Pub Date : 2019-01-01DOI: 10.18287/1613-0073-2019-2391-153-159
V. Nesterov, V. Mukhin, D. Nesterov
Original method of reconstructing the real coordinates of moving objects from their plane images is presented. The method uses multidimensional test objects whose parameters are measures and which are known with high accuracy. In order to ensure the process of measuring movements in real space a test object must be connected with a real object and mathematical models of images of multicomponent movements of a test object must be formed. The parameters of test objects that are used in the named mathematical models are vectors. Such models are used in the construction of systems of measurement equations the solution of which gives the desired components movements of a moving object in 3D space. The method was experimentally tested on specially created stand.
{"title":"Method for reconstructing the real coordinates of an object from its plane image","authors":"V. Nesterov, V. Mukhin, D. Nesterov","doi":"10.18287/1613-0073-2019-2391-153-159","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2391-153-159","url":null,"abstract":"Original method of reconstructing the real coordinates of moving objects from their plane images is presented. The method uses multidimensional test objects whose parameters are measures and which are known with high accuracy. In order to ensure the process of measuring movements in real space a test object must be connected with a real object and mathematical models of images of multicomponent movements of a test object must be formed. The parameters of test objects that are used in the named mathematical models are vectors. Such models are used in the construction of systems of measurement equations the solution of which gives the desired components movements of a moving object in 3D space. The method was experimentally tested on specially created stand.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72979670","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: 10.18287/1613-0073-2019-2416-19-25
V. Klyachkin, D. A. Zhukov, E. Zentsova
Stable functioning of the technical objects is estimated using methods of the statistical process control. However this approach does not always provide the timely detection of violations. It is suggested using machine learning methods for the binary classification of object states (stable or unstable). A program has been developed for calculation in the Matlab environment which allows for analysis of impact of the learning method, classification quality criteria, method of validation set as well as methods of selection of significant indicators on the object’s stable functioning forecast precision. Stable operation of the water treatment management system, stable vibration of the hydraulic unit, machining operation process are taken as examples.
{"title":"Analysis of stable functioning of objects using machine learning","authors":"V. Klyachkin, D. A. Zhukov, E. Zentsova","doi":"10.18287/1613-0073-2019-2416-19-25","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2416-19-25","url":null,"abstract":"Stable functioning of the technical objects is estimated using methods of the statistical process control. However this approach does not always provide the timely detection of violations. It is suggested using machine learning methods for the binary classification of object states (stable or unstable). A program has been developed for calculation in the Matlab environment which allows for analysis of impact of the learning method, classification quality criteria, method of validation set as well as methods of selection of significant indicators on the object’s stable functioning forecast precision. Stable operation of the water treatment management system, stable vibration of the hydraulic unit, machining operation process are taken as examples.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76481364","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: 10.18287/1613-0073-2019-2416-95-103
E. Gladchenko, O. Saprykin, A. Tikhonov
Logistics problems require special attention, because every year they become more complicated and multivariable. On the one hand, a supply chain management includes incessant monitoring of such issues as requests elaboration, paths determination, routing of shipments, multimodal choice, set up of transhipments, fleet choice and maintenance, warehousing, packaging and others. On the other hand, dozens of people are involved in the logistics process. All these moments complicate the decision-making that is why data driven decisions are required nowadays. As well as shipment problems are NP-hard, the heuristic methods should be applied to resolve them. In this article we propose a genetic algorithm to solve the complex problem that consists of the Travelling Salesman Problem combined with the Knapsack Problem. We have developed an urban freight transportation model which is focused on the minimization of the underway time as well as on the maximization of the truck’s loading. A significant contribution in our method is the census of traffic frequency by using traffic zoning. The developed approach has been implemented using the Python programming language in the Zeppelin environment. The first version of the system has been approved in the city of Samara (Russia) with test demand dataset.
