Skip to main content

Über dieses Buch

This two-volume set constitutes the proceedings of the Third Conference on Creativity in Intellectual Technologies and Data Science, CIT&DS 2019, held in Volgograd, Russia, in September 2019.

The 67 full papers, 1 short paper and 3 keynote papers presented were carefully reviewed and selected from 231 submissions. The papers are organized in topical sections in the two volumes. Part I: cyber-physical systems and Big Data-driven world. Part II: artificial intelligence and deep learning technologies for creative tasks; intelligent technologies in social engineering.





Designing AI Futures: A Symbiotic Vision

The new “AI spring” of Machine Learning and Deep learning, backed by Big Data and immense computational power, is opening up potential for innovation of new drugs, medical diagnosis, social robots, ‘Robo-Nurse’ and virtual assistants, but there are also imponderable existential downsides and deep anxiety that AIs are going to take over our jobs, our interaction with societal institutions and our lives. With the accelerated integration of powerful artificial intelligence systems into core social institutions and in our everyday lives, we are confronted with an electronic world where digital bots or electronic ‘agents’ are already representing us in our interactions. We face a challenge of the untamed integration of AI to come up with possible human-machine futures that mitigate the impact of the instrumental models of AI tools and systems. How can we transcend ‘machine thinking’ to mold technological futures for the common good? We need to address questions such as, can we harness collective intelligence as a transforming tool for addressing unpredictable problems of complex social systems? What are the possibilities and limitations of designing creative intelligent systems that are shaped by purpose and judgment, transcending instrument reason of the causal model? The talk will explore these issues, drawing upon current AI narratives of the relations between society and the scientific project of AI and the challenges it poses for us to come up with possible symbiotic AI futures.

Karamjit S. Gill

Artificial Intelligence: Issues, Challenges, Opportunities and Threats

The world is experiencing a period of instability in a range of pillar institutions in the international system. These instabilities and unsustainable systems may have serious implications for humanity. Catastrophic physical phenomena are on the rise, lately and many say that this is due to human disrespect to the environment. Urgently valuable and sustainable solutions are needed. One scientific approach to address these challenging questions is Artificial Intelligence (AI). Theories of AI are reviewed. Machine learning (ML), Neural Networks (NN) and Deep Learning (DL) are briefly presented. Certain criticisms of AI and DL are carefully analyzed. A number of challenges and opportunities of AI are identified. The future of AI and potential threats of it are discussed. Artificial Intelligence (AI) and Deep Learning (DL) are relying mainly on data analysis without taking into consideration the human nature. Theories of Fuzzy Cognitive Maps (FCM) seem to provide a useful tool in developing new AI theories answering this problem.

Peter P. Groumpos

On Approach for the Development of Patents Analysis Formal Metrics

Analysis and modeling of the cross-thematic states of the world prior-art is a voluminous task that includes many subtasks. In order to assess the prior art, build forecasts and carry out analysis, it is necessary to develop and construct cross-thematic relationships between patents within an array in many ways. The scientific result of the work was the first developed formal metric “belonging to the technological epoch” for assessing the cross-thematic states of the world prior art, as well as the technique and method of applying formal metrics. This paper presents the development of a software module based on the developed metric.

Alla G. Kravets

Cyber-Physical Systems and Big Data-Driven World. Pro-active Modeling in Intelligent Decision Making Support


A New Approach to Reduce Time Consumption of Data Quality Assessment in the Field of Energy Consumption

This paper is devoted to solving the problem of reducing the time costs of the process of data quality assessment. The data describe energy resources consumption of various enterprises and institutions. The first part of the paper contains a review of recent data quality assessment studies was made. The analysis describes the problems of this process and the characteristics of the data, metadata and the algorithms used in it. The next part of the paper shows a new approach to reduce the time consumption of the process of assessing the data quality, which differs from the existing ones by the presence of a data-packaging and decision-making support using the oDMN+ notation. Finally, this paper presents an implementation example of the oDMN+ model for data on the energy consumption of the Volgograd hardware plant. The results showed that the use of data packaging and modeling the assessment process is a promising approach for modeling and reducing time costs in the process of data quality assessment for energy management systems used in the enterprises and institutions.

