Pub Date : 2020-03-31DOI: 10.17323/2587-814x.2020.1.41.50
E. Agbozo, A. Medvedev
The goal of e-government is to provide public services to end users – be it citizens or residents – of a given nation. Research has shown that there is the susceptibility of governments to check all the boxes so as to present an image of having e-government implementations, yet end users eventually do not benefit from these electronic services. Quality public service delivery is an issue of priority today and, with the increasing availability of modern technological tools and techniques, it is attainable. Datadriven e-government is a necessary ingredient in the modern day public sector due to the widespread availability and rapid production of data (i.e. big data) and it aims at value creation. This study proposes a novel research concept, using the Multi-Channel Service Delivery model as a catalyst to attain the data-driven ecosystem in the public sector. The model was developed based on recommendations from works of previous research to address the changing landscape of the public sector. By integrating the Multi-Channel Service Delivery model into e-government and public sector decision making, governments will be able to bridge the divide and offer services to end users with access to e-services, as well as those who do not. In doing so, the United Nations’ Sustainable Development Goals (SDGs) which are aimed at leaving none behind will be arrived at.
{"title":"Towards a Multi-Channel Service Delivery model in the data-driven public sector","authors":"E. Agbozo, A. Medvedev","doi":"10.17323/2587-814x.2020.1.41.50","DOIUrl":"https://doi.org/10.17323/2587-814x.2020.1.41.50","url":null,"abstract":"The goal of e-government is to provide public services to end users – be it citizens or residents – of a given nation. Research has shown that there is the susceptibility of governments to check all the boxes so as to present an image of having e-government implementations, yet end users eventually do not benefit from these electronic services. Quality public service delivery is an issue of priority today and, with the increasing availability of modern technological tools and techniques, it is attainable. Datadriven e-government is a necessary ingredient in the modern day public sector due to the widespread availability and rapid production of data (i.e. big data) and it aims at value creation. This study proposes a novel research concept, using the Multi-Channel Service Delivery model as a catalyst to attain the data-driven ecosystem in the public sector. The model was developed based on recommendations from works of previous research to address the changing landscape of the public sector. By integrating the Multi-Channel Service Delivery model into e-government and public sector decision making, governments will be able to bridge the divide and offer services to end users with access to e-services, as well as those who do not. In doing so, the United Nations’ Sustainable Development Goals (SDGs) which are aimed at leaving none behind will be arrived at.","PeriodicalId":41920,"journal":{"name":"Biznes Informatika-Business Informatics","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2020-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48994914","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-12-31DOI: 10.17323/1998-0663.2019.4.28.38
R. Karayev
One of the most crucial and vulnerable stages of strategic management is the cognitive stage associated with the transformation of the strategic vision and of the enterprise’s mission into its strategic goals. At this stage, management is faced with the problem of developing a coordinated collective opinion on the content of the goals being formed and with the problem of objective assessment of their effectiveness. The difficulties here are due to the phenomenological features of the stage, such as the informal nature of the transformation procedure, the multi-criteria nature of goals, numerous uncertainties and risks exacerbated by the increased variability of business environments, cognitive barriers caused by linguistic discrepancies and differences in the professional experience of strategy developers. Such features of the stage ultimately lead to ambiguous decisions regarding the content of goals and ambiguous assessments of their effectiveness. In these circumstances, traditional support tools (numerous versions of expert methods, brainstorming, Norton and Kaplan's BSC, SMART technology, etc.) face serious limitations. This paper proposes a cognitive technology for forming a coordinated set of the enterprise’s business goals that to a large extent takes into account the features of the given stage. The technology is a single procedure integrating the capabilities of traditional support tools and expanding the creative potential of support based on psychosemantic models and nonmetric multidimensional scaling methods. The results of a real study conducted at a number of enterprises show that cognitive technologies open up new prospects for goal analysis. They can serve as a useful complement to existing support tools and contribute to the design of more effective and realistic business strategies.
