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Application of Blockchain Technology for Verification of State Documents in the Russian Federation

Application of Blockchain Technology for Verification of Sta...

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Siberian Conference on control and Communications (SIBCON)

作者： Mikhail V. Vladimirov Pavel V. Senchenko Anatoly A. Sidorov Department of Data Processing Automation Tomsk State University of Control Systems and Radioelectronics Tomsk Russian Federation

ISBN: (纸本)9781665476294

The article provides an analysis of the possibilities of using Blockchain technology in the framework of programs for economic digitalization and development of the educational sector. Three main areas of blockchain use are highlighted: cryptocurrencies, tracking the uniqueness of items and smart-contracts. A classification of blockchain-based systems dividing existing systems by scope has also been proposed. The article discusses the current methods of using this technology for the implementation of various tasks within the framework of individual enterprises, states and the world. A promising solution in accordance with the current trends and directions of development has also been proposed. The problems associated with the implementation of blockchain systems are also described.

关键词： Training Economics Instruments Bitcoin Market research Blockchains Behavioral sciences

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Prediction of the Magnitude of Lightning Impulse Interference in an Electronic Device Using an Artificial Neural Network

Prediction of the Magnitude of Lightning Impulse Interferenc...

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International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM)

作者： Zinnur Gizatullin Ramis Mubarakov Department for Automated Systems for Information Processing and Control Department for Computer-Aided Design Systems Kazan National Research Technical University named after A.N. Tupolev-KAI Kazan Russian Federation Department for Computer-Aided Design Systems Kazan National Research Technical University named after A.N. Tupolev-KAI Kazan Russian Federation

ISBN: (数字)9798350395013

ISBN: (纸本)9798350395020

Reliable operation of modern electronic devices is the basis for their effective use. Electromagnetic interference, such as lightning, creates the risk of temporary or permanent disruption of the functioning of device elements. Therefore, it is necessary to take into account the possible consequences of such interference on the basis of prediction even at the design stage of electronic devices. The paper a technique for predicting the magnitude of lightning impulse interference in electronic devices using an artificial neural network is proposed. The advantage of this approach over simulation modeling is that rather complex three-dimensional models and long computation times are not needed. A stand was developed and obtained by measuring the amount of lightning interference in an electronic device. The features of the task of training an artificial neural network based on experimental data are considered. The architecture and parameters of the artificial neural network have been selected. An artificial neural network was trained based on experimental data. The root mean square error between the predicted data and the average impulse interference voltage values on the training data does not exceed acceptable values. The results of predicting the magnitude of lightning interference in an electronic device are presented. If we consider further prospects for using an artificial neural network to predict electromagnetic interference, we can note the relevance of the problem of the impact of electrostatic discharge, intentional short pulse and etc.

关键词： Training Solid modeling Magnetic field measurement Computational modeling Electromagnetic interference Lightning Training data

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Management of Scientific Agricultural Digital Ecosystems Based on Ecosystem Classification

Management of Scientific Agricultural Digital Ecosystems Bas...

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International Conference on Management of Large-Scale System Development (MLSD)

作者： Vladimir Kulba Viktor Medennikov Laboratory of Modular Data Processing and Control Systems V.A. Trapeznikov Institute of Control Sciences of the Russian Academy of Sciences Moscow Russia Information and Computing Systems Department Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences Moscow Russia

The paper considers a mathematical model for managing a scientific digital ecosystem exemplified by the agriculture case; the model enables assessing the impact science exerts on the regions’ socioeconomic position in order to build an adequate response to the advanced economies’ regime of severe sanctions against Russia. For these purposes, a systemic analysis of the subject identification and classification of ecosystems was conducted to address the critical issue of determining the basic concepts and terms of the country’s digitalization.

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Specifics of Project Management System Development for Large Organizations

Specifics of Project Management System Development for Large...