Alexander Sokolov, Maxim V. Shcherbakov, Anton Tyukov, Timur Janovsky

Decision Support System for the Socio-Economic Development of the Northern Part of the Volga-Akhtuba Floodplain (Russia)

In this paper we present a decision suppost system for the socio-economic development of the northern part of the Volga-Aktuba floodplain. It provides data, algorithmic and instrumental tools for searching, modeling, analyzing and evaluating the scenarios of the socio-economic development and the spatially localized and integral characteristics of the floodplain state. We show that mutual dependence of the floodplain hydrological and nature and socio-economic structures requires their target changes coherence in the effective scenarios of its development. The main role in these changes is played by hydrotechnical projects. Their implementation creates a new hydrological structure of this territory, contributing to its socio-economic development.

Inessa I. Isaeva, Alexander A. Voronin, Alexander V. Khoperskov, Konstantin E. Dubinko, Anna Yu. Klikunova

Modeling and Optimization of Proactive Management of the Production Pollutions in the Conditions of Information Asymmetry

On the basis of the constructed mathematical model, an analysis is made of which of the instruments for regulating industrial emissions of enterprises - environmental standards or quotas sold for industrial emissions of pollutants - allows minimizing the total costs of the strategy of environmental regulation. The necessity of taking into account the asymmetry of information support of the optimization process is shown. It has been proved that the environmental policy regulator, aiming to limit the aggregate level of emissions of a given pollutant by several enterprises, can minimize total costs by applying enterprise-specific environmental standards. The system of quotas sold for production emissions allows minimizing the total costs of the strategy of environmental and economic regulation only if the costs of the environmental audit are the same for all enterprises. It is established that in the event that the cost of implementing penalties varies between enterprises, the competitive market for emission allowances will not minimize the total costs of providing the total amount of emissions for a certain level, allowing a certain degree of non-compliance with environmental requirements.

Aleksey F. Rogachev, Maksim S. Lukashin

Making a Choice of Resulting Estimates of Characteristics with Multiple Options of Their Evaluation

The paper dwells on the analysis of the efficiency of different algorithms for numerical expert data processing. Five methods were chosen for comparison: (1) on the basis of mean values; (2) on the basis of mean values with regard to experts’ competence assessment; (3) by means of getting average values on the basis of the maximum likelihood estimation method; (4) by means of getting median values on the basis of the maximum likelihood estimation method; (5) by means of getting median values on the basis of the least squares method. A complex criterion, based on evaluation of the degree of experts’ opinion consistency, the degree of closeness of the obtained results to their true values and the degree of convenience of the obtained results for solving specific tasks, is chosen as an efficiency criterion. The paper presents procedures of estimation of the mentioned components of the complex criterion and derivation of a complex estimate on the basis of known estimates of individual components. The experiment showed that, in the context of assessment of importance of individual PC components under the process of information security provision, the best result of the expert data processing is obtained with the use of the maximum likelihood estimation method on the basis of mean values, and the worst result is obtained with the use of the classical processing method on the basis of mean values. It is proposed to apply a procedure of getting a resulting estimate on the basis of a balanced consideration of the estimates obtained through different methods.

Georgi A. Popov, Irina Yu. Kvyatkovskaya, Olga I. Zholobova, Anastasia E. Kvyatkovskaya, Elena V. Chertina

Adaptive Analysis of Merchant Big Data

There is proposed a method and technology for adaptive analysis of demand and supply of regional banking acquiring services based on Big Data processing. The paper introduces a new technology of acquiring services demand and supply monitoring and analysis using specifically designed and developed software solution. The proposed approach and its implementation become a basis for acquiring service marketing, locations perspective search and tariffs calculation considering the individual characteristics of sales and services business. The developed technique is implemented by software for decision-making support system pro-bated on model data of the St. Petersburg financial environment.

