Journal Archive

Issue 2 (2024)

System Programming
ANALYSIS OF THE APPLICABILITY AND POTENTIAL USEFULNESS OF USING THE MODEL-VIEW-CONTROLLER-SERVICE PATTERN IN THE DEVELOPMENT OF AUTOMATED SYSTEMS FOR COLLECTING AND PROCESSING DIGITAL REPORTING DOCUMENTS FOR INDUSTRIAL ENTERPRISES
Annotation: The article briefly provides an overview of the main architectural design patterns - Model-View-Controller, Model-View-Presenter, Model-View-ViewModel. The Model-View-Controller-Service design pattern is discussed in more detail. An example of using the Model-View-Controller-Service architectural pattern is given in the context of developing the server part of an automated system for collecting and processing digital reporting documents for industrial enterprises. The main problems of developing automated systems that do not use design patterns are highlighted. An analysis of the applicability and potential usefulness of using the Model-View-Controller-Service pattern in the context of the subject area was carried out and the advantages of use, as well as the positive impact of using this design pattern, were highlighted. Thus, the work reflects the result of the influence of using the Model-View-Controller-Service architectural pattern using the example of developing the server part of an automated system for collecting and processing digital reporting documents for industrial enterprises.
Page numbers: 4-13.
STUDY OF THE INFLUENCE OF THE SEARCH AREA SHAPE ON THE PERFORMANCE OF POPULATION-BASED OPTIMIZATION ALGORITHMS
Annotation: This paper considers population-based optimization algorithms and the dependence of its performance on the geometry of the search area shape in the solution space. A defect inherent in some algorithms is described, due to which, when the search area is disproportionately reduced, the optimization accuracy deteriorates, which is an undesirable effect and makes the use of such algorithms impractical. To detect it, a simple two-step approach is proposed, which uses a one-tailed Mann-Whitney U test and relative characteristics that make it possible to numerically assess the severity of the defect. To validate the proposed approach, more than 150 different population-based optimization algorithms are tested in this paper. The results obtained from the experiments are discussed and analyzed.
Page numbers: 24-31.
SOLUTION TO THE TASK ON RECOGNITION AND INTERPRETATION OF OBJECT IMAGES BASED ON THE MIXED REALITY HEADSET
Annotation: The paper considers the task of recognition and interpretation of object images based on the mixed reality headset Microsoft Hololens 2 in the context of optimization of the process of identification of personal computer components (PCCs). To solve the task, the software tools (ST) with client-server architecture have been developed. The client part of the ST is located on the Microsoft Hololens 2 and is responsible for the graphical interface, generation of the PCC images, as well as sending requests to the server. The server part of the ST contains image annotation module, text description translation module, and also the database module with information about the PCC names, their text descriptions and verification images. The annotation and text translation modules are based on the application of deep learning neural network models such as BLIP and T5, respectively, which are transformer models. The finetuning of the BLIP model is performed on the dataset containing examples from the subject area in the form of pairs "image – annotation": it allowed to form accurate annotations of the PCCs in the process of image recognition. The developed STs can be used to inventorize the PCCs using Microsoft Hololens 2 to optimize the process of their identification, as well as in the training of personnel working with the PCCs.
Page numbers: 42-55.
Methods and means of management in organizational systems
ON ORGANIZATIONAL APPROACHES TO THE PREPARATION, JUSTIFICATION AND CONFIRMATION OF THE RESULTS OF DIGITAL TRANSFORMATION PROJECTS OF MACHINE-BUILDING ENTERPRISES WITH A DISCRETE TYPE OF PRODUCTION
Annotation: Organizational approaches to the preparation and justification of projects for the digital transformation of machine-building enterprises of discrete type production are considered by including additional stages at the predesign stage of projects. Proposals have been formed on the composition of information necessary for making management decisions on the start of projects. The basic basis of this information is the requirements for the digital transformation strategy, a description of the business benefits of individual projects in numerical form and the total costs of their implementation. A three-level organizational structure is proposed as decision-making managers that allows synchronizing the requirements of the enterprise strategy and project goals. Points for applying efforts to adapt organizational culture for the successful implementation of projects and a system of key performance indicators are proposed. Practice-oriented technologies for obtaining confirmation of the results of digital transformation projects are proposed to assess the project's target indicators and take these results into account in subsequent projects.
Page numbers: 14-23.
System analysis, management and information processing
DEVELOPMENT OF A METHODOLOGY FOR EXCTRACTING CHEMICAL REACTION CONDITIONS FROM TEXT WITHIN IMAGE
Annotation: This paper discusses a methodology for extracting key information regarding the conditions of a chemical reaction from unstructured textual data present in illustrations within scientific articles. The proposed methodology aims to expedite the process of acquiring and organizing data on the synthesis of compounds presented in scientific literature. To solve this task, a module was developed that performs text recognition in an image, as well as identification and classification of reaction parameters in the recognized text using neural networks. In order to reduce the amount of labeled data necessary for training a robust text recognition model, an application for generating synthetic images and corresponding labels has been created. For the same purpose a pre-training strategy has been applied for named entities recognition model by utilizing a large publicly available dataset of chemical patents. During training of the text recognition model, input image augmentations were used to simulate various features in the target data, increase the size of the training set, increase its variety, and enhance generalizability of the model. A modified algorithm of BERT embeddings extraction was proposed to incorporate verbal information when using character-level tokenization. After training the models, the module was deployed and tested, performance and resource consumption measurements were performed.
Page numbers: 32-41.
QUALITY INDICATORS OF THE DATA LINEAGE BASED ON STATIC ANALYSIS OF SQL QUERIES
Annotation: When working with big data, it is important to keep track of where the data is coming from in the system. This knowledge helps both in the processes of modifying and expanding the reporting functionality, and contributes to the analysis of calculations in terms of the efficiency of using computing resources. To analyze the origin of data in reporting, a Data Lineage is used. You can generate a data line using a variety of tools, one of the most wellknown tools involves the use of static analysis of SQL queries using the Abstract Syntax Tree (AST) model. Since the data generation line is an oriented acyclic graph, it can be analyzed and used to calculate various indicators. In this paper, we propose a list of indicators that allow us to evaluate the effectiveness of the generated data line. These indicators allow us to evaluate the effectiveness of both the entire data line and individual transformations within it. The proposed indicators make it possible to carry out the calculation optimization process more efficiently and visually.
Page numbers: 56-64.
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