Separate Blocks Research Articles

КОМПЛЕКСНАЯ МЕТОДИКА ОПТИМИЗАЦИИ АГРОПРОИЗВОДСТВЕННОГО КЛАСТЕРА АДМИНИСТРАТИВНЫХ РАЙОНОВ РЕСПУБЛИКИ БЕЛАРУСЬ

Ensuring the growth of the economy of Belarus provides for sustainable socio-economic development of admin-istrative districts, which significantly increases the level of income and quality of lifeof the population. The main trigger for the development of administrative districts is the increase in the eco-nomic efficiency of the functioning of their agro-production cluster, which consists of agricultural organizations and food and light industry processing enterprises. As a re-sult of the research, a comprehensive methodology for optimizing the agro-production cluster of administrative districts has been developed, including a three-level economic and mathematical model in which all agricultural organizations, on-farm production units and processing enterprises are represented as separate blocks, including components in the form of restrictions of the main and connecting blocks. The objective function of the model is designed to determine the max-imumgross value added. The model was tested on the example of the agro-industrial cluster of the Gorkiadministrative district of the Mogilev region of the Republic of Belarus(hereinafter –Gorki district), which includes 8 agricultural organi-zations and a milk processing enterprise, the butter and cheese plant OJSC Molochny Gorki. During the calculations, the substantiation of the prospective crop yields and annual livestock productivity in the farms of the Gorki district was per-formed using correlation models. The optimal number of livestock and sown areas of commercial crops have been calcu-lated. The reserves for the growth of production volumes and economic efficiency of the functioning of the agro-production cluster and the Gorki district have been determined.

Methodological principles of the construction of a linear megapolis “Street of the World” around the globe

The article is based on an architectural concept that was developed at the St. Petersburg State University of Architecture and Civil Engineering at the Department of Architectural Design, in the architectural studio “ANESTIKA”. The main objectives of this experiment are related to the issues of a conceptual idea creation, its development and implementation in the developed intellectual architectural concept. A volumetric-spatial model of the fragmentary structure of the Street of the World was completed as a result of the work. The model presented the developed compositional solutions in the form of separate functional blocks and zones. They were united by a common three-dimensional structural frame of the supporting structures in the form of a linear habitable bridge. It is an architectural manifesto in which “Street of the World” represents a great intellectual international infinite linear megapolis formed by an environmental space without borders around the entire globe. It is based on the unification of the world space around a unified unique grandiose architectural object. The endless street is built for all the states of the globe.

WRA-Net: Wide Receptive Field Attention Network for Motion Deblurring in Crop and Weed Image.

Automatically segmenting crops and weeds in the image input from cameras accurately is essential in various agricultural technology fields, such as herbicide spraying by farming robots based on crop and weed segmentation information. However, crop and weed images taken with a camera have motion blur due to various causes (e.g., vibration or shaking of a camera on farming robots, shaking of crops and weeds), which reduces the accuracy of crop and weed segmentation. Therefore, robust crop and weed segmentation for motion-blurred images is essential. However, previous crop and weed segmentation studies were performed without considering motion-blurred images. To solve this problem, this study proposed a new motion-blur image restoration method based on a wide receptive field attention network (WRA-Net), based on which we investigated improving crop and weed segmentation accuracy in motion-blurred images. WRA-Net comprises a main block called a lite wide receptive field attention residual block, which comprises modified depthwise separable convolutional blocks, an attention gate, and a learnable skip connection. We conducted experiments using the proposed method with 3 open databases: BoniRob, crop/weed field image, and rice seedling and weed datasets. According to the results, the crop and weed segmentation accuracy based on mean intersection over union was 0.7444, 0.7741, and 0.7149, respectively, demonstrating that this method outperformed the state-of-the-art methods.

СОДЕРЖАТЕЛЬНО-ТЕХНОЛОГИЧЕСКОЕ ОБЕСПЕЧЕНИЕ ФОРМИРОВАНИЯ МОДЕЛИ ЭТИКО-ДЕОНТОЛОГИЧЕСКОЙ КОМПЕТЕНТНОСТИ БУДУЩИХ ПЕДАГОГОВ

Generalization of the theoretical foundations of the modeling process made it possible to develop a structural and functional model for the formation of ethical and deontological competence of future teachers in the process of studying at a university. The authors substantiate the components of the structural and functional model of the formation of ethical and deontological competence of future teachers. When developing the model, the authors proceeded from a structural and functional approach and sought to ensure that all components of this model had access to the content and technological support of the process of forming the ethical and deontological competence of students - future teachers. A separate structural block of this model defines the conditions for the formation of ethical and deontological competence. Such conditions include: planning and organization of social and educational work in universities, taking into account basic ethical and deontological categories; introduction of various interactive forms of social and educational work with students; orientation of communicative interaction of subjects of social and educational work on the formation of ethical and deontological competence of students. In this regard, this article details the content of the formative work by generalizing the theoretical and methodological foundations of the process of forming the ethical and deontological competence of future teachers.