Oleg Surnin, Mariia Sigova, Pavel Sitnikov, Anton Ivaschenko, Anastasia Stolbova

Big Data in the Stochastic Model of the Passengers Flow at the Megalopolis Transport System Stops

The problem of the passengers flow model development is proposed as the subsystem of the general municipal passengers transport system operation model of megalopolis. The specific features of the application subject (Volgograd city, Russia) were detected to simplify the big data simulation problem. The difficulties caused by the high dimensionality were overcome by means of the double time scaling in passengers’ flow estimation. The hour time scale was accepted to the computation of the hourly flow from each departure stop to the city district of destination without the pointing of the specific destination stop. The minute time scale was accepted to distribute the hourly flow between the destinations stops located in this district. The algorithms of the destination stops choice simulation were carried out. The follows examples of simulation results are presented: hourly passengers flow directed to the departure stops; daily variations of districts population caused by the inter-district passengers’ flows; influence of the of competition on the municipal transport system operation; destination stops choice variants according to the stops’ attractiveness scores designed by experts.

Elena Krushel, Ilya Stepanchenko, Alexander Panfilov, Elena Berisheva

Building a Company’s Maturity Management Trajectory Based on the Methods of Optimal Control of Letov-Kalman

The article proposes a solution to the problem of building optimal management of the maturity level of the company’s business processes. The level of maturity is described as a linear dynamic control system. This work is part of the solution to the problem of developing a system for managing the level of maturity of an enterprise’s business processes.A set of indicators of a company’s business processes maturity is described as a dynamic model of a control system in discrete time. It is shown that such a model adequately describes the behavior of a system of indicators of the maturity of a company’s business processes.When developing the model, the method of analytical construction of optimal regulators (ACOR) staged on Kalman-Letov’s interpretation is used. The constructed model shows plausible behavior in predicting the process of managing organizational maturity. Reproduces the effect of accelerated growth of controlled indicators identified in the model as a priority.

Mikhail Dorrer

Networkalization of Network–Unlike Entities: How to Preserve Encoded Information

More than for twenty years network science with complex networks as its basic component has brought the idea to analyze a wide spectrum of entities through a focus on relations between the actors and has implemented the concomitant powerful instruments of the analysis. Some entities (objects, processes, and data) with their intrinsic web nature might be interpreted as networks naturally. Network ontology of another family, Network–Unlike Entities, e.g. spatial and temporal ones, is severely ambiguous and encounters with tough problems on the way to convert data into networks. We concentrate on separation the properties of data in line with their scale diversity – in the distance, time, and nature and suggested a 3 step algorithm (scale-based technique) to convert Network–Unlike Entities into complex networks. The technique was applied for networkalization of landscape and land use maps representing Olkhon district, Irkutsk region, Baikal Lake territory, RF. It was found that the technique with its coarse-graining and area-like connecting conserves natural information inherent to the entities and imbeds accordingly scale-free and small world properties into output networks, thus making them really complex in their structure.

Olga Berestneva, Olga Marukhina, Alessandra Rossodivita, Alexei Tikhomirov, Andrey Trufanov

HR Decision-Making Support Based on Natural Language Processing

This paper presents an overview and analysis of IT solution of text understanding being applied to a programming professional domain. Conclusions summarize the authors’ experience in NLP/NLU in the last years. Binary classification and logistic regression is used to solve typical problems. The results of practical research are presented. The paper develops the ideas of understanding texts in software development domain using standard text processing tools. The proposed solution is recommended for HR professionals who search suitable candidates for a job based on their blogs, online presence and code.