{"title":"Cognitive analysis and choice of an enterprise’s strategic goals","authors":"R. Karayev","doi":"10.17323/1998-0663.2019.4.28.38","DOIUrl":"https://doi.org/10.17323/1998-0663.2019.4.28.38","url":null,"abstract":"One of the most crucial and vulnerable stages of strategic management is the cognitive stage associated with the transformation of the strategic vision and of the enterprise’s mission into its strategic goals. At this stage, management is faced with the problem of developing a coordinated collective opinion on the content of the goals being formed and with the problem of objective assessment of their effectiveness. The difficulties here are due to the phenomenological features of the stage, such as the informal nature of the transformation procedure, the multi-criteria nature of goals, numerous uncertainties and risks exacerbated by the increased variability of business environments, cognitive barriers caused by linguistic discrepancies and differences in the professional experience of strategy developers. Such features of the stage ultimately lead to ambiguous decisions regarding the content of goals and ambiguous assessments of their effectiveness. In these circumstances, traditional support tools (numerous versions of expert methods, brainstorming, Norton and Kaplan's BSC, SMART technology, etc.) face serious limitations. This paper proposes a cognitive technology for forming a coordinated set of the enterprise’s business goals that to a large extent takes into account the features of the given stage. The technology is a single procedure integrating the capabilities of traditional support tools and expanding the creative potential of support based on psychosemantic models and nonmetric multidimensional scaling methods. The results of a real study conducted at a number of enterprises show that cognitive technologies open up new prospects for goal analysis. They can serve as a useful complement to existing support tools and contribute to the design of more effective and realistic business strategies.","PeriodicalId":41920,"journal":{"name":"Biznes Informatika-Business Informatics","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2019-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41388329","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-12-31DOI: 10.17323/1998-0663.2019.4.73.86
N. Chernavin
In this article we study problems of the committee machine method when applied to decision-making when there are many signals from different technical indicators of a stock exchange market. The committee machine method is a data classification method which can find non-linear data dependencies by construction of several linear classifiers. In the framework of this research, the basis for committee machine construction is a unified partially integer programming model, within which various logics of committee structures can be implemented. The subject of the research is the interrelation of indicators of technical indicators of a stock exchange market with pricing for financial instruments of stock exchange trading. Accordingly, the goal of the research is to show the efficiency of committee structures for solving the problems of forecasting the future value of financial instruments listed on stock exchange markets. To accomplish this goal, basic stock exchange data on Sberbank shares were collected from the Moscow Stock Exchange for the period from 2010 to 2019. On the basis of this, the technical indicators and interrelated parameters were calculated. They were used as data for the committee machine models with different numbers of committee members and voting logics. The result of the calculation was to obtain definitive rules, which when applied in speculative trading on the stock exchange market can generate stable profits. For comparison, we show the solutions of a similar problem by classical classification methods. The comparison shows that methods which work with the non-linear data dependencies provide results in terms of classification quality similar to committee machine results. This research may be interesting to the professional traders, investment analysts, specialists in data science and students with a mathematical and/or financial specialization.
{"title":"Application of the committee machine method to analysis of stock market technical indicators","authors":"N. Chernavin","doi":"10.17323/1998-0663.2019.4.73.86","DOIUrl":"https://doi.org/10.17323/1998-0663.2019.4.73.86","url":null,"abstract":"In this article we study problems of the committee machine method when applied to decision-making when there are many signals from different technical indicators of a stock exchange market. The committee machine method is a data classification method which can find non-linear data dependencies by construction of several linear classifiers. In the framework of this research, the basis for committee machine construction is a unified partially integer programming model, within which various logics of committee structures can be implemented. The subject of the research is the interrelation of indicators of technical indicators of a stock exchange market with pricing for financial instruments of stock exchange trading. Accordingly, the goal of the research is to show the efficiency of committee structures for solving the problems of forecasting the future value of financial instruments listed on stock exchange markets. To accomplish this goal, basic stock exchange data on Sberbank shares were collected from the Moscow Stock Exchange for the period from 2010 to 2019. On the basis of this, the technical indicators and interrelated parameters were calculated. They were used as data for the committee machine models with different numbers of committee members and voting logics. The result of the calculation was to obtain definitive rules, which when applied in speculative trading on the stock exchange market can generate stable profits. For comparison, we show the solutions of a similar problem by classical classification methods. The comparison shows that methods which work with the non-linear data dependencies provide results in terms of classification quality similar to committee machine results. This research may be interesting to the professional traders, investment analysts, specialists in data science and students with a mathematical and/or financial specialization.","PeriodicalId":41920,"journal":{"name":"Biznes Informatika-Business Informatics","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2019-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42625919","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-12-31DOI: 10.17323/1998-0663.2019.4.60.72
V. Barakhnin, O. Kozhemyakina, R. Mukhamedyev, Yu. S. Borzilova, K. Yakunin
