articles
| In the paper requirements are formulated for representation models, algorithms for obtaining, complexing and processing weakly formalized heterogeneous data to build a spatial model of the research object. An approach to aggregation of multispectral data has been developed using the example task of combining visual data from aerial photography and geographic coordinates of objects obtained using unmanned aerial vehicles. An algorithm for combining visual data is proposed based on the recurrent combining of aerial photography images, which includes key point’s detection in the images and building a RANSAC regression model based on these points. An algorithm for comparing geographic coordinates with points of the combined image is also proposed. The algorithm is based on the idea of equivalent transformations over visual data and geographic coordinates of objects. The proposed algorithms are implemented as a software tool, it is tested on several sets of aerial photography data. Prospects for the development of the proposed approach and the shortcomings of its algorithms that need to be eliminated are identified. It has been established that further optimization of memory use when combining aerial photography images and further research in the direction of compensating for perspective distortion are necessary. The applicability of the proposed approach is shown in the problems of obtaining, complexing, processing and visualizing weakly formalized multispectral data in the field of aerial photography of images of various ranges (thermal imaging, optical, etc.), as well as in other areas of data processing and analysis, such as detection and semantic segmentation objects in aerial photography images. Additional spatial information can improve the accuracy of classification and segmentation of objects in images. Continue... | |
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№ 2(110)
26 april 2024 year
Rubric: Software engineering Authors: Puchkov A., Fedulov Y., Nezamaev S. |
The results of a study are presented, the purpose of which was to create an intelligent machine learning system for modeling the processes of charge agglomeration during processing of phosphate ore raw materials. The relevance of the study is justified by the need to improve the information support of technological systems management processes in the context of the digital transformation of the production environment, carried out within the framework of the Fourth Industrial Revolution and characterized by the massive introduction of the industrial Internet of things, which leads to an avalanche-like increase in the volume of technological data. Their processing using modern analysis methods, including artificial intelligence methods, can improve the quality of decisions made and provide competitive advantages. The scientific novelty of the research results is the structure of the proposed hybrid intelligent machine learning system for modeling phosphate ore processing processes, which is based on the joint use of a dynamic model of the sintering process in the Simulink environment and a deep neural network. The architecture of the neural network was developed taking into account the specifics of the mathematical description of the agglomeration process and includes input fully connected layers that receive measurement results of process variables, as well as a recurrent layer that processes the combined sequence from the outputs of fully connected layers. The integration of a Simulink model and a deep neural network makes it possible to quickly adapt an intelligent system to a specific sintering machine through the use of a two-stage machine learning procedure – first on a Simulink simulation model, and then on a real object. Taking into account the significant inertia of the processes accompanying agglomeration, this approach ensures prompt changes in the settings of the hybrid intelligent machine learning system for the new composition of raw materials and technological parameters. A program has been developed that provides a convenient graphical interface for preparing and using an intelligent system, and simulation experiments have shown that the process of additional training for new technological parameters is much faster than initial training while maintaining high accuracy of the obtained modeling results. Continue... |
| The purpose of the presented research is to refine the initial release of the graphical shell for the OpenFOAM package by designing and connecting an additional module focused on numerical experiments using the twoPhaseEulerFoam solver in the field of modeling problems in continuum mechanics. This module, unlike existing analogue applications, has the status of an open source software product, does not require the purchase of maintenance services, and has a Russian-language interface. In the presented software, to simplify further support and modification, the source code of the external part of the application is separated from the code that provides the operating logic. The key original approaches proposed by the author also include a subsystem for serializing design parameters, which allows you to convert the parameters of a design case into json and csv objects and perform the reverse process. This allows the user to switch between different parameter sets for one design case. In addition, it is worth emphasizing the presence in the created software module of a mechanism for checking the completeness of the design case before starting the numerical experiment. Some features of the solver and the principles of its use in preparing calculation cases are considered. The purpose of the study was determined and a list of required tasks was compiled. The selected technology stack is described, as well as development aids. A process diagram is provided to demonstrate how the application works, along with a description of each step. The results of the study were tested using the example of one of the fundamental problems of continuum mechanics and are presented in the form of an updated version of the graphical shell, publicly available on the GitHub resource. Based on the results of the study, the effectiveness of the selected technology stack for achieving development goals was confirmed, and the completed tasks were noted. The practical significance of the results is formulated, expressed in the potential saving of working time for engineers and researchers, minimizing modeling errors and simplifying the process of preparing a design case. Continue... | |