Anton Ivaschenko, Michael Milutkin

The Algorithm for the Classification of Methods for Processing Multidimensional Heterogeneous Data in Application to Designing of Oil Fields Development

An algorithm of methods selection for processing multidimensional heterogeneous data based on the general properties of the data used and the methods included in the review is proposed in this paper. The algorithm is implemented in the form of software and a group of interpolation algorithms is compared by the example of the problem of constructing an oil field model for field development designing. It is shown that the proposed algorithm for selecting data processing methods works successfully for a group of data interpolation methods.

Alena A. Zakharova, Stepan G. Nebaba, Dmitry A. Zavyalov

Detection of the Patterns in the Daily Route Choices of the Urban Social Transport System Clients Based on the Decoupling of Passengers’ Preferences Between the Levels of Uncertainty

The ideas of data mining techniques were applied for the problem of municipal passengers transport system simulation and its results interpreting and generalization. The purpose of the presented work is to propose and justify the passengers flow model suitable for the detection of hidden patterns in the processes of flow forming with the application of the available sources for model identification. The patterns of the daily route choices detection are based on the decoupling of the general model between the sub-models according to the different levels of uncertainty of passengers intentions in route choice, and on the following joining of the computational results received for the sub-models. The availability of the approach was illustrated by the examples of the typical patterns in the destination stops choice and in hourly passengers’ flow from the departure stops. The model testing shows the high correlation of the simulated passengers’ flow with the results of the real observations.

Elena Krushel, Ilya Stepanchenko, Alexander Panfilov, Tatyana Lyutaya

Analysis a Short-Term Time Series of Crop Sales Based on Machine Learning Methods

The main goal of this article is to solve the problem associated with identifying sales seasons in time series in order to build the most accurate forecast of sales of various crops and provide decision support and improve the efficiency of business processes of agro-industrial companies. In this regard, the necessity of developing an algorithm that allows to form a time series of sales in accordance with the seasons available in it to improve the accuracy of existing sales forecasting methods is justified. This study provides a detailed description of the problem and its solutions in the form of an algorithm, as well as a comparison of the accuracy of building prediction models before and after its application, which confirms the consistency of the developed method for the formation of time series.

Mohammed A. Al-Gunaid, Maxim V. Shcherbakov, Vladislav N. Trubitsin, Alexandr M. Shumkin, Kirill Y. Dereguzov

A Multifactor Small Business Management Model

The previously existing system of industrial development USSR was aimed at the construction of industries and the arrangement of cities around them. Such cities, which have one or several city-forming enterprises, are called “monotowns”. A monotown is a complex structure in which the town and the city-forming enterprises are closely related. The constructed multifactor dynamic model in the article allows to organize the process of managing a small business by influencing all of its microindicators using the monotown’s mesoindicators. This approach lets the municipality at every moment influencing indicators of small business with its socio-economic indicators, contribute to the sustainable development of the urban economy.

Andrey N. Vazhdaev, Artur A. Mitsel

Tourism Cluster Enterprises Departments’ Resource Management Based on Mobile Technologies

In the conditions of modern management of hospitality facilities, the used approaches and tools for resource management play an important role. The article discusses the use of mobile technologies in resource management of the hotel’s housekeeping service. The mobile application «Mobile Housekeeping» is used to manage the resources of the hotel’s housekeeping service in addition to the automated PaRM web system. The automated system is based on a proactive methodology, the description of which is given in the article. In the mobile application “Mobile housekeeping” functionality is supported, which requires the operational use of the personnel of housekeeping service at any point of the hotel. The use of integrated software allows you to effectively manage the resources of the enterprise’s departments of the tourism cluster.

