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Preprints of the IFAC Conference on Manufacturing Modelling, Management, and Control MIM ‘2013 June 19 to 21, 2013, Saint Petersburg, Russia
СПб. :
-, 2013.
Nowadays, production control problems has been widely studied and a lot of valuable approaches have been implemented. Some work addresses the problem of tracking the uncertain demand in case of uncertain production speeds. The uncertainties are described by deterministic inequalities and the performance is analyzed in from of the worst-case scenario. First, simple mathematical models are introduced and the control problem is formulated. In continuous-time, the cumulative output of a manufacturing machine is the integral of the production speed over time. At the same time, the production speed is bounded from below and above, and hence the manufacturing process can be modeled as an integrator with saturated input. Since the cumulative demand (which is the reference signal to track) is a growing function of time, it is natural to consider control policies that involve integration of the mismatch between the current output and current demand. In the simplest consideration it results in models similar to a double integrator closed by saturated linear feedback with an extra input that models disturbances of a different nature. This model is analyzed and particular attention is devoted to the integrator windup phenomenon: lack of global stability of the system solutions that correspond to the same input signal.
Chapters
Afanasiev V., , in: Preprints of the IFAC Conference on Manufacturing Modelling, Management, and Control MIM ‘2013 June 19 to 21, 2013, Saint Petersburg, Russia.: St. Petersburg: -, 2013. P. 1505–1509.
An optimal control problem is formulated for a class of nonlinear systems which can be presented by system with linear structure and state-depended coefficients (SDC). The system being under the influence of uncontrollable disturbance is supposed. The linearity of the transformed system structure and the quadratic functional make it possible to pass over from the ...
Added: September 23, 2013
Dorofeuk A., Dorofeuk Y. A., Pokrovskaya I., , in: Preprints of the IFAC Conference on Manufacturing Modelling, Management, and Control MIM ‘2013 June 19 to 21, 2013, Saint Petersburg, Russia.: St. Petersburg: -, 2013. P. 1826–1831.
Added: June 5, 2014
Lazarev A. A., Мусатова Е. Г., Хуснуллин Н. Ф., , in: Preprints of the IFAC Conference on Manufacturing Modelling, Management, and Control MIM ‘2013 June 19 to 21, 2013, Saint Petersburg, Russia.: St. Petersburg: -, 2013. P. 1684–1687.
In this research it was considered the particular case of a railway problem, specifically, the construction of orders delivery schedule for one locomotive plying among three railway station. In this paper it was suggested a polynomial algorithm and were shown the results of a computing experiment. ...
Added: October 20, 2014
Research target:
Computer Science
Language:
English
Gadzhimirzaev S., Хельвас А. В., Computer Research and Modeling 2026 Vol. 18 No. 2 P. 423–438
This article presents a model of a fully automated warehouse with deep storage racks designed
for boxed goods storage. The study focuses on optimizing warehouse operations through discrete
multiagent simulation of shuttle movements for pallet loading and unloading tasks. The authors
investigate various product placement strategies, including the Nearest Channel Positioning Algorithm
(NCPA), Most Empty ChannelGroup Placement (MECGP), and ...
Added: June 24, 2026
Podolskaia E., Sinitsina A., European Journal of Forest Engineering 2026 Vol. 12 No. 1 P. 7–21
Machine learning in transport modeling has become a trend in science and industry. In this paper, we observe its main directions and focus on a dataset of seasonal road creation. Seasonality as a parameter in transport modeling has a significant impact on transport scenarios but is underestimated worldwide and in Russia, despite modern data challenges. ...
Added: June 24, 2026
Atlasov B., Selskiy A., Russian Journal of Information Technology in Sports 2025 Vol. 2 No. 1 P. 13–21
The article examines the current state of the global virtual and augmented reality (VR/AR) technology market in sports, noting its growth, although slower than previously expected. Special attention is paid to the Russian market, where the development of VR technologies in sports lags behind world leaders such as the United States, EU countries and China, ...
Added: June 23, 2026
IEEE, 2026.
The 9th International Scientific Conference on Information, Control, and Communication Technologies (ICCT-2025) had been held October 7-11, 2025 in Gomel, Belarus. The main technical areas and applications covered by the proceedings are optoelectronics, acousto-optic, microwave technology, antenna systems, measuring technology, metamaterials, nanostructures, nanofilms, photonic crystals, biology and medicine, biophotonics, bioengineering, neural networks in communication technologies; ...
