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2024 Sixth International Conference Neurotechnologies and Neurointerfaces (CNN)
IEEE, 2024.
Chapters
Monahhova E., Morozova A., Gorodnicheva Y. et al., , in: 2024 Sixth International Conference Neurotechnologies and Neurointerfaces (CNN).: IEEE, 2024. P. 120–123.
The current study examined behavioral and electrophysiological responses to attitude-consistent and attitude-inconsistent auditory deepfakes on COVID-19 vaccination topic. Deepfakes portrayed Russian media- influencers (two speaker types: a prominent medical doctor and COVID-dissident), broadcasting statements opposite to their public opinion. We hypothesized that people would evaluate the trust-associated statements higher to deepfake aligning with their internal ...
Added: October 10, 2024
Koriakina M., Луков М., Барцева К. et al., , in: 2024 Sixth International Conference Neurotechnologies and Neurointerfaces (CNN).: IEEE, 2024. P. 70–73.
This study explored different paradigms and protocols to investigate participants' psychoemotional states. The study involved testing a variety of stimuli, including videos with dramatic content, videos with neutral themes, physiological stress induction, and presentation of polar stimuli. The subjects' emotional reactions were assessed using the DES. The study showed a decrease in shame-related emotions in ...
Added: October 10, 2024
Pomelova E., Popyvanova A., Bredikhin D. et al., , in: 2024 Sixth International Conference Neurotechnologies and Neurointerfaces (CNN).: IEEE, 2024.
Transcranial random noise stimulation (tRNS) is a type of transcranial electrical stimulation. tRNS at the primary motor cortex affects corticospinal system (CSS) excitability. We assume that applying analogous protocols at the spinal cord level could similarly influence on CSS excitability, enabling a comparison of stimulation outcomes. This research aims to scrutinize the impact of combining ...
Added: October 11, 2024
Morozova A., Monahhova E., Gorodnicheva Y. et al., , in: 2024 Sixth International Conference Neurotechnologies and Neurointerfaces (CNN).: IEEE, 2024. P. 124–127.
Fake news has become a serious problem with the development of the Internet and social networks. Due to their rapid spread and influence on people's opinions and decision-making, the need to combat media fakes become evident. This pilot study investigated behavioral and neuropsychological responses to fake news corrections that indicate the presence of the fake. ...
Added: October 23, 2024
Ivanova M., Grigoriy Kopytin, Moiseeva V. et al., , in: 2024 Sixth International Conference Neurotechnologies and Neurointerfaces (CNN).: IEEE, 2024.
Prediction error and volatility estimate are important concepts in the predictive coding theory. In the present study, we derive the values of prediction error and volatility estimate from a hierarchical Bayesian model - Hierarchical Gaussian Filter. Using support vector machine (SVM) method, we predict the values of prediction error and volatility estimate from brain activity ...
Added: November 29, 2024
Martinez-Saito M., Alexey Belianin, Grygory Kopytin et al., , in: 2024 Sixth International Conference Neurotechnologies and Neurointerfaces (CNN).: IEEE, 2024.
In the field of economics, traditional decision-making models are often built on a foundation of extensive assumptions that might not always hold true in practical situations. Alternatively, models that utilize adaptive learning without assumptions are capable of adjusting to varying levels of uncertainty, though this adaptability might come at the expense of efficiency. In scenarios ...
Added: November 29, 2024
Perevoznyuk G., Ragimova A., Pleskovskaya A. et al., , in: 2024 Sixth International Conference Neurotechnologies and Neurointerfaces (CNN).: IEEE, 2024. P. 144 – 147.
The impact of transcranial direct current stimulation (tDCS) on motor imagery (MI) holds significant potential for neurorehabilitation. Most studies focus on tDCS of the primary motor cortex (M1), neglecting other cerebral cortex regions involved in MI. This study examines the effects of tDCS of the visual cortex using different currents (anode, cathode, sham) on MI. ...
Added: December 3, 2024
Perevoznyuk G., Ragimova A., Batov A. et al., , in: 2024 Sixth International Conference Neurotechnologies and Neurointerfaces (CNN).: IEEE, 2024. P. 140 – 143.
This study is dedicated to identifying differences in 4 types of motor imagery: first-person visual imagery, third-person visual imagery, kinesthetic imagery and sensory imagery. The research task includes Transcranial Magnetic Stimulation (TMS) over the motor cortex, during which Motor Evoked Potentials over 3 arm muscles will be measured. Also, correlations will be calculated between MEP ...
Added: December 3, 2024
Mokienko O., Zisman M. A., Bobrov Pavel et al., American Journal of Physical Medicine and Rehabilitation 2026 Vol. 105 No. 6 P. 555–563
Brain-computer interfaces (BCIs) represent a promising technology for restoring lower limb motor functions and gait after stroke. The application of BCIs in this field is supported by a limited number of studies. The objective of the review was to systematically and critically evaluate the current evidence on the use of BCIs for lower limb function ...
Added: May 28, 2026
М.: Институт проблем управления им. В.А. Трапезникова РАН, 2024.