Alla G. Kravets, Aleksandr O. Morozov, Konstantin S. Zadiran, Gais Al-Merri, Ekaterina Trishkina

The Information and Analytical Platform for the Big Data Mining About Innovation in the Region

The article describes an information and analytical platform for collecting and processing big data for the study of innovative development processes of the constituent entities of the Russian Federation. The toolkit of the platform solves the problem of searching, collecting, processing and downloading data from the Internet for the analysis and prognostic modeling of innovation indicators of economic agents in the region. The results are used to assess the dynamics of changes in the innovative development of enterprises and the region as a whole. The objectives of the research are to select leaders who actively develop and implement innovations, benchmarking analysis of regional enterprises with leaders, develop recommendations for managing innovative development mechanisms, and increase the efficiency of innovative activities of enterprises in the region. It is proposed to create a set of tools for analytic processing of big data in the form of a convergent platform with horizontal scaling. To perform the procedures of loading large data into the cloud storage, the streaming architecture of the data search and integration subsystem is implemented with the possibility of parallel preprocessing of information. The components of the information and analytical platform have been developed and implemented.

Leyla Gamidullaeva, Alexey Finogeev, Sergey Vasin, Michael Deev, Anton Finogeev

Cyber-Physical Systems and Big Data-Driven World. Design Creativity in CASE/CAI/CAD/PDM


Meta-design of Processes Based on Visualization Tools

Interactive visualization, used to represent and interpret input data, makes it possible to employ visual perception potential to search for and resolve internal contradictions in the studied data, the source of which in many cases is errors made during the development of the program. The purpose of visual analytics in this study is to identify contradictions in the design of an educational process, provided by the curriculum, and to form students’ meaningful variable and individual educational trajectories.

Alena A. Zakharova, Anton Krysko, Evgeniya Vekhter, Aleksey Shklyar

Designing Zero-Energy Buildings Using Advanced Fuzzy Cognitive Maps

Energy efficient buildings are able to provide effective solutions to reduce energy consumption and carbon emissions, support environmental-friendly energy management and facilitate significant energy savings. The concept of Zero-Energy Buildings is gaining a constant increasing focus. The use of Advanced Fuzzy Cognitive Maps (AFCMs) as a new modelling methodology to provide energy performance indicators in a quantified manner that will drive the appropriate integration of required renewable energy generation, in order to design a (nearly) Zero-Energy Building (nZEB) is considered. The new approach is used to calculate the energy balance of buildings in alternative climate contexts and thus to explore their energy efficiency in six use cases. Simulation results and observations show that AFCMs could provide valuable insight to design and development issues of nZEBs.

Theodor Panagiotakopoulos, Nikolaos Zafeirakis, Iliana-Vasiliki Tsoulea, Peter P. Groumpos

The Evaluation Method of the Design Department’s Information Assets

The activity of the design department (DD) is currently one of the most significant areas in the field of nuclear energy, the defense and rocket, and space industries. This area characterized by large volumes of used economic, technological, industrial and other resources. One of the tasks of the DD is to evaluate information assets (IA) and protect them from threats. The objectives of this article are to develop a method for assessing DD’s IA, as well as discussing the possibility of using this method in practice and the risks to which the DD is exposed unless special measures are taken to evaluate IA and threat analysis. Studies related to the assessment of the importance of information IA, the development of a threat model, and damage prediction investigated. The specificity of DD and processing of IA has been determined. In this paper, it is proposed to use the set-theoretic model for evaluating the IA of the DD that takes into account their structure, attributes, and life cycle. To assess the damage caused by the threat, it proposed to use the method of ALE. For the first time, a method for evaluating the IA of DD proposed. This method implemented in software. The software implementation successfully tested in an enterprise that includes the DD. The investigated problem studied quite recently. Therefore, there are open questions such as the classification of information assets of the DD and their categorization (confidentiality stamping), analysis of the life cycle of IA and threats, determination of the criticality level of the DD’s IA, assessment of damage from the realization of the threat. The prospect for the development of the research is the development of a threat model for information systems of the DD.