Added: June 23, 2026
Buzaev F., Mullakhmetov R., Bogachev R. et al., Association for Computational Linguistics, 2026.
Playlist generation based on textual queries using large language models (LLMs) is becoming an important interaction paradigm for music streaming platforms. User queries span a wide spectrum from highly personalized intent to essentially catalog-style requests. Existing systems typically rely on non-personalized retrieval/ranking or apply a fixed level of preference conditioning to every query, which can ...
Added: June 22, 2026
Herbert A., Cherednichenko O., Lybrand T. et al., International Journal of Molecular Sciences 2025 Vol. 26 No. 6 Article 2422
The double-stranded RNA editing enzyme ADAR1 connects two forms of genetic programming, one based on codons and the other on flipons. ADAR1 recodes codons in pre-mRNA by deaminating adenosine to form inosine, which is translated as guanosine. ADAR1 also plays essential roles in the immune defense against viruses and cancers by recognizing left-handed Z-DNA and ...
Added: June 22, 2026
Калужский печатный двор, 2026.
Conference Proceedings INTERNATIONAL CONFERENCE
“Mathematical Ideas of Academician
P.L. Chebyshev, Their Applications in Natural
Sciences and Artificial Intelligence Technologies”
dedicated to the 205th anniversary of his birth ...
Added: June 20, 2026
Stognieva O., Чеснокова Н. Е., Отечественная и зарубежная педагогика 2026 Т. 1 № 3 (115) С. 123–131
Integration of generative artificial intelligence tools into educational practice highlights the need for pedagogically grounded approaches to their use in the creation of educational video content, which is increasingly applied in language and professionally oriented instruction.
The purpose of this article is to conduct a comparative analysis of educational video content created using generative AI tools ...
Added: June 20, 2026
Cherednichenko O., Herbert A., Poptsova M., Computational and Structural Biotechnology Journal 2025 Vol. 27 P. 992–1000
Large language models (LLMs) in genomics have successfully predicted various functional genomic elements. While their performance is typically evaluated using genomic benchmark datasets, it remains unclear which LLM is best suited for specific downstream tasks, particularly for generating whole-genome annotations. Current LLMs in genomics fall into three main categories: transformer-based models, long convolution-based models, and state-space models ...
Added: June 19, 2026
Poptsova M., Briefings in Bioinformatics 2025 Vol. 26 No. 2 P. 1–11
Kolmogorov–Arnold networks (KANs) emerged as a promising alternative for multilayer perceptrons (MLPs) in dense fully connected networks. Multiple attempts have been made to integrate KANs into various deep learning architectures in the domains of computer vision and natural language processing. Integrating KANs into deep learning models for genomic tasks has not been explored. Here, we ...
Added: June 19, 2026
Анненков А. Н., Nesterov R., Моделирование и анализ информационных систем 2026 Т. 33 № 2 С. 176–205
Declarative process models are widely used in process mining to describe flexible process behavior through sets of constraints. However, models discovered automatically from event logs may contain inconsistent constraints, which can make them difficult to interpret and unusable for execution, conformance checking, or further analysis. Existing methods for consistency analysis either rely on automata-based constructions ...
Added: June 18, 2026
Cham: Springer Publishing Company, 2026.
The four-volume set LNCS 16483-16486 constitutes the refereed conference proceedings of the 48th European Conference on Information Retrieval, ECIR 2026, held in Delft, The Netherlands, during March 29–April 2, 2026.
The 46 full papers and 37 short papers presented together with 10 findings papers, 9 reproducibility papers, 17 resource papers, 11 workshop papers, 7 tutorial papers, ...
Added: June 18, 2026
Poddiakov A., Троицкий вариант. Наука 2026 № 12 С. 24–25
В научно-популярной заметке представлен обзор содержания поста филдсовского медалиста Тимоти Гауэрса о возможностях ИИ в математике и содержания комментариев под постом. Обзор сделан в основном чат-ботом DeepSeek. В заключение обсуждается возможность не только решения задач искусственным интеллектом, но и их постановки. ...
Added: June 18, 2026
Beznosikov A., Kormakov G., Grigorievskiy A. et al., Journal of Optimization Theory and Applications 2026 Vol. 209 Article 18
The objective of Vertical Federated Learning (VFL) is to collectively train a model using features available on different devices while sharing the same users. This paper focuses on the saddle point reformulation of the VFL problem via the classical Lagrangian function. We first demonstrate how this formulation can be solved using deterministic methods.More importantly, we explore various stochastic modifications to ...