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2020 International Multi-Conference on Industrial Engineering and Modern Technologies, FarEastCon 2020

作者： Mukhamadiev, R. Staroverova, N. Shustrova, M. Kazan National Reseach Technological Univercity Department of the Automated Systems of Data Obtaining and Processing Kazan Russia

ISBN: (纸本)9781728169514

The relevance of the work arises from the fact that it is difficult to imagine the functioning of large organizations without the use of information systems. The article reviews the process of developing an effective project management system, based on all the requirements of such systems. The subject of the research is project management systems and the specifics of the project development process. The purpose of this work is to analyze one of the major functioning information systems and to find solutions to improve the quality of its work. The prototype system running on the FengOffice platform was analyzed using Google's tools to analyze the functionality of web applications. Ruby on Rails and NodeJS were selected to develop the new project management system as a web application. The main criteria defined for the system were speed and lack of redundant functionality. In addition, the system is designed to have minimal access to the disk system, as I-O operations are considered to be a long-term operation. The latest developments in modeling and designing were used to design the database structure. A comparison between the developed system and the prototype system revealed that the developed system was significantly superior to the other. The speed of page loading with the introduction of the new system has increased 67-fold, and the usability and efficiency of the software has increased due to the elimination of redundant functionality. The information presented in this work can be useful for web application developers, project management systems developers and IT specialists. © 2020 IEEE.

关键词： Project management

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Integration of Earth Remote Sensing data on the Digital Platform of Russian Agriculture 7

Integration of Earth Remote Sensing Data on the Digital Plat...

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7th IEEE International Conference on Information Technology and Nanotechnology, ITNT 2021

作者： Medennikov, Victor Raikov, Alexander Federal Research Center 'Informatics and Control' of the Russian Academy of Sciences Information and Computing Systems Department Moscow Russia Laboratory of Modular Data Processing and Control Systems V.A. Trapeznikov Institute of Control Sciences of the Russian Academy of Sciences Moscow Russia

ISBN: (纸本)9781665432177

The paper addresses the state and development trends of Earth remote sensing technologies, which currently are becoming one of the main tools of accelerating the development of precision farming technologies and technologies for improving management in related industries. The authors show that these technologies are developing from the digitalization of elementary operations to the digitalization of the complete complex of all operations based on an architectural approach, end-to-end digital and cloud technologies. The paper proposes a scientific basis for integrating Earth remote sensing data into a single digital platform for agriculture in Russia, substantiated using mathematical and ontological modelling of digital platforms for managing the industry's economy. © 2021 IEEE.

关键词： Agriculture

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Mathematical Model of Managing the Agricultural Holdings in Building a Digital Platform 14

Mathematical Model of Managing the Agricultural Holdings in ...

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14th International Conference Management of Large-Scale System Development, MLSD 2021

作者： Kulba, Vladimir Medennikov, Viktor Laboratory of Modular Data Processing and Control Systems V.A. Trapeznikov Institute of Control Sciences Russian Academy of Sciences Moscow Russia Federal Research Center 'Computer Science and Control' Russian Academy of Sciences Information and Computing Systems Department Moscow Russia

ISBN: (纸本)9781665412308

This work presents the original proprietary mathematical model for interregional agricultural holding management relying on the harmonized digital platform of the Russian agrarian sector that allows conceiving the general formalized approach to the strategic direction of various integrated establishments within the sector. The approach provides a theoretical substantiation for harmonized approaches to the long-term digital transformation of major agricultural associations followed by medium and small businesses. © 2021 IEEE.

关键词： Agriculture

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automated Human Facial Emotion Recognition System Using Depthwise Separable Convolutional Neural Network

Automated Human Facial Emotion Recognition System Using Dept...

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2023 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology, IAICT 2023

作者： Hashan, Antor Mahamudul Al-Saeedi Adnan Adhab, K. Islam, Rizu Md Rakib Ul Avinash, Kumar Dey, Subhankar Ural Federal University Named after the First President of Russia B. N. Yeltsin Department of Intelligent Information Technologies Yekaterinburg Russia National University of Science and Technology 'MISiS' Department of Automated Control Systems Moscow Russia Ural Federal University Named after the First President of Russia B. N Yeltsin Department of Information Technology and Management Systems Yekaterinburg Russia Ural Federal University Named after the First President of Russia B. N. Yeltsin Department of Big Data Analytics and Video Analysis Methods Yekaterinburg Russia

ISBN: (纸本)9798350313635

The automatic human facial emotion recognition (AHFER) system has its wide significant contribution in several disciplines, such as human-computer collaboration, human-robot interaction, and so on. Multiple research projects have been conducted regarding this topic because it is a challenging and interesting task, especially in the area of computer vision. The purpose of the work is to recognize facial emotions using a depthwise separable convolutional neural network (DS-CNN). Apart from that, a facial emotion dataset has been proposed, and splitting functions, intensity normalization, image cropping, and grayscale conversion have been used in data pre-processing. The AHFER system is capable of recognizing four types of emotions: happy, sad, angry, and neutral. The results of the experiment showed that the AHFER method is 99 percent accurate when training and 93 percent accurate when validating. Additionally, we determined the confusion matrix with precision, recall, and fl-score. A comparison between the DS-CNN and DNN models was performed. The DS-CNN model performed significantly better than the DNN model. The DS-CNN model could be improved in the future by including more facial emotion categories. © 2023 IEEE.

