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Eng. Proc., 2023, INTELS’22

15th International Conference “Intelligent Systems” (INTELS’22)

Moscow, Russia | 14–16 December 2022

Volume Editors:
Askhat Diveev, Russian Academy of Sciences, Russia
Ivan Zelinka, VSB-Technical University of Ostrava, Czech Republic
Arutun Avetisyan, Russian Academy of Sciences, Russia
Alexander Ilin, Lomonosov Moscow State University, Russia

Number of Papers: 67

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Cover Story (view full-size image): The 15th International Conference "Intelligent Systems - 2022" (INTELS'22) will be held on 14–16 December 2023 at the Russian Academy of Sciences, Moscow, Russia. It is a biennial event with a [...] Read more.
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1 pages, 173 KiB  
Editorial
Statement of Peer Review
by Askhat Diveev, Ivan Zelinka, Arutun Avetisyan and Alexander Ilin
Eng. Proc. 2023, 33(1), 1; https://doi.org/10.3390/engproc2023033001 - 08 May 2023
Viewed by 786
Abstract
In submitting conference proceedings to Engineering Proceedings, the volume editors of the proceedings certify to the publisher that all papers published in this volume have been subjected to peer review that was administered by the volume editors [...] Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))

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4 pages, 227 KiB  
Proceeding Paper
Optimality Conditions for the Principle of Trajectory Division
by Valentin Bereznev
Eng. Proc. 2023, 33(1), 2; https://doi.org/10.3390/engproc2023033002 - 09 May 2023
Viewed by 642
Abstract
This paper considers the problem of controlling a mobile robot in the presence of circular obstacles. To solve this problem, it is proposed to use the previously suggested principle of dividing permissible trajectories into a sequence of rectilinear sections and arcs of circles [...] Read more.
This paper considers the problem of controlling a mobile robot in the presence of circular obstacles. To solve this problem, it is proposed to use the previously suggested principle of dividing permissible trajectories into a sequence of rectilinear sections and arcs of circles that are the boundaries of circular obstacles. The conditions for the solution based on this principle of optimality are obtained. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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9 pages, 270 KiB  
Proceeding Paper
Quality of Labeled Data in Machine Learning: Common Sense and the Controversial Effect for User Behavior Models
by Maxim Bakaev and Vladimir Khvorostov
Eng. Proc. 2023, 33(1), 3; https://doi.org/10.3390/engproc2023033003 - 09 May 2023
Cited by 1 | Viewed by 769
Abstract
Intelligent systems today are increasingly required to predict or imitate human perception and behavior. In this, feature-based Machine Learning (ML) models are still common, since collecting appropriate training data from human subjects for the data-hungry Deep Learning models is costly. Considerable effort is [...] Read more.
Intelligent systems today are increasingly required to predict or imitate human perception and behavior. In this, feature-based Machine Learning (ML) models are still common, since collecting appropriate training data from human subjects for the data-hungry Deep Learning models is costly. Considerable effort is put into ensuring data quality, particularly in crowd-annotation platforms (e.g., Amazon MTurk), where fees of top workers can be several times higher than the median. The common knowledge is that quality of input data is beneficial for the end quality of ML models, though quantitative estimations of the effect are rare. In our study, we investigate how labeled data quality affects the accuracy of models that predict users’ subjective impressions—per the scales of Complexity, Aesthetics and Orderliness assessed by 70 subjects. The material, about 500 web page screenshots, was also labeled by 11 workers of varying diligence, whose work quality was validated by another 20 verifiers. Unexpectedly, we found significant negative correlations between the workers’ precision and R2s of the models, for two out of the three scales (r11=0.768 for Aesthetics, r11=0.644 for Orderliness). We speculate that the controversial effect might be explained by a bias in the indiligent labelers’ output that corresponds to subjectivity in human perception of visual objects. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
7 pages, 1286 KiB  
Proceeding Paper
Predictive Diagnosis of Breast Cancer Based on Cytokine Profile
by Marina Barulina, Yuliya Gergenreter, Natalia Zakharova, Vladimir Maslyakov, Vladimir Fedorov and Ivan Ulitin
Eng. Proc. 2023, 33(1), 4; https://doi.org/10.3390/engproc2023033004 - 09 May 2023
Viewed by 946
Abstract
A predictive model for the early diagnosis of breast cancer based on the concentration of some cytokines in the tumor microenvironment in the blood was built in this paper. In the work, the influence of the following cytokines was studied: monocytic chemoattractant protein-1, [...] Read more.
A predictive model for the early diagnosis of breast cancer based on the concentration of some cytokines in the tumor microenvironment in the blood was built in this paper. In the work, the influence of the following cytokines was studied: monocytic chemoattractant protein-1, vascular endothelial growth factor, tumor necrosis factor-alpha, interferon gamma, transforming growth factor-beta1, granulocyte colony stimulating factor, and granulocyte-macrophage colony stimulating factor. As a result of preliminary statistical analysis, some combinations of these cytokines that allowed for almost reliable detection of the presence or absence of breast cancer were identified. Based on the identified combinations, new features were constructed. A machine learning model was trained using gradient boosting for its classification method. The built model has an accuracy equal to 1.0 at this stage, so the authors find it reasonable to carry out additional tests of the model for more patients. However, even at this stage, it can be concluded that the concentration of cytokines in the blood serum is applicable for the early diagnosis of breast cancer. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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7 pages, 1145 KiB  
Proceeding Paper
Using the STEGO Neural Network for Scintigraphic Image Analysis
by Ivan Ulitin, Marina Barulina and Marina Velikanova
Eng. Proc. 2023, 33(1), 5; https://doi.org/10.3390/engproc2023033005 - 09 May 2023
Viewed by 991
Abstract
Currently, neural networks are being widely implemented for the diagnosis of various diseases, including cancer of various localizations and stages. The vast majority of such solutions use supervised or unsupervised convolutional neural networks, which require a great deal of training data. Using unsupervised [...] Read more.
Currently, neural networks are being widely implemented for the diagnosis of various diseases, including cancer of various localizations and stages. The vast majority of such solutions use supervised or unsupervised convolutional neural networks, which require a great deal of training data. Using unsupervised image segmentation algorithms can be considered the preferred trend since their use significantly reduces the complexity of neural network training. So, developing unsupervised image segmentation algorithms is one of the topical tasks of machine learning. This year, a team of developers from Google, MIT, and Cornell University developed the STEGO algorithm, which is an unsupervised and non-convolutional neural network. As its author stated, the STEGO algorithm performs well at image segmentation problems compared with other machine learning models. And this algorithm does not need a large amount of training data, unlike convolutional neural networks, which are widely used for medical image analysis. So, the aim of this work is to check the possibility of using this neural network for scintigraphy image segmentation by testing whether the STEGO algorithm is relevant when applied to a scintigraphy dataset. To achieve this goal, the intersection over union metric (IoU) was chosen for evaluating the correctness of the detection of the location of metastases. The training dataset consists of scintigraphic images of patients with various types of cancer and various metastasis appearances. Another version of this metric (mIoU, mean intersection over union) was also used by the creators of STEGO to assess the quality of the model to segment images with different kinds of content. Since the calculated metrics are not good enough, the use of this algorithm for scintigraphic image analysis is not possible or requires the development of a special methodology for this. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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8 pages, 365 KiB  
Proceeding Paper
Synthesis of a Feedback Controller by the Network Operator Method for a Mobile Robot Rosbot in Gazebo Environment
by Elizaveta Shmalko and Yuri Rumyantsev
Eng. Proc. 2023, 33(1), 6; https://doi.org/10.3390/engproc2023033006 - 16 May 2023
Viewed by 651
Abstract
The article presents an approach based on machine learning with symbolic regression for the synthesis of a stabilization system for a mobile robot. This approach is universal and allows you to numerically solve the synthesis problem in a general setting without the need [...] Read more.
The article presents an approach based on machine learning with symbolic regression for the synthesis of a stabilization system for a mobile robot. This approach is universal and allows you to numerically solve the synthesis problem in a general setting without the need to form a training sample, instead relying only on the value of the functional. The synthesis is implemented to stabilize the mobile robot Rosbot in the Gazebo simulation environment. The feedback stabilization system is received by the network operator method. The advantage of the method is that it can be applied to a control object of any complexity and linearity. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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7 pages, 494 KiB  
Proceeding Paper
Additional Requirement in the Formulation of the Optimal Control Problem for Applied Technical Systems
by Elizaveta Shmalko and Askhat Diveev
Eng. Proc. 2023, 33(1), 7; https://doi.org/10.3390/engproc2023033007 - 16 May 2023
Viewed by 551
Abstract
This paper considers the difficulties that arise in the implementation of solutions to the optimal control problem. When implemented in real systems, as a rule, the object is subject to some perturbations, and the control obtained as a function of time as a [...] Read more.
This paper considers the difficulties that arise in the implementation of solutions to the optimal control problem. When implemented in real systems, as a rule, the object is subject to some perturbations, and the control obtained as a function of time as a result of solving the optimal control problem does not take into account these factors, which leads to a significant change in the trajectory and deviation of the object from the terminal goal. This paper proposes to supplement the formulation of the optimal control problem. Additional requirements are introduced for the optimal trajectory. The fulfillment of these requirements ensures that the trajectory remains close to the optimal one under perturbations and reaches the vicinity of the terminal state. To solve the problem, it is proposed to use numerical methods of machine learning based on symbolic regression. A computational experiment is presented in which the solutions of the optimal control problem in the classical formulation and with the introduced additional requirement are compared. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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7 pages, 1299 KiB  
Proceeding Paper
Autonomous Navigation of Mobile Robot Assisted by Its Identified Neural Network Model
by Igor Prokopiev, Elizaveta Shmalko and Askhat Diveev
Eng. Proc. 2023, 33(1), 8; https://doi.org/10.3390/engproc2023033008 - 17 May 2023
Cited by 2 | Viewed by 865
Abstract
Autonomous navigation is one of the key tasks in the development of control systems for real autonomous mobile objects. This paper presents the developed technology for accurately determining the position of a mobile robot in an autonomous operating mode without an external positioning [...] Read more.