Svetlana Kozunova, Alla G. Kravets, Natalia Solovieva

Technology Model to Support the Initiation of Innovation Artefacts

The current paper proposes a technology model to support the process of creating innovative artefacts, where artefact is any project proposal, business plan, business solution, article with a high degree of innovation. The model is based on an advanced technology stack, in which the central role is played by semantic high-performance computing. Several functionalities are available both for academic researchers and business consultants, from validating the innovation degree of an idea, to supporting its development with useful bibliographical recommendations or building research proposals based on that idea.

Maria-Iuliana Dascalu, Elisabeth Lazarou, Victor Florin Constantin

Solving the Inverse Kinematics of Robotic Arm Using Autoencoders

In the modern era, robotics is an attractive field for many researchers since robots are involved in many aspects of everyday life due to the conveniences and solutions that they provide in various daily difficulties. For this reason, the inverse kinematics of robotic arms is a challenging problem that seems more appealing to researchers as years pass by. In this paper, a novel approach to solve this problem is assessed, which is based on autoencoders. In our implementation the goal is not only to find one random (of the infinite solutions) of this problem, but to determine the one that minimizes both the position error between the actual and desired position of the end-effector of the robotic arm and the joint movement. For the training of the Neural Network of the autoencoder, four different types of the loss function and their corresponding results are examined. A robotic arm with three Degrees of Freedom is used for the evaluation of our implementation and the accurate results demonstrate the efficiency and effectiveness of our proposed method.

Konstantinos D. Polyzos, Peter P. Groumpos, Evangelos Dermatas

Structural and Parametrical Model of the Physical Functional Principle of the Microelectronic Capacitive Pressure Sensor

In this paper it is shown that one of the most important problems of technical progress development is productions automation. The leading place in the world on production and the number of the granted patents is occupied by microelectronic sensors of pressure. The retrospective analysis of patent, scientific and technical literature was made by authors. Importance of initial design stages was proved. The solution of a formalization problem of the processes description of information transformation in microelectronic capacitive pressure sensors by means of model’s development on the basis of the theory of energy and information circuit models is proposed. The parametric structural scheme is developed. Mathematical dependences of its quantities and parameters on actual physical quantities are defined. The adequacy of model is proved. The developed model is intended for the automated synthesis of new technical solutions at a stage of search design and for predesign of sensors’ output parameters at a stage of outline design.

Mikhail Shikulskiy, Olga Shikulskaya, Irina Yu. Petrova, Gennady Popov, Issa Bogatyrev, Victor Samsonov, Alla Kachalova

Theoretical Bases of the Application of Various-Color Graphs in the Solution of Intellectual Chemical Tasks

The paradigm of using artificial neural networks (ANN) for solving intellectual problems of chemistry and chemical technology is considered: classification, identification, design, modeling, optimization, and others. Using the example of studying the applicability of colored graphs in the neural network analysis of chemical structures at the site «structure-property-application» relationship, the possibility of identifying chemical structures when creating actual substances is shown. Artificial neural network learning to identify graphs is shown. The results obtained are mathematical software that allows solving creative problems and creating decision rules when choosing chemical-technological systems formalized in terms of graph theory and intended to support decision-making.

Ilya V. Germashev, Evgeniya V. Derbisher, Vyacheslav E. Derbisher

Cyber-Physical Systems and Big Data-Driven World. Intelligent Internet of Services and Internet of Things


Forecasting and Optimization Internet of Things System

Currently many methods and approaches related to the management of Internet of Things systems are associated with the collection of large amounts of information. The results of the rating assessment from the management point of view are limited. In many cases we need to involve modeling and optimization techniques in the management process. This paper shows how an integral assessment of the efficiency of Internet of Things systems is formed. The optimization model of the problem is developed and the procedures of expert evaluation of management decisions are formed. On the basis of the methods used, the results demonstrating their efficiency are obtained.