关键词： Convolution

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control of an Autonomous Energy Complex with Renewable Energy Sources, taking into account the Type of Input Information Uncertainty 4

Control of an Autonomous Energy Complex with Renewable Energ...

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4th International Conference on control in Technical systems, CTS 2021

作者： Simankov, Vladimir S. Buchatskiy, Pavel Yu. Shopin, Andrey V. Teploukhov, Semen V. Buchatskaya, Victoria V. Department of Computer Technologies and Information Security Kuban State Technological University Krasnodar Russia Department of Automated Systems of Processing Information and Control Adyghe State University Maykop Russia Department of Applied Mathematics Information Technology and Information Security Adyghe State University Maykop Russia

ISBN: (纸本)9781665424547

This article discusses the management of autonomous energy complex with renewable energy within the smart grid solutions in terms of different types of input data uncertainty. On the basis of the theory of fuzzy logic and a fuzzy situational network, an approach has been developed that allows one to calculate the type of uncertainty of the input information, and then select the most appropriate mathematical model and control strategy for AEC with RES. © 2021 IEEE.

关键词： Smart power grids

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Threshold Wavelet Filtering of Images Based on Weight Model

Threshold Wavelet Filtering of Images Based on Weight Model

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Applied Mathematics, Computational Science and Mechanics: Current Problems (AMCSM)

作者： Maya Lyasheva Stella Lyasheva Mikhail Shleymovich Department for Automated Systems for Information Processing and Control Kazan National Research Technical University named after A.N. Tupolev-KAI Kazan Russian Federation Department for Applied Mathematics and Informatics Kazan National Research Technical University named after A.N. Tupolev-KAI Kazan Russian Federation

ISBN: (数字)9798350348576

ISBN: (纸本)9798350348583

Many modern information processing and control systems are based on computer vision technologies. In such systems, a number of tasks are solved, including the task of primary image processing. The primary processing is designed to transform the geometric, brightness and color characteristics of images, ensuring that they are brought to the best possible appearance for further analysis. Brightness conversion must be performed to implement image enhancement and restoration procedures. Threshold wavelet filtering is the basis of one of the frequently used approaches for solving these problems. To build the appropriate procedures in this article, it is proposed to use a weight model of the image. This model allows us to obtain estimates of the significance of the contribution of pixels to the total energy of the analyzed image.

关键词： Wavelet transforms Computer vision Analytical models Filtering Noise Brightness Information processing

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Application of the Weight Model to Detect the State Registration Number of the Vehicle in the Image

Application of the Weight Model to Detect the State Registra...

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2021 International Russian Automation Conference, RusAutoCon 2021

作者： Lyasheva, Maya M. Lyasheva, Stella A. Shleymovich, Mikhail P. Kazan National Research Technical University Named after A. N. Tupolev-KAI Department for Automated Systems for Information Processing and Control Kazan Russia Kazan National Research Technical University Named after A. N. Tupolev-KAI Department for Applied Mathematics and Informatics Kazan Russia

ISBN: (纸本)9780738131566

The article deals with the issues of detecting state registration numbers of vehicles in images when solving the problem of their identification in intelligent transport systems. The main approaches for solving this problem are described, which belong to two classes-based on image processing and based on machine learning. It is shown that, despite the effectiveness of methods based on machine learning, it is advisable to use methods based on image processing for certain specific conditions. Among the image processing methods for detecting vehicle license plates, edge analysis methods are the fastest. At the same time, you can use the properties of the wavelet transform to analyze the edges. This is the basis of the approach proposed by the authors, which provides for the use of a weight model based on the coefficients of the multiple-scale orthogonal Haar wavelet transform. As a result of building such a model, weights are calculated that reflect the significance of the pixels of the original image for the analysis of the edges when searching for the area of the vehicle number. The weight model allows you to emphasize the characteristics of the vehicle number area in the image and use additional processing to find its location. The advantages of the proposed approach include simplicity in implementation, the detection of vehicle numbers in images obtained under various conditions, and the possibility of supplementing it with operations that ensure increased efficiency at all stages. © 2021 IEEE.

关键词： Wavelet transforms

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