Autonomous navigation is one of the key tasks in the development of control systems for real autonomous mobile objects. This paper presents the developed technology for accurately determining the position of a mobile robot in an autonomous operating mode without an external positioning system. The approach involves using a high-precision model of a real robot identified by a neural network. The robot adjusts its position, determined using odometry and video camera, according to the position of the robot, obtained using an accurate model. To train the neural network, a training set is used that takes into account the features of the movement of a wheeled robot, including wheel slip. In the experimental part, the problem of autonomous movement of a mobile robot along a given trajectory is considered. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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9 pages, 585 KiB  
Proceeding Paper
The System Architecture and Methods for Efficient Resource-Saving Scheduling in the Fog
by Anna Klimenko
Eng. Proc. 2023, 33(1), 9; https://doi.org/10.3390/engproc2023033009 - 17 May 2023
Viewed by 548
Abstract
The problem of resource-saving scheduling in a fog environment is considered in this paper. The objective function of the problem in question presupposes the fog nodes’ reliability function maximizing. Therefore, to create a schedule, the following is required: the history of the fog [...] Read more.
The problem of resource-saving scheduling in a fog environment is considered in this paper. The objective function of the problem in question presupposes the fog nodes’ reliability function maximizing. Therefore, to create a schedule, the following is required: the history of the fog devices’ state changes and the search space, which consists of preselected nodes of the cloud-fog broker neighbourhood. The obvious approach to providing the scheduler with this information is to poll the fog nodes, yet this can consume the unacceptable time because of the QoS requirements. In this paper, the system architecture and general methods for efficient resource-saving scheduling is presented. The system is based on distributed ledger element usage, which provides the nodes with the proper awareness about the surroundings. The usage of the distributed ledger allows not only for the creation of the resource-saving schedule but also the reduction of the scheduling problem-solving time, which frees addition time that can be used for the solving of user tasks. The latter also affects the overall resource-saving via reliability. The novelty of this paper consists in the development of the hybrid ledger-based system, which integrates and arranges the elements of various ledger types to solve the newly formulated problem. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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9 pages, 572 KiB  
Proceeding Paper
Monitoring the Condition of a Patient with Parkinson’s Disease
by Yulia Shichkina, Roza Fatkieva and Nikita Isaenko
Eng. Proc. 2023, 33(1), 10; https://doi.org/10.3390/engproc2023033010 - 23 May 2023
Viewed by 760
Abstract
Currently, interest in the development of Internet-of-Things technologies is increasingly penetrating the field of clinical medicine. This paper provides an overview of the use of Internet-of-Things technologies in medical practice using the Scopus database of publications. The classification of publications on the topic [...] Read more.
Currently, interest in the development of Internet-of-Things technologies is increasingly penetrating the field of clinical medicine. This paper provides an overview of the use of Internet-of-Things technologies in medical practice using the Scopus database of publications. The classification of publications on the topic of research directions with promising development trends has been performed. With this in mind, the concept of the architecture of a system for monitoring the condition of a patient with Parkinson’s disease is presented. The necessary hardware and software solutions have been developed, taking into account the needs in order to more effectively adjust treatment and monitor the course of the disease. To more accurately determine the state of progression of the patient’s disease, tests have been designed and developed to assess overall emotional and physical well-being. For the most effective correction and control of drug therapy, a prototype of a drug administration device with four compartments for a drug has been designed, each compartment of which is individually controlled by a specially developed Bluetooth data transmission protocol. Access to each compartment is individual, which ensures the versatility of the device for taking several medications throughout the day. The practical application of the solution has also shown the relevance of its use in the task of studying the course of Parkinson’s disease as well as for monitoring the condition of a patient with existing concomitant diseases and the degree of their influence on the course of the underlying disease. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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6 pages, 244 KiB  
Proceeding Paper
Mathematical Model of Information Exchange in the Autonomous Underwater Vehicle Network
by Elizaveta G. Litunenko, Alexander M. Gruzlikov, Nikolai V. Kolesov and Iurii M. Skorodumov
Eng. Proc. 2023, 33(1), 11; https://doi.org/10.3390/engproc2023033011 - 30 May 2023
Viewed by 554
Abstract
Nowadays, a lot of attention is given to autonomous underwater exploration. To reduce the time of such explorations groups of networked underwater vehicles are used. The implementation of such communication is rather problematic because of low message transfer speed and other factors related [...] Read more.
Nowadays, a lot of attention is given to autonomous underwater exploration. To reduce the time of such explorations groups of networked underwater vehicles are used. The implementation of such communication is rather problematic because of low message transfer speed and other factors related to the underwater environment. In such networks, messages often pass through a chain of relay nodes to reach their destination point. Moreover, vehicles can form queues of messages to be transmitted. The order of messages in the queue can influence the total transmission time. In complex information exchange scenarios, it is crucial to order the messages that should be delivered to ensure optimal management of the process. The proposed article discusses an optimization of messaging in a network of autonomous underwater vehicles. The authors propose algorithms for scheduling information exchanges in an underwater network. These algorithms are suboptimal. Algorithms that satisfy the criteria of the minimum upper bounds for either the total or average delivery time have been proposed. The authors considered situations when messages are unordered, as well as when messages are partially pre-ordered. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
10 pages, 519 KiB  
Proceeding Paper
Stabilization of Movement along an Optimal Trajectory and Its Solution
by Askhat Diveev, Elena Sofronova, Nurbek Konyrbaev and Ainur Bexeitova
Eng. Proc. 2023, 33(1), 12; https://doi.org/10.3390/engproc2023033012 - 08 Jun 2023
Cited by 1 | Viewed by 491
Abstract
The extended optimal control problem is considered. It is necessary to find an optimal control function, that not only provides the achievement of terminal state with optimal value of the given quality criterion, but also is implemented in the control system of a [...] Read more.
The extended optimal control problem is considered. It is necessary to find an optimal control function, that not only provides the achievement of terminal state with optimal value of the given quality criterion, but also is implemented in the control system of a real object. It means, that the control function should depend on the state space vector, and the optimal solution should keep optimality property at small perturbations of the found solution. To solve this problem machine learning control by symbolic regression is used. In the extended optimal control problem, the problem statement of stabilization system synthesis for movement along the optimal trajectory is included. Synthesis problem is solved by the network operator method. In the synthesis problem a domain of initial conditions is considered instead of one point of initial state. It provides less sensitivity of found solution to perturbations of initial states. An example of solving the extended optimal control problem with complex phase constraints in the form of bottleneck for four quadcopters is presented. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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7 pages, 743 KiB  
Proceeding Paper
Improved Social Network User Recommendation System—The Machine Learning Approach
by Yana A. Bekeneva and Titus U. Eze
Eng. Proc. 2023, 33(1), 13; https://doi.org/10.3390/engproc2023033013 - 09 Jun 2023
Viewed by 604
Abstract
In this paper, we propose a recommendation system for social media users which makes recommendations on the basis of the user profile information and the contents posted by users-the bio-aware algorithm. Text mining techniques are used to pre-process the words before feeding it [...] Read more.
In this paper, we propose a recommendation system for social media users which makes recommendations on the basis of the user profile information and the contents posted by users-the bio-aware algorithm. Text mining techniques are used to pre-process the words before feeding it to an LDA model which handles the topic and feature extraction. In this way, we determine the similarity between users based on their interests. We further trained a machine learning model which is able to identify and score the top interests of a particular social media user. Other users who share similar scores are shown as recommendations to each other. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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8 pages, 1218 KiB  
Proceeding Paper
Use of Dynamic Models in Cognitive Cyber-Physical Systems
by Michael Chervontsev, Alexey Subbotin, Alexander Vodyaho and Nataly Zhukova
Eng. Proc. 2023, 33(1), 14; https://doi.org/10.3390/engproc2023033014 - 09 Jun 2023
Cited by 1 | Viewed by 592
Abstract
This article discusses an approach to the development of large-scale cognitive cyber-physical systems characterized by a high level of structural, functional and architectural dynamics. The main idea of the proposed approach is the use of several modern paradigms to build cyber-physical systems, such [...] Read more.
This article discusses an approach to the development of large-scale cognitive cyber-physical systems characterized by a high level of structural, functional and architectural dynamics. The main idea of the proposed approach is the use of several modern paradigms to build cyber-physical systems, such as continuous architecture, agile architecture, digital twins and digital threads. A three-level model of a cognitive cyber-physical system is proposed. In order to ensure the required level of flexibility of the system, such possibility should be laid at earlier stages of the life cycle, i.e., at the development stage. At the upper level, the system is described in terms of a continuous architecture; at the middle level, the system is represented as a system with agile architecture, which is described as a multi-level relatively finite automaton, and at the lower level, structural and functional models are used that illustrate the system in the process of functioning. This article provides examples of using the proposed approach. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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8 pages, 852 KiB  
Proceeding Paper
Particle Swarm Optimization for Target Encirclement by a UAV Formation
by Tagir Muslimov
Eng. Proc. 2023, 33(1), 15; https://doi.org/10.3390/engproc2023033015 - 09 Jun 2023
Cited by 1 | Viewed by 856
Abstract
This paper presents an idea of using particle swarm optimization (PSO) to tune the control system of a decentralized unmanned aerial vehicle (UAV) formation. Simulations were run on a consensus-based decentralized UAV formation. Vector field guidance was used to control the formation. A [...] Read more.
This paper presents an idea of using particle swarm optimization (PSO) to tune the control system of a decentralized unmanned aerial vehicle (UAV) formation. Simulations were run on a consensus-based decentralized UAV formation. Vector field guidance was used to control the formation. A fitness function is proposed that is based not only on the error of distance to the circular path, but also on the relative inter-UAV distance error. To demonstrate the effectiveness of the proposed method, the obtained results of such tuning are compared to those obtainable by the conventional trial and error method. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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9 pages, 1216 KiB  
Proceeding Paper
Active Simultaneous Localization and Mapping Method Based on Model Prediction
by Anna N. Daryina and Igor V. Prokopiev
Eng. Proc. 2023, 33(1), 16; https://doi.org/10.3390/engproc2023033016 - 09 Jun 2023
Viewed by 449
Abstract
In the process of controlling an unmanned vehicle, it is practically important that under conditions of rapidly changing dynamic constraints, control laws be developed that would be optimal with respect to a given quality functional or a multicriteria functional. When static and dynamic [...] Read more.
In the process of controlling an unmanned vehicle, it is practically important that under conditions of rapidly changing dynamic constraints, control laws be developed that would be optimal with respect to a given quality functional or a multicriteria functional. When static and dynamic constraints do not allow the optimal movement to be chosen to a given quality functional, the authors consider the transition to another quality functional using the predictive integral path model and the method of active simultaneous localization and mapping. In this case, the strategy for choosing the state space is more efficient than the strategy for choosing the control space. The practical question is how to achieve this. The paper presents a method and experiments using an unmanned vehicle platform at a test site in the form of a complex environment, showing the feasibility of the method. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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7 pages, 1564 KiB  
Proceeding Paper
Real-Time Hardware Identification of Complex Dynamical Plant by Artificial Neural Network Based on Experimentally Processed Data by Smart Technologies
by Valerii I. Kruzhkov, Yuri V. Mitrishkin and Eugenia A. Pavlova
Eng. Proc. 2023, 33(1), 17; https://doi.org/10.3390/engproc2023033017 - 13 Jun 2023
Viewed by 533
Abstract
Artificial neural networks with different structures are used for identification of complex dynamic plant with distributed parameters. The plant is a high-temperature plasma in the spherical Globus-M2 tokamak. Experimental data from it were processed by plasma reconstruction code based on Picard iterations, namely, [...] Read more.