One of the most difficult tasks in the field of data mining is the development of universal tools for the analysis of texts written in the literary and business styles. A popular path in the development of algorithms for processing text document corpus is the use of machine learning methods that allow one to solve NLP (natural language processing) tasks. The basis for research in the field of natural language processing is to be found in the following factors: the specificity of the structure of literary and business style texts (all of which requires the formation of separate datasets and, in the case of machine learning methods, the additional feature selection) and the lack of complete systems of mass processing of text documents for the Russian language (in relation to the scientific community-in the commercial environment, there are some systems of smaller scale, which are solving highly specialized tasks, for example, the definition of the tonality of the text). The aim of the current study is to design and further develop the structure of a text document corpus processing system. The design took into account the requirements for large-scale systems: modularity, the ability to scale components, the conditional independence of components. The system we designed is a set of components, each of which is formed and used in the form of Docker-containers. The levels of the system are: the data processing level, the data storage level, the visualization and management of the results of data processing (visualization and management level). At the data processing level, the text documents (for example, news events) are collected (scrapped) and further processed using an ensemble of machine learning methods, each of which is implemented in the system as a separate Airflow-task. The results are placed for storage in a relational database; ElasticSearch is used to increase the speed of data search (more than 1 million units). The visualization of statistics which is obtained as a result of the algorithms is carried out using the Plotly plugin. The administration and the viewing of processed texts are available through a web-interface using the Django framework. The general scheme of the interaction of components is organized on the principle of ETL (extract, transform, load). Currently the system is used to analyze the corpus of news texts in order to identify information of a destructive nature. In the future, we expect to improve the system and to publish the components in the open repository GitHub for access by the scientific community.
{"title":"The design of the structure of the software system for processing text document corpus","authors":"V. Barakhnin, O. Kozhemyakina, R. Mukhamedyev, Yu. S. Borzilova, K. Yakunin","doi":"10.17323/1998-0663.2019.4.60.72","DOIUrl":"https://doi.org/10.17323/1998-0663.2019.4.60.72","url":null,"abstract":"One of the most difficult tasks in the field of data mining is the development of universal tools for the analysis of texts written in the literary and business styles. A popular path in the development of algorithms for processing text document corpus is the use of machine learning methods that allow one to solve NLP (natural language processing) tasks. The basis for research in the field of natural language processing is to be found in the following factors: the specificity of the structure of literary and business style texts (all of which requires the formation of separate datasets and, in the case of machine learning methods, the additional feature selection) and the lack of complete systems of mass processing of text documents for the Russian language (in relation to the scientific community-in the commercial environment, there are some systems of smaller scale, which are solving highly specialized tasks, for example, the definition of the tonality of the text). The aim of the current study is to design and further develop the structure of a text document corpus processing system. The design took into account the requirements for large-scale systems: modularity, the ability to scale components, the conditional independence of components. The system we designed is a set of components, each of which is formed and used in the form of Docker-containers. The levels of the system are: the data processing level, the data storage level, the visualization and management of the results of data processing (visualization and management level). At the data processing level, the text documents (for example, news events) are collected (scrapped) and further processed using an ensemble of machine learning methods, each of which is implemented in the system as a separate Airflow-task. The results are placed for storage in a relational database; ElasticSearch is used to increase the speed of data search (more than 1 million units). The visualization of statistics which is obtained as a result of the algorithms is carried out using the Plotly plugin. The administration and the viewing of processed texts are available through a web-interface using the Django framework. The general scheme of the interaction of components is organized on the principle of ETL (extract, transform, load). Currently the system is used to analyze the corpus of news texts in order to identify information of a destructive nature. In the future, we expect to improve the system and to publish the components in the open repository GitHub for access by the scientific community.","PeriodicalId":41920,"journal":{"name":"Biznes Informatika-Business Informatics","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2019-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41762916","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-12-31DOI: 10.17323/1998-0663.2019.4.7.16
V. Makarov, A. Bakhtizin, G. Beklaryan
This article presents a new approach to developing digital twins of production companies with the use of simulation methods. It describes the concept of digital twins as an integrated system that aggregates simulation models, databases and intelligent software modules of the class of genetic optimization algorithms, subsystems of data mining, etc. The article presents examples of simulation models of different production companies, in particular, a typical assembly plant and a typical oil production enterprise. The first company carries out activities to assembly products from individual components with its own individual characteristics. To describe the behavior of such an enterprise, methods of agent and discrete-event modeling are used. The second enterprise produces raw carbohydrate materials at existing fields with individual characteristics. The integrated simulation models thus developed are integrated with a subject-oriented database and optimization modules that facilitate providing a control of the technological and resource characteristics of the respective production enterprises. The development of these models was performed using AnyLogic and Powersim simulation systems that support agent-based modeling and system dynamics methods. We demonstrate here the possibility of creating ‘digital twins’ for production companies using modern simulation tools.