Added: June 17, 2026
Chertenkov V. I., Shchur L., Lobachevskii Journal of Mathematics 2026 Vol. 47 No. 2 P. 720–727
Supervised machine learning is successfully applied to the study of critical phenomena and allows us to obtain a numerical estimate of the phase transition temperature and the correlation length exponent. We discuss the influence of possible systematic errors, as well as statistical errors, on the accuracy of such numerical estimates. Errors in the training and ...
Added: June 16, 2026
Deeb B., Andrey V. Savchenko, Makarov I., IEEE Access 2026 Vol. 13 P. 56283–56295
Speech Emotion Recognition has gained considerable attention in speech processing and machine learning due to its potential applications in human-computer interaction, mental health monitoring, and customer service. However, state-of-the-art models for speech emotion recognition use many parameters, which leads to computational complexity. In this paper, we introduce a novel deep-learning model to enhance the accuracy ...
Added: June 16, 2026
Makarov N., Savchenko A., Zemtsova I. et al., Scientific Reports 2025 Vol. 15 Article 26641
The grey wolf (Canis lupus) is a pivotal species for ecological studies. As a key participant in ecosystem
processes, it also serves as a model for investigating social structure formation and ecological
adaptation. However, the species’ complex social behavior, spatial dynamics, and expansive habitats
make monitoring and population assessments across large areas particularly challenging. In recent
years, audio traps ...
Added: June 16, 2026
Vasilev R., Savchenko A., Blinov P. et al., Frontiers in Medicine 2026 Vol. 13
Automated disease screening systems face challenges when applied to multi-class medical image analysis, particularly under severe class imbalance inherent in clinical datasets. Retinal fundus imaging enables non-invasive screening for multiple ocular and systemic diseases simultaneously, yet current automated systems typically assess risk for only a single pathology or a limited disease range. We developed a ...
Added: June 16, 2026
Novopoltsev M., Tulenkov A., Murtazin R. et al., IEEE Access 2025 Vol. 13 P. 188170–188181
Video-based Isolated Sign Language Recognition (ISLR) problem presents significant challenges in scaling across diverse languages due to data scarcity and the computational costs associated with training of language-specific models. In this paper, we introduce a novel training pipeline that leverages self-supervised learning on a large-scale sign language dataset. To obtain the foundation model, we utilize ...
Added: June 16, 2026
Stepin A., Mozikov M., Kabanov A. et al., IEEE Access 2026 Vol. 14 P. 48127–48144
The deployment of large language models (LLMs) in interactive roles such as automated negotiators, customer service agents, and strategic partners requires them to handle not only logical tasks but also the socio-emotional dimensions of interaction. In these situations, success often relies on understanding social cues, building trust, and using persuasion effectively. These skills are closely ...
Added: June 16, 2026
Abdullaeva I., Karpukhin I., Filatov A. et al., IEEE Access 2026 Vol. 14 P. 59390–59408
Event sequences, a specialized type of tabular data annotated with timestamps, are prevalent across practical domains such as finance, retail, social networks, and healthcare. Despite the importance of event sequence modeling and analysis, there has been little effort to adapt Large Language Models (LLMs) to this domain. In this paper, we propose a novel solution ...
Added: June 16, 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
Optimal Control for Stochastic Multi-agent Systems With the Use of Parallel Hybrid Genetic Algorithm
Akopov A. S., Beklaryan A., , in: Numerical Computations: Theory and Algorithms. 4th International Conference, NUMTA 2023, Pizzo Calabro, Italy, June 14–20, 2023, Revised Selected Papers, Part IVol. 14476.: Springer Publishing Company, 2025. P. 273–280.
In modern times, stochastic large-scale multi-agent systems (MAS) aimed at supporting socio-economic planning are being developed. There is a well known problem of a high computational complexity task of an optimal control for multiple agents’ behaviour in models of random interactions. In particular, agents (such as sellers and buyers) should make individualised decisions on establishing ...
Added: November 23, 2025
Ronzhina M., Manita L., , in: Systems Analysis: Modeling and Control: Materials of the International Conference in memory of Academician A.V. Kryazhimskiy, Moscow, January 23–24, 2024. Abstracts.: -, 2024. P. 25–26.
For some class of small-dimensional optimal control problems we found a family of extremals in the form of logarithmic spirals. These extremals reach the singular surface in a finite time, while the control performs an infinite number of rotations around the circle. ...
Added: October 8, 2025