Artificial neural networks with different structures are used for identification of complex dynamic plant with distributed parameters. The plant is a high-temperature plasma in the spherical Globus-M2 tokamak. Experimental data from it were processed by plasma reconstruction code based on Picard iterations, namely, the Flux-Current Distribution Identification (FCDI) code. This represents smart technology employed to obtain distributed plasma parameters by minimizing the difference between measured and reconstructed signals. An artificial neural network was then applied to identify the data obtained by the FCDI code on the hardware as a real-time testbed realized on a Speedgoat computer. The aim of this repeated identification is to increase the operational response speed in real time in the closed-loop control system of the plasma shape. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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8 pages, 488 KiB  
Proceeding Paper
Improving Collaborative Robotic Complex Efficiency: An Approach to the Intellectualization of the Control System
by Mikhail Gorkavyy, Yuri Ivanov, Sergey Sukhorukov, Sergey Zhiganov, Makrel Melnichenko, Alexander Gorkavyy and Daniil Grabar
Eng. Proc. 2023, 33(1), 18; https://doi.org/10.3390/engproc2023033018 - 13 Jun 2023
Viewed by 513
Abstract
This paper proposes an original approach to improving the efficiency of technological processes based on collaborative robots, which differs from the existing ones by the possibility of intensifying the process of modeling the human factor when forming a control law. A structural and [...] Read more.
This paper proposes an original approach to improving the efficiency of technological processes based on collaborative robots, which differs from the existing ones by the possibility of intensifying the process of modeling the human factor when forming a control law. A structural and functional diagram of the model of a standard cobot control system in the basic industrial configuration is presented. The shortcomings of a standard solution for the formation of laws for controlling the movement of a cobot in a nondeterministic environment in the same workspace with a person are demonstrated. Structural and functional solutions are proposed to outline a strategy for increasing the degree of synergistic effect of human–machine interaction. The effect can be achieved through the introduction of an extended system of sensors and analytics and an intelligent module robot trajectory movement formation and optimization under disturbing influences. The results of the comparison between the standard control system of the cobot and the prototype of the intelligent system are presented. As an example, the operation of the implementation of collision avoidance that occurs due to the appearance of a stationary object in the working area is given. The results obtained demonstrate a significant time- and energy-saving effect (from 15% to 182% depending on the operation) in the case of using an intelligent control system. A feature of the proposed approach is to strengthen the integration links of intelligent analysis and optimization modules, which allow real-time multimodal processing of sensory data and environmental modeling to predict human actions and form cobot reactions. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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9 pages, 1588 KiB  
Proceeding Paper
Using an Ensemble of Deep Neural Networks to Detect Human Keypoints in the Workspace of a Collaborative Robotic System
by Yuri Ivanov, Sergey Zhiganov, Mikhail Gorkavyy, Sergey Sukhorukov and Daniil Grabar
Eng. Proc. 2023, 33(1), 19; https://doi.org/10.3390/engproc2023033019 - 13 Jun 2023
Cited by 3 | Viewed by 619
Abstract
It is suggested that the use an ensemble of deep neural networks can determine the spatial position of the operator using keypoints with a multicamera sensor system. The advantage of the algorithm is the use of a multicamera system that allows keypoints to [...] Read more.
It is suggested that the use an ensemble of deep neural networks can determine the spatial position of the operator using keypoints with a multicamera sensor system. The advantage of the algorithm is the use of a multicamera system that allows keypoints to be linked to the local coordinate system of an industrial robotic complex. The testing of this work was made on the basis of modern embedded computing hardware and software. The effectiveness of the proposed approach is demonstrated even when only a subset of key points is found in the frame, as well as when they partially overlap. A software module in Python has been developed for detecting and localizing key points of the operator and industrial manipulator. The proposed approach will make it possible to plan the robot’s trajectories for the safe execution of joint operations in one workspace. The developed algorithm will be used to predict the operator’s actions in the workspace and detect abnormal situations and possible intersections in the trajectories of the collaborative robot. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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6 pages, 728 KiB  
Proceeding Paper
Deep Learning for Detecting Dangerous Objects in X-rays of Luggage
by Nikita Andriyanov
Eng. Proc. 2023, 33(1), 20; https://doi.org/10.3390/engproc2023033020 - 13 Jun 2023
Viewed by 942
Abstract
The investigation presented in this text is the study of object detection algorithms in the task of analyzing images of baggage and hand luggage. A modified version of the YOLOv5 convolutional neural network with additional rechecking based on the VGG-19 network is proposed. [...] Read more.
The investigation presented in this text is the study of object detection algorithms in the task of analyzing images of baggage and hand luggage. A modified version of the YOLOv5 convolutional neural network with additional rechecking based on the VGG-19 network is proposed. The modification is based on transfer learning from the available images. A comparison is made with other known algorithms. The article shows that the application of the proposed model made it possible to achieve the value of the mean average recall (mAR) at the level of 87% for dangerous objects of five classes. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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10 pages, 2196 KiB  
Proceeding Paper
Design and Development of Information and Computational System for Energy Facilities’ Impact Assessment on Environment
by Vladimir R. Kuzmin, Tatyana N. Vorozhtsova and Liudmila V. Massel
Eng. Proc. 2023, 33(1), 21; https://doi.org/10.3390/engproc2023033021 - 13 Jun 2023
Viewed by 504
Abstract
In this article we consider authors’ information and computational system for energy facilities’ impact assessment on the environment. The necessity of such assessments and development of this system is substantiated. We developed this system as a Web application using the agent-service approach. To [...] Read more.
In this article we consider authors’ information and computational system for energy facilities’ impact assessment on the environment. The necessity of such assessments and development of this system is substantiated. We developed this system as a Web application using the agent-service approach. To develop a database for the system, we utilized ontological engineering of energy and ecology. For assessments, we developed a set of information susbsystems that use approved regulatory methods. Our system can be used for assessment of the impact of both existing and planning energy facilities and also for planning measures to reduce the harmful impact of such facilities. We also performed a set of computational experiments in order to test the developed system. Experiments have shown the correctness of the methods used, and the results of one of them are presented in the article. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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6 pages, 1048 KiB  
Proceeding Paper
An Overview of Object Detection and Tracking Algorithms
by Kehao Du and Alexander Bobkov
Eng. Proc. 2023, 33(1), 22; https://doi.org/10.3390/engproc2023033022 - 13 Jun 2023
Cited by 2 | Viewed by 1480
Abstract
With the development of information technology, the vision-based detection and tracking of moving objects is gradually penetrating into all aspects of people’s lives, and its importance is becoming more prominent, attracting more and more scientists and research institutions at home and abroad to [...] Read more.
With the development of information technology, the vision-based detection and tracking of moving objects is gradually penetrating into all aspects of people’s lives, and its importance is becoming more prominent, attracting more and more scientists and research institutions at home and abroad to participate in research in this field. With in-depth research into vision-based object detection and tracking, various superior algorithms have appeared in recent years. In this article, we attempt to compare some of the classic algorithms in this area of detection and tracking that have appeared recently. This article examines and summarizes two areas: the detection and the tracking of moving objects. First, we divide object detection into one-stage algorithms and two-stage algorithms depending on whether a region proposal should be generated, and we accordingly outline some commonly used object detection algorithms. Second, we separate object tracking into the KCF and SORT algorithms according to the differences in the underlying algorithms. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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9 pages, 369 KiB  
Proceeding Paper
Modified Evolutionary Test Data Generation Algorithm Based on Dynamic Change in Fitness Function Weights
by Tatiana Avdeenko and Konstantin Serdyukov
Eng. Proc. 2023, 33(1), 23; https://doi.org/10.3390/engproc2023033023 - 13 Jun 2023
Viewed by 478
Abstract
In this paper, we investigate a modification of the method of data generation for multiple code paths within a single launch of the genetic algorithm. This method allows the consideration of the remoteness of paths initiated by different test cases by introducing an [...] Read more.
In this paper, we investigate a modification of the method of data generation for multiple code paths within a single launch of the genetic algorithm. This method allows the consideration of the remoteness of paths initiated by different test cases by introducing an additional additive component into the fitness function. Previous studies have shown that the parameter defining the relationship between the different components of the fitness function has a rather strong effect on code coverage. To eliminate this effect, we propose the modification of the first component of the fitness function, which is responsible for path complexity. This modification is based on a dynamic change in code statement weights between generations to achieve greater population diversity. We propose several methods for implementing this modification, divided into two groups. In the first group, the statement weights change depending only on the fact of statement coverage in a generation, and the rate of change depends on the number of previous generations in which it was covered. In the second group, the rate of change depends on the proportion of statement coverage by the test sets in the previous generation. Each of the proposed methods is investigated to achieve complete coverage with different values of the parameter defining the ratio of the components of the fitness function. As a result, the best method is determined, which eliminates the need to determine this parameter for each testing code, thus achieving a greater universality for the algorithm. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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8 pages, 608 KiB  
Proceeding Paper
Computer Simulation of Anti-Drone System
by Nikita Bykov and Vadim Fedulov
Eng. Proc. 2023, 33(1), 24; https://doi.org/10.3390/engproc2023033024 - 14 Jun 2023
Viewed by 986
Abstract
In this article, we present the results of an anti–drone system simulation. The system is designed to counter mini unmanned aerial vehicles. A radar system with one or several antennas and an elimination system with one or more countermeasures are included in the [...] Read more.
In this article, we present the results of an anti–drone system simulation. The system is designed to counter mini unmanned aerial vehicles. A radar system with one or several antennas and an elimination system with one or more countermeasures are included in the system. The drones are destroyed by kinetic weapons. In the developed computer model, it is possible to simulate a raid of several drones against several countermeasures in an environment without obstacles. The computer model-specific feature is a discrete-event approach that provides higher calculating performance compared with the “soft time” method. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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8 pages, 381 KiB  
Proceeding Paper
Comparative Analysis of Feature Extraction Methods for Intelligence Estimation Based on Resting State EEG Data
by Tatiana Avdeenko, Anastasiia Timofeeva and Marina Murtazina
Eng. Proc. 2023, 33(1), 25; https://doi.org/10.3390/engproc2023033025 - 14 Jun 2023
Cited by 1 | Viewed by 564
Abstract
This paper presents a comparative study of relationship estimation between intelligence indicators and single-channel and multi-channel feature sets extracted from resting EEG data. In the first case, the power of four frequency bands (alpha, theta, beta, delta) calculated using the discrete Fourier transform [...] Read more.