В сборник вошли материалы VIII Международной научной конференции «Информационные технологии и технические средства управления» (ICCT-2024). На конференции были рассмотрены вопросы, касающиеся перспектив развития научного приборостроения в телекоммуникационных и управляющих системах, биомедицинской информатики, аппаратного и программного обеспечения информационнокоммуникационных систем, надежности, диагностики и неразрушающего контроля, систем управления и автоматизации, цифровых экосистем, управления производством и логистикой, методов математического ...
Added: May 27, 2026
Degtyarev A., Bakhurin S., Yudin N., DSPA 2026 P. 1–6
This paper investigates one possible solution to the problem of self-interference cancellation (SIC) arising in the design of in-band full-duplex (IBFD) communication systems. Self-interference cancellation is performed in the digital domain using multilayer nonlinear models adapted via gradient-based optimization. The presence of local minima and saddle points during the adaptation of multilayer models limits the ...
Added: May 26, 2026
Androsov I., Proceedings of the Institute for System Programming of the RAS 2026 Vol. 38 No. 3 P. 87–114
This paper examines echo state networks (ESNs), one of the most prevalent approaches to
implementing reservoir computing. An ESN consists of a recurrent neural network with fixed (untrained)
weights and a readout layer that is typically linear and trainable. This approach enables the creation of energyefficient and computationally efficient neural networks capable of real-time learning. However, since ...
Added: May 26, 2026
Караваева Е. А., Кулигин Л. А., Rezunik L. et al., Труды Института системного программирования РАН 2026 Т. 38 № 3 С. 67–94
В статье представлен метод рефакторинга исходного кода на основе интеграции большой языковой модели (LLM) и расширенной UML-модели программного кода. Предложенный подход позволяет выявлять проблемные участки кода с использованием функций тревожности и структурных метрик классов, а затем выполнять автоматизированный рефакторинг. Ключевой особенностью метода является использование LLM для генерации формальных спецификаций на языке OCL (Object Constraint Language), ...
Added: May 24, 2026
Tyukin I., Tyukina T., van Helden D. P. et al., Information Sciences 2024 Vol. 678 Article 120856
AI errors pose a significant challenge, hindering real-world applications. This work introduces a novel approach to cope with AI errors using weakly supervised error correctors that guarantee a specific level of error reduction. Our correctors have low computational cost and can be used to decide whether to abstain from making an unsafe classification. We provide ...
Added: May 23, 2026
Zaikin A., Sviridov I., Sosedka A. et al., Technologies 2026 Vol. 14 No. 2 Article 84
High-dimensional tabular data are common in biomedical and clinical research, yet conventional machine learning methods often struggle in such settings due to data scarcity, feature redundancy, and limited generalization. In this study, we systematically evaluate Synolitic Graph Neural Networks (SGNNs), a framework that transforms high-dimensional samples into sample-specific graphs by training ensembles of low-dimensional pairwise ...
Added: May 23, 2026
Chertopolokhov V., Mukhamedov A., Bugriy G. et al., IEEE Access 2026 Vol. 14 P. 14369–14392
This study presents on-the-fly identification and multi-step prediction of nonlinear systems with delayed inputs using a dynamic neural network combined with a smooth projection onto ellipsoids. The projection enforces parameter constraints that guarantee stability, while a Lyapunov–Krasovskii analysis yields computable ultimate error bounds. Riccati-type matrix inequalities are derived, providing an efficient vectorization–projection–devectorization implementation suitable for ...
Added: May 22, 2026
Loshkareva M. E., Matveeva N., Вестник Томского государственного университета. История 2026 № 100 С. 112–118
This research is an endeavor to apply social network analysis (SNA) to the study of a medieval narrative source. The authors suppose that the use of network analysis may offer new possibilities in the study of the history of regions characterized by some political fragmentation. Authors tried to construct networks of historical interactions from 1193 ...
Added: May 22, 2026
Jin S., Komarov M. M., Scientific Reports 2026
Intrabody communication (IBC) channels offer physiological diversity that can be leveraged for passive biometric identification in wearable devices. Recent reports of over 99 per cent identification accuracy have frequently resulted from data leakage, where samples from the same subject are seen in both training and evaluation, yielding inflated and unreliable metrics. In this work, we ...
Added: May 21, 2026
Shipilov F., Barnyakov A., Ivanov A. et al., / Series Physics "arxiv.org". 2026.
A fast simulation of the detector response is a vital task in high-energy physics (HEP). Traditional Monte-Carlo methods form the backbone of modern particle physics simulation software but are computationally expensive. We present a machine-learning-based approach to fast simulation of the Focusing Aerogel Ring Imaging Cherenkov (FARICH) detector response. Given a particle track and momentum, ...
Added: May 19, 2026
Rabat: Association for Computational Linguistics, 2026.
