This article solves the problem of developing a technology for supporting large information storages and organizing delimited user access to this information, which provides a service both for managing these objects and organizing access to these objects. Solving the problem will allow you to create a conceptual model with the allocation of basic entities among information objects and the establishment of relationships between them. It will also allow the development of technical documentation reflecting the results of the first stage of creating an information system: solving problems of syntactic and technical interoperability, developing a single interface, interacting with users, etc. In existing DL developments, as a rule, search and access to information are provided only through visual graphical interfaces. The task of the subsystem for integrating various digital resources is to provide other subsystems with a single interface for access to information stored in the data sources of the system. That is, any resource must be cataloged in a standard way, provided with metadata, access rules, and a unique identifier. To implement search functions outside of graphical interfaces, support for special network services and query languages is required. Ideally, all IS should support a single search profile and a single query language.
<span lang="EN-US">Image processing systems are currently used to solve many applied problems. The article is devoted to the identification of negative factors affecting the growth of grain in different periods of harvesting, using a program implemented in the MATLAB software environment, based on aerial photographs. The program is based on the Law’s textural mask method and successive clustering. This paper presents the algorithm of the program and shows the results of image processing by highlighting the uniformity of the image. To solve the problem, the spectral luminance coefficient (SBC), normalized difference vegetation index (NDVI), Law’s textural mask method, and clustering are used. This approach is general and has great potential for identifying objects and territories with different boundary properties on controlled aerial photographs using groups of images of the same surface taken at different vegetation periods. That is, the applicability of sets of Laws texture masks with original image enhancement for the analysis of experimental data on the identification of pest outbreaks is being investigated.</span>
The purpose of this work is to develop methods, technologies and tools for creating and maintaining intelligent scientific and educational internet resources (ISEIR) based on a service-oriented approach and Semantic Web technologies. The main purpose of ISEIR is to provide meaningful access to scientific and educational information resources of a given field of knowledge and integrated information processing services. According to the preliminary concept, an intelligent scientific and educational internet resource will be an information system accessible via the internet which provides ontology-based systematization and integration of scientific knowledge, data and information resources into a single information space together with a meaningful effective access to them as well as supporting their use in solving various scientific and educational tasks. ISEIR is equipped with an ergonomic web-based user interface and special editors designed to manage the knowledge integrated into it. The proposed approach to the construction of intelligent scientific and educational internet resources is the basis for the developed technology in creating and maintaining information environments for distributed learning.
The article presents an approach to organizing scientific portals based on ontologies. Ontology is the information basis of the Internet portal of knowledge, which should provide integration and systematization of scientific knowledge and information resources of a certain subject, as well as meaningful access to them from any "point" of Internet space. The ontology automatically builds a diagram of the portal's internal database and forms for filling it out, organizes navigation through the portal's information space, and ensures that search queries are formulated in terms of the knowledge portal's subject area. The division of the portal's ontology into subject-independent and subject-specific ontologies makes the portal customizable for almost any field of scientific knowledge. This technology allows declarative adjustment of the ontology during the operation of the knowledge portal, which allows you to track the dynamics of the emergence of new knowledge and information resources on the subject of the portal and thus provides support for its relevance and usefulness.
This <span>article is about methods of analyzing aerial images. Images from Planet.com for crops in North Kazakhstan owned by the Center for Cereal Production and Research. A.I. Barayev. The main goal of the research work is to develop and implement algorithms that allow identifying and distinguishing factors in aerial photographs that adversely affect the growth of plants during the growing season. Spectral brightness coefficient (SBC), normalized difference vegetation index (NDVI), textural features, clustering, and integral transformations are used to solve the problem. Particular attention has been paid to the development of software tools for selecting features that describe textural differences to divide texture regions into subregions. That is weeds, and pests in aerial images. The application of a set of textural features and orthogonal transformations to the analysis of experimental data is explored to identify regions of potentially correlated features in the future. The analysis of the received data made it possible to determine the characteristics of changes in the reflective capacity of agricultural plants and weeds in certain stages of the growing season. The obtained information is of great importance for confirming the observations from space remote from the aerial images.</span>
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