This paper presents a comparative study of relationship estimation between intelligence indicators and single-channel and multi-channel feature sets extracted from resting EEG data. In the first case, the power of four frequency bands (alpha, theta, beta, delta) calculated using the discrete Fourier transform (DFT) and the power spectral density (PSD) estimated through the Welch’s method for each of the channels were extracted as features from the EEG signals. In the second case, Imaginary Coherence (iMOCH) measure values for a pair of channels in the frequency bands were extracted. Graph theoretical connectivity metrics were calculated for iMOCH. As part of the experimental part of the study, the data of the EEG records of 79 subjects at rest and the values of four IQ indicators (IQ2—ability to abstract; IQ3—verbal analogies and combinatorial abilities; IQ7—figure detecting, combinatorial abilities; IQ8—spatial imagination) of the structure of intelligence were analyzed by the Amthauer method. For relationship estimation, a principal component regression was used. The performance evaluation is based on the nested Monte-Carlo cross-validation. The single-channel feature set provides the smallest standard deviation of mean absolute error. For non-verbal intelligence, the results of the multi-channel approach are better. For verbal intelligence, on the contrary, the single-channel approach gives the best result. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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8 pages, 813 KiB  
Proceeding Paper
Integration of Mathematical and Cognitive Modelling in the Software Package “INTEC-A”
by Liudmila Massel, Aleksei Massel and Timur Mamedov
Eng. Proc. 2023, 33(1), 26; https://doi.org/10.3390/engproc2023033026 - 14 Jun 2023
Viewed by 417
Abstract
Studies of the directions of development of the energy sector (ES) are of a multivariate nature. With a combinatorial approach, in order to form possible options for the development of the energy sector, the number of options reaches several million, of which the [...] Read more.
Studies of the directions of development of the energy sector (ES) are of a multivariate nature. With a combinatorial approach, in order to form possible options for the development of the energy sector, the number of options reaches several million, of which the researcher needs to select several for research. To ease the burden on the researcher, an IT environment was developed that supports a two-level technology for researching energy security problems, including the stages of qualitative and quantitative analysis using semantic modeling methods and numerical calculations. Now, the transition from semantic models to numerical calculations is carried out manually, therefore it is proposed to integrate semantic and mathematical modeling into the software packages (SP) “INTEC-A”. This article discusses the integration of cognitive and mathematical modeling in the SP “INTEC-A”. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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6 pages, 1426 KiB  
Proceeding Paper
Application of Neural Networks to Power Analysis
by Alla Levina and Roman Bolozovskii
Eng. Proc. 2023, 33(1), 27; https://doi.org/10.3390/engproc2023033027 - 15 Jun 2023
Cited by 1 | Viewed by 484
Abstract
The purpose of this work is to research the possibility of a side-channel attack, more precisely power consumption attack (recovering the encryption key according to the board’s power consumption schedule) on the AES-128 algorithm implemented in hardware. Basically, various methods can be used [...] Read more.
The purpose of this work is to research the possibility of a side-channel attack, more precisely power consumption attack (recovering the encryption key according to the board’s power consumption schedule) on the AES-128 algorithm implemented in hardware. Basically, various methods can be used to make an attack, including SPA (Simple Power Consumption Attack) and DPA (Differential Power Consumption Attack). SPA methods involve a simple visual analysis of energy consumption graphs, while DPA involves the use of statistical methods to recover the encryption key. One way to make side-channel attacks more effective is to implement machine learning methods for the described purposes. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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8 pages, 3360 KiB  
Proceeding Paper
Lightweight 2D Map Construction of Vehicle Environments Using a Semi-Supervised Depth Estimation Approach
by Alexey Kashevnik and Ammar Ali
Eng. Proc. 2023, 33(1), 28; https://doi.org/10.3390/engproc2023033028 - 15 Jun 2023
Cited by 1 | Viewed by 572
Abstract
This paper addresses the problem of constructing a real-time 2D map for driving scenes from a single monocular RGB image. We presented a method based on three neural networks (depth estimation, 3D object detection, and semantic segmentation). We proposed a depth estimation neural [...] Read more.
This paper addresses the problem of constructing a real-time 2D map for driving scenes from a single monocular RGB image. We presented a method based on three neural networks (depth estimation, 3D object detection, and semantic segmentation). We proposed a depth estimation neural network architecture that is fast and accurate in comparison with the state-of-the-art models. We designed our model to work in real time on light devices (such as an NVIDIA Jetson Nano and smartphones). The model is based on an encoder–decoder architecture with complex loss functions, i.e., normal loss, VNL, gradient loss (dx, dy), and mean absolute error. Our results show competitive results in comparison with the state-of-the-art methods, as our method is 30 times faster and smaller. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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7 pages, 502 KiB  
Proceeding Paper
Reinforcement Learning for Solving Control Problems in Robotics
by Askhat Diveev, Elena Sofronova, Sergey Konstantinov and Viktoria Moiseenko
Eng. Proc. 2023, 33(1), 29; https://doi.org/10.3390/engproc2023033029 - 15 Jun 2023
Viewed by 470
Abstract
The use of reinforcement learning technology for the optimal control problem solution is considered. To solve the optimal control problem an evolutionary algorithm is used that finds control to ensure the movements of a control object along different trajectories with approximately the same [...] Read more.
The use of reinforcement learning technology for the optimal control problem solution is considered. To solve the optimal control problem an evolutionary algorithm is used that finds control to ensure the movements of a control object along different trajectories with approximately the same values of the quality criterion. Additional conditions for passing the trajectory in the neighbourhood of given areas of the state space are included in the quality criterion. To build a stabilization system for the movement of an object along a given trajectory, machine learning control by symbolic regression is used. An example of solving the optimal control problem for a quadcopter is given. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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9 pages, 1196 KiB  
Proceeding Paper
Designing a Digital Twin of a Wind Farm
by Liudmila Massel, Aleksei Massel, Nikita Shchukin and Aleksey Tsybikov
Eng. Proc. 2023, 33(1), 30; https://doi.org/10.3390/engproc2023033030 - 16 Jun 2023
Cited by 3 | Viewed by 865
Abstract
The article is devoted to the development of a prototype digital twin of a wind farm. An overview of existing works and solutions in the field of digital twins in wind energy is given. The approach to building a digital twin based on [...] Read more.
The article is devoted to the development of a prototype digital twin of a wind farm. An overview of existing works and solutions in the field of digital twins in wind energy is given. The approach to building a digital twin based on ontological engineering, which is widely used in the works of the authors, is considered in detail. An ontological approach is described, which the authors develop and use in the design and development of digital twins (the development is carried out on digital twins of wind farms and photovoltaic systems). The adapted stages of ontological engineering, examples of fragments of the ontological knowledge space in the field of wind energy and the ontology of tasks of the digital twin of a wind farm are given. The architecture of the digital twin prototype under development has been developed and proposed for consideration. The key parts in the structure of the developed digital twin are described. A mathematical model for determining the operation parameters of a wind farm is considered. Special attention is paid to the stages of implementation of the prototype of the digital twin of the wind farm. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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9 pages, 1769 KiB  
Proceeding Paper
Decision Support in the Analysis of Cyber Situational Awareness of Energy Facilities
by Daria Gaskova and Elena Galperova
Eng. Proc. 2023, 33(1), 31; https://doi.org/10.3390/engproc2023033031 - 16 Jun 2023
Cited by 2 | Viewed by 625
Abstract
Cyber situational awareness is the result of both the analysis of cyber security and situational awareness studies and the line of research that uses artificial intelligence methods in the field of cybersecurity. It covers both methods of automatic detection of cyber threats in [...] Read more.
Cyber situational awareness is the result of both the analysis of cyber security and situational awareness studies and the line of research that uses artificial intelligence methods in the field of cybersecurity. It covers both methods of automatic detection of cyber threats in the network and methods of providing information to an analyst for further risk analysis and decision making to protect of the assets of the facility. Investigations of cyber situational awareness in the energy sector have become pertinent resulting from both the concept of the digital transformation of energy and the consideration of energy facilities and systems as cyber-physical systems. The problems of ensuring cybersecurity and raising awareness about the cyber environment of an energy facility are compounded by their high significance for the economies of countries. In this regard, such facilities are considered as critical infrastructure. The first part of this article discusses the basic concepts of cyber situational awareness, some knowledge representation models and some existing security metrics. The second part considers the use of frame, production and network models of knowledge representation in the analysis of the cyber situational awareness of energy facilities and the software components that implement them. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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7 pages, 1900 KiB  
Proceeding Paper
Structural Analysis of Hydrodynamical Interaction of Full-Submerged Archimedes Screws of Rotary-Screw Propulsion Units of Snow and Swamp-Going Amphibious Vehicles with Water Area via Methods of Computer Simulation
by Svetlana Karaseva, Aleksey Papunin, Vladimir Belyakov, Vladimir Makarov and Dmitry Malahov
Eng. Proc. 2023, 33(1), 32; https://doi.org/10.3390/engproc2023033032 - 19 Jun 2023
Viewed by 471
Abstract
The paper considers the problems of estimation and provision of efficiency of rotary-screw propulsion units (RSP) for snow and swamp-going amphibious vehicles. The performance curves of fully submerged Archimedes screws of RSP are presented with parameters typical for snow and swamp-going amphibious vehicles. [...] Read more.
The paper considers the problems of estimation and provision of efficiency of rotary-screw propulsion units (RSP) for snow and swamp-going amphibious vehicles. The performance curves of fully submerged Archimedes screws of RSP are presented with parameters typical for snow and swamp-going amphibious vehicles. These parameters were obtained from the results of computer simulation. For a wide range of performance modes, the impact of particular elements of Archimedes screws on the general efficiency of the propulsion unit is analysed. According to the results of analysis of data received, lines of further research will aim to increase the efficiency of RSP when moving afloat. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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8 pages, 1035 KiB  
Proceeding Paper
Algorithm for Determining the Singularity-Free and Interference-Free Workspace of a Robotic Platform for Fruit Harvesting
by Dmitry Malyshev, Larisa Rybak, Elena Gaponenko and Artem Voloshkin
Eng. Proc. 2023, 33(1), 33; https://doi.org/10.3390/engproc2023033033 - 19 Jun 2023
Cited by 2 | Viewed by 384
Abstract
This paper proposes a robotic system for fruit harvesting, which includes a mobile platform with a fruit basket, on which a parallel platform is installed, and in the center of the moving platform a telescopic link is installed for harvesting fruit from trees. [...] Read more.
