We consider algorithms of 3D reconstruction for the internal surface of cardiac vessels. The precise reconstruction of vessel geometry is necessary for the creating a hydrodynamic model of blood supply for the heart and computing various parameters of blood flow. To compute a triangulation of blood vessel walls, we use the combination of two methods. At the first stage we apply the 3D seeded region growing algorithm to reconstruct a set of voxels inside vessels. At the second stage we use the isosurface reconstruction algorithm based on the tessellation of 3D space into small tetrahedral cells. We use the tetrahedral mesh, which was proposed in the works of S. Chan, E. Purisima (1998), and V. Skala (2000). Tetrahedra in this mesh are constructed on common faces of adjacent cubes in a cubic lattice, so it fits well with the voxel model. The mesh is constructed only in the neighborhood of the border of voxel set obtained at the first stage as the result of seeded region growing algorithms.

Despite the large number of existing methods of the diagnosis of the brain, brain remains the least studied part of the human body. Electroencephalography (EEG) is one of the most popular methods of studying of brain activity due to its relative cheapness, harmless, and mobility of equipment. While analyzing the EEG data of the brain, the problem of solving of the inverse problem of electroencephalography, the localization of the sources of electrical activity of the brain, arises. This problem can be formulated as follows: according to the signals recorded on the surface of the head, it is necessary to determine the location of sources of these signals in the brain. The purpose of my research is to develop a software system for localization of brain activity sources based on the joint analysis of EEG and sMRI data. There are various approaches to solving of the inverse problem of EEG. To obtain the most exact results, some of them involve the use of data on the individual anatomy of the human head - structural magnetic resonance imaging (sMRI data). In this paper, one of these approaches is supposed to be used - Electromagnetic Spatiotemporal Independent Component Analysis (EMSICA) proposed by A. Tsai. The article describes the main stages of the system, such as preprocessing of the initial data; the calculation of the special matrix of the EMSICA approach, the values of which show the level of activity of a certain part of the brain; visualization of brain activity sources on its three-dimensional model.

The article is devoted to the development of new knowledge generation methods based on the analysis of natural language texts. To extract knowledge from natural language texts, the method of presenting sentences in the form of binary predicates with new constant-situation is used. For the representation of knowledge in a formal form, we use quantifier-free sentences of predicate logic, as well as the OWL DL language. The generation of new knowledge is realized with the help of reasoners, using pre-defined patterns of inference rules. A software system has been developed that allows users to get answers to specific questions related to given natural language texts. The answers are built in a natural language, using not only the knowledge that is explicitly contained in the document being processed, but also the knowledge generated by the reasoners.

Music recommender systems (MRS) help users of music streaming services to find interesting music in the music catalogs. The sparsity problem is an essential problem of MRS research. It refers to the fact that user usually rates only a tiny part of items. As a result, MRS often has not enough data to make a recommendation. To solve the sparsity problem, in this paper, a new approach that uses related items’ ratings is proposed. Hybrid MRS based on this approach is described. It uses tracks, albums, artists, genres normalized ratings along with information about relations between items of different types in the music catalog. The proposed MRS is evaluated and compared to collaborative method for users’ preferences prediction.

The article is devoted to the development of semi-automated methods for integrating knowledge extracted from natural language texts. To solve this problem, we use methods for converting natural language sentences into fragments of atomic diagram of algebraic systems. The knowledge extracted from texts is formalized with atomic sentences of signature consisting of constant symbols, binary predicates and additional situation-constants. We developed methods for integrating knowledge contained in several sentences of natural language, allowing to take their semantic contexts into account.

Nowadays the number of electronic devices has increased as well as their complexity. At the same time only few people are reading user guides for these devices. Moreover, in certain cases even no guides are provided by the manufacturer. Therefore there is a large number of cases when people use such devices incorrectly. This issue could be possibly solved with a system automatically recognizing the type of the device. Such system could provide all necessary user information about that device. This article suggests one of possible implementations of such device type recognition system. It recognizes type of device in an unsupevised way and shows main characteristics and user guides for the recognized gadget. Our approach for constructing such system relies on machine learning methods since greedy search for an object pattern is not efficient, as it was found out by recent scholarly works. Moreover, automatic object patterns classifiers show higher performance in this task and allow to scale the system to various kinds of input data. The algorithms that we are using for object classification are based on feature extraction from an graphical representation of the object look. This representation is usually proposed in an digital photography format. We consider our study as the first work towards automated defining characteristics of a device based on its graphical representation.

The article is devoted to the technique of automated testing of NSUts - automatic assessment system for programming tasks developed at NSU. The main priority for this technique is to test both the old and the new versions of the application, so that the same or minimally modified tests could be executed on two versions of the system with different architectures. This could be useful while organizing the development process for other applications with a long life cycle. To test not only the server but also the client side of the web application, we suggest using tools like Selenium WebDriver to simulate user actions by sending commands to real browsers. We use the well-known Page Object design pattern to handle differences in HTML layout and functionality, and describe a number of ways to make developed tests less fragile and easily adapt those to work with the new version of the system. The article also describes the use of this technique to organize automated testing of the NSUts system and analyzes its effectiveness. The analysis shows that the estimated code coverage by these tests is quite high, and therefore the technique can be considered effective and applied to other similar web applications.

The article is devoted to development of methods of search of information on the Internet. Currently the issue of fast and automatic data extraction from different sources is very actual. The aim of this work is creation of instrument to solve this problem. The idea of the approach is to develop semi-automatic methods of linguistic templates construction for given fragment of atomic diagram. Algorithm of templates construction for the fragment of atomic diagram is performed in 2 stages. On the 1^st stage generation of the simple templates is done, on the 2^nd stage more seldom and complicated templates are found, using templates from 1^st part of algorithm. Processing texts in natural language on the Internet using gotten templates, needed information may be found.

The article provides an overview of projects, technologies, software products developed to implement the ideas of an object-oriented approach to database design. In the 80s of the 20^th century, there were many projects devoted to the idea of OODB, many experts expected that in the near future relational databases would be crowded out with object-oriented ones. Despite the impressive number of projects conducted by both teams of scientists and commercial companies focused on practical implementation, there was no clear formulation of an object-oriented data model, each team presented its own vision of applying object-oriented concepts to database design. The absence of a universal data model, with a well-developed mathematical apparatus (as in the case of relational databases), is still the main problem in the distribution of an OODBMS. However, the use of relational DBMS raises a lot of problems that are most acutely felt in areas such as computer-aided design, computer-aided production, knowledge-based systems, and others. OODB allow to combine the program code and data, to avoid differences between the representations of information in the database and the application program, as a result of which modern developers show interest in them. There are a lot of OODBMS, but they cannot compete with the largest storage organization systems.