{"title":"Developing digital twins for production enterprises","authors":"V. Makarov, A. Bakhtizin, G. Beklaryan","doi":"10.17323/1998-0663.2019.4.7.16","DOIUrl":"https://doi.org/10.17323/1998-0663.2019.4.7.16","url":null,"abstract":"This article presents a new approach to developing digital twins of production companies with the use of simulation methods. It describes the concept of digital twins as an integrated system that aggregates simulation models, databases and intelligent software modules of the class of genetic optimization algorithms, subsystems of data mining, etc. The article presents examples of simulation models of different production companies, in particular, a typical assembly plant and a typical oil production enterprise. The first company carries out activities to assembly products from individual components with its own individual characteristics. To describe the behavior of such an enterprise, methods of agent and discrete-event modeling are used. The second enterprise produces raw carbohydrate materials at existing fields with individual characteristics. The integrated simulation models thus developed are integrated with a subject-oriented database and optimization modules that facilitate providing a control of the technological and resource characteristics of the respective production enterprises. The development of these models was performed using AnyLogic and Powersim simulation systems that support agent-based modeling and system dynamics methods. We demonstrate here the possibility of creating ‘digital twins’ for production companies using modern simulation tools.","PeriodicalId":41920,"journal":{"name":"Biznes Informatika-Business Informatics","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2019-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41932828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-12-31DOI: 10.17323/1998-0663.2019.4.39.48
A. Borodin, R. Veynberg, Dmitry I. Pisarev, O. Litvishko
Messengers are popular today on mobile devices and traditional computers. Starting as a small text messaging service, they have turned into effective communication channels for both private and corporate users, becoming more than just an SMS replacement. Users entrust to them a huge amount of information, such as a time-based map of activity, photos and other personal data. Messengers changed the way communication is done; they reduce the distance to the user and along with social networks become tools for fraud, spam or blackmail and terrorism. In this regard, it is vital to study instant messengers from a forensic point of view. This research explores and compares two popular messengers: Viber and Telegram, which is rapidly gaining popularity in the criminal world and the darknet as secure message tools. The main purpose of the research is to investigate and analyze potential artefacts remaining during the installation and use of instant messengers, as well as after their uninstallation. The authors have done several experiments to investigate the artefacts in different environments and provide clear explanation of the results. The experiments showed that even though Telegram is considered to be one of the most secure instant messengers, important and useful material on a hard drive and registry remain after complete uninstallation of the application. Exploring Viber artefacts showed up information that helps to restore the whole history of a communication. Moreover, the study confirmed that artefacts are still accessible in Windows after removal of the application. INFORMATION SECURITY
{"title":"Simulation of artefact detection in Viber and Telegram instant messengers in Windows operating systems","authors":"A. Borodin, R. Veynberg, Dmitry I. Pisarev, O. Litvishko","doi":"10.17323/1998-0663.2019.4.39.48","DOIUrl":"https://doi.org/10.17323/1998-0663.2019.4.39.48","url":null,"abstract":"Messengers are popular today on mobile devices and traditional computers. Starting as a small text messaging service, they have turned into effective communication channels for both private and corporate users, becoming more than just an SMS replacement. Users entrust to them a huge amount of information, such as a time-based map of activity, photos and other personal data. Messengers changed the way communication is done; they reduce the distance to the user and along with social networks become tools for fraud, spam or blackmail and terrorism. In this regard, it is vital to study instant messengers from a forensic point of view. This research explores and compares two popular messengers: Viber and Telegram, which is rapidly gaining popularity in the criminal world and the darknet as secure message tools. The main purpose of the research is to investigate and analyze potential artefacts remaining during the installation and use of instant messengers, as well as after their uninstallation. The authors have done several experiments to investigate the artefacts in different environments and provide clear explanation of the results. The experiments showed that even though Telegram is considered to be one of the most secure instant messengers, important and useful material on a hard drive and registry remain after complete uninstallation of the application. Exploring Viber artefacts showed up information that helps to restore the whole history of a communication. Moreover, the study confirmed that artefacts are still accessible in Windows after removal of the application. INFORMATION SECURITY","PeriodicalId":41920,"journal":{"name":"Biznes Informatika-Business Informatics","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2019-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42004941","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-12-31DOI: 10.17323/1998-0663.2019.4.17.27
M. Belov, Mikhail Shakhmuradyan
The rapid increase of the population, as well as the high rate of urbanization, are leading to an increased need for medical supplies, as well as the need for faster release of new drugs to the market. In this article, the authors analyze and aggregate the activities of a number of pharmaceutical companies at the preclinical stage of drug development to identify optimal management models at the stage of each operational iteration. The work methodology is based on an empirical study based on two progressive stages: a qualitative analysis of the business processes of pharmaceutical enterprises, reflected in regulatory rules and company reports, as well as in-depth interviews with representatives of these commercial organizations. Based on the results obtained at the end of the first stage, the authors established the problem of the lack of a unified presentation of standardized operating procedures, as well as an aggregated representation of the stage of research work on the production of the drug. When considering each business process of this stage, the authors presented a model of the minimum unit of integrated activity (MUnIA). This model most optimally describes local operational business processes during drug development, and can also serve as an instrumental framework for guiding preclinical studies in the formation of a document on standardization of operational procedures. The results of the first stage of the empirical analysis were verified during the second part of the work - in-depth interviews with industry representatives. The findings of this study can be used by project managers at the preclinical testing stage to reduce the time spent on operating procedures.