This paper proposes a robotic system for fruit harvesting, which includes a mobile platform with a fruit basket, on which a parallel platform is installed, and in the center of the moving platform a telescopic link is installed for harvesting fruit from trees. Numerical algorithms are developed for determining the workspace of platforms with a parallel structure, represented as an ordered set of integers, and for transferring constraints from the platform orientation coordinate space to the end-effector coordinate space. The limits of the workspace are the permissible ranges of rod lengths and the condition that there are no singularities or link interference. The results of modeling are presented. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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9 pages, 926 KiB  
Proceeding Paper
Anomaly Detection on Video by Detecting and Tracking Feature Points
by Ivan Fomin, Yurii Rezets and Ekaterina Smirnova
Eng. Proc. 2023, 33(1), 34; https://doi.org/10.3390/engproc2023033034 - 19 Jun 2023
Viewed by 711
Abstract
There is a well-known problem of video sequence analysis when it is necessary to identify and localize areas of abnormal movement of objects. This is necessary to attract the attention of the operator in the process of work or when analyzing the archive [...] Read more.
There is a well-known problem of video sequence analysis when it is necessary to identify and localize areas of abnormal movement of objects. This is necessary to attract the attention of the operator in the process of work or when analyzing the archive of video recordings. One of the solutions is based on tracklet analysis using short segments of the object’s trajectory that characterize its movement over a certain period of time, and then analysis of activity in various areas of the frame. Since the construction of the tracklet and trajectory is based on the optical flow, the quality and performance of the algorithm significantly depend on the choice and configuration of methods for detecting and tracking feature points. We have analyzed various combinations of these methods using the examples of test videos of normal and abnormal activity in a pedestrian zone. The necessity of a preliminary analysis of the methods used when setting up a video surveillance system to solve specific tasks is shown. Suitable combinations of methods are proposed. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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8 pages, 1308 KiB  
Proceeding Paper
Methods of Recognition Based on Wavelet Transform for Analysis of Characteristics of Spherical Quantum Dot
by Evgenia Kozhanova, Sergey Danilov and Victor Belyaev
Eng. Proc. 2023, 33(1), 35; https://doi.org/10.3390/engproc2023033035 - 20 Jun 2023
Cited by 1 | Viewed by 523
Abstract
The paper contains the results of a recognition technique based on the comparison of statistical and stochastic characteristics of the wavelet coefficients of energy density describing the emission energy of a nanocrystal with a quantum dot according to the Brus equation for traditional [...] Read more.
The paper contains the results of a recognition technique based on the comparison of statistical and stochastic characteristics of the wavelet coefficients of energy density describing the emission energy of a nanocrystal with a quantum dot according to the Brus equation for traditional and perspective materials for quantum dots (CdSe, GaAs, CdTe, PbS) used in optoelectronic engineering and technology, in order to analyze their characteristics. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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6 pages, 399 KiB  
Proceeding Paper
Feedback Linearization Control of Nonlinear System
by Ivan Sergeevich Trenev and Daniil Dmitrievich Devyatkin
Eng. Proc. 2023, 33(1), 36; https://doi.org/10.3390/engproc2023033036 - 20 Jun 2023
Viewed by 945
Abstract
In this work, a neural network controller is developed for a wide class of nonlinear systems including dynamic systems in the Brunovsky canonical form and those with skew-symmetry properties and bounded nonlinearities. An example of the applicability of this controller to the control [...] Read more.
In this work, a neural network controller is developed for a wide class of nonlinear systems including dynamic systems in the Brunovsky canonical form and those with skew-symmetry properties and bounded nonlinearities. An example of the applicability of this controller to the control of the position of a magnet over an electromagnet is considered. The modeling has been provided through the Simulink environment. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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7 pages, 379 KiB  
Proceeding Paper
Data Generation with Variational Autoencoders and Generative Adversarial Networks
by Daniil Devyatkin and Ivan Trenev
Eng. Proc. 2023, 33(1), 37; https://doi.org/10.3390/engproc2023033037 - 20 Jun 2023
Viewed by 601
Abstract
The paper considers the problem of modelling the distribution of data with noise in the input data. In this paper, we consider encoders and decoders, which solve the problem of modelling data distribution. The improvement of variational autoencoders (VAEs) is discussed. Practical implementation [...] Read more.
The paper considers the problem of modelling the distribution of data with noise in the input data. In this paper, we consider encoders and decoders, which solve the problem of modelling data distribution. The improvement of variational autoencoders (VAEs) is discussed. Practical implementation is performed using the Python programming language and the Keras framework. Generative adversarial networks (GANs) and VAEs with noisy data are demonstrated. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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7 pages, 671 KiB  
Proceeding Paper
Investigation of Internal Model for Unmanned Vehicle Control in Case of Its Aggressive Motion along a Spatial Trajectory
by Igor Prokopiev, Elena Sofronova and Viktoria Moiseenko
Eng. Proc. 2023, 33(1), 38; https://doi.org/10.3390/engproc2023033038 - 20 Jun 2023
Viewed by 341
Abstract
The work is devoted to the study of methods that are used to control the movement of an object along a given trajectory. A control method involving an accurate internal model is proposed. This internal model was built on the basis of the [...] Read more.
The work is devoted to the study of methods that are used to control the movement of an object along a given trajectory. A control method involving an accurate internal model is proposed. This internal model was built on the basis of the object’s mathematical model and real object, performed by artificial neural networks. For a limited period of time the model is able to determine the object state without surveillance system usage. The dynamic model of an unmanned vehicle was obtained by method developed at the Robotics Center of the FRC CSC RAS. This method acquires experimental data and performs model identification by means of a neural network. The trajectory is a set of spatial points generated by the developed real unmanned vehicle simulator. The control was carried out on the basis of PID-controller and model predictive control method. The comparison of control methods for a real and virtual unmanned vehicles was conducted in the simulator developed. The results of field experiments, during which control by internal model was applied, are presented. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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9 pages, 312 KiB  
Proceeding Paper
Anisotropy-Based Estimation for Sensor Network with Non-Centered Disturbance
by Alexander V. Yurchenkov and Arkadiy Yu. Kustov
Eng. Proc. 2023, 33(1), 39; https://doi.org/10.3390/engproc2023033039 - 20 Jun 2023
Viewed by 345
Abstract
This paper concerns the anisotropy-based estimation design for sensor networks with coloured external disturbance. The boundedness criterion of anisotropic norm for estimation problems in network systems relies on the analysis of multiplicative noise systems in the framework of anisotropy-based theory. The solution of [...] Read more.
This paper concerns the anisotropy-based estimation design for sensor networks with coloured external disturbance. The boundedness criterion of anisotropic norm for estimation problems in network systems relies on the analysis of multiplicative noise systems in the framework of anisotropy-based theory. The solution of the considered problem is reduced to a convex optimization problem. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
11 pages, 538 KiB  
Proceeding Paper
Evaluation of Computer Technologies for Calculation of Exact Approximations of Statistics Probability Distributions
by Andrey Melnikov, Ilya Levin, Aleksey Dordopulo and Lyubov Slasten
Eng. Proc. 2023, 33(1), 40; https://doi.org/10.3390/engproc2023033040 - 21 Jun 2023
Viewed by 636
Abstract
This paper is devoted to the evaluation of the hardware resources of computer systems for solving a computationally expensive problem such as the calculation of the probability distributions of statistics by the second multiplicity method based on Δ-exact approximations of samples with [...] Read more.
This paper is devoted to the evaluation of the hardware resources of computer systems for solving a computationally expensive problem such as the calculation of the probability distributions of statistics by the second multiplicity method based on Δ-exact approximations of samples with a size of 320–1280 characters and an alphabet power of 128–256 characters. The accuracy is Δ=105 and the total solution time should not exceed 30 days or 2.592×106 seconds for 24/7 computing. Owing to the use of the properties of the second multiplicity method, the computational complexity of the calculations can be brought within the range of 9.68×10221.60×1052 operations with the number of tested vectors at 6.50×10231.39×1050. The solution of this problem for the specified parameters of samples during the given time requires hardware resources which cannot be provided by modern computer technology such as processors, graphics accelerators and programmable logic integrated circuits. Therefore, in this paper, we analyze the possibilities of promising quantum and photon technologies for solving the problem with the given parameters. The main advantage of quantum computer systems is the high speed of calculations for all possible parameter values. However, quantum acceleration will not be achieved to calculate the probability distributions of statistics due to the need to check all the obtained solutions. Here, the number of obtained solutions corresponds to the dimension of the problem. In addition, due to the current development level of quantum hardware components, it is impossible to create and use 120 qubit quantum computers for the solution of the considered problem. Photon computers can provide high computation speeds at low power consumptions and require the smallest number of nodes to solve the considered problem. However, unsolved problems with the physical implementation of efficient memory elements and the lack of available hardware components make the use of photon computer technologies impossible for calculating the probability distributions of statistics in the near future (5–7 years). Therefore, it is most reasonable to use hybrid computer systems containing nodes of different architectures. To solve the problem on various hardware platforms (general purpose processors, GPUs and FPGAs) and configurations of hybrid computer systems, we suggest to use the architecture-independent high-level programming language SET@L. The language combines the representation of calculations as sets and collections (based on the alternative set theory of P. Vopenka), the absolutely parallel form of the problem represented as an information graph and the paradigm of aspect-oriented programming. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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9 pages, 720 KiB  
Proceeding Paper
Extracting and Processing of Russian Unstructured Clinical Texts for a Medical Decision Support System
by Irina Bolodurina, Alexander Shukhman, Leonid Legashev, Lyubov Grishina and Arthur Zhigalov
Eng. Proc. 2023, 33(1), 41; https://doi.org/10.3390/engproc2023033041 - 26 Jun 2023
Viewed by 397
Abstract
The rapid growth in the volume of medical data is pushing the development and implementation of artificial intelligence (AI) tools. One of the directions of the application of AI in the field of healthcare is the use of natural language processing methods to [...] Read more.