| The speed, precision and recall of information search in e-commerce are critical indicators for business success. A large number of academic studies are aimed at increasing these indicators through more efficient utilization of hardware and the development of machine learning models with new “layers”, training data and loss functions. In this study, the author focused on the practical task of speeding up the search by using knowledge about the nature of the load and data. Widely used Approximate Nearest Neighbors methods use artificial clusters to reduce the processing time of a search query. At the same time, the recall of the list of candidates found worsens. This approach is justified by its universality in relation to data. But in the case of an electronic online trading platform, the data are products and their modalities – name, description, product class, images, which makes it possible to use this knowledge about data to create more effective search structures and algorithms. In conditions of high dynamics of changes in product data, it is also necessary to take into account the speed, accuracy and completeness for offline and online processes. Therefore, the author considered the task of forming the completeness and accuracy of search results within the framework of an end-to-end process, and not only as an retrieval phase. As a result, the author received an improvement in the recall and precision of the retrieved product information by more than 50% without reducing the speed of search query processing. Continue... | |
| The effectiveness of management activities is largely determined by the degree of reasonableness and efficiency of selecting a decision-maker and delegating the necessary powers to him. To solve this problem, it is advisable to use mathematical methods and information technologies that ensure the specified selection in an automated mode. This approach involves the creation of a DSS using unpopulated decision-making technologies. This allows you to identify employees or groups of employees who are most suitable for the implementation of managerial functions in terms of certain quality indicators. The use of unpopulated decision-making technologies in the interests of economic entities makes it possible to reduce the time and cost of their adoption by automating the transit management level. The purpose of the study considered in this article is to solve the problem of organizing the effective selection of a decision maker (DPR), or a group of people, as well as transferring the task to be performed automatically. To achieve this goal, the mathematical modeling of the LPR selection algorithm (LPR group) was carried out by performing operations on sets containing significant indicators and solving a mathematical programming problem. The proposed mathematical apparatus makes it possible to create a subsystem of the DSS responsible for the selection of a DSS (group of DSS) capable of making a high-quality management decision under given constraints, and transferring tasks to it for execution. The specified restrictions contain the type of task to be solved, the possibility of its implementation with the help of unpopulated decision-making technologies, competence limitations of LPR (groups of LPR), time constraints. The DSS subsystem, created on the basis of the proposed mathematical apparatus containing the task of optimizing the selection of LPR (LPR group) according to the cost criterion, makes it possible to minimize the cost of decision-making. Continue... | |
| The current period of technological progress is characterized by a significant penetration of digital technologies into all spheres of life and society. At the moment, a fairly extensive material has been accumulated with the results of research aimed at recognizing the effects, mostly implicit or weakly exposed, which are inherent in digital technologies, as well as to disclose the mechanisms producing them. However, work in which the task of creating a holistic representation would be solved, reflecting the most important effects in their entire entirety, have not yet been published. The article attempted to analyze all the main features of the application of such technologies in an academic environment, closely related to information processes and where the introduction of digital technologies is especially active. In order to summarize theoretically and practically proven strengths of digital technologies, to identify the most successful applications built on their base, to identify negative manifestations and effective steps taken to neutralize threats, a fairly representative set of research results on identifying individual factors and the study of the effects due to them, specific for digital technologies for a certain applied orientation. Based on the basic concepts, taking into account the experience of the implementation of organizational and administrative measures, focused on achieving the most positive effect of the introduction of digital technologies and elimination of sources of undesirable consequences, a set of key objects of comprehensive analysis is proposed, which should precede decision-making to integrate technologies into the practical activities of the academic structures and serve as the basis for the formation of general policy and strategic plan. Continue... |
