Development of a Methodology for the Transition to Information Modeling Technologies in Engineering Surveys (On the Example of Engineering and Environmental Surveys)

Information modeling technology also known as BIM is becoming an important part of working with data in various fields of activity. At the same time, there are still no specific recommendations for the transition to the use of digital models at the survey stage. Although engineering survey data is the basis for further actions within the life cycle of objects. The article characterizes the methodology for the modernization of engineering surveys in the context of information modeling, operating with the methods of systems analysis, foresight research and risk management. The combination of these methods allows you to identify ways of development and characterize them. All changes in the engineering survey system are described using the example of the engineering and environmental section. This is due to the fact that environmental engineering surveys use information from other sections of the survey and show reactions to changes in the system. The authors believe that under existing conditions, the most effective direction is the presentation of the results of engineering surveys in a standard form, provided that they are supplemented with a set of digital models by type of survey. In this case, it is assumed that the role of information modeling will gradually increase.

Cloud Service for Multidimensional Processing of Quantitative Data for Solving Geological

The study describes the developed cloud web service for multidimensional processing of quantitative data for solving a wide class of scientific geological tasks. The computing node “Multidimensional methods of data analysis” provides processing of tabular data using various methods of modern data analysis and allows to set their parameters and visualize the results. The node includes wide range of methods such as data preprocessing, descriptive statistics, cluster analysis, factor analysis, correlation analysis, regression analysis. Computing node “Multidimensional methods of data analysis” is a part of Computational analytical geological environment of State Geological Museum of RAS and is integrated with its services. At the same time, the computing node is an independent cloud web service which implements REST API for interaction with it. This allows a wide range of users to access multidimensional data analysis methods located on a computing node and provides capabilities of its integration into information systems as a thirdparty application for processing tabular data.

Development of Software for Control of Virtual Objects Using Event-Related Potential P300

The article considers the principle of operation of brain-computer interfaces (BCI) and a method for detecting the focus of a person's attention using event-related potential (P300). The review of the existing hardware and software solutions for the implementation of BCIs was performed including the identification of their advantages and disadvantages. The program that allows you to choose the desired stimulus from a variety of presented was developed.An electroencephalograph of the BiTronics Lab company on the Arduino platform was used to receive the signal. Signal filtering, classifier training and visualization are implemented in Python.

New End-Stopped Complex Cell Model Applicable in Convolutional Neural Networks

This article is dedicated to modeling the end-stopped neuron. This type of neuron gives the maximum response at the end of the line and is used to refine the edge. The article provides an overview of different models of end-stopped neurons. I have proposed a simpler and more accurate model of an end-stopped neuron based on the use of Gabor filters in antiphase. For this purpose, the models of simple and complex cells whose output is used in the proposed model are also described. Simple cells are based on the use of a Gabor filter, the parameters of which are also described in this article. The proposed model has shown its effectiveness.

Gamification of Applied Technical Disciplines

Three forms of interaction between teacher and students, which have become widespread, are described. The main purpose of the work is to study the fundamental differences between games and gamification in order to identify and modify the most effective methods for introducing active learning elements in the educational process. After decomposition of games and gamification, the following features of activities were revealed. Already at this stage, differences are noticeable between the goals of games where you need to win, and gamification – to learn. It is shown that the selection of optimal game mechanics, to improve the learning process, was carried out according to subjective criteria, and the result according to objective – academic performance, aimed at students of technical specialties. Thus, repeated studies for groups of other specialties can give different, but no less interesting situations. It was found that the use of game scenarios during a laboratory practice objectively increases academic performance, thereby increasing the formation of skills and abilities of professional competencies.

Paper2vec and Cite2vec Methods for Analyzing Collections of Scientific Publications

Visualizations are used to better understand collections of scientific publications. Various methods of analyzing text collections can be used to build these visualizations. This article discusses two methods Paper2vec and Cite2vec that get vector representations of documents using citation information. To demonstrate a work of these techniques and an example of their application, visualizations were developed, which are described in this paper.

Semantic Image Segmentation in Duckietown

The article is devoted to evaluation of the applicability of existing semantic segmentation algorithms for the “Duckietown” simulator. The article explores classical semantic segmentation algorithms as well as ones based on neural networks. We also examined machine learning frameworks, taking into account all the limitations of the “Duckietown” simulator. According to the research results, we selected neural network algorithms based on U-Net, SegNet, DeepLab-v3, FC-DenceNet and PSPNet networks to solve the segmentation problem in the “Duckietown” project. U-Net and SegNet have been tested on the “Duckietown” simulator.

Building Service Compositions Based on data on Use of Services by Users

The automatic service composition is discussed in the article. The method is proposed for building the service composition based on the processing of statistical data on individual applying services (tasks) by users. The method is based on linking tasks to each other, determining data dependencies, parameters of services whose values are rigidly set by the composition of services, and parameters whose values can be changed by the user are highlighted. Service compositions are built in the form of a directed graph of DAG. The methods have been developed for reducing the set of obtained service compositions, which allow us to highlight useful ones and rank them by degree of use. In particular, equivalent service compositions based on isomorphism of DAG graphs are determined, trivial ones are discarded, and only compositions that lead to the published result are left behind.

Twitter Data Import Models

In this paper, the authors describe an algorithm for importing data from the social network Twitter and building weighted social graphs. To import data, the given posts are taken as a basis, users who have had any of the recorded interactions with them are downloaded. Further, the algorithm focuses on the given configuration and uses it to calculate the weights on the edges of the resulting graph. The configuration takes into account the type of user interaction with each other. The authors introduce the concept of (F, L, C, R)-model of information interaction.The authors describe the developed algorithm and implemented software for constructing weighted graphs. The paper shows the application of the algorithm and three models on the example of both a single post and a series of posts.

The Method of Cyber Awareness Analysis of an Energy Facility

The article proposes to analyze cyber-situational awareness of an energy facility in three stages. There are i) analysis of cyber threats to the energy infrastructure; ii) modeling of extreme situations scenarios in the energy sector caused by the implementation of the cyber threats; iii) risk assessment of the cybersecurity disruption to energy infrastructure. Three methods are presented, corresponding to each stage. The authors propose to apply semantic modeling methods to analyze the impact of cyber threats to energy facilities, taking into account energy security within the presented approach. Such methods show their effectiveness in the absence or incompleteness of data for modeling the behavior of systems, which defies formal description or accurate forecasting. The presented approach to the cyber situational awareness analysis of energy facilities considered as a synthesis of cybersecurity and situational awareness studies, characterized by the use of semantic modeling methods.