Yakov Lvovich, Igor Lvovich, Andrey Preobrazhenskiy, Oleg Choporov

Modeling a Microgrid Using Fuzzy Cognitive Maps

The energy problem is among the most important issues in the global community over the last decades. Worldwide researchers have focused their attention and work to the increased use of renewable energy sources as a solution to the greenhouse effect. The reduction of the emitted pollutants, as well as managing, controlling and saving energy, are key research items. This paper attempts to cover part of the load of the studied microgrid, which consists of three buildings of the University of Patras using the method of Fuzzy Cognitive Maps. The goal is using renewable energy sources to cover 20% of their total load, aiming to decongest the network at peak times.

Vassiliki Mpelogianni, George Kosmas, Peter P. Groumpos

Data-Driven Framework for Predictive Maintenance in Industry 4.0 Concept

Supporting the operation of the equipment at the operational stage with minimal costs is an urgent task for various industries. In the modern manufacturing industry machines and systems become more advanced and complicated, traditional approaches (corrective and preventive maintenance) to maintenance of complex systems lose their effectiveness. The latest trends of maintenance lean towards condition-based maintenance (CBM) techniques. This paper describes the framework to build predictive maintenance models for proactive decision support based on machine learning and deep learning techniques. The proposed framework implemented as a package for R, and it provides several features that allow to create and evaluate predictive maintenance models. All features of the framework can be attributed to one of the following groups: data validation and preparation, data exploration and visualization, feature engineering, data preprocessing, model creating and evaluation. The use case provided in the paper highlights the benefits of the framework toward proactive decision support for the estimation of the turbofan engine remaining useful life (RUL).

Van Cuong Sai, Maxim V. Shcherbakov, Van Phu Tran

Method of Acquiring the Video Conference Using the Skill in Investigative Actions

The current law does not directly establish the possibility of remote investigative actions. However, it does not contain direct bans on the introduction of this progressive procedural form. Nevertheless, the practice of using information and communication technologies by an investigator in his work will inevitably lead to the need for detailed regulation of such improvements. The decision of the legislature on the full legal regulation of this problem is brewing. It is necessary to supplement the content of the training of the official’s persons, who will be in charge of criminal cases, at the expense of developing the skill to use the video conference system as needed during a number of investigative actions.

Evgeny Kravets, Svetlana Gladkova, Vladimir Shinkaruk, Vladimir Ovchinnikov, Nikolai Bukharov

Development the Methodology of Urban Area Transport Coherence Assessment

The present paper analyzes modern approaches to assessing the balance of urban infrastructure. The definition of transport coherence is given. The developed methodology of urban area transport coherence assessment is described. The method of localized assessment of transport provision has been tested in cities of various shapes and sizes: positive results and limits of the method applicability are analyzed by example of Volgograd, St. Petersburg, Novosibirsk, Moscow, Elista, Astrakhan, Uryupinsk and Kamyshin. The features of application of technologies and data of OSRM and OSM are highlighted. Checking options for calculating the coefficient of coherence for cells was held. Verification of the results obtained by the four methods of calculating the average is performed by comparing the estimates of connectedness with the length of roads in the corresponding cells. For this, a method for calculating the local density of the road network has been proposed. It is proposed to use a transport plasmograph of the territory for a visual demonstration of the coherence of space and the possibility of assessing its main structural features. The paper describes the method of creating a plasmograph and provides examples of the analysis with its help of the territory of Novosibirsk and St. Petersburg. Conclusions are drawn about the possibilities of formalizing the infrastructure integrity of cities based on an analysis of their transport coherence and suggest promising areas for further research using the established methods for analyzing other types of infrastructure, as well as comparative analysis of cities.