The rapid growth in the volume of medical data is pushing the development and implementation of artificial intelligence (AI) tools. One of the directions of the application of AI in the field of healthcare is the use of natural language processing methods to build medical decision support systems based on electronic medical record (EMC) data. As a result of this study, a module for the extraction and pretreatment of patients’ EMC was developed. In addition, an approach was implemented to extract features from the unstructured textual information of patient admission protocols, with the formation of an appropriate vector representation of data. Predictive models for the diagnosis of groups of diseases based on the logistic regression model and BERT were developed. The highest efficiency in the experiments was shown by the logistic regression model, with a F1-score of 0.81 and Matthews correlation coefficient of 0.75. The obtained results have been posted for public access based on the django framework and can be used for preliminary assessment of patient health status, as well as integrated into existing medical decision support systems. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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10 pages, 466 KiB  
Proceeding Paper
Automating the Study of a Linearized Model of Diabetes Mellitus and Tuning a PID Controller for This Model
by Denis Andrikov and Sinan Kurbanov
Eng. Proc. 2023, 33(1), 42; https://doi.org/10.3390/engproc2023033042 - 27 Jun 2023
Viewed by 482
Abstract
This paper proposes a simulation linear model created in the MATLAB environment, which provides a process for regulating blood sugar levels. The controller is built for the need for any type of diabetes to control and normalize the blood sugar content of the [...] Read more.
This paper proposes a simulation linear model created in the MATLAB environment, which provides a process for regulating blood sugar levels. The controller is built for the need for any type of diabetes to control and normalize the blood sugar content of the patient in order to eliminate the differences in the quality of life of a diabetic patient and a healthy person. The linearization of the nonlinear model was performed, and the adequacy of the linearized model was verified and confirmed using the MATLAB simulation. The choice of the PID controller and the CHR method for its adjustment was justified and MATLAB tools were used to show the implementation of these methods. The model of the patient with the controller has been built; the algorithm for the automatic adjustment of the PID controller parameters has been developed and realized. The directions for continuation of the work on this problem regarding regulation in the system under study are proposed. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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9 pages, 11181 KiB  
Proceeding Paper
Control of Unmanned Vehicles in Smart Cities Using a Multi-Modal Brain–Computer Interface
by Daniyar Wolf, Mark Mamchenko and Elena Jharko
Eng. Proc. 2023, 33(1), 43; https://doi.org/10.3390/engproc2023033043 - 28 Jun 2023
Cited by 1 | Viewed by 949
Abstract
The article presents an overview of several studies in the field of Brain–Computer Interfaces (BCIs), the requirements for the architecture of such promising devices, as well as multi-modal BCI for drone control in a smart-city environment. Distinctive features of the proposed solution are [...] Read more.
The article presents an overview of several studies in the field of Brain–Computer Interfaces (BCIs), the requirements for the architecture of such promising devices, as well as multi-modal BCI for drone control in a smart-city environment. Distinctive features of the proposed solution are the simplicity of the architecture (the use of only one smartphone for both receiving and processing bio-signals from the headset and transmitting commands to the drone), an open-source software solution for signal processing, generating, and sending commands to the unmanned aerial vehicle (UAV), as well as multimodality of the BCI (the use of both electroencephalographic (EEG) and electrooculographic (EOG) signals of the operator). For bio-signal acquisition, we used the NeuroSky Mindwave Mobile 2 headset, which is connected to an Android-based smartphone via Bluetooth. The developed Android application (Tello NeuroSky) processes signals from the headset and generates and transmits commands to the DJI Tello UAV via Wi-Fi. The decrease (depression) and increase of α- and β-rhythms of the brain, as well as EOG signals that occur during blinking were the triggers for UAV commands. The developed software allows the manual setting of the minimum, maximum and threshold values for the processed bio-signals. The following commands for the UAV were implemented: take-off, landing, forward movement, and backwards movement. Two threads of the smartphone’s central processing unit (CPU) were utilized when processing signals in the software to increase the performance: for signal processing (1-D Daubechies 2 (db2) wavelet transform) and updating data on the diagrams, and for generating and transmitting commands to the drone. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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9 pages, 2325 KiB  
Proceeding Paper
An Intelligent Gait Data Processing Algorithm Based on Mobile Phone Accelerometers
by Nikolay Dorofeev and Anastasya Grecheneva
Eng. Proc. 2023, 33(1), 44; https://doi.org/10.3390/engproc2023033044 - 03 Jul 2023
Viewed by 343
Abstract
This paper describes an algorithm for extracting human gait movements in data obtained from accelerometer sensors of a mobile phone, provided that the mobile phone is used in the usual mode. The algorithm also performs a classification of the selected movements based on [...] Read more.
This paper describes an algorithm for extracting human gait movements in data obtained from accelerometer sensors of a mobile phone, provided that the mobile phone is used in the usual mode. The algorithm also performs a classification of the selected movements based on a feed-forward neural network. The developed algorithm selects the best areas in the accelerometer data, which reflect individual steps, according to the optimality criterion. For the selected area, the optimality criterion is the maximum value of the correlation coefficient with all other data segments. The selected plots are used as templates. Changing the parameters of patterns over time is necessary to assess changes in the individual rate of the functioning of the musculoskeletal system. Due to the correction of tolerance limits at the segmentation stage, the algorithm adapts to the change in gait speed. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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8 pages, 2782 KiB  
Proceeding Paper
From Matryoshka and Fukuruma to Hierarchies of Criteria and Ranking Methods in Multi-Criteria Problems of Analysis and Decision Making
by Nicolay Klevanskiy, Victor Glazkov, Yermek Saparov and Vladimir Mavzovin
Eng. Proc. 2023, 33(1), 45; https://doi.org/10.3390/engproc2023033045 - 04 Jul 2023
Viewed by 427
Abstract
Compound toys simulate the hierarchy of single inclusion. We propose classification of criteria and ranking methods for multi-criteria problems of analysis and decision making. The definitions of subjective and objective criteria are introduced. The application of two methods of cognitive visualization to identify [...] Read more.
Compound toys simulate the hierarchy of single inclusion. We propose classification of criteria and ranking methods for multi-criteria problems of analysis and decision making. The definitions of subjective and objective criteria are introduced. The application of two methods of cognitive visualization to identify the structure of ranking algorithms is represented: the method of separation of the ranking scheme and that of the color shading of individual elements of the scheme. A multiple-inclusion hierarchy was identified for the criteria and ranking methods. Visualization of the identified hierarchies of multiple inclusions was performed using circular representations similar to Euler–Venn diagrams. The use of objective criteria and their application in ranking algorithms was shown on the example of solving the problems of forming schedules and calendar schedules. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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7 pages, 889 KiB  
Proceeding Paper
A Review of Engineering Techniques for EEG Processing
by Veronica Tolmanova and Denis Andrikov
Eng. Proc. 2023, 33(1), 46; https://doi.org/10.3390/engproc2023033046 - 10 Jul 2023
Cited by 1 | Viewed by 525
Abstract
This article provides not only a description of an electroencephalogram (EEG), the principle of its operation, conditions of use, methods of decoding but also studies aimed at improving this procedure and facilitating the work of highly professional employees studying EEG results. A study [...] Read more.
This article provides not only a description of an electroencephalogram (EEG), the principle of its operation, conditions of use, methods of decoding but also studies aimed at improving this procedure and facilitating the work of highly professional employees studying EEG results. A study of published articles related to electroencephalograms was carried out in order to trace the entire path of development and use of EEGs. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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6 pages, 443 KiB  
Proceeding Paper
Exponential Particle Swarm Optimization Algorithm for Complexly Structured Images Segmentation
by Samer El-Khatib, Yuri Skobtsov and Sergey Rodzin
Eng. Proc. 2023, 33(1), 47; https://doi.org/10.3390/engproc2023033047 - 13 Jul 2023
Cited by 1 | Viewed by 372
Abstract
Image segmentation is the process of dividing an image into homogeneous regions according to certain features and is widely used in image processing. Complexly structured images usually contain complex and essential objects. These images are non-linear structural images and they contain a large [...] Read more.
Image segmentation is the process of dividing an image into homogeneous regions according to certain features and is widely used in image processing. Complexly structured images usually contain complex and essential objects. These images are non-linear structural images and they contain a large number of elements with required specifications. The main goal of the proposed EPSO (Exponential Particle Swarm Optimization) algorithm is to prevent local solutions and find the exact global optimal solutions for the task of segmenting medical images. The execution time is compared with well-known segmentation algorithms. The EPSO method is superior to the segmentation methods studied, including the graph algorithm. Comparisons were made with existing segmentation algorithms (Grow cut, Random Walker, DPSO, K-means PSO, and hybrid-K-means ant colony optimization algorithm) in tabular form. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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13 pages, 648 KiB  
Proceeding Paper
Methodological Approach to Controlling the Degree of Intentions about Novel Knowledge for the Digital Economy
by Alexander A. Zatsarinnyy and Alexander P. Shabanov
Eng. Proc. 2023, 33(1), 48; https://doi.org/10.3390/engproc2023033048 - 17 Jul 2023
Viewed by 463
Abstract
The methodological approach to controlling the level of intentions about new knowledge in the field of artificial intelligence, which are expressed by organizational systems in the scientific industry and in the real sector of the economy, is investigated. Control is carried out in [...] Read more.
The methodological approach to controlling the level of intentions about new knowledge in the field of artificial intelligence, which are expressed by organizational systems in the scientific industry and in the real sector of the economy, is investigated. Control is carried out in a digital platform based on semantic databases, which are structured under control concepts, under data entity accounting strategies, under the functions of the implementation management process and under the requirements for the timeliness of data transmission. The novelty lies in the ranking of studies depending on the degree of coincidence of intentions. The practical significance is manifested in the priority provision of new knowledge, which is most significant in the digital economy. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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6 pages, 420 KiB  
Proceeding Paper
A Neuro-Fuzzy System for Power Supply Control
by Sergey Morozov and Mikhail Kupriyanov
Eng. Proc. 2023, 33(1), 49; https://doi.org/10.3390/engproc2023033049 - 17 Jul 2023
Viewed by 393
Abstract
Automatic control of power supply sources is considered. Different types of batteries behave differently inside a device and require specific optimal conditions to perform efficiently. Using the wrong operating mode of a battery can lead to malfunctions within it, which may affect the [...] Read more.