{"title":"Optimization of urban freight transportation based on evolutionary modelling","authors":"E. Gladchenko, O. Saprykin, A. Tikhonov","doi":"10.18287/1613-0073-2019-2416-95-103","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2416-95-103","url":null,"abstract":"Logistics problems require special attention, because every year they become more complicated and multivariable. On the one hand, a supply chain management includes incessant monitoring of such issues as requests elaboration, paths determination, routing of shipments, multimodal choice, set up of transhipments, fleet choice and maintenance, warehousing, packaging and others. On the other hand, dozens of people are involved in the logistics process. All these moments complicate the decision-making that is why data driven decisions are required nowadays. As well as shipment problems are NP-hard, the heuristic methods should be applied to resolve them. In this article we propose a genetic algorithm to solve the complex problem that consists of the Travelling Salesman Problem combined with the Knapsack Problem. We have developed an urban freight transportation model which is focused on the minimization of the underway time as well as on the maximization of the truck’s loading. A significant contribution in our method is the census of traffic frequency by using traffic zoning. The developed approach has been implemented using the Python programming language in the Zeppelin environment. The first version of the system has been approved in the city of Samara (Russia) with test demand dataset.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77362166","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: 10.18287/1613-0073-2019-2416-424-431
D. Y. Polukarov, A. P. Bogdan
Modelling large-scale networks requires significant computational resources on a computer that produces a simulation. Moreover, the complexity of the calculations increases nonlinearly with increasing volume of the simulated network. On the other hand, cluster computing has gained considerable popularity recently. The idea of using cluster computing structures for modelling computer networks arises naturally. This paper describes the creation of software which combines an interactive mode of operation, including a graphical user interface for the OMNeT++ environment, with a batch mode of operation more natural to the high-performance cluster, "Sergey Korolev". The architecture of such a solution is developed. An example of using this approach is also given.
{"title":"Using the cluster \"Sergey Korolev\" for modelling computer networks","authors":"D. Y. Polukarov, A. P. Bogdan","doi":"10.18287/1613-0073-2019-2416-424-431","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2416-424-431","url":null,"abstract":"Modelling large-scale networks requires significant computational resources on a computer that produces a simulation. Moreover, the complexity of the calculations increases nonlinearly with increasing volume of the simulated network. On the other hand, cluster computing has gained considerable popularity recently. The idea of using cluster computing structures for modelling computer networks arises naturally. This paper describes the creation of software which combines an interactive mode of operation, including a graphical user interface for the OMNeT++ environment, with a batch mode of operation more natural to the high-performance cluster, \"Sergey Korolev\". The architecture of such a solution is developed. An example of using this approach is also given.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77152913","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: 10.18287/1613-0073-2019-2416-126-133
V. Zakharov, S. Shalagin, B. F. Eminov
The problem of processing images, i. e., two-dimensional data arrays, was solved through implementing two-dimensional fast Fourier transform (FFT) when using single-type hardware modules – IP-cores in the Virtex-6 FPGA architecture. We have shown the possibility of the parallel implementation of each stage in the two-dimensional FFT, based on four “butterfly”-type transforms (BTr) over four elements of the data array being processed. Estimations were obtained regarding time- and hardware complexity of the IPcore implementing BTrs and used in implementing the one-dimensional FFT. The results obtained can be used in estimating hardware and time consumption when performing a twodimensional FFT over an array of the pre-defined dimensionality in using existing and forthcoming distributed programmable-architecture systems.
{"title":"Distributed image processing based on the same IP-cores in FPGA-architecture","authors":"V. Zakharov, S. Shalagin, B. F. Eminov","doi":"10.18287/1613-0073-2019-2416-126-133","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2416-126-133","url":null,"abstract":"The problem of processing images, i. e., two-dimensional data arrays, was solved through implementing two-dimensional fast Fourier transform (FFT) when using single-type hardware modules – IP-cores in the Virtex-6 FPGA architecture. We have shown the possibility of the parallel implementation of each stage in the two-dimensional FFT, based on four “butterfly”-type transforms (BTr) over four elements of the data array being processed. Estimations were obtained regarding time- and hardware complexity of the IPcore implementing BTrs and used in implementing the one-dimensional FFT. The results obtained can be used in estimating hardware and time consumption when performing a twodimensional FFT over an array of the pre-defined dimensionality in using existing and forthcoming distributed programmable-architecture systems.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83589687","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: 10.18287/1613-0073-2019-2416-463-476
R. R. Akhmedyanov, K. F. Tagirova, A. M. Vulfin, V. V. Berkholts, R. Gayanov
The paper discusses the issue of creating an intelligent diagnostic system for welded joints based on the radiographic method. This will speed up the process of decoding radiographic images and reduce the number of errors associated with human factors, since at this time most of the work on decoding images is done manually. The goal of the work is to develop an intelligent system for finding defects in a welded joint in a radiographic image using neural networks. The obtained results are the algorithm of operation of the intelligent diagnostic system for welded joints based on the radiographic method, a trained neural network for detecting defects of welded joints.