Danila Parygin, Alexander Aleshkevich, Alexey Golubev, Natalia Sadovnikova, Maxim V. Shcherbakov, Oksana Savina

Cryptographic Protection of Data Transmission Channel

Data transmission over the network is the most vulnerable stage of the information life cycle in the information system. The main way to protect data when transmitting over a communication channel is to hide its content. For this purpose, cryptographic means of information protection are used. Among the cryptographic means, encryption and digital signature are distinguished. There are different algorithms that allow performing encryption or digital signature. So which one is better? What algorithms should be used to make cryptographic protection the most effective? The study of the effectiveness of approaches to the construction of encryption algorithms is carried out. SP-network is recognized as more efficient than Feistel network. The study of the effectiveness of approaches to the construction of digital signature algorithms is carried out. The study took into account how the algorithm is used in conjunction with SP-network. Algorithm of the elliptic curve is recognized as the most efficient. As a result, the protocol of secure data transmission over the network is developed.

Arina Nikishova, Ekaterina Vitenburg, Mikhail Umnitsyn, Tatiana Omelchenko

Use of Fuzzy Neural Networks for a Short Term Forecasting of Traffic Flow Performance

The method for a short term forecasting of the traffic in the urban road network and of the average vehicle speed is suggested. The author’s method is based on a regulatory approach to the calculation of the traffic capacity of the city road network. This method is completed with the methodology of forecasting the changes in the hourly traffic intensity. As the mathematical tool for the implementation of the forecasting methodology, the fuzzy neural networks are taken. It is suggested to make the forecast of short-term traffic intensity taking into account time of day, day of the week and season. On the basis of the data on the traffic capacity, the authors provide the relationships of an average speed change. The example of the calculation of transport flow performance is made in one of the motorways in the city of Volgograd.

Skorobogatchenko Dmitry, Viselskiy Sergey

Effective Quaternion and Octonion Cryptosystems and Their FPGA Implementation

An approach for effective hardware implementation of the proposed quaternion encryption algorithm (HW-R4) as well as modifications for known quaternion HW-QES and octonion HW-OES schemes are discussed. Instead of 3-D rotations as usually, 4-D transformations for encryption with quaternions and 8-D with octonions are suggested. Such size of transformation matrices increases the size of plaintext/ciphertext blocks and eliminates the need to calculate elements of rotation matrices. To speed up an encryption process the HW-R4, HW-QES, and HW-OES include mainly addition and shift operations with modular arithmetic. In our experiments, we used a product Intel (former Altera) OpenCL SDK (AOCL), which allows compiling OpenCL programs for FPGAs. The launch of the developed algorithms was carried out on two devices: the Intel Core i7 920 CPU and the Terasic DE5-Net FPGA (Stratix V). Experimental results show that the proposed algorithms and modifications are about 30–50% more effective in the encryption speed of signals than the original HW-QES/HW-OES. Additionally, HW-R4 is shown to be more effective in the encryption quality of images than the original QES. Our approach can also be used for robustness increasing when the Feistel network is added to the system.

Andrey Andreev, Mikhail Chalyshev, Vitaly Egunov, Evgueni Doukhnitch, Kristina Kuznetsova

Smart Contracts for Multi-agent Interaction of Regional Innovation Subjects

The main obstacle to effective interaction between innovation agents is high innovation transaction costs. The development of innovation requires the continuous interaction of participants at all stages of the innovation process, from idea to commercialization. The article discusses the creation of a safe and reliable way to support such interaction in regional innovation systems based on blockchain technology and smart contracts. This approach is recommended to exclude unfair and fraudulent actions on the part of participants. Another feature is the transfer of third-party functions to a smart contract to ensure safe communication. The smart contract will allow, on the one hand, to realize trustful and reliable relationships between the project participants themselves, and, on the other hand, between participants and stakeholders. The article discusses the possibilities of the Ethereum blockchain platform, with the help of which the main components of a smart contract were synthesized for concluding contracts for creating and introducing innovations, transferring intellectual property rights, using licenses, etc. The basis of the smart contract is a distributed registry of transactions and a database with descriptions of innovative objects.

Leyla Gamidullaeva, Alexey Finogeev, Sergey Vasin, Anton Finogeev, Sergey Schevchenko


Weitere Informationen

Premium Partner