Collection of selected papers of the III International Conference on Information Technology and Nanotechnology最新文献_第8页

Network traffic analyzing algorithms on the basis of machine learning methods 基于机器学习方法的网络流量分析算法

Collection of selected papers of the III International Conference on Information Technology and Nanotechnology Pub Date : 2019-01-01 DOI: 10.18287/1613-0073-2019-2416-445-456

R. I. Battalov, A. Nikonov, M. Gayanova, V. V. Berkholts, R. Gayanov

引用次数: 1

Data-driven profiling of traffic flow with varying road conditions 不同路况下的交通流数据驱动分析

Collection of selected papers of the III International Conference on Information Technology and Nanotechnology Pub Date : 2019-01-01 DOI: 10.18287/1613-0073-2019-2416-149-157

O. Golovnin

引用次数: 6

Decision support system in the task of ensuring information security of automated process control systems 决策支持系统中的任务是保证信息安全的自动化过程控制系统

Collection of selected papers of the III International Conference on Information Technology and Nanotechnology Pub Date : 2019-01-01 DOI: 10.18287/1613-0073-2019-2416-477-486

A. Kirillova, V. Vasilyev, A. Nikonov, V. V. Berkholts

引用次数: 0

Using genetic algorithm for generating optimal data sets to automatic testing the program code 采用遗传算法生成最优数据集，对程序代码进行自动测试

Collection of selected papers of the III International Conference on Information Technology and Nanotechnology Pub Date : 2019-01-01 DOI: 10.18287/1613-0073-2019-2416-173-182

K. Serdyukov, T V Avdeenko

引用次数: 3

Industrial application of big data services in digital economy 大数据服务在数字经济中的产业应用

Collection of selected papers of the III International Conference on Information Technology and Nanotechnology Pub Date : 2019-01-01 DOI: 10.18287/1613-0073-2019-2416-409-416

Oleg Surnin, P. Sitnikov, Anastasia Khorina, A. Ivaschenko, A. Stolbova, N. Ilyasova

{"title":"Industrial application of big data services in digital economy","authors":"Oleg Surnin, P. Sitnikov, Anastasia Khorina, A. Ivaschenko, A. Stolbova, N. Ilyasova","doi":"10.18287/1613-0073-2019-2416-409-416","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2416-409-416","url":null,"abstract":"Nowadays, the world is moving to automation. Appropriate programs for the implementation of industrial applications are developed by many companies. But is it so easy to implement systems capable of processing large amounts of information in production? Despite multiple positive results in research and development of Big Data technologies, their practical implementation and use remain challenging. At the same time most prominent trends of digital economy require Big Data analysis in various problem domains. We carried out the analysis of existing data processing works. Based on generalization of theoretical research and a number of real economy projects in this area there is proposed in this paper an architecture of a software development kit that can be used as a solid platform to build industrial applications. Was formed a basic algorithm for processing data from various sources (sensors, corporate systems, etc.). Examples are given for automobile industry with a reference of Industry 4.0 paradigm implementation in practice. The given examples are illustrated by trends graphs and by subject area ontology of the automotive industry.","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":"76033474","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}

引用次数: 6

Optimization of computational complexity of lossy compression algorithms for hyperspectral images 高光谱图像有损压缩算法的计算复杂度优化

Collection of selected papers of the III International Conference on Information Technology and Nanotechnology Pub Date : 2019-01-01 DOI: 10.18287/1613-0073-2019-2391-297-301

L. Lebedev, A. O. Shakhlan

引用次数: 1

Solution for the problem of the parameters identification for autoregressions with multiple roots of characteristic equations 特征方程多根自回归参数辨识问题的求解

Collection of selected papers of the III International Conference on Information Technology and Nanotechnology Pub Date : 2019-01-01 DOI: 10.18287/1613-0073-2019-2391-79-85

N. Andriyanov, M. N. Sluzhivyi

{"title":"Solution for the problem of the parameters identification for autoregressions with multiple roots of characteristic equations","authors":"N. Andriyanov, M. N. Sluzhivyi","doi":"10.18287/1613-0073-2019-2391-79-85","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2391-79-85","url":null,"abstract":"When describing a real image using a mathematical model, the problem of model parameters identification is of importance. In this case the identification itself is easier to perform when a particular type of model is known. In other words, if there is a number of models characterized by different properties, then if there is a correspondence with the type of suitable images, then the model to be used can be determined in advance. Therefore, in this paper, we do not consider the criteria for model selection, but perform the identification of parameters for autoregressive models, including those with multiple roots of characteristic equations. This is due to the fact that the effectiveness of identification is verified by the images generated by this model. However, even using this approach where the model is known, one must first determine the order of the model. In this regard, on the basis of YuleWalker equations, an algorithm for determining the order of the model is investigated, and the optimal parameters of the model are also found. In this case the proposed algorithm can be used when processing real images.","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":"89537449","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}

引用次数: 4

Optimization of the process of 3D visualization of the model of urban environment objects generated on the basis of the attributive information from a digital map 基于数字地图属性信息生成的城市环境对象模型的三维可视化过程优化

Collection of selected papers of the III International Conference on Information Technology and Nanotechnology Pub Date : 2019-01-01 DOI: 10.18287/1613-0073-2019-2416-534-541

M. P. Osipov, O. A. Chekodaev

引用次数: 2

Local approximation of discrete processes by interpolation polynomials 离散过程的插值多项式局部逼近

Collection of selected papers of the III International Conference on Information Technology and Nanotechnology Pub Date : 2019-01-01 DOI: 10.18287/1613-0073-2019-2416-104-110

A. A. Kolpakov, Y. Kropotov

引用次数: 0

Comparative analysis of segmentation algorithms for the allocation of microcalcifications on mammograms 乳房x光片微钙化分割算法的比较分析

Collection of selected papers of the III International Conference on Information Technology and Nanotechnology Pub Date : 2019-01-01 DOI: 10.18287/1613-0073-2019-2391-121-127

Y. Podgornova, S. S. Sadykov

{"title":"Comparative analysis of segmentation algorithms for the allocation of microcalcifications on mammograms","authors":"Y. Podgornova, S. S. Sadykov","doi":"10.18287/1613-0073-2019-2391-121-127","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2391-121-127","url":null,"abstract":"Breast cancer is the most common disease of the current century in the female population of the world. The main task of the research of most scientists is the detection of this pathology at an early stage (the tumor size is less than 7 mm) when a woman can still be helped. An indicator of this disease is the presence of small-point microcalcifications, located in groups within or in the immediate circle of the tumor. Microcalcification is a small-point character at cancer, reminding grains of sand of irregular shape which sizes are from 100 to 600 microns. The probability of breast cancer increases with the increase in the number of microcalcifications per unit area. So, the probability of cancer is 80% if more than 15 microcalcifications on 1 sq. cm. The microcalcifications are often the only sign of breast cancer, therefore, their detection even in the absence of a tumor node could be a harbinger to cancer. Image segmentation is one way to identify microcalcifications. The conducted research allowed us to choose the optimal segmentation algorithms of mammograms to highlight areas of microcalcifications for further analysis of their groups, sizes, and so on.","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":"87160744","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}

引用次数: 7