An Efficient Lightweight Generative Adversarial Network for Compressed Sensing Magnetic Resonance Imaging Reconstruction

Compressed-sensing-based magnetic resonance imaging (CS-MRI) methods can significantly shorten scanning time while ensuring reconstructed image quality. Recently, deep learning methods, particularly generative adversarial networks (GAN), have been introduced into CS-MRI. However, these GAN-based methods suffer from their heavy learning parameters and ignore long-range dependency, which degrades the reconstructed image quality. Thus, the objective of this study is to design an efficient lightweight GAN to achieve more accurate MRI reconstruction. The proposed framework, named SepGAN, utilises depthwise separable convolution as the basic component to reduce the number of learning parameters. Two modules, the dilated depthwise separable convolution dense block and a squeeze-and-excitation lightweight self-attention module were proposed to extract the long-range dependency and improve the representational ability. The focal frequency loss was also involved in assisting the model to focus on high-frequency information. To evaluate the performance of the three proposed methods and SepGAN, two brain datasets were used in our experiment. From the results of our comparison analysis, SepGAN possesses the minimum number of parameters and multiply–accumulate operations (i.e., 7.32 M and 13.62G) and outperforms other methods in a variety of evaluation metrics, especially in Frechet inception distance, proving that reconstructed images of our method have better visual effects. For unseen pathological data, SepGAN can also perform effective reconstruction with explicit tumour textures and boundaries. The experimental results demonstrate that SepGAN can reconstruct high quality images with fewer parameters and exhibit remarkable generalisation ability.

CATEGORY OF POLITENESS IN RUSSIAN AND GERMAN BUSINESS CORRESPONDENCE

Politeness is an integral part of any communication — it acts as a regulator of the communicative process in different spheres of human activity. This category is particularly significant in the official communication, where careful selection of language means is necessary. The actual study of politeness in the official and business communication styles is presented in a contrastive aspect, comparing national-cultural peculiarities of politeness in different countries. Therefore, the novelty of this article lies in the comparative analysis of business letters in German and Russian and in the study of the means of politeness expression in separate communicative blocks as well. This study is structured considering modern trends in the development of conventional norms of official communication, the processes of their personalization, democratization, dialogization and individualization. The textbooks on business correspondence published in Germany and Russia are used as material. In addition, this article uses contextual and semantic analysis. The authors for the first time resort to the method of rubricating business letters into communicative blocks, identifying verbal means of politeness expression. As a result, differences between the analyzed types of German and Russian business letters were identified not only in the manifestation of the above-mentioned trends, but also in the representation of politeness expression in each of the communicative blocks. The results reveal socio-cultural specificity of these texts in German and Russian correspondence, which allows us to use them in teaching native and foreign language for business communication, as well as in the process of teaching translation.

РЕПУТАЦИЯ В ГОСУДАРСТВЕННЫХ ЗАКУПКАХ: ОСОБЕННОСТИ РЕГУЛИРОВАНИЯ, КЛЮЧЕВЫЕ ИНДИКАТОРЫ И ОЦЕНКИ ЭФФЕКТИВНОСТИ

The article presents a literature review on reputation factor in public procurement. Reputation is one of the tools for solving the principal-agent problem, which is typical for contractual relations. In line with the spread of New Public Management theory in public procurement, alternative methods of supplier selection are being developed, in particular, based on suppliers’ reputation. In contrast to the private sector, public buyers’ ability to consider reputation when choosing a supplier is highly regulated. It is shown that in the world practice of public procurement the reputation of suppliers is considered to varying degrees, there is no single approach to indicators, mechanisms for providing information and procedural aspects. Therefore, it is timely to analyse the arguments for and against expanding the possibilities of reputational considerations in public procurement. To answer this question, a separate block focuses on the effects of reputational considerations in public procurement in terms of barriers to entry, public procurement efficiency, and building trust between procurers and suppliers. Conclusions about the positive effects of reputational considerations are of interest to procurers who decide on the choice of supplier evaluation criteria. Relevant aspects of reputational considerations for Russian regulation concerning reputation indicators and mechanisms for providing information are identified. The article differs from existing reviews on the topic of reputation by focusing on the specificity of public procurement. An original classification of sources is presented in accordance with the following parameters: definitions and indicators of reputation, possibilities and limitations of reputational considerations and their effects in public procurement. Poorly studied aspects of interest for further research are identified.

