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Advances in Intelligent Systems and Computing
Vol. 451: Proceedings of the First International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’16).
Springer, 2016.
Academic editor: A. Abraham, S. Kovalev, V. Tarassov, V. Snášel
This volume of Advances in Intelligent Systems and Computing contains papers presented in the main track of IITI 2016, the First International Conference on Intelligent Information Technologies for Industry held in May 16-21 in Sochi, Russia. The conference was jointly co-organized by Rostov State Transport University (Russia) and VŠB – Technical University of Ostrava (Czech Republic) with the participation of Russian Association for Artificial Intelligence (RAAI) and Russian Association for Fuzzy Systems and Soft Computing (RAFSSC). The volume is devoted to practical models and industrial applications related to intelligent information systems. The conference has been a meeting point for researchers and practitioners to enable the implementation of advanced information technologies into various industries. Nevertheless, some theoretical talks concerning the-state-of-the-art in intelligent systems and soft computing are included in the proceedings as well.
Chapters
Evsyutin O., Kokurina A., Мещеряков Р. В. et al., , in: Advances in Intelligent Systems and ComputingVol. 451: Proceedings of the First International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’16).: Springer, 2016.
On the example of digital images there are investigated properties of the discrete Fourier transform (DFT) used to embed information into the phase spectrum. The investigation helped to form a new steganografic algorithm that can be used in case of non- compressed images. Peculiarity of the algorithm is changeable size of information put into the ...
Added: September 8, 2019
Language:
English
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
Kibkalo Vladislav, Chertopolokhov V., Mukhamedov A. 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
Plotnikov S., Альманах современной метрологии 2024 № 2 (38) С. 140–149
The results of the analysis of data collected by the method of expert questioning of Russian scientific metrological institutes’ employees, as well as buyers of measuring instruments, are presented. ...
Added: May 21, 2026
Plotnikov S., Апрелев А. В., Апрелева М. А. et al., Альманах современной метрологии 2022 № 2 (30) С. 94–101
The results of the analysis of data from the Federal Information Fund for Ensuring the Uniformity of Measurements in terms of oscilloscopes are presented. ...
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
Pikalov V., Meshcheryakov V., Kondratev S. et al., Technologies 2026 Vol. 14 No. 1 P. 1–27
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 P. 1–15
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
Гущина В. А., / Series chemrxiv-2023-vpzhz-v2 "ChemRxiv". 2023.
All-inorganic perovskite CsPbBr3 and Cs4PbBr6 nanoparticles are being intensively studied due to their unique properties and wide range of applications; however, however, the nature of their optical properties is not yet fully understood due to the difficulty of synthesis of singlephase nanoparticles. In this article we describe the features of the synthesis of single-phase particles ...
Added: May 14, 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
Stepanyants V., Долгов И. М., Хорошилов Г. С. et al., Труды Института системного программирования РАН 2026 Т. 38 № 3 С. 95–110
Highly automated and connected vehicles are gradually entering the market. Currently, solutions are being proposed that allow these technologies to be used for cooperative driving automation, which can significantly improve traffic safety. Such technologies and their software should be tested to ensure safety before being implemented in real systems. Verification and validation of vehicular control ...
Added: May 12, 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
Derkacheva A., Sakirkina M., Kraev G. et al., /. 2026.
Comprehensive data on natural hazards and their consequences are crucial for effective for risk assessment, adaptation planning, and emergency response. However, many countries face challenges with fragmented, inconsistent, and inaccessible data, particularly regarding local-scale events. To address this data gap in Russia, we developed an end-to-end processing pipeline that scrapes news from various online sources, ...
Added: April 28, 2026
Pilé I., Deng Y., Shchur L., / Series arXiv "math". 2026. No. 2604.10254.
We investigate the spatial overlap of successive spin configurations in Markov chain Monte Carlo simulations using the local Metropolis algorithm and the Svendsen-Wang and Wolff cluster algorithms. We examine the dynamics of these algorithms for two models in different universality classes: the Ising model and the Potts model with three components. The overlap of two ...
Added: April 20, 2026
Gabdullin N., Androsov I., / Series Computer Science "arxiv.org". 2026.
Label prediction in neural networks (NNs) has O(n) complexity proportional to the number of classes. This holds true for classification using fully connected layers and cosine similarity with some set of class prototypes. In this paper we show that if NN latent space (LS) geometry is known and possesses specific properties, label prediction complexity can ...
Added: April 2, 2026