{"title":"Improvement of a pharmaceutical enterprise’s business processes at the stage of preclinical development of new drugs","authors":"M. Belov, Mikhail Shakhmuradyan","doi":"10.17323/1998-0663.2019.4.17.27","DOIUrl":"https://doi.org/10.17323/1998-0663.2019.4.17.27","url":null,"abstract":"The rapid increase of the population, as well as the high rate of urbanization, are leading to an increased need for medical supplies, as well as the need for faster release of new drugs to the market. In this article, the authors analyze and aggregate the activities of a number of pharmaceutical companies at the preclinical stage of drug development to identify optimal management models at the stage of each operational iteration. The work methodology is based on an empirical study based on two progressive stages: a qualitative analysis of the business processes of pharmaceutical enterprises, reflected in regulatory rules and company reports, as well as in-depth interviews with representatives of these commercial organizations. Based on the results obtained at the end of the first stage, the authors established the problem of the lack of a unified presentation of standardized operating procedures, as well as an aggregated representation of the stage of research work on the production of the drug. When considering each business process of this stage, the authors presented a model of the minimum unit of integrated activity (MUnIA). This model most optimally describes local operational business processes during drug development, and can also serve as an instrumental framework for guiding preclinical studies in the formation of a document on standardization of operational procedures. The results of the first stage of the empirical analysis were verified during the second part of the work - in-depth interviews with industry representatives. The findings of this study can be used by project managers at the preclinical testing stage to reduce the time spent on operating procedures.","PeriodicalId":41920,"journal":{"name":"Biznes Informatika-Business Informatics","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2019-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46644046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-12-31DOI: 10.17323/1998-0663.2019.4.49.59
V. Alekseev, D. Lakomov, A. A. Shishkin, G. Maamari
In modern control systems and information processing, the recognition of objects in the image is complicated by the fact that the impact of negative factors introduces uncertainty into this process, leading to blurring of images. In this regard, it is necessary to develop models and algorithms that would reduce the degree of uncertainty in image processing. These models are necessary, for example, when monitoring environmentally hazardous objects, for search and detection of unauthorized burial of household waste, in the field of information security, in the analysis of x-rays and thermograms, in the actions of unmanned aerial vehicles of law enforcement agencies in autonomous mode. This article presents a description of information technology for recognition in the automated mode of objects in images. The basis of this technology is the algorithm of contour analysis of images. The main distinguishing feature of the algorithm is the use of convolution of the image in four directions, as well as the tracing procedure. The aim of the study was to develop algorithms for high-speed automated visualization of external objects. We present the results of the study of the algorithm of contour analysis in the processing of various images in the visible and infrared wavelengths. Recommendations are formulated for the choice of parameters of the contour analysis algorithm, such as the mean square deviation in image blur, minimum and maximum thresholds for filtering. The results of the study can be used in production management systems, life support of the city, technical vision, environmental conditions, monitoring of business processes, as well as in the creation of simulators for training operators of complex systems, etc. In addition, we show the expediency of applying the algorithm we developed in decision support systems.
