Pub Date : 2023-07-02DOI: 10.15588/1607-3274-2023-2-17
А. Stenin, I. G. Drozdovych, M. O. Soldatova
Context. In this article, a generalized parametric identification procedure for linear nonstationary systems is proposed, which uses spline functions and orthogonal expansion in a series according to the Walsh function system, which makes it possible to find estimates of the desired parameters by minimizing the integral quadratic criterion of discrepancy based on solving a system of linear algebraic equations for a wide class of linear dynamical systems. The accuracy of parameter estimation is ensured by constructing a spline with a given accuracy and choosing the number of terms of the Walsh series expansion when solving systems of linear algebraic equations by the A. N. Tikhonov regularization method. To improve the accuracy of the assessment, an algorithm for adaptive partitioning of the observation interval is proposed. The partitioning criterion is the weighted square of the discrepancy between the state variables of the control object and the state variables of the model. The choice of the number of terms of the expansion into the Walsh series is carried out on the basis of adaptive approximation of non-stationary parameters in the observation interval, based on the specified accuracy of their estimates. The quality of the management of objects with variable parameters is largely determined by the accuracy of the evaluation of their parameters. Hence, obtaining reliable information about the actual nature of parameter changes is undoubtedly an urgent task. Objective. Improving the accuracy of parameter estimation of a wide class of linear dynamical systems through the joint use of spline functions and Walsh functions. Method. A generalized parametric identification procedure for a wide class of linear dynamical systems is proposed. The choice of the number of terms of the expansion into the Walsh series is made on the basis of the proposed algorithm for adaptive partitioning of the observation interval. Results. The results of modeling of specific linear non-stationary systems confirm the effectiveness of using the proposed approaches to estimating non-stationary parameters. Conclusions. The joint use of spline functions and Walsh functions makes it possible, based on the proposed generalized parametric identification procedure, to obtain analytically estimated parameters, which is very convenient for subsequent use in the synthesis of optimal controls of real technical objects. This procedure is applicable to a wide class of linear dynamical systems with concentrated and distributed parameters.
上下文。本文在求解一类广义线性动力系统的线性代数方程组的基础上，提出了一种线性非平稳系统的广义参数辨识方法，该方法利用样条函数和沃尔什函数系统的正交级数展开式，通过最小化差异积分二次判据来求得期望参数的估计。在用a . N. Tikhonov正则化方法求解线性代数方程组时，通过构造具有给定精度的样条和选择Walsh级数展开的项数来保证参数估计的准确性。为了提高评估的准确性，提出了一种观测区间的自适应划分算法。划分准则是控制对象状态变量与模型状态变量之差的加权平方。扩展到Walsh序列的项数的选择是在观测区间内非平稳参数的自适应逼近的基础上进行的，基于它们的估计的指定精度。可变参数对象的管理质量在很大程度上取决于其参数评价的准确性。因此，获得有关参数变化的实际性质的可靠信息无疑是一项紧迫的任务。目标。通过样条函数和沃尔什函数的联合应用，提高了一类线性动力系统参数估计的精度。方法。提出了一类广义线性动力系统的广义参数辨识方法。根据所提出的自适应分割观测区间的算法，选择展开到Walsh序列的项数。结果。具体线性非平稳系统的建模结果证实了采用所提方法估计非平稳参数的有效性。结论。利用样条函数和Walsh函数的联合应用，可以根据所提出的广义参数辨识方法得到解析估计的参数，为后续在实际技术对象的最优控制综合中使用提供了方便。该方法适用于具有集中和分布参数的各种线性动力系统。
{"title":"APPLICATION OF SPLINE FUNCTIONS AND WALSH FUNCTIONS IN PROBLEMS OF PARAMETRIC IDENTIFICATION OF LINEAR NONSTATIONARY SYSTEMS","authors":"А. Stenin, I. G. Drozdovych, M. O. Soldatova","doi":"10.15588/1607-3274-2023-2-17","DOIUrl":"https://doi.org/10.15588/1607-3274-2023-2-17","url":null,"abstract":"Context. In this article, a generalized parametric identification procedure for linear nonstationary systems is proposed, which uses spline functions and orthogonal expansion in a series according to the Walsh function system, which makes it possible to find estimates of the desired parameters by minimizing the integral quadratic criterion of discrepancy based on solving a system of linear algebraic equations for a wide class of linear dynamical systems. The accuracy of parameter estimation is ensured by constructing a spline with a given accuracy and choosing the number of terms of the Walsh series expansion when solving systems of linear algebraic equations by the A. N. Tikhonov regularization method. To improve the accuracy of the assessment, an algorithm for adaptive partitioning of the observation interval is proposed. The partitioning criterion is the weighted square of the discrepancy between the state variables of the control object and the state variables of the model. The choice of the number of terms of the expansion into the Walsh series is carried out on the basis of adaptive approximation of non-stationary parameters in the observation interval, based on the specified accuracy of their estimates. The quality of the management of objects with variable parameters is largely determined by the accuracy of the evaluation of their parameters. Hence, obtaining reliable information about the actual nature of parameter changes is undoubtedly an urgent task. \u0000Objective. Improving the accuracy of parameter estimation of a wide class of linear dynamical systems through the joint use of spline functions and Walsh functions. \u0000Method. A generalized parametric identification procedure for a wide class of linear dynamical systems is proposed. The choice of the number of terms of the expansion into the Walsh series is made on the basis of the proposed algorithm for adaptive partitioning of the observation interval. \u0000Results. The results of modeling of specific linear non-stationary systems confirm the effectiveness of using the proposed approaches to estimating non-stationary parameters. \u0000Conclusions. The joint use of spline functions and Walsh functions makes it possible, based on the proposed generalized parametric identification procedure, to obtain analytically estimated parameters, which is very convenient for subsequent use in the synthesis of optimal controls of real technical objects. This procedure is applicable to a wide class of linear dynamical systems with concentrated and distributed parameters.","PeriodicalId":43783,"journal":{"name":"Radio Electronics Computer Science Control","volume":"31 1","pages":""},"PeriodicalIF":0.5,"publicationDate":"2023-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84853345","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 : 2023-07-02DOI: 10.15588/1607-3274-2023-2-14
M. M. Seniv
Context. With the development of the software industry, the number of applied methodologies and hybrid approaches based on them constantly increases, that is why, the choice of the most suitable/optimal methodology for the project is an urgent problem of software engineering, since the selection process is poorly formalized, requires sufficient experience of the person who will make this decision and depends on many related factors.