{"title":"Data mining algorithms in the task of diagnosing the welded joints quality","authors":"R. R. Akhmedyanov, K. F. Tagirova, A. M. Vulfin, V. V. Berkholts, R. Gayanov","doi":"10.18287/1613-0073-2019-2416-463-476","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2416-463-476","url":null,"abstract":"The paper discusses the issue of creating an intelligent diagnostic system for welded joints based on the radiographic method. This will speed up the process of decoding radiographic images and reduce the number of errors associated with human factors, since at this time most of the work on decoding images is done manually. The goal of the work is to develop an intelligent system for finding defects in a welded joint in a radiographic image using neural networks. The obtained results are the algorithm of operation of the intelligent diagnostic system for welded joints based on the radiographic method, a trained neural network for detecting defects of welded joints.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78265907","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: 10.18287/1613-0073-2019-2416-300-307
D. Stankevich
Orbital angular momentum (OAM) multiplexing is a promising method for MIMO multiplexing strategy. OAM multiplexing has previously been demonstrated for underwater acoustic communication, where data transmission was carried out within a single acoustic beam. Inner-product method is most often used for OAM demultiplexing, but it is sensitive to changes of signal parameters. For example, parameters changes can be associated with wave propagation through heterogeneous medium. I propose and demonstrate an approach using of machine learning methods to increase demultiplexing accuracy to 96% for non-stationary signals. In article presents experimental and numerical investigation results of proposed method.
{"title":"Orbital angular momentum acoustic modes demultiplexing by machine learning methods","authors":"D. Stankevich","doi":"10.18287/1613-0073-2019-2416-300-307","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2416-300-307","url":null,"abstract":"Orbital angular momentum (OAM) multiplexing is a promising method for MIMO multiplexing strategy. OAM multiplexing has previously been demonstrated for underwater acoustic communication, where data transmission was carried out within a single acoustic beam. Inner-product method is most often used for OAM demultiplexing, but it is sensitive to changes of signal parameters. For example, parameters changes can be associated with wave propagation through heterogeneous medium. I propose and demonstrate an approach using of machine learning methods to increase demultiplexing accuracy to 96% for non-stationary signals. In article presents experimental and numerical investigation results of proposed method.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76418716","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: 10.18287/1613-0073-2019-2416-432-444
D. Smuseva, A. Rolich, L. Voskov, I. Malakhov
The paper reviews the current situation of the Augmented Reality and Internet of Things markets. The implementing possibilities of AR for Big Data visualization from IoT devices are considered in this paper. The review and the analysis of methods, tools, products and data system of the visualization are presented. The paper provides an overview of the programs and devices of Augmented Reality, and an overview of development environments. The paper presents the existing classifications of computerized data visualization tools and proposes new classification, which takes into account interactive visualization, the purpose of the tool, the type of software product, the availability of ready-made templates, and other characteristics. The article proposes the architecture of the system for collecting data from IoT endpoint devices based on the Heltec modules. Experiments based on the developed experimental stand were carried out with Heltec devices of both versions to determine the number of losses with increasing distance between the sending device and the receiving device. The results of measuring the power consumption of these devices are presented in two modes: in standby mode and when sending a message to the Heltec endpoint device and in standby mode and when receiving a message for the base station. These studies were conducted using various data transfer protocols (LoRa, Wi-Fi and Bluetooth). The paper presents the result of the development of a digital twin of a university building and the development of augmented reality software for receiving data from real-time data collection devices.