Added: May 19, 2026
Bezzubov S., Malikov D., Krasnov L. et al., Scientific data 2026 Vol. 13 Article 727
Solubility is a crucial property of organic compounds, impacting their potential applications in synthetic chemistry, materials science and drug design. Moreover, in technological processes mixtures of solvents are often utilized, making the solubility assessment more complicated. Predicting solubility values in mixtures of solvents from a molecular structure can help to address this issue, although a ...
Added: May 19, 2026
Kondratev S., Yulia Dyrchenkova, Georgiy Nikitin et al., Technologies 2026 Vol. 14 No. 1 Article 69
This paper presents Aerokinesis, an IoT-based software–hardware system for intuitive gesture-driven control of quadcopter unmanned aerial vehicles (UAVs), developed within the Robot Operating System 2 (ROS2) framework. The proposed system addresses the challenge of providing an accessible human–drone interaction interface for operators in scenarios where traditional remote controllers are impractical or unavailable. The architecture comprises ...
Added: May 19, 2026
Kondratev S., Yulia Dyrchenkova, Georgiy Nikitin et al., Technologies 2026 Vol. 14 No. 1 Article 69
This paper presents Aerokinesis, an IoT-based software–hardware system for intuitive gesture-driven control of quadcopter unmanned aerial vehicles (UAVs), developed within the Robot Operating System 2 (ROS2) framework. The proposed system addresses the challenge of providing an accessible human–drone interaction interface for operators in scenarios where traditional remote controllers are impractical or unavailable. The architecture comprises ...
Added: May 19, 2026
Springer, 2025.
This book constitutes the refereed proceedings of the 19th International Conference on Parallel Computational Technologies, PCT 2025, held in Moscow, Russia, during April 8–10, 2025.
The 31 full papers included in this volume were carefully reviewed and selected from 122 submissions. These papers were organized under the following topical sections: High Performance Architectures, Tools and Technologies; ...
Added: May 18, 2026
Ronglin Z., Wei L., Jiahong C. et al., Journal of Signal Processing Systems 2026 Vol. 98 Article 31
To address the need for lightweight and low-latency protection in massive resource-constrained 5G Internet of Things (IoT) systems, this paper proposes Key-Controlled Modulation Hopping and Constellation Rotation (KMHCR). KMHCR is designed as a physical-layer confidentiality-enhancement mechanism that avoids bit-wise full-payload encryption in the protection pipeline. It uses a shared key derived from channel-reciprocity secret key ...
Added: May 16, 2026
Suvorov N. M., Proceedings of the Institute for System Programming of the RAS 2026 Vol. 38 No. 3(2) P. 49–66
Data Petri Nets (DPNs) extend classical Petri nets to model processes where data directly influences control-flow, enabling a comprehensive view of system behavior and possibility to detect failure points that could otherwise be hidden. Soundness is a correctness criterion that captures such failure points as deadlocks and livelocks as well as model boundedness and absence ...
Added: May 16, 2026
Федоров Н. С., Финансовый журнал 2025 Т. 17 № 6 С. 99–112
The DCF model is one of the most commonly used models in valuing companies for investment deci sions. Nevertheless, estimating the accuracy of this model remains an important research question. This article presents an assessment of the accuracy of DCF model specifications based on analyzing the variance of fair share prices of companies listed on ...
Added: May 15, 2026
Федоров Н. С., Финансы и бизнес 2025 Т. 21 № 3 С. 34–50
Currently, the role of artificial intelligence is increasingly playing a significant role in various fields, including the increasing role of machine learning in finance. On the other hand, company valuation remains an important part of research due to its difficulty in correctly predicting the accuracy of target stock prices. This study provides an analysis of ...
Added: May 15, 2026
Xiong N., Long W., He D. et al., Algorithms 2026 Vol. 19 No. 5 Article 386
In the era of data-driven education, educational social networks generate large volumes of high-dimensional and complex-structured data through learner interactions, collaborative activities, and resource-sharing behaviors, posing significant challenges to traditional unsupervised learning methods. Such data often exhibit non-convex distributions, heterogeneity, and noise sensitivity, making conventional clustering approaches insufficient for capturing their intrinsic structural relationships. To ...
Added: May 13, 2026
Velichkov B., Nikolova-Koleva I., Slavcheva M., Shumen: INCOMA Ltd, 2025.
The RANLP 2025 Student Research Workshop (RANLPStud’2025) is a special track of the established international conference Recent Advances in Natural Language Processing (RANLP’2025).
The RANLPStud is being organised for the 9th time and this year is running in parallel with the other tracks of the main RANLP 2025 conference. The target of RANLPStud’25 is to be a ...
Added: May 12, 2026
М.: Экономический факультет МГУ им. М.В. Ломоносова, 2026.
В сборнике приводятся тексты лучших докладов участников Международной ежегодной научной конференции «Ломоносовские чтения-2025» (секция экономи ческих наук) «Настоящее и будущее социально-экономического развития: потен циал ИИ и новые вызовы», состоявшейся 9–11 апреля 2025 г. на экономическом факультете МГУ имени М. В. Ломоносова. Материалы сгруппированы по тематическим направлениям. ...
Added: May 12, 2026