{"title":"Image processing of concentrated and scattered objects","authors":"V. Alekseev, D. Lakomov, A. A. Shishkin, G. Maamari","doi":"10.17323/1998-0663.2019.4.49.59","DOIUrl":"https://doi.org/10.17323/1998-0663.2019.4.49.59","url":null,"abstract":"In modern control systems and information processing, the recognition of objects in the image is complicated by the fact that the impact of negative factors introduces uncertainty into this process, leading to blurring of images. In this regard, it is necessary to develop models and algorithms that would reduce the degree of uncertainty in image processing. These models are necessary, for example, when monitoring environmentally hazardous objects, for search and detection of unauthorized burial of household waste, in the field of information security, in the analysis of x-rays and thermograms, in the actions of unmanned aerial vehicles of law enforcement agencies in autonomous mode. This article presents a description of information technology for recognition in the automated mode of objects in images. The basis of this technology is the algorithm of contour analysis of images. The main distinguishing feature of the algorithm is the use of convolution of the image in four directions, as well as the tracing procedure. The aim of the study was to develop algorithms for high-speed automated visualization of external objects. We present the results of the study of the algorithm of contour analysis in the processing of various images in the visible and infrared wavelengths. Recommendations are formulated for the choice of parameters of the contour analysis algorithm, such as the mean square deviation in image blur, minimum and maximum thresholds for filtering. The results of the study can be used in production management systems, life support of the city, technical vision, environmental conditions, monitoring of business processes, as well as in the creation of simulators for training operators of complex systems, etc. In addition, we show the expediency of applying the algorithm we developed in decision support systems.","PeriodicalId":41920,"journal":{"name":"Biznes Informatika-Business Informatics","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2019-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42531155","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-09-30DOI: 10.17323/1998-0663.2019.3.20.34
L. Chernyakhovskaya, M. Nizamutdinov, V. Oreshnikov, A. Atnabaeva
This article deals with the formulation of a decision support system (DSS) in the field of regional development management. The review of existing approaches in this area presented here attests, on the one hand, to their diversity, and on the other hand allows us to draw conclusions about the need to address several methodological and practical issues of decision support in terms of innovative development of regions. Based on this, the goal of the research was to develop the concept of DSS to justify the parameters of an innovative development strategy for regional development based on adaptive mechanisms for coordinating the interests of economic agents. MODELING OF SOCIAL AND ECONOMIC SYSTEMS
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Pub Date : 2019-09-30DOI: 10.17323/1998-0663.2019.3.67.77
A. Biryukov
The paper describes a practical approach which can be used by internal IT organizations to gain their business customers’ trust. The variety of customers of the internal IT service provider is limited to internal customers only. The distinguishing feature of the proposed approach is that it is completely practice-oriented, i.e. primarily aimed at building trust among IT service providers and their customers in a particular organization. The approach is based on the idea that there are measurable prerequisites for the emergence of a customer’s trust which allow you to partially formalize the IT organization’s intention to earn its customers’ trust. A model of intra-organizational trust is proposed; it is progressively improved as the IT organization develops its trust-building capabilities. The model comprises all IT service customers in an organization along with their communications and accounts for internal organizational IT service market specifics. A high-level blueprint of the trust model is described which can serve as a starting point when developing a full-scale trust model in a particular IT organization. We present an approach to the trust model improvement which builds upon principles adopted from widely recognized CMMI model. With this approach, an internal IT service provider can benefit from maturity assessment methods to improve its trust building capabilities.
{"title":"How can an IT organization earn its customers’ trust: A practical approach","authors":"A. Biryukov","doi":"10.17323/1998-0663.2019.3.67.77","DOIUrl":"https://doi.org/10.17323/1998-0663.2019.3.67.77","url":null,"abstract":"The paper describes a practical approach which can be used by internal IT organizations to gain their business customers’ trust. The variety of customers of the internal IT service provider is limited to internal customers only. The distinguishing feature of the proposed approach is that it is completely practice-oriented, i.e. primarily aimed at building trust among IT service providers and their customers in a particular organization. The approach is based on the idea that there are measurable prerequisites for the emergence of a customer’s trust which allow you to partially formalize the IT organization’s intention to earn its customers’ trust. A model of intra-organizational trust is proposed; it is progressively improved as the IT organization develops its trust-building capabilities. The model comprises all IT service customers in an organization along with their communications and accounts for internal organizational IT service market specifics. A high-level blueprint of the trust model is described which can serve as a starting point when developing a full-scale trust model in a particular IT organization. We present an approach to the trust model improvement which builds upon principles adopted from widely recognized CMMI model. With this approach, an internal IT service provider can benefit from maturity assessment methods to improve its trust building capabilities.","PeriodicalId":41920,"journal":{"name":"Biznes Informatika-Business Informatics","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2019-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42103799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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