Automatic control of power supply sources is considered. Different types of batteries behave differently inside a device and require specific optimal conditions to perform efficiently. Using the wrong operating mode of a battery can lead to malfunctions within it, which may affect the device’s performance. Adaptive methods for optimizing power modes are presented. The adaptivity of the method is achieved by using a baseline, which is based on artificial intelligence concepts. These concepts are neural networks and fuzzy logic, which are used to create systems capable of learning and being interpretable. This method is able to execute control over a batteries state and take actions which are required to save a battery and prolong its lifespan. The adaptivity of the system is demonstrated by the ability to take information about the environment into account. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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8 pages, 937 KiB  
Proceeding Paper
Functional Converter for Intelligent Sensor and Its Layout Design
by Olga Bureneva, Sergey Mironov, Nikolay Safyannikov and Zhanna Sukhinets
Eng. Proc. 2023, 33(1), 50; https://doi.org/10.3390/engproc2023033050 - 17 Jul 2023
Cited by 2 | Viewed by 379
Abstract
Recently, the number of cyber-physical systems and systems with embedded sensors has been increasing. In order to minimize the amount of information transmitted, a new paradigm is being developed that involves moving data processing as close as possible to the point of its [...] Read more.
Recently, the number of cyber-physical systems and systems with embedded sensors has been increasing. In order to minimize the amount of information transmitted, a new paradigm is being developed that involves moving data processing as close as possible to the point of its generation. At the same time, there is a need to create devices that will provide computations near the sensors. The article considers an approach to the primary processing of a quasi-digital sensor signal. The authors show a variant of the organization of calculations in pulse form, based on the method of small increments. The method is focused on the usage of simple logical elements with the realization of a transfer function in the base of increment/decrement operations. The solution proposed by the authors is effective in terms of simplicity of hardware implementation and can be used to connect sensors with pulse output to digital processing systems. The considered circuit solutions can be used for the implementation in programmable logic device of different levels of complexity, as well as for the manufacture of the transducer in the form of a custom circuit. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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10 pages, 676 KiB  
Proceeding Paper
Application of a Deterministic Optical Network Model for the Implementation of an Expert System Knowledge Base for Information Transmission Failure Management
by Vladislav Kosyanchuk, Nikolay Selvesyuk, Evgeniy Zybin, Valeriy Novikov, Valentin Olenev, Andrey Solovyov and Mikhail Semyonov
Eng. Proc. 2023, 33(1), 51; https://doi.org/10.3390/engproc2023033051 - 19 Jul 2023
Viewed by 361
Abstract
This article presents an approach for the construction of an expert system, which helps to make the decisions when parrying failures during information exchange in real-time systems based on a deterministic optical network. The authors analyze the requirements for deterministic data exchange environments [...] Read more.
This article presents an approach for the construction of an expert system, which helps to make the decisions when parrying failures during information exchange in real-time systems based on a deterministic optical network. The authors analyze the requirements for deterministic data exchange environments and consider the trends for the development of software and hardware for deterministic networks. The main goal of this article is to propose a concept for the implementation of a deterministic control unit based on an all-optical network with spectral division multiplexing. Two main steps for the implementation of such a system are described. The first is the implementation of the DOS protocol stack and its model, which was used in several protocol development stages. This model is a part of a proposed concept for an automation design and development system for information exchanges. The second presented step is the development of an expert decision support system, based on the principles of the supervisory approach. This article presents a neurocontroller, which provides hardware support for the implementation of individual modes of operation of an expert system. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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8 pages, 1501 KiB  
Proceeding Paper
Research of a Virtual Infrastructure Network with Hybrid Software-Defined Switching
by Yuri Ushakov, Margarita Ushakova and Leonid Legashev
Eng. Proc. 2023, 33(1), 52; https://doi.org/10.3390/engproc2023033052 - 19 Jul 2023
Viewed by 451
Abstract
Modern trends in the information technology have led to the fact that entire systems of infrastructure are becoming software-defined. Modern hyper-converged solutions use software-defined networking and soft switches for the hypervisor networking subsystem. The paper goal is to study traffic processing in hyperconverged [...] Read more.
Modern trends in the information technology have led to the fact that entire systems of infrastructure are becoming software-defined. Modern hyper-converged solutions use software-defined networking and soft switches for the hypervisor networking subsystem. The paper goal is to study traffic processing in hyperconverged structures with software switching based on OpenFlow versus traditional approaches. The features of the hyperconverged solutions network infrastructure are considered, approaches to the study of software-defined environments are described. A model of the processing traffic internal structure of a converged node, combining the functions of a hypervisor, a storage system and a switch, is proposed. Interface models reproduced traffic switching with the traditional approach and with higher-level OpenFlow processing have been developed. The approaches to the implementation of the developed models based on experimental studies of network equipment are described. The results of an experimental study of a network node and a synthesized model are presented. The possibility of implementing the proposed approaches within the specified accuracy are described. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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6 pages, 285 KiB  
Proceeding Paper
Aircraft Optimal Control for Longitudinal Maneuvers Using Population-Based Algorithm
by Oleg Korsun, Alexandr Poliyev and Alexandr Stulovskii
Eng. Proc. 2023, 33(1), 53; https://doi.org/10.3390/engproc2023033053 - 19 Jul 2023
Cited by 1 | Viewed by 416
Abstract
This report considers optimization of aircraft maneuvers in the vertical plane based on direct control methods. It proposes an object model for longitudinal motion suitable for optimal control, algorithms for control approximation and a numerical solution to the problem via a population-based optimization [...] Read more.
This report considers optimization of aircraft maneuvers in the vertical plane based on direct control methods. It proposes an object model for longitudinal motion suitable for optimal control, algorithms for control approximation and a numerical solution to the problem via a population-based optimization algorithm. The suggested method proves its applicability by forming the control signals for basic aircraft maneuvers in the vertical plane, including climb, speed increment, descent and speed decrement. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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8 pages, 275 KiB  
Proceeding Paper
Providing High-Speed Data Access for Parallel Computing in the HPC Cluster
by Sergey Denisov, Konstantin Volovich and Alexander Zatsarinny
Eng. Proc. 2023, 33(1), 54; https://doi.org/10.3390/engproc2023033054 - 21 Jul 2023
Viewed by 470
Abstract
The article discusses approaches to building parallel data storage systems in high- performance clusters. The features of building data structures in parallel file systems for various applied tasks are analyzed. Approaches are proposed to improve the efficiency of access to data by computing [...] Read more.
The article discusses approaches to building parallel data storage systems in high- performance clusters. The features of building data structures in parallel file systems for various applied tasks are analyzed. Approaches are proposed to improve the efficiency of access to data by computing nodes of the cluster due to the correct distribution of data in parallel file storage. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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7 pages, 217 KiB  
Proceeding Paper
Dynamic Job Queue Management for Interactive and Batch Computation on HPC System
by Sergey Denisov, Vadim Kondrashev and Alexander Zatsarinny
Eng. Proc. 2023, 33(1), 55; https://doi.org/10.3390/engproc2023033055 - 21 Jul 2023
Viewed by 416
Abstract
The article discusses HPC system computing resources distribution management during execution of interactive and batch jobs. A set of queues for interactive and batch jobs is proposed, and an algorithm for the dynamic resources allocation between the proposed job queues is described. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
10 pages, 6114 KiB  
Proceeding Paper
Convolutional Neural Network Application to Automate the Process of Aliquoting Biosamples
by Sergey Khalapyan, Larisa Rybak, Anna Nozdracheva and Tatyana Semenenko
Eng. Proc. 2023, 33(1), 56; https://doi.org/10.3390/engproc2023033056 - 25 Jul 2023
Viewed by 488
Abstract
To automate the aliquoting process, it is necessary to determine the required depth of immersion of the pipette into the blood serum. This paper presents the results of a study aimed at creating a vision system that makes it possible to determine the [...] Read more.
To automate the aliquoting process, it is necessary to determine the required depth of immersion of the pipette into the blood serum. This paper presents the results of a study aimed at creating a vision system that makes it possible to determine the position and nature of the fractional interface based on the use of a convolutional neural network. As a result of training on photographic images of tubes ready for aliquoting, the neural network acquired the ability to determine the visible part of the tube, the upper fraction of its contents, and the fibrin strands with high accuracy, allowing the required pipette immersion depth to be calculated. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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6 pages, 522 KiB  
Proceeding Paper
Artificial Neural Networks Multicriteria Training Based on Graphics Processors
by Vladimir A. Serov, Evgenia L. Dolgacheva, Elizaveta Y. Kosyuk, Daria L. Popova, Pavel P. Rogalev and Anastasia V. Tararina
Eng. Proc. 2023, 33(1), 57; https://doi.org/10.3390/engproc2023033057 - 25 Jul 2023
Viewed by 513
Abstract
The report considers the task of training a multilayer perceptron, formulated as a problem of multiobjective optimization under uncertainty. To solve this problem, the principle of vector minimax was used. A parallel software implementation of a hierarchical evolutionary algorithm for solving a multicriteria [...] Read more.
The report considers the task of training a multilayer perceptron, formulated as a problem of multiobjective optimization under uncertainty. To solve this problem, the principle of vector minimax was used. A parallel software implementation of a hierarchical evolutionary algorithm for solving a multicriteria optimization problem under uncertainty based on a GPU is presented. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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10 pages, 490 KiB  
Proceeding Paper
A Hybrid Transdimensional Evolutionary Algorithm for Dynamical System Control Multicriteria Optimization
by Vladimir A. Serov, Evgeny M. Voronov, Evgenia L. Dolgacheva and Elizaveta Y. Kosyuk
Eng. Proc. 2023, 33(1), 58; https://doi.org/10.3390/engproc2023033058 - 27 Jul 2023
Viewed by 411
Abstract
The article develops a new hybrid evolutionary algorithm for the optimal control law multicriteria synthesis of a dynamical system based on transdimensional search models. The transdimensional search model implies the combined usage of finite-dimensional and infinite-dimensional multicriteria optimization evolutionary algorithms, implementing the stages [...] Read more.
The article develops a new hybrid evolutionary algorithm for the optimal control law multicriteria synthesis of a dynamical system based on transdimensional search models. The transdimensional search model implies the combined usage of finite-dimensional and infinite-dimensional multicriteria optimization evolutionary algorithms, implementing the stages of the global approximate and local clarifying search for optimal solutions. A comparative analysis of the effectiveness of various hybrid transdimensional models of the evolutionary search is carried out for the problem of the bioreactor program control optimal law multicriteria synthesis. It is shown that the transdimensional hybridization of evolutionary algorithms using infinite-dimensional search models provides a higher solving accuracy of the problem. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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6 pages, 278 KiB  
Proceeding Paper
Neuro-Evolutionary Synthesis of Game Models of Control under Uncertainty Based on Distributed Computing Technology
by Vladimir A. Serov, Daria L. Popova, Pavel P. Rogalev and Anastasia V. Tararina
Eng. Proc. 2023, 33(1), 59; https://doi.org/10.3390/engproc2023033059 - 25 Jul 2023
Viewed by 641
Abstract
The methodology basic principles of the neuro-evolutionary synthesis of multi-object multi-criteria systems control models under conflict and uncertainty in real time are discussed. The proposed methodology includes the following main stages: a hierarchical optimization game model under conflict and uncertainty development; a library [...] Read more.