{"title":"Big Data, Internet of Things, Augmented Reality: technology convergence in visualization issues","authors":"D. Smuseva, A. Rolich, L. Voskov, I. Malakhov","doi":"10.18287/1613-0073-2019-2416-432-444","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2416-432-444","url":null,"abstract":"The paper reviews the current situation of the Augmented Reality and Internet of Things markets. The implementing possibilities of AR for Big Data visualization from IoT devices are considered in this paper. The review and the analysis of methods, tools, products and data system of the visualization are presented. The paper provides an overview of the programs and devices of Augmented Reality, and an overview of development environments. The paper presents the existing classifications of computerized data visualization tools and proposes new classification, which takes into account interactive visualization, the purpose of the tool, the type of software product, the availability of ready-made templates, and other characteristics. The article proposes the architecture of the system for collecting data from IoT endpoint devices based on the Heltec modules. Experiments based on the developed experimental stand were carried out with Heltec devices of both versions to determine the number of losses with increasing distance between the sending device and the receiving device. The results of measuring the power consumption of these devices are presented in two modes: in standby mode and when sending a message to the Heltec endpoint device and in standby mode and when receiving a message for the base station. These studies were conducted using various data transfer protocols (LoRa, Wi-Fi and Bluetooth). The paper presents the result of the development of a digital twin of a university building and the development of augmented reality software for receiving data from real-time data collection devices.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83939534","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: 10.18287/1613-0073-2019-2391-72-78
N. Andriyanov, K. Vasiliev
The use of mathematical models allows to compare the theoretical expressions and simulation results. Autoregressive random fields can be used for description of the images, however, such models have pronounced anisotropy, and the simulated images are too sharp. The elimination of this drawback is possible through the use of models with multiple roots of characteristic equations. The analysis shows that using models with multiple roots in filtering images with smoothly varying brightness provides smaller errors than the use of autoregressive random fields. However, studies of the dependences of filtering efficiency on various model parameters and signal-to-noise ratios for multidimensional autoregressive random fields were almost not carried out. The article discusses the solution of the problem of optimal filtering of images based on models with multiple roots of characteristic equations. Theoretical dependences of the relative variance of the filtering error on the dimension of random fields are obtained. Furthermore, it was presented some results of filtering real images by such model in comparison with autoregressive model.
{"title":"Optimal filtering of multidimensional random fields generated by autoregressions with multiple roots of characteristic equations","authors":"N. Andriyanov, K. Vasiliev","doi":"10.18287/1613-0073-2019-2391-72-78","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2391-72-78","url":null,"abstract":"The use of mathematical models allows to compare the theoretical expressions and simulation results. Autoregressive random fields can be used for description of the images, however, such models have pronounced anisotropy, and the simulated images are too sharp. The elimination of this drawback is possible through the use of models with multiple roots of characteristic equations. The analysis shows that using models with multiple roots in filtering images with smoothly varying brightness provides smaller errors than the use of autoregressive random fields. However, studies of the dependences of filtering efficiency on various model parameters and signal-to-noise ratios for multidimensional autoregressive random fields were almost not carried out. The article discusses the solution of the problem of optimal filtering of images based on models with multiple roots of characteristic equations. Theoretical dependences of the relative variance of the filtering error on the dimension of random fields are obtained. Furthermore, it was presented some results of filtering real images by such model in comparison with autoregressive model.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88987128","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: 10.18287/1613-0073-2019-2391-144-152
M. Elantcev, I. Arkhipov, R. Gafarov
The work deals with a method of eliminating the perspective distortion of an image acquired from an unmanned aerial vehicle (UAV) camera in order to transform it to match the parameters of the satellite image. The normalization is performed in one of the two ways. The first variant consists in the calculation of an image transformation matrix based on the camera position and orientation. The second variant is based on matching the current frame with the previous one. The matching results in the shift, rotation, and scale parameters that are used to obtain an initial set of pairs of corresponding keypoints. From this set four pairs are selected to calculate the perspective transformation matrix. This matrix is in turn used to obtain a new set of pairs of corresponding keypoints. The process is repeated while the number of the pairs in the new set exceeds the number in the current one. The accumulated transformation matrix is then multiplied by the transformation matrix obtained during the normalization of the previous frame. The final part presents the results of the method that show that the proposed method can improve the accuracy of the visual navigation system at low computational costs.
{"title":"A method of iterative image normalization for tasks of visual navigation of UAVs","authors":"M. Elantcev, I. Arkhipov, R. Gafarov","doi":"10.18287/1613-0073-2019-2391-144-152","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2391-144-152","url":null,"abstract":"The work deals with a method of eliminating the perspective distortion of an image acquired from an unmanned aerial vehicle (UAV) camera in order to transform it to match the parameters of the satellite image. The normalization is performed in one of the two ways. The first variant consists in the calculation of an image transformation matrix based on the camera position and orientation. The second variant is based on matching the current frame with the previous one. The matching results in the shift, rotation, and scale parameters that are used to obtain an initial set of pairs of corresponding keypoints. From this set four pairs are selected to calculate the perspective transformation matrix. This matrix is in turn used to obtain a new set of pairs of corresponding keypoints. The process is repeated while the number of the pairs in the new set exceeds the number in the current one. The accumulated transformation matrix is then multiplied by the transformation matrix obtained during the normalization of the previous frame. The final part presents the results of the method that show that the proposed method can improve the accuracy of the visual navigation system at low computational costs.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89074292","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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