Objective. The support of decision-making in the process of choosing a methodology for the software project development and increase of the level of adequacy of the above choice.
Method. Based on the previously developed algorithm by the author, a generalized method for selecting the best software development methodology is proposed, which consists of 14 steps and takes into account the characteristics of the project, based on the multi-criteria analysis approaches, taking into consideration the opinions of experts for a more reasonable choice of the most suitable methodology for this project. The method uses the aggregated expert evaluation. It was decided to use the AHP to calculate the criteria weights. Based on the established values of criteria, their weights and expert evaluation, the score is calculated for each methodology using the weighted sum and TOPSIS methods.
Results. The application of the developed method to the data of actual projects showed a match in 83% of cases (in five out of six cases, the application of the method resulted in the selection of methodology that corresponded to the one actually used in an existing project). In cases when the methodology chosen by the proposed method differed from the one that was actually used, the application of the proposed method recommends going to the stage of the initial determination of criteria and their weights, which will allow making a more adequate choice of methodology.
Conclusions. The proposed method can be applied in practice by software project managers to support the decision-making process, and will allow reducing time spent on project management.
{"title":"METHOD FOR SELECTING A SOFTWARE DEVELOPMENT METHODOLOGY TAKING INTO ACCOUNT PROJECT CHARACTERISTICS","authors":"M. M. Seniv","doi":"10.15588/1607-3274-2023-2-14","DOIUrl":"https://doi.org/10.15588/1607-3274-2023-2-14","url":null,"abstract":"Context. With the development of the software industry, the number of applied methodologies and hybrid approaches based on them constantly increases, that is why, the choice of the most suitable/optimal methodology for the project is an urgent problem of software engineering, since the selection process is poorly formalized, requires sufficient experience of the person who will make this decision and depends on many related factors.
 Objective. The support of decision-making in the process of choosing a methodology for the software project development and increase of the level of adequacy of the above choice.
 Method. Based on the previously developed algorithm by the author, a generalized method for selecting the best software development methodology is proposed, which consists of 14 steps and takes into account the characteristics of the project, based on the multi-criteria analysis approaches, taking into consideration the opinions of experts for a more reasonable choice of the most suitable methodology for this project. The method uses the aggregated expert evaluation. It was decided to use the AHP to calculate the criteria weights. Based on the established values of criteria, their weights and expert evaluation, the score is calculated for each methodology using the weighted sum and TOPSIS methods.
 Results. The application of the developed method to the data of actual projects showed a match in 83% of cases (in five out of six cases, the application of the method resulted in the selection of methodology that corresponded to the one actually used in an existing project). In cases when the methodology chosen by the proposed method differed from the one that was actually used, the application of the proposed method recommends going to the stage of the initial determination of criteria and their weights, which will allow making a more adequate choice of methodology.
 Conclusions. The proposed method can be applied in practice by software project managers to support the decision-making process, and will allow reducing time spent on project management.","PeriodicalId":43783,"journal":{"name":"Radio Electronics Computer Science Control","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135802115","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 : 2023-07-02DOI: 10.15588/1607-3274-2023-2-16
S. Chernov, Lb. S. Chernova, Ld. S. Chernova, N. Kunanets, S. Titov, E. Trushliakov
Context. The article proposes a method of analyzing the proposals of team members in order to avoid conflict situations at the stage of team formation. Objective. The object of the study is the method of analyzing the proposals of team members while solving project tasks. The purpose of the work is to analyze the developed method of analysis of proposals of team members to avoid or resolve conflict situations at the stage of team activation Method. The developed method is based on the theory of matrix games. Conflicts between individual team members mainly arise at the stage of team formation. For the project manager, it is important to identify the conflict situation in time and find a way out of it to satisfy both team members and without harming the teamwork as a whole. A team created to implement an IT project is often faced with a situation where two of its members have different visions of approaches to creating the final product. At the same time, each of them has experience in the development of similar software products or services by different teams. To effectively solve this situation, we suggest using approaches typical of bimatrix games, when each of these team members is considered as a player. This takes into account the fact that the bimatrix theory of games is based on a conflict between two players whose interests are opposite – an antagonistic zero-sum game is precisely the basis of the developed approach. Results. The proposed method of analysis of proposals of team members contributes to the avoidance or resolution of conflict situations at the stage of their closer interaction. For efficient solution of the said situation, we propose to use approaches being typical for bimatrix games when each of these team members is treated as a player. At the same time, account is taken of the fact that the bimatrix game theory is based on a conflict of two players whose interests are opposite – an antagonistic game with a zero sum being that very element to constitute the basis of the approach developed. Conclusions. The given calculation of the model example shows that the use of the proposed method allows the project manager to give a reasonable preference to another team member, since the expected average profit of this player is greater than that of the first player. In this case, the manager has an opportunity to simulate situations for the players (for the team) and promptly respond to probable deviations of their behavioral strategies from the optimal ones, establish healthy relationships between team members and choose the best proposals for solving project tasks.