The methodology basic principles of the neuro-evolutionary synthesis of multi-object multi-criteria systems control models under conflict and uncertainty in real time are discussed. The proposed methodology includes the following main stages: a hierarchical optimization game model under conflict and uncertainty development; a library development of hierarchical coevolutionary algorithms for multi-criteria optimization under conflict and uncertainty; software implementation of hierarchical coevolutionary algorithms library based on distributed computing technology; and game algorithms of control under uncertainty synthesis based on the technology of neural networks ensembles. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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4 pages, 271 KiB  
Proceeding Paper
A Hierarchical Model of a Vector Nash Equilibrium Search in a Control Problem under Conflict and Uncertainty
by Vladimir A. Serov and Evgeny M. Voronov
Eng. Proc. 2023, 33(1), 60; https://doi.org/10.3390/engproc2023033060 - 25 Jul 2023
Cited by 1 | Viewed by 319
Abstract
A hierarchical model of a vector Nash equilibrium search under uncertainty is developed. The sufficient conditions for a vector Nash equilibrium of a noncooperative game under uncertainty are formulated, which can be used as a criterion to achieve the required degree of nonquilibrium [...] Read more.
A hierarchical model of a vector Nash equilibrium search under uncertainty is developed. The sufficient conditions for a vector Nash equilibrium of a noncooperative game under uncertainty are formulated, which can be used as a criterion to achieve the required degree of nonquilibrium for an acceptable solution to the problem of multi-object multicriteria systems’ control optimization under conflict and uncertainty. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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24 pages, 9310 KiB  
Proceeding Paper
Hierarchical Cascade Control Systems for Time-Dependent Dynamical Plants as Applied to Magnetic Plasma Control in D-Shaped Tokamaks
by Yuri V. Mitrishkin
Eng. Proc. 2023, 33(1), 61; https://doi.org/10.3390/engproc2023033061 - 07 Aug 2023
Viewed by 699
Abstract
The systems of poloidal field coils in D-shaped Tokamaks such as ITER, EAST, JET, ASDEX Upgrade, TCV, GLOBUS-M2, DIII-D, SPARC, IGNITOR, JT-60SA, DEMO-9.1, DEMO-1.6, T-15MD, and TRT are analyzed for their efficiency in the application of plasma position, current, and shape control systems [...] Read more.
The systems of poloidal field coils in D-shaped Tokamaks such as ITER, EAST, JET, ASDEX Upgrade, TCV, GLOBUS-M2, DIII-D, SPARC, IGNITOR, JT-60SA, DEMO-9.1, DEMO-1.6, T-15MD, and TRT are analyzed for their efficiency in the application of plasma position, current, and shape control systems in these Tokamaks. The problem of magnetic plasma control in Tokamaks is presented. A methodology for designing hierarchical cascade systems of magnetic plasma control in D-shaped Tokamaks has been developed on the basis of generalizations of existing plasma magnetic control systems. The hierarchical levels are as follows: multivariable robust cascade control level, adaptation level, artificial intelligence level, and decision-making level. To implement these systems in the practice of physical experimentation, it is proposed to use digital twins, the basis of which is a real-time digital testbed created by Lomonosov Moscow State University and the Trapeznikov Institute of Control Sciences of the Russian Academy of Sciences. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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6 pages, 1099 KiB  
Proceeding Paper
Robust System of Algorithms for the Functioning of Biocompatible Artificial Liver Devices
by Alexey Ganshin and Denis Andrikov
Eng. Proc. 2023, 33(1), 62; https://doi.org/10.3390/engproc2023033062 - 15 Aug 2023
Viewed by 345
Abstract
This article concerns liver transplantation and its associated difficulties and risks, and also describes a more progressive method of saving people in need of a liver transplant—an artificial liver. An analysis of the BioUML software platform for modeling bioartificial liver systems is also [...] Read more.
This article concerns liver transplantation and its associated difficulties and risks, and also describes a more progressive method of saving people in need of a liver transplant—an artificial liver. An analysis of the BioUML software platform for modeling bioartificial liver systems is also presented. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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8 pages, 1727 KiB  
Proceeding Paper
Natural Data Analysis Method Based on Wavelet Filtering and NARX Neural Networks
by Oksana Mandrikova, Yurii Polozov and Bogdana Mandrikova
Eng. Proc. 2023, 33(1), 63; https://doi.org/10.3390/engproc2023033063 - 16 Aug 2023
Viewed by 423
Abstract
A method for analyzing natural data and detecting anomalies is proposed. The method is based on combining wavelet filtering operations with the NARX neural network. The analysis of natural data and the detection of anomalies are of particular relevance in the problems of [...] Read more.
A method for analyzing natural data and detecting anomalies is proposed. The method is based on combining wavelet filtering operations with the NARX neural network. The analysis of natural data and the detection of anomalies are of particular relevance in the problems of geophysical monitoring. An important requirement of these methods is their adaptability, accuracy and efficiency. Efficiency makes it possible to detect anomalies timely in order to prevent catastrophic natural phenomena. Wavelet filtering operations include the application of a multi-scale analysis construction and threshold functions. The article proposes a wavelet filtering algorithm and a method for estimating thresholds based on a stochastic approach. The operations of the method implementation are described. It is shown that the use of wavelet filtering allows one to suppress noise, simplifies the data structure and, as a result, allows one to obtain a more accurate NARX neural network model. The effectiveness of the method for detecting ionospheric anomalies during periods of magnetic storms is shown using the data of the critical frequency of the ionosphere as an example. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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7 pages, 535 KiB  
Proceeding Paper
Optimal Design of a Reliability Experiment Based on the Wiener Degradation Model under Limitations of the Degradation Index
by Evgeniya Osintseva and Ekaterina Chimitova
Eng. Proc. 2023, 33(1), 64; https://doi.org/10.3390/engproc2023033064 - 23 Aug 2023
Viewed by 314
Abstract
There are many degradation models that are used in reliability analyses. The Wiener degradation model is the most popular across different applications. In this paper, we propose an approach for searching for an optimal design on the basis of the Wiener degradation model. [...] Read more.
There are many degradation models that are used in reliability analyses. The Wiener degradation model is the most popular across different applications. In this paper, we propose an approach for searching for an optimal design on the basis of the Wiener degradation model. The distinguishing feature of the approach is that the condition that the degradation index cannot exceed a critical level has been taken into account. The elements of the conditional Fisher information matrix have been obtained. This enables us to calculate the optimal stress levels by maximizing the functional of the conditional Fisher information matrix. Moreover, a degradation analysis of light-emitting diodes (LEDs) has been considered. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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9 pages, 278 KiB  
Proceeding Paper
On the Stability of Collinear Libration Points in the Three-Body Problem with Two Radiating Masses
by Abdilda Tureshbaev, Ulbossyn Omarova and Ramatilla Myrzayev
Eng. Proc. 2023, 33(1), 65; https://doi.org/10.3390/engproc2023033065 - 22 Aug 2023
Viewed by 378
Abstract
The stability of cloud accumulations of gas and dust particles in the field of binary star systems is studied. As a dynamic model, we consider a restricted three-body problem in which both main bodies are radiating. We study the stability of collinear libration [...] Read more.
The stability of cloud accumulations of gas and dust particles in the field of binary star systems is studied. As a dynamic model, we consider a restricted three-body problem in which both main bodies are radiating. We study the stability of collinear libration points (CLL) in a nonlinear formulation. The problem of CLP stability is considered in three-dimensional parametric space. It is shown that at the resonance of the fourth order in the plane problem, the points under study are stable in the sense of Lyapunov. In this case, the invariant normal form and Markeev’s theorem are used. The stability of the CLP in the spatial problem is considered. The Birkhoff normal form is used and the Arnold–Moser theorem is used. Results are obtained on stability for most initial conditions (in the Lebesgue measure) and formal stability. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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8 pages, 1345 KiB  
Proceeding Paper
ADRC-Based UAV Control Scheme for Automatic Carrier Landing
by Ruiyang Zhou and Konstantin A. Neusypin
Eng. Proc. 2023, 33(1), 66; https://doi.org/10.3390/engproc2023033066 - 09 Oct 2023
Cited by 1 | Viewed by 501
Abstract
In this paper the problem of atmospheric disturbances during the UAV carrier landing operation is considered. A UAV dynamics model, and a wind gust and airwake disturbance model are introduced. A LADRC-based cascade control scheme is developed for fixed-wing UAVs. In the control [...] Read more.
In this paper the problem of atmospheric disturbances during the UAV carrier landing operation is considered. A UAV dynamics model, and a wind gust and airwake disturbance model are introduced. A LADRC-based cascade control scheme is developed for fixed-wing UAVs. In the control scheme, three ADRC controllers are designed for attitude control, and another two ADRC controllers are designed for course and altitude tracking. Finally, a series of simulations are implemented in Simulink and the results are presented to demonstrate the performance of the proposed control scheme. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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9 pages, 270 KiB  
Proceeding Paper
AGI’s Hierarchical Component Approach to Unsolvable by Direct Statistical Methods Complex Problems
by Vladimir Smolin and Sergey Sokolov
Eng. Proc. 2023, 33(1), 67; https://doi.org/10.3390/engproc2023033067 - 10 Oct 2023
Viewed by 379
Abstract
The amazing deep neural network (DNN) advances over the past 10 years have made it possible, if there is enough data and computing power, to achieve solutions to unexpectedly complex problems. But DNN does not explicitly use decomposition, the main advancement method in [...] Read more.
The amazing deep neural network (DNN) advances over the past 10 years have made it possible, if there is enough data and computing power, to achieve solutions to unexpectedly complex problems. But DNN does not explicitly use decomposition, the main advancement method in complicated task solving. The automatic complex scenes decomposition can be carried out based on mapping by a neural network. The problem is the impossibility to map complex objects and phenomena state spaces. The hierarchical complex scene’s division into simple components can be a key for solving the problem. The hierarchically organized structure of simple objects and phenomena maps of different abstraction levels can make it possible to solve problems in a complex environment, in which all properties cannot directly be revealed by statistical methods. Operation modes of such a hierarchical structure can be correlated with terms used in philosophy and psychology. Full article
(This article belongs to the Proceedings of 15th International Conference “Intelligent Systems” (INTELS’22))
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