Issue 2 (2024)
System Programming
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.
Keywords: architectural design patterns, Model-View-Controller-Service, automated system architecture, automated
system development
Page numbers: 4-13.
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.
Keywords: numerical optimization, population-based algorithms, test functions, Mann-Whitney U test, unevenness
problem
Page numbers: 24-31.
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.
Keywords: software tools, Microsoft Hololens 2, neural network, transformer, BLIP, T5, dataset, pre-training, fine-tuning,
image annotation, text description translation, personal computer component
Page numbers: 42-55.
Methods and means of management in organizational systems
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.
Keywords: digital transformation, industrial company of a discrete type of production, digital transformation project,
project planning, project justification, confirmation of project outcomes
Page numbers: 14-23.
System Analysis, Control and Information Processing
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.
Keywords: machine learning, deep learning, key information extraction, optical character recognition, named entities
recognition, pre-training, synthetic data
Page numbers: 32-41.
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.
Keywords: Big Data, transformations over big data, static analysis, abstract syntax tree, data lineage, optimization of
computing processes
Page numbers: 56-64.
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