{"title":"USING THE BEHAVIOR ANTAGONISM AND THE BIMATRIX GAME THEORY IN THE IT PROJECT MANAGEMENT","authors":"S. Chernov, Lb. S. Chernova, Ld. S. Chernova, N. Kunanets, S. Titov, E. Trushliakov","doi":"10.15588/1607-3274-2023-2-16","DOIUrl":"https://doi.org/10.15588/1607-3274-2023-2-16","url":null,"abstract":"Context. The article proposes a method of analyzing the proposals of team members in order to avoid conflict situations at the stage of team formation. \u0000Objective. The object of the study is the method of analyzing the proposals of team members while solving project tasks. \u0000The purpose of the work is to analyze the developed method of analysis of proposals of team members to avoid or resolve conflict situations at the stage of team activation \u0000Method. The developed method is based on the theory of matrix games. Conflicts between individual team members mainly arise at the stage of team formation. For the project manager, it is important to identify the conflict situation in time and find a way out of it to satisfy both team members and without harming the teamwork as a whole. A team created to implement an IT project is often faced with a situation where two of its members have different visions of approaches to creating the final product. At the same time, each of them has experience in the development of similar software products or services by different teams. To effectively solve this situation, we suggest using approaches typical of bimatrix games, when each of these team members is considered as a player. This takes into account the fact that the bimatrix theory of games is based on a conflict between two players whose interests are opposite – an antagonistic zero-sum game is precisely the basis of the developed approach. \u0000Results. The proposed method of analysis of proposals of team members contributes to the avoidance or resolution of conflict situations at the stage of their closer interaction. For efficient solution of the said situation, we propose to use approaches being typical for bimatrix games when each of these team members is treated as a player. At the same time, account is taken of the fact that the bimatrix game theory is based on a conflict of two players whose interests are opposite – an antagonistic game with a zero sum being that very element to constitute the basis of the approach developed. \u0000Conclusions. The given calculation of the model example shows that the use of the proposed method allows the project manager to give a reasonable preference to another team member, since the expected average profit of this player is greater than that of the first player. In this case, the manager has an opportunity to simulate situations for the players (for the team) and promptly respond to probable deviations of their behavioral strategies from the optimal ones, establish healthy relationships between team members and choose the best proposals for solving project tasks.","PeriodicalId":43783,"journal":{"name":"Radio Electronics Computer Science Control","volume":"15 1","pages":""},"PeriodicalIF":0.5,"publicationDate":"2023-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83945547","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 : 2023-07-02DOI: 10.15588/1607-3274-2023-2-15
Y. Dorofieiev, L. M. Lyubchyk, O. S. Melnikov
Context. The presence of time delays occurs in many complex dynamical systems, particularly in the areas of modern communication and information technologies, such as the problem of stabilizing networked control systems and high-speed communication networks. In many cases, time-delays lead to a decrease in the efficiency of such systems and even to the loss of stability. In the last decade, many interesting solutions using the Lyapunov-Krasovskii functional have been proposed for stability analysis and synthesis of a stabilizing regulator for discrete-time dynamic systems with unknown but bounded state-delays. The presence of nonlinear constraints on the amplitude of controls such as saturation further complicates this problem and requires the development of new approaches and methods. Objective. The purpose of this study is to develop a procedure for calculating the control gain matrix of state feedback that ensures the asymptotic stability of the analyzed system, as well as a procedure for calculating the maximum permissible value of the state-delay under which the stability of the closed-loop system can be ensured for a given set of admissible initial conditions. Method. The paper uses the method of descriptor transformation of the model of a closed-loop system and extends the invariant ellipsoids method to systems with unknown but bounded state-delays. The application of the Lyapunov-Krasovskii functional and the technique of linear matrix inequalities made it possible to reduce the problem of calculating the control gain matrix to the problem of semi-definite programming, which can be solved numerically. An iterative algorithm for solving the bilinear matrix inequality is proposed for calculating the maximum permissible value of the time-delay. Results. The results of numerical modeling confirm the effectiveness of the proposed approach in the problems of stabilizing discrete-time systems under the conditions of state-delays and nonlinear constraints on controls, which allows to recommend the proposed method for practical use for the problem of stability analysis and synthesis of stabilizing regulator, as well as for calculating the maximum permissible value of time-delay. Conclusions. An approach is proposed that allows extending the invariant ellipsoids method to discrete-time dynamic systems with unknown but bounded state-delays for solving the problem of system stabilization using static state feedback based on the application of the Lyapunov-Krasovskii functional. The results of numerical modeling confirm the effectiveness of the proposed approach in the presence of the saturation type nonlinear constraints on the control signals.
{"title":"STABILIZATION OF DISCRETE-TIME SYSTEMS WITH STATE-DELAYS AND SATURATING CONTROL INPUTS","authors":"Y. Dorofieiev, L. M. Lyubchyk, O. S. Melnikov","doi":"10.15588/1607-3274-2023-2-15","DOIUrl":"https://doi.org/10.15588/1607-3274-2023-2-15","url":null,"abstract":"Context. The presence of time delays occurs in many complex dynamical systems, particularly in the areas of modern communication and information technologies, such as the problem of stabilizing networked control systems and high-speed communication networks. In many cases, time-delays lead to a decrease in the efficiency of such systems and even to the loss of stability. In the last decade, many interesting solutions using the Lyapunov-Krasovskii functional have been proposed for stability analysis and synthesis of a stabilizing regulator for discrete-time dynamic systems with unknown but bounded state-delays. The presence of nonlinear constraints on the amplitude of controls such as saturation further complicates this problem and requires the development of new approaches and methods. \u0000Objective. The purpose of this study is to develop a procedure for calculating the control gain matrix of state feedback that ensures the asymptotic stability of the analyzed system, as well as a procedure for calculating the maximum permissible value of the state-delay under which the stability of the closed-loop system can be ensured for a given set of admissible initial conditions. \u0000Method. The paper uses the method of descriptor transformation of the model of a closed-loop system and extends the invariant ellipsoids method to systems with unknown but bounded state-delays. The application of the Lyapunov-Krasovskii functional and the technique of linear matrix inequalities made it possible to reduce the problem of calculating the control gain matrix to the problem of semi-definite programming, which can be solved numerically. An iterative algorithm for solving the bilinear matrix inequality is proposed for calculating the maximum permissible value of the time-delay. \u0000Results. The results of numerical modeling confirm the effectiveness of the proposed approach in the problems of stabilizing discrete-time systems under the conditions of state-delays and nonlinear constraints on controls, which allows to recommend the proposed method for practical use for the problem of stability analysis and synthesis of stabilizing regulator, as well as for calculating the maximum permissible value of time-delay. \u0000Conclusions. An approach is proposed that allows extending the invariant ellipsoids method to discrete-time dynamic systems with unknown but bounded state-delays for solving the problem of system stabilization using static state feedback based on the application of the Lyapunov-Krasovskii functional. The results of numerical modeling confirm the effectiveness of the proposed approach in the presence of the saturation type nonlinear constraints on the control signals.","PeriodicalId":43783,"journal":{"name":"Radio Electronics Computer Science Control","volume":"80 1","pages":""},"PeriodicalIF":0.5,"publicationDate":"2023-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74864997","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 : 2023-07-01DOI: 10.15588/1607-3274-2023-2-13
V. Morkun, S. Hryshchenko, V. Nizhehorodtsev, M. Filonenko, V. V. Lagovsky
Context. The constant growth in the volume of information, the increase in the speed of information flows in digital communication networks, as before, makes the task of assessing the service stability for traffic flows an urgent one. A simple solution to ensure high service stability is to build a network of sufficient capacity for any traffic that will be thrown at it. To solve the problems of analyzing telecommunication systems, it is necessary to have appropriate models and engineering methods that allow to assess the service stability and predict the characteristics of their operation based on measurement data. In these conditions, the development of new methods for analyzing the traffic of multiservice networks that provide simplicity of calculations and their acceptable accuracy becomes especially relevant. Objective. The purpose of this paper is to study the traffic and service stability for users. Method. We propose a hybrid method for detecting anomalies in multiservice network traffic that uses algorithms without identification, adaptation and Mamdani fuzzy inference. The peculiarity of multiservice traffic as an object for assessing the existence of anomalies is the presence of stochastic processes in it subject to different distribution laws. For the experimental evaluation of the proposed method and algorithms, we have chosen the Poisson and Pareto distribution laws that define the limiting cases of traffic regularity. The method allows for monitoring and managing faults in a multiservice network in order to determine the causes of their occurrence. The following requirements are imposed on the developed algorithms for detecting anomalies in the traffic on multiservice networks: functioning in real or near real time; maintaining a given service stability; simplicity of implementation. The algorithms belong to the class of adaptive hybrid algorithms for identifying traffic parameters. They are used for both stationary and nonstationary traffic. Traffic is modeled as stochastic processes. Each belongs to the corresponding class, which is determined by the law of distribution of stochastic processes. Results. Experimental evaluation of the proposed method and algorithms has shown that they allow us to estimate the trends of these stochastic processes in real time, with high accuracy and while maintaining the service stability. Conclusions. The application of the developed method of troubleshooting management in a multiservice environment helps to improve the service stability by timely detecting problems, reducing the time of their elimination and reducing downtime, which, in turn, affects the increase in service reliability.
{"title":"DEVELOPMENT OF A METHOD FOR STUDYING TRAFFIC OF MULTISERVICE NETWORKS","authors":"V. Morkun, S. Hryshchenko, V. Nizhehorodtsev, M. Filonenko, V. V. Lagovsky","doi":"10.15588/1607-3274-2023-2-13","DOIUrl":"https://doi.org/10.15588/1607-3274-2023-2-13","url":null,"abstract":"Context. The constant growth in the volume of information, the increase in the speed of information flows in digital communication networks, as before, makes the task of assessing the service stability for traffic flows an urgent one. A simple solution to ensure high service stability is to build a network of sufficient capacity for any traffic that will be thrown at it. To solve the problems of analyzing telecommunication systems, it is necessary to have appropriate models and engineering methods that allow to assess the service stability and predict the characteristics of their operation based on measurement data. In these conditions, the development of new methods for analyzing the traffic of multiservice networks that provide simplicity of calculations and their acceptable accuracy becomes especially relevant. \u0000Objective. The purpose of this paper is to study the traffic and service stability for users. \u0000Method. We propose a hybrid method for detecting anomalies in multiservice network traffic that uses algorithms without identification, adaptation and Mamdani fuzzy inference. The peculiarity of multiservice traffic as an object for assessing the existence of anomalies is the presence of stochastic processes in it subject to different distribution laws. For the experimental evaluation of the proposed method and algorithms, we have chosen the Poisson and Pareto distribution laws that define the limiting cases of traffic regularity. The method allows for monitoring and managing faults in a multiservice network in order to determine the causes of their occurrence. The following requirements are imposed on the developed algorithms for detecting anomalies in the traffic on multiservice networks: functioning in real or near real time; maintaining a given service stability; simplicity of implementation. The algorithms belong to the class of adaptive hybrid algorithms for identifying traffic parameters. They are used for both stationary and nonstationary traffic. Traffic is modeled as stochastic processes. Each belongs to the corresponding class, which is determined by the law of distribution of stochastic processes. \u0000Results. Experimental evaluation of the proposed method and algorithms has shown that they allow us to estimate the trends of these stochastic processes in real time, with high accuracy and while maintaining the service stability. \u0000Conclusions. The application of the developed method of troubleshooting management in a multiservice environment helps to improve the service stability by timely detecting problems, reducing the time of their elimination and reducing downtime, which, in turn, affects the increase in service reliability.","PeriodicalId":43783,"journal":{"name":"Radio Electronics Computer Science Control","volume":"34 1","pages":""},"PeriodicalIF":0.5,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84292966","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 : 2023-07-01DOI: 10.15588/1607-3274-2023-2-12
O. Kungurtsev, S. Zinovatna
Context. Use cases are widely used as a means of formulating requirements in the development of information systems. All subsequent design stages depend on the quality of their presentation. Structuring use cases can significantly increase their understanding and maintenance in the face of changing requirements.. Objective. Flexible technologies involve working in small teams. The existing communication between teams is not sufficient to highlight sub use cases at the project level. There is a need for automated analysis of the corpus of all use cases. Method. A mathematical model of a use case which makes it possible to define the criteria for comparing scenarios and eliminate the redundancy of descriptions is proposed. A four-step method for restructuring use cases has been developed. At the first stage, use cases are presented in a formalized form. At the second, they are stored in the repository, which ensures their quick search and placement. At the third stage, procedures of scenario comparison are performed. Scenario similarity criteria are proposed. At the fourth stage, the formation of subordinate use cases is carried out, their texts are coordinated with all interested teams, and the use cases that cause subordinate use cases are corrected. Results. Experiments providing the formalized compilation of use cases by several development teams followed by automated restructuring were carried out to test the proposed solutions. As a result, new subordinate use cases were correctly identified and the scope of use of previously formed ones was expanded. There was a significant reduction in the time for restructuring. Conclusions. The proposed method of restructuring use cases improves the clarity and consistency of requirements, the possibility of their adjustment and maintenance, and reduces the compilation time. The method can be used in the design of any information system, where the requirements are presented in the form of use cases.
{"title":"TECHNOLOGY FOR IDENTIFYING AND FORMING POSSIBLE RELATIONSHIPS BETWEEN USE CASES IN THE PROCESS OF THE INFORMATION SYSTEM DESIGN","authors":"O. Kungurtsev, S. Zinovatna","doi":"10.15588/1607-3274-2023-2-12","DOIUrl":"https://doi.org/10.15588/1607-3274-2023-2-12","url":null,"abstract":"Context. Use cases are widely used as a means of formulating requirements in the development of information systems. All subsequent design stages depend on the quality of their presentation. Structuring use cases can significantly increase their understanding and maintenance in the face of changing requirements.. \u0000Objective. Flexible technologies involve working in small teams. The existing communication between teams is not sufficient to highlight sub use cases at the project level. There is a need for automated analysis of the corpus of all use cases. \u0000Method. A mathematical model of a use case which makes it possible to define the criteria for comparing scenarios and eliminate the redundancy of descriptions is proposed. A four-step method for restructuring use cases has been developed. At the first stage, use cases are presented in a formalized form. At the second, they are stored in the repository, which ensures their quick search and placement. At the third stage, procedures of scenario comparison are performed. Scenario similarity criteria are proposed. At the fourth stage, the formation of subordinate use cases is carried out, their texts are coordinated with all interested teams, and the use cases that cause subordinate use cases are corrected. \u0000Results. Experiments providing the formalized compilation of use cases by several development teams followed by automated restructuring were carried out to test the proposed solutions. As a result, new subordinate use cases were correctly identified and the scope of use of previously formed ones was expanded. There was a significant reduction in the time for restructuring. \u0000Conclusions. The proposed method of restructuring use cases improves the clarity and consistency of requirements, the possibility of their adjustment and maintenance, and reduces the compilation time. The method can be used in the design of any information system, where the requirements are presented in the form of use cases.","PeriodicalId":43783,"journal":{"name":"Radio Electronics Computer Science Control","volume":"10 1","pages":""},"PeriodicalIF":0.5,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73364475","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 : 2023-06-30DOI: 10.15588/1607-3274-2023-2-11
Удк, Технологія Аналізу Україномовних, Твітів Для, Прогнозування Зміни, Динаміки Громадської, НА Думки, Основі Машинного Навчання
Context. Automation of public opinion research will allow not only to reduce the amount of manual work, but also to obtain time slices of the results without additional efforts. Since direct interaction with respondents should be avoided, public opinion should be analyzed based on the sources of its free expression. Social networks are great for this role, as their people freely publish their thoughts or emotionally truthfully react to published information about certain events. Statistics show that data from social networks is not enough to obtain a full-fledged result, because a significant percentage of people do not use social networks. However, the automation of the study of even such a stratum of the population is already a good result for analyzing the dynamics of changes in public opinion in accordance with events in the country/world and, accordingly, for correcting the processes of public administration in the future. Objective of the study is to develop a technology for analyzing the flow of Ukrainian-language content in social networks for public opinion research based on finding clustered thematic groups of tweets. Method. The article develops a technology for finding tweet trends based on clustering, which forms a data stream in the form of short representations of clusters and their popularity for further research of public opinion. An effective approach to tweet collection, filtering, cleaning and pre-processing based on a comparative analysis of Bag of Words, TF-IDF and BERT algorithms is described. The impact of stemming and lemmatization on the quality of the obtained clusters was determined. And optimal combinations of clustering methods (K-Means, Agglomerative Hierarchical Clustering and HDBSCAN) and vectorization of tweets were found based on the analysis of 27 clusterings of one data sample. The method of presenting clusters of tweets in a short format is selected. Results. Algorithms using the Levenstein Distance, i.e. fuzz sort, fuzz set and levenshtein, showed the best results. These algorithms quickly perform checks, have a greater difference in similarities, so it is possible to more accurately determine the limit of similarity. According to the results of the clustering, the optimal solutions are to use the HDBSCAN clustering algorithm and the BERT vectorization algorithm to achieve the most accurate results, and to use K-Means together with TF-IDF to achieve the best speed with the optimal result. Stemming can be used to reduce execution time. Conclusions. In this study, the optimal options for comparing cluster fingerprints among the following similarity search methods were experimentally found: Fuzz Sort, Fuzz Set, Levenshtein, Jaro Winkler, Jaccard, Sorensen, Cosine, Sift4. In some algorithms, the average fingerprint similarity reaches above 70%. 3 effective tools were found to compare their similarity, as they show a sufficient difference between comparisons of similar and different clusters (> 20%). Based on
{"title":"UKRAINIAN LANGUAGE TWEETS ANALYSIS TECHNOLOGY FOR PUBLIC OPINION DYNAMICS CHANGE PREDICTION BASED ON MACHINE LEARNING","authors":"Удк, Технологія Аналізу Україномовних, Твітів Для, Прогнозування Зміни, Динаміки Громадської, НА Думки, Основі Машинного Навчання","doi":"10.15588/1607-3274-2023-2-11","DOIUrl":"https://doi.org/10.15588/1607-3274-2023-2-11","url":null,"abstract":"Context. Automation of public opinion research will allow not only to reduce the amount of manual work, but also to obtain time slices of the results without additional efforts. Since direct interaction with respondents should be avoided, public opinion should be analyzed based on the sources of its free expression. Social networks are great for this role, as their people freely publish their thoughts or emotionally truthfully react to published information about certain events. Statistics show that data from social networks is not enough to obtain a full-fledged result, because a significant percentage of people do not use social networks. However, the automation of the study of even such a stratum of the population is already a good result for analyzing the dynamics of changes in public opinion in accordance with events in the country/world and, accordingly, for correcting the processes of public administration in the future. \u0000Objective of the study is to develop a technology for analyzing the flow of Ukrainian-language content in social networks for public opinion research based on finding clustered thematic groups of tweets. \u0000Method. The article develops a technology for finding tweet trends based on clustering, which forms a data stream in the form of short representations of clusters and their popularity for further research of public opinion. An effective approach to tweet collection, filtering, cleaning and pre-processing based on a comparative analysis of Bag of Words, TF-IDF and BERT algorithms is described. The impact of stemming and lemmatization on the quality of the obtained clusters was determined. And optimal combinations of clustering methods (K-Means, Agglomerative Hierarchical Clustering and HDBSCAN) and vectorization of tweets were found based on the analysis of 27 clusterings of one data sample. The method of presenting clusters of tweets in a short format is selected. \u0000Results. Algorithms using the Levenstein Distance, i.e. fuzz sort, fuzz set and levenshtein, showed the best results. These algorithms quickly perform checks, have a greater difference in similarities, so it is possible to more accurately determine the limit of similarity. According to the results of the clustering, the optimal solutions are to use the HDBSCAN clustering algorithm and the BERT vectorization algorithm to achieve the most accurate results, and to use K-Means together with TF-IDF to achieve the best speed with the optimal result. Stemming can be used to reduce execution time. \u0000Conclusions. In this study, the optimal options for comparing cluster fingerprints among the following similarity search methods were experimentally found: Fuzz Sort, Fuzz Set, Levenshtein, Jaro Winkler, Jaccard, Sorensen, Cosine, Sift4. In some algorithms, the average fingerprint similarity reaches above 70%. 3 effective tools were found to compare their similarity, as they show a sufficient difference between comparisons of similar and different clusters (> 20%). Based on","PeriodicalId":43783,"journal":{"name":"Radio Electronics Computer Science Control","volume":"34 1","pages":""},"PeriodicalIF":0.5,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75813378","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 : 2023-06-30DOI: 10.15588/1607-3274-2023-2-9
V. Moskalenko
Context. The problem of optimizing the resilience of artificial intelligence systems to destructive disturbances has not yet been fully solved and is quite relevant for safety-critical applications. The task of optimizing the resilience of an artificial intelligence system to disturbing influences is a high-level task in relation to efficiency optimization, which determines the prospects of using the ideas and methods of meta-learning to solve it. The object of current research is the process of meta-learning aimed at optimizing the resilience of an artificial intelligence system to destructive disturbances. The subjects of the study are architectural add-ons and the meta-learning method which optimize resilience to adversarial attacks, fault injection, and task changes. Objective. Stated research goal is to develop an effective meta-learning method for optimizing the resilience of an artificial intelligence system to destructive disturbances. Method. The resilience optimization is implemented by combining the ideas and methods of adversarial learning, fault-tolerant learning, model-agnostic meta-learning, few-shot learning, gradient optimization methods, and probabilistic gradient approximation strategies. The choice of architectural add-ons is based on parameter-efficient knowledge transfer designed to save resources and avoid the problem of catastrophic forgetting. Results. A model-agnostic meta-learning method for optimizing the resilience of artificial intelligence systems based on gradient meta-updates or meta-updates using an evolutionary strategy has been developed. This method involves the use of tuner and metatuner blocks that perform parallel correction of the building blocks of a original deep neural network. The ability of the proposed approach to increase the efficiency of perturbation absorption and increase the integral resilience indicator of the artificial intelligence system is experimentally tested on the example of the image classification task. The experiments were conducted on a model with the ResNet-18 architecture, with an add-on in the form of tuners and meta-tuners with the Conv-Adapter architecture. In this case, CIFAR-10 is used as a base set on which the model was trained, and CIFAR-100 is used as a set for generating samples on which adaptation is performed using a few-shot learning scenarios. We compare the resilience of the artificial intelligence system after pre-training tuners and meta-tuners using the adversarial learning algorithm, the fault-tolerant learning algorithm, the conventional model-agnostic meta-learning algorithm, and the proposed meta-learning method for optimizing resilience. Also, the meta-learning algorithms with meta-gradient updating and meta-updating based on the evolutionary strategy are compared on the basis of the integral resilience indicator. Conclusions. It has been experimentally confirmed that the proposed method provides a better resilience to random bit-flip injection compared
{"title":"MODEL-AGNOSTIC META-LEARNING FOR RESILIENCE OPTIMIZATION OF ARTIFICIAL INTELLIGENCE SYSTEM","authors":"V. Moskalenko","doi":"10.15588/1607-3274-2023-2-9","DOIUrl":"https://doi.org/10.15588/1607-3274-2023-2-9","url":null,"abstract":"Context. The problem of optimizing the resilience of artificial intelligence systems to destructive disturbances has not yet been fully solved and is quite relevant for safety-critical applications. The task of optimizing the resilience of an artificial intelligence system to disturbing influences is a high-level task in relation to efficiency optimization, which determines the prospects of using the ideas and methods of meta-learning to solve it. The object of current research is the process of meta-learning aimed at optimizing the resilience of an artificial intelligence system to destructive disturbances. The subjects of the study are architectural add-ons and the meta-learning method which optimize resilience to adversarial attacks, fault injection, and task changes. \u0000Objective. Stated research goal is to develop an effective meta-learning method for optimizing the resilience of an artificial intelligence system to destructive disturbances. \u0000Method. The resilience optimization is implemented by combining the ideas and methods of adversarial learning, fault-tolerant learning, model-agnostic meta-learning, few-shot learning, gradient optimization methods, and probabilistic gradient approximation strategies. The choice of architectural add-ons is based on parameter-efficient knowledge transfer designed to save resources and avoid the problem of catastrophic forgetting. \u0000Results. A model-agnostic meta-learning method for optimizing the resilience of artificial intelligence systems based on gradient meta-updates or meta-updates using an evolutionary strategy has been developed. This method involves the use of tuner and metatuner blocks that perform parallel correction of the building blocks of a original deep neural network. The ability of the proposed approach to increase the efficiency of perturbation absorption and increase the integral resilience indicator of the artificial intelligence system is experimentally tested on the example of the image classification task. The experiments were conducted on a model with the ResNet-18 architecture, with an add-on in the form of tuners and meta-tuners with the Conv-Adapter architecture. In this case, CIFAR-10 is used as a base set on which the model was trained, and CIFAR-100 is used as a set for generating samples on which adaptation is performed using a few-shot learning scenarios. We compare the resilience of the artificial intelligence system after pre-training tuners and meta-tuners using the adversarial learning algorithm, the fault-tolerant learning algorithm, the conventional model-agnostic meta-learning algorithm, and the proposed meta-learning method for optimizing resilience. Also, the meta-learning algorithms with meta-gradient updating and meta-updating based on the evolutionary strategy are compared on the basis of the integral resilience indicator. \u0000Conclusions. It has been experimentally confirmed that the proposed method provides a better resilience to random bit-flip injection compared","PeriodicalId":43783,"journal":{"name":"Radio Electronics Computer Science Control","volume":"2 1","pages":""},"PeriodicalIF":0.5,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74372881","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 : 2023-06-30DOI: 10.15588/1607-3274-2023-2-10
Удк, Видалення Компонентів, Дощу З Одиночних, З Зображень, Використанням Рекурентної, Нейронної Мережі
Context. Removing the undesirable consequences of rain effects from single images is an actual problem in many computer vision tasks, because rain streaks can significantly degrade the visual quality of images and seriously interfere with the operation of various intelligent systems, which are used for their processing and further analysis. Objective. The goal of the work is to develop a method for detecting and removing undesirable effects of the rain from single images, which is based on the using of a convolutional neural network with a recurrent structure. Method. The main component of the proposed method is a convolutional neural network, which has a recurrent multi-stage structure. A feature of this network architecture is the use of repeated blocks (layers), at the output of which you can get an intermediate result of «cleaning» the original image. Moreover at the output of each next layer of the network we get an image with less influence of rain components than on the previous one. Each network layer contains two independent sub-networks (branches) for parallel image processing. The main branch is designed to detect and remove the effect of rain from the image and the attention branch is used to improve and speed up the process of detecting undesirable rain components (for rain attention map formation). Results. An approach has been developed to automatically detect and remove the rain effect from single images. The process of “cleaning” the original image is based on the use of a convolutional neural network with a recurrent structure, which was trained on the Rain100H and Rain100L datasets. The results of computer experiments, which testifies to the effectiveness and expediency of using the proposed method for solving practical tasks of pre-processing “contaminated” images are presented. Conclusions. The advantage of the developed method for removing undesirable components of rain from images is that the recurrent multi-stage network architecture, on which it is based allows it to be potentially applied to solving tasks under conditions of limited computing resources. The proposed method can be successfully used in the development of intelligent systems for area monitoring with surveillance cameras, autonomous vehicles control, processing aerial photography results, etc. In the future, it should be considered the possibility of forming a separate sub-network to eliminate blurring in the image and train the network on datasets that contain image samples with different components of rain, which will make the method more «resistant» to different forms of the rain effect and increase the quality of image “cleaning”.
{"title":"REMOVAL OF RAIN COMPONENTS FROM SINGLE IMAGES USING A RECURRENT NEURAL NETWORK","authors":"Удк, Видалення Компонентів, Дощу З Одиночних, З Зображень, Використанням Рекурентної, Нейронної Мережі","doi":"10.15588/1607-3274-2023-2-10","DOIUrl":"https://doi.org/10.15588/1607-3274-2023-2-10","url":null,"abstract":"Context. Removing the undesirable consequences of rain effects from single images is an actual problem in many computer vision tasks, because rain streaks can significantly degrade the visual quality of images and seriously interfere with the operation of various intelligent systems, which are used for their processing and further analysis. \u0000Objective. The goal of the work is to develop a method for detecting and removing undesirable effects of the rain from single images, which is based on the using of a convolutional neural network with a recurrent structure. \u0000Method. The main component of the proposed method is a convolutional neural network, which has a recurrent multi-stage structure. A feature of this network architecture is the use of repeated blocks (layers), at the output of which you can get an intermediate result of «cleaning» the original image. Moreover at the output of each next layer of the network we get an image with less influence of rain components than on the previous one. Each network layer contains two independent sub-networks (branches) for parallel image processing. The main branch is designed to detect and remove the effect of rain from the image and the attention branch is used to improve and speed up the process of detecting undesirable rain components (for rain attention map formation). \u0000Results. An approach has been developed to automatically detect and remove the rain effect from single images. The process of “cleaning” the original image is based on the use of a convolutional neural network with a recurrent structure, which was trained on the Rain100H and Rain100L datasets. The results of computer experiments, which testifies to the effectiveness and expediency of using the proposed method for solving practical tasks of pre-processing “contaminated” images are presented. \u0000Conclusions. The advantage of the developed method for removing undesirable components of rain from images is that the recurrent multi-stage network architecture, on which it is based allows it to be potentially applied to solving tasks under conditions of limited computing resources. The proposed method can be successfully used in the development of intelligent systems for area monitoring with surveillance cameras, autonomous vehicles control, processing aerial photography results, etc. In the future, it should be considered the possibility of forming a separate sub-network to eliminate blurring in the image and train the network on datasets that contain image samples with different components of rain, which will make the method more «resistant» to different forms of the rain effect and increase the quality of image “cleaning”.","PeriodicalId":43783,"journal":{"name":"Radio Electronics Computer Science Control","volume":"10 1","pages":""},"PeriodicalIF":0.5,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79079411","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 : 2023-06-30DOI: 10.15588/1607-3274-2023-2-8
I. Katerynchuk, A. Babaryka, R. P. Khoptinskiy
Context. The probability of detecting the object by the operator of the video surveillance system depends on a number of parameters (geometric dimensions of the object of observation, distance to the object of observation, parameters of the video surveillance camera, monitor parameters, etc.). Objective. The purpose of the article is to develop an indicator of the effectiveness of detecting dynamic objects when evaluating the functioning of video surveillance systems. Method. An indicator of the effectiveness of object detection when evaluating the functioning of video surveillance systems is proposed. The proposed indicator is expressed in the probability of detection of the object of interest by the i-th operator thanks to the person’s own visual apparatus or with the help of a software algorithm. This indicator differs from the existing ones by taking into account the parameters of the optical system, the parameters of the information display device (monitor), the number of video surveillance cameras, etc. The developed indicator makes it possible to estimate the probability of detection of an object by a video surveillance system operator thanks to a person's own visual apparatus or with the help of a software algorithm, depending on the distance to such an object. Results. According to the results of experimental calculations, it has been proven that the effectiveness of the use of video surveillance systems with the use of video analytics functions (using the example of the dynamic object detection algorithm). Conclusions. The conducted experimental calculations confirmed the efficiency of the proposed mathematical apparatus and allow us to recommend it for use in practice when solving problems of evaluating the effectiveness of the functioning of video surveillance systems.
{"title":"OBJECT DETECTION PERFORMANCE INDICATOR IN VIDEO SUVEILLANCE SYSTEMS","authors":"I. Katerynchuk, A. Babaryka, R. P. Khoptinskiy","doi":"10.15588/1607-3274-2023-2-8","DOIUrl":"https://doi.org/10.15588/1607-3274-2023-2-8","url":null,"abstract":"Context. The probability of detecting the object by the operator of the video surveillance system depends on a number of parameters (geometric dimensions of the object of observation, distance to the object of observation, parameters of the video surveillance camera, monitor parameters, etc.). \u0000Objective. The purpose of the article is to develop an indicator of the effectiveness of detecting dynamic objects when evaluating the functioning of video surveillance systems. \u0000Method. An indicator of the effectiveness of object detection when evaluating the functioning of video surveillance systems is proposed. The proposed indicator is expressed in the probability of detection of the object of interest by the i-th operator thanks to the person’s own visual apparatus or with the help of a software algorithm. This indicator differs from the existing ones by taking into account the parameters of the optical system, the parameters of the information display device (monitor), the number of video surveillance cameras, etc. The developed indicator makes it possible to estimate the probability of detection of an object by a video surveillance system operator thanks to a person's own visual apparatus or with the help of a software algorithm, depending on the distance to such an object. \u0000Results. According to the results of experimental calculations, it has been proven that the effectiveness of the use of video surveillance systems with the use of video analytics functions (using the example of the dynamic object detection algorithm). \u0000Conclusions. The conducted experimental calculations confirmed the efficiency of the proposed mathematical apparatus and allow us to recommend it for use in practice when solving problems of evaluating the effectiveness of the functioning of video surveillance systems.","PeriodicalId":43783,"journal":{"name":"Radio Electronics Computer Science Control","volume":"49 1","pages":""},"PeriodicalIF":0.5,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88491773","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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