significantly reduces accuracy loss in Convolutional Neural Networks (CNN). Motivated by the need for high-fidelity quantization without costly retraining, MinMAE directly minimizes the Mean Absolute Error (MAE) between original and dequantized activations, making it robust to outliers that degrade standard methods. ...
Added: May 3, 2026
Solovyev Roman A., Telpukhov Dmitry, Shafeev I. et al., Technologies 2026 Vol. 14 No. 3 Article 169
With the continuous scaling of semiconductor design technologies, evaluating static IR drop has become a critical bottleneck in the physical synthesis flow. This paper presents a machine learning-based framework that transforms the power delivery network (PDN) analysis problem into an image-to-image translation task using a U-Net architecture with MaxViT and EfficientNet encoders. By implementing a ...
Added: May 3, 2026
Neznanov A., Glushko A., Овчинников С. et al., В кн.: Интеллектуальный анализ данных в нефтегазовой отрасли.: М.: ООО «Геомодель Развитие», 2024. С. 140–143.
With the development of monitoring systems, now we have the opportunity to collect key performance indicators of devices in the process of artificial lift. Every day a huge amount of telemetry is generated by our devices, which can be used to forecast the working mode and health state of the equipment after the process of ...
Added: April 29, 2026
Kirsanova E., Pakshin P., Право и экономика 2026 № 3 (456) С. 26–34
The article examines the legal regime of intellectual property created by artificial intelligence. Changes to the existing legal framework towards recognizing artificial intelligence as a legal entity would violate the rationale and fundamental principles of the intellectual property rights system. This article provides an overview of different views on the rationale for granting copyright to ...
Added: April 28, 2026
Lazarev M., Derkach D., Ratnikov F., Scientific data 2026 Vol. 13 Article 1003
In this study, we present a comprehensive set of experimental data aimed at uncovering the mechanisms and regularities governing the deformation behavior of composites reinforced with continuous carbon fibers (CF) based on thermoplastic polymers. This work describes data extraction techniques that can later be used to optimize the mechanical properties of such structures using neural ...
Added: April 23, 2026
Krasnov L., Malikov D., Kiseleva M. et al., Journal of Medicinal Chemistry 2026 Vol. 69 No. 8 P. 8838–8851
In this work, we developed a straightforward data-driven approach to predict the cytotoxicity of metal complexes based entirely on their (metal + ligands) composition. To this end, we have manually curated MetalCytoToxDB─a comprehensive experimental database comprising 26,500 IC50 values for 7050 metal complexes against 754 cell lines from 1921 articles. Based on these, machine learning ...
Added: April 23, 2026
Ершов И. А., Системная инженерия и инфокоммуникации 2025 № 4 С. 11–14
The heat consumption of residential buildings is a stochastic series. It is necessary for the design of thermal energy regulators the creation of a neural network model. In the paper, the model is carried out based on Long Short-Term Memory (LSTM). The high accuracy of reproducing the series was achieved by training the model on ...
Added: April 22, 2026
Чудинова О. С., Первицкая Л. А., Ramenskaya A., Индустриальная экономика 2026 № 1 С. 65–78
This article is devoted to the development of an algorithm for analyzing news information using machine learning methods implemented in Python libraries. The choice of tools used at each stage of the algorithm is justified by calculating metrics for the quality of the solution to the corresponding machine learning problems. The algorithm’s results are presented ...
Added: April 20, 2026