Separable Convolution Network With Dual-Stream Pyramid Enhanced Strategy for Speech Steganalysis

Steganography based on fixed codebook has become one of the most important branches of speech steganography due to its high imperceptibility and having the largest available carrier space. As its countermeasure technique, this paper presents a novel steganalysis method based on separable convolution network (SepSteNet) with dual-stream pyramid enhanced strategy (DPES). Specifically, to better acquire discriminative representations, we design the pulse-aware separable block to capture the pulse correspondence along independent levels of pulse positions, where the pulse-aware excitation module is plugged to avoid noisy clue accumulation by adaptively emphasizing the salient part. Moreover, the global attending block is introduced to enhance correspondence features through calculating global responses at distinct subframes. In addition, to eliminate the negative impact of sample content, DPES is leveraged to incorporate cross-domain coherence features by the inverted connected dual-stream branches. With the original and calibration speech samples, two branches enable the correspondence of two detection feature domains to interact with each other to generate coherence features independent of sample content, thereby improving the detection performance. The performance of the presented method is comprehensively evaluated and compared with the state of the arts. The experimental results demonstrate that the presented method significantly outperforms the existing ones. Furthermore, DPES is shown to be a general enhancement strategy that can effectively improve the performance of the existing deep neural network for speech steganalysis. The source code for this work will be publicly available on GitHub.

COMPLEX METHOD FOR AUTOMATIC RECOGNITION OF NATURAL LANGUAGE AND EMOTIONAL STATE

Current trends in NLP emphasize universal models and learning from pre-trained models. This article explores these trends and advanced models of pre-service learning. Inputs are converted into words or contextual embeddings that serve as inputs to encoders and decoders. The corpus of the author's publications over the past six years is used as the object of the research. The main methods of research are the analysis of scientific literature, prototyping, and experimental use of systems in the direction of research. Speech recognition players are divided into players with huge computing resources for whom training on large unlabeled data is a common procedure and players who are focused on training small local speech recognition models on pre-labeled audio data due to a lack of resources. Approaches and frameworks for working with unlabeled data and limited computing resources are almost not present, and methods based on iterative training are not developed and require scientific efforts for development. The research aims to develop methods of iterative training on unlabeled audio data to obtain productively ready speech recognition models with greater accuracy and limited resources. A separate block proposes methods of data preparation for use in training speech recognition systems and a pipeline for automatic training of speech recognition systems using pseudo marking of audio data. The prototype and solution of a real business problem of emotion detection demonstrate the capabilities and limitations of owl recognition systems and emotional states. With the use of the proposed methods of pseudo-labeling, it is possible to obtain recognition accuracy close to the market leaders without significant investment in computing resources, and for languages with a small amount of open data, it can even be surpassed.

Impact of cerebellar beta entrainment using non-invasive brain stimulation: Insights from an ongoing rhythmic TMS—EEG study in healthy human participants

Abstract Oscillations play a pivotal role in shaping cerebellar local activity and its communication with neocortical areas involved in learning motor skills. Previous studies have emphasized the presence and the potentially important role of beta (15-30 Hz) cerebellar oscillations in such processes. Yet, the distribution and causal nature of local and interregional synchronization patterns at such frequencies remain elusive. The present study aims to better understand the functional mechanisms by which the cerebellum synchronizes with widespread cortical regions. This will pave the way to identify and better modulate the specific electrophysiological properties of these networks. To this end, we sought to entrain beta frequency cerebellar oscillations with transcranial magnetic stimulation (TMS) and to characterize the cerebello-cortical synchronization patterns in the sensory-motor networks. A cohort of 20 healthy adult participants received trial-by-trial blocks of 4-pulses bursts of either rhythmic (20 Hz, experimental condition) or arrhythmic (control condition) TMS delivered over the right cerebellum, while EEG was also recorded. The stimulation of a right occipital/parietal cortical site performed in separate blocks served to assess the specificity of cerebellar stimulation. After cleaning and pre-processing, we computed and averaged the power and the inter-trial coherence of EEG signals elicited by TMS in frontal, central and parietal areas. Current interim analyses support the tolerability and feasibility of cerebellar TMS—EEG recordings, and our ability to assess signs of beta-induced entrainment while ruling out unspecific effects (artifacts triggered by the TMS clicking-sound, scalp-tapping, etc). This is the first study overcoming the limitations of ‘offline’ repetitive TMS approaches assessing effective connectivity between cerebellar and cerebral systems using TMS—EEG approaches. The outcome of this study will characterize the neurophysiological properties of cerebello-cortical communication based on frequency-specific synchronization mechanisms, which would ultimately influence learning processes. Research Category and Technology and Methods Basic Research: 10. Transcