Pub Date : 2019-01-01DOI: 10.18287/1613-0073-2019-2416-43-49
M. Geraskin
The problem of developing tools for the stimulation system of socially optimal actions (volunteering) is considered. Based on the study of the population’s differentiation according to the propensity to an altruism, the game-theoretic model of the social group’s behavior is formed, accounting for the incentives for volunteering. In the cases of the linear decreasing incentive function and the linear cost functions of agents, the Cournot-Nash equilibrium mechanism in the corresponding game is proved. An existence of the equilibrium actions and an impact of incentives on the volunteers’ time distribution are confirmed by the simulation of the volunteers’ behavior in Russia.
{"title":"Game-theoretic model of wide social groups’ behavior with stimulation of volunteering activities","authors":"M. Geraskin","doi":"10.18287/1613-0073-2019-2416-43-49","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2416-43-49","url":null,"abstract":"The problem of developing tools for the stimulation system of socially optimal actions (volunteering) is considered. Based on the study of the population’s differentiation according to the propensity to an altruism, the game-theoretic model of the social group’s behavior is formed, accounting for the incentives for volunteering. In the cases of the linear decreasing incentive function and the linear cost functions of agents, the Cournot-Nash equilibrium mechanism in the corresponding game is proved. An existence of the equilibrium actions and an impact of incentives on the volunteers’ time distribution are confirmed by the simulation of the volunteers’ behavior in Russia.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":"26 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87467082","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 : 2019-01-01DOI: 10.18287/1613-0073-2019-2391-134-143
A. Morozov, O. Sushkova, I. Kershner, A. F. Polupanov
The terahertz video surveillance opens up new unique opportunities in the field of security in public places, as it allows to detect and thus to prevent usage of hidden weapons and other dangerous items. Although the first generation of terahertz video surveillance systems has already been created and is available on the security systems market, it has not yet found wide application. The main reason for this is in that the existing methods for analyzing terahertz images are not capable of providing hidden and fully-automatic recognition of weapons and other dangerous objects and can only be used under the control of a specially trained operator. As a result, the terahertz video surveillance appears to be more expensive and less efficient in comparison with the standard approach based on the organizing security perimeters and manual inspection of the visitors. In the paper, the problem of the development of a method of automatic analysis of the terahertz video images is considered. As a basis for this method, it is proposed to use the semantic fusion of video images obtained using different physical principles, the idea of which is in that the semantic content of one video image is used to control the processing and analysis of another video image. For example, the information about 3D coordinates of the body, arms, and legs of a person can be used for analysis and proper interpretation of color areas observed on a terahertz video image. Special means of the object-oriented logic programming are developed for the implementation of the semantic fusion of the video data, including special built-in classes of the Actor Prolog logic language for acquisition, processing, and analysis of video data in the visible, infrared, and terahertz ranges as well as 3D video data.
{"title":"Development of a Method of Terahertz Intelligent Video Surveillance Based on the Semantic Fusion of Terahertz and 3D Video Images","authors":"A. Morozov, O. Sushkova, I. Kershner, A. F. Polupanov","doi":"10.18287/1613-0073-2019-2391-134-143","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2391-134-143","url":null,"abstract":"The terahertz video surveillance opens up new unique opportunities in the field of security in public places, as it allows to detect and thus to prevent usage of hidden weapons and other dangerous items. Although the first generation of terahertz video surveillance systems has already been created and is available on the security systems market, it has not yet found wide application. The main reason for this is in that the existing methods for analyzing terahertz images are not capable of providing hidden and fully-automatic recognition of weapons and other dangerous objects and can only be used under the control of a specially trained operator. As a result, the terahertz video surveillance appears to be more expensive and less efficient in comparison with the standard approach based on the organizing security perimeters and manual inspection of the visitors. In the paper, the problem of the development of a method of automatic analysis of the terahertz video images is considered. As a basis for this method, it is proposed to use the semantic fusion of video images obtained using different physical principles, the idea of which is in that the semantic content of one video image is used to control the processing and analysis of another video image. For example, the information about 3D coordinates of the body, arms, and legs of a person can be used for analysis and proper interpretation of color areas observed on a terahertz video image. Special means of the object-oriented logic programming are developed for the implementation of the semantic fusion of the video data, including special built-in classes of the Actor Prolog logic language for acquisition, processing, and analysis of video data in the visible, infrared, and terahertz ranges as well as 3D video data.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":"52 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85334863","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 : 2019-01-01DOI: 10.18287/1613-0073-2019-2391-350-357
E. Medvedeva, A. Evdokimova
The authors offer a method for detecting the edges of texture objects in remote sensing images. This method is based on the evaluation of textural and brightness attributes. It is proposed to use transition probabilities for three-dimensional Markov chains with two states as texture features, averaged within a sliding window. It makes possible to improve the detection accuracy of texture objects on multichannel or multi-time snapshots. To reduce the computational resources, it is proposed to determine the signs by the bit planes of the senior, most informative digits of the digital image. The simulation results confirm the effectiveness of the proposed method.
{"title":"Improving the accuracy of detecting the edges of texture objects in remote sensing images","authors":"E. Medvedeva, A. Evdokimova","doi":"10.18287/1613-0073-2019-2391-350-357","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2391-350-357","url":null,"abstract":"The authors offer a method for detecting the edges of texture objects in remote sensing images. This method is based on the evaluation of textural and brightness attributes. It is proposed to use transition probabilities for three-dimensional Markov chains with two states as texture features, averaged within a sliding window. It makes possible to improve the detection accuracy of texture objects on multichannel or multi-time snapshots. To reduce the computational resources, it is proposed to determine the signs by the bit planes of the senior, most informative digits of the digital image. The simulation results confirm the effectiveness of the proposed method.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":"37 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78051573","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 : 2019-01-01DOI: 10.18287/1613-0073-2019-2391-243-249
A. Kovalenko, Y. Demyanenko
This paper describes an approach to solving the problem of finding similar images by visual similarity using neural networks on previously unmarked data. We propose to build special architecture of the neural network - autoencoder, through which high-level features are extracted from images. The search for the nearest elements is realized by the Euclidean metric in the generated feature space, after a preliminary decomposition into two-dimensional space. Proposed approach of generate feature space can be applied to the classification task using pre-clustering.
{"title":"Image clustering by autoencoders","authors":"A. Kovalenko, Y. Demyanenko","doi":"10.18287/1613-0073-2019-2391-243-249","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2391-243-249","url":null,"abstract":"This paper describes an approach to solving the problem of finding similar images by visual similarity using neural networks on previously unmarked data. We propose to build special architecture of the neural network - autoencoder, through which high-level features are extracted from images. The search for the nearest elements is realized by the Euclidean metric in the generated feature space, after a preliminary decomposition into two-dimensional space. Proposed approach of generate feature space can be applied to the classification task using pre-clustering.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88786443","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 : 2019-01-01DOI: 10.18287/1613-0073-2019-2391-97-102
N. Glumov, M. Gashnikov
We consider the compression of multidimensional signals on the aircraft board. We describe the data of such signals as a hypercube, which is "rotated" in a special way. To compress this hypercube, we use a hierarchical compression method. As one of the stages of this method, we use an adaptive interpolation algorithm. The adaptive algorithm automatically switches between different interpolating functions at each signal point. We perform computational experiments in real-world multidimensional signals. Computational experiments confirm that the use of proposed adaptive interpolator allows increasing (up to 31%) the compression ratio of the “rotated” hypercube corresponding to multidimensional hyperspectral signals.
{"title":"Adaptive interpolation of multidimensional signals for compression on board an aircraft","authors":"N. Glumov, M. Gashnikov","doi":"10.18287/1613-0073-2019-2391-97-102","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2391-97-102","url":null,"abstract":"We consider the compression of multidimensional signals on the aircraft board. We describe the data of such signals as a hypercube, which is \"rotated\" in a special way. To compress this hypercube, we use a hierarchical compression method. As one of the stages of this method, we use an adaptive interpolation algorithm. The adaptive algorithm automatically switches between different interpolating functions at each signal point. We perform computational experiments in real-world multidimensional signals. Computational experiments confirm that the use of proposed adaptive interpolator allows increasing (up to 31%) the compression ratio of the “rotated” hypercube corresponding to multidimensional hyperspectral signals.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":"33 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87969173","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 : 2019-01-01DOI: 10.18287/1613-0073-2019-2391-114-120
A. Tashlinskii, A. Zhukova, D. Kraus
Several approaches to the numerical description of image inter-frame geometric deformations parameters estimates behavior at iterations of non-identification relay stochastic gradient estimation are considered. The probability density of the Euclidean mismatch distance of estimates vector is chosen as an argument of the characteristics forming the numerical values. It made it possible to ensure invariance of research to the set of parameters of the used inter-frame geometric deformations model. The mathematical expectation, the probability of exceeding a given threshold value of the convergence rate and the confidence interval of the Euclidean mismatch distance were investigated as characteristics. Probabilistic mathematical modeling is applied to calculate the probability density of the Euclidean mismatch distance.
{"title":"Convergence characteristics at stochastic estimation of image inter-frame deformations","authors":"A. Tashlinskii, A. Zhukova, D. Kraus","doi":"10.18287/1613-0073-2019-2391-114-120","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2391-114-120","url":null,"abstract":"Several approaches to the numerical description of image inter-frame geometric deformations parameters estimates behavior at iterations of non-identification relay stochastic gradient estimation are considered. The probability density of the Euclidean mismatch distance of estimates vector is chosen as an argument of the characteristics forming the numerical values. It made it possible to ensure invariance of research to the set of parameters of the used inter-frame geometric deformations model. The mathematical expectation, the probability of exceeding a given threshold value of the convergence rate and the confidence interval of the Euclidean mismatch distance were investigated as characteristics. Probabilistic mathematical modeling is applied to calculate the probability density of the Euclidean mismatch distance.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":"2400 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86573498","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 : 2019-01-01DOI: 10.18287/1613-0073-2019-2391-285-292
D. Murashov, Y. Obukhov, I. Kershner, M. Sinkin
In this paper, a technique for automated detecting diagnostic events in the video channel of video and electroencephalographic monitoring data is presented. The technique is based on the analysis of the quantitative features of facial expressions in images of video data. The analysis of video sequences is aimed at detecting a group of frames characterized by high activity of frame regions. For detecting the frames, a criterion computed from the optical flow is proposed. The preliminary results of the analysis of real clinical data are presented. The intervals of synchronous muscle and brain activity, which may correspond to an epileptic seizure, are detected. These intervals can be used for diagnosing epileptic seizures and distinguishing them from non-epileptic events. Requirements for video shooting conditions are formulated.
{"title":"A technique for detecting diagnostic events in video channel of synchronous video and electroencephalographic monitoring data","authors":"D. Murashov, Y. Obukhov, I. Kershner, M. Sinkin","doi":"10.18287/1613-0073-2019-2391-285-292","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2391-285-292","url":null,"abstract":"In this paper, a technique for automated detecting diagnostic events in the video channel of video and electroencephalographic monitoring data is presented. The technique is based on the analysis of the quantitative features of facial expressions in images of video data. The analysis of video sequences is aimed at detecting a group of frames characterized by high activity of frame regions. For detecting the frames, a criterion computed from the optical flow is proposed. The preliminary results of the analysis of real clinical data are presented. The intervals of synchronous muscle and brain activity, which may correspond to an epileptic seizure, are detected. These intervals can be used for diagnosing epileptic seizures and distinguishing them from non-epileptic events. Requirements for video shooting conditions are formulated.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":"30 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85111188","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 : 2019-01-01DOI: 10.18287/1613-0073-2019-2416-87-94
M. Bolotov, V. Pechenin, N. V. Ruzanov, D. Balyakin
The quality of aircraft and rocket engines depends primarily on the geometric accuracy of assembly units and parts. Mathematical models implemented in the form of computer models are used to predict quality indicators (in particular, assembly parameters). Direct modeling of the conjugation process using numerical conjugation and finite-element models of assemblies requires significant computational resources and is often accompanied by problems convergence of solutions. In order to solve the above problems, it is possible to use neural network models describing the main regularities of the pairing process based on the accumulated results. The work presents a neural network model for predicting assembly parameters of the parts based on the use of actual surfaces of the parts obtained as a result of mathematical modeling. Assembly on conical surfaces is considered. A convolutional neural network was used to predict assembly parameters.
{"title":"Neural network model in digital prediction of geometric parameters for relative position of the aircraft engine parts","authors":"M. Bolotov, V. Pechenin, N. V. Ruzanov, D. Balyakin","doi":"10.18287/1613-0073-2019-2416-87-94","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2416-87-94","url":null,"abstract":"The quality of aircraft and rocket engines depends primarily on the geometric accuracy of assembly units and parts. Mathematical models implemented in the form of computer models are used to predict quality indicators (in particular, assembly parameters). Direct modeling of the conjugation process using numerical conjugation and finite-element models of assemblies requires significant computational resources and is often accompanied by problems convergence of solutions. In order to solve the above problems, it is possible to use neural network models describing the main regularities of the pairing process based on the accumulated results. The work presents a neural network model for predicting assembly parameters of the parts based on the use of actual surfaces of the parts obtained as a result of mathematical modeling. Assembly on conical surfaces is considered. A convolutional neural network was used to predict assembly parameters.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":"9 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86337640","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 : 2019-01-01DOI: 10.18287/1613-0073-2019-2416-199-203
S. Vostokin, I. Bobyleva
The article discusses the application of the bag of tasks programming model for the problem of sorting a large data array. The choice is determined by the generality of its algorithmic structure with various problems from the field of data analysis including correlation analysis, frequency analysis, and data indexation. The sorting algorithm is a blockby-block sorting, followed by the pairwise merging of the blocks. At the end of the sorting, the data in the blocks form an ordered sequence. The order of sorting and merging tasks is set by a static directed acyclic graph. The sorting algorithm is implemented using MPI library in C ++ language with centralized storing of data blocks on the manager process. A feature of the implementation is the transfer of blocks between the master and the worker MPI processes for each task. Experimental study confirmed the hypothesis that the intensive data exchange resulting from the centralized nature of the bag of task model does not lead to a loss of performance. The data processing model makes it possible to weaken the technical requirements for the software and hardware.
{"title":"Using the bag-of-tasks model with centralized storage for distributed sorting of large data array","authors":"S. Vostokin, I. Bobyleva","doi":"10.18287/1613-0073-2019-2416-199-203","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2416-199-203","url":null,"abstract":"The article discusses the application of the bag of tasks programming model for the problem of sorting a large data array. The choice is determined by the generality of its algorithmic structure with various problems from the field of data analysis including correlation analysis, frequency analysis, and data indexation. The sorting algorithm is a blockby-block sorting, followed by the pairwise merging of the blocks. At the end of the sorting, the data in the blocks form an ordered sequence. The order of sorting and merging tasks is set by a static directed acyclic graph. The sorting algorithm is implemented using MPI library in C ++ language with centralized storing of data blocks on the manager process. A feature of the implementation is the transfer of blocks between the master and the worker MPI processes for each task. Experimental study confirmed the hypothesis that the intensive data exchange resulting from the centralized nature of the bag of task model does not lead to a loss of performance. The data processing model makes it possible to weaken the technical requirements for the software and hardware.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":"210 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76210087","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 : 2019-01-01DOI: 10.18287/1613-0073-2019-2391-326-333
A. V. Goncharova, I. Safonov, I. Romanov
In the paper, we propose an approach for selection a correction parameter for images damaged by backlighting. We consider the photos containing underexposed areas due to backlit conditions. Such areas are dark and have poorly discernible details. The correction parameter controls the level of amplification of local contrast in shadow tones. Besides, the correction parameter can be considered as a quality estimation factor for such photos. For an automatic selection of the correction parameter, we apply regression by supervised machine learning. We propose new features calculated from the co-occurrence matrix for the training of the regression model. We compare the performance of the following techniques: the least square method, support vector machine, random forest, CART, random forest, two shallow neural networks as well as blending and staking of several models. We apply two-stage approach for the collection of a big dataset for training: initial model is trained on a manually labeled dataset containing about two hundred of photos, after that we use the initial model for searching for photos damaged by backlit in social networks having public API. Such approach allowed to collect about 1000 photos in conjunction with their preliminary quality assessments that were corrected by experts if it was necessary. In addition, we investigate an application of several well-known blind quality metrics for the estimation of photos affected by backlit.
{"title":"The regression model for the procedure of correction of photos damaged by backlighting","authors":"A. V. Goncharova, I. Safonov, I. Romanov","doi":"10.18287/1613-0073-2019-2391-326-333","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2391-326-333","url":null,"abstract":"In the paper, we propose an approach for selection a correction parameter for images damaged by backlighting. We consider the photos containing underexposed areas due to backlit conditions. Such areas are dark and have poorly discernible details. The correction parameter controls the level of amplification of local contrast in shadow tones. Besides, the correction parameter can be considered as a quality estimation factor for such photos. For an automatic selection of the correction parameter, we apply regression by supervised machine learning. We propose new features calculated from the co-occurrence matrix for the training of the regression model. We compare the performance of the following techniques: the least square method, support vector machine, random forest, CART, random forest, two shallow neural networks as well as blending and staking of several models. We apply two-stage approach for the collection of a big dataset for training: initial model is trained on a manually labeled dataset containing about two hundred of photos, after that we use the initial model for searching for photos damaged by backlit in social networks having public API. Such approach allowed to collect about 1000 photos in conjunction with their preliminary quality assessments that were corrected by experts if it was necessary. In addition, we investigate an application of several well-known blind quality metrics for the estimation of photos affected by backlit.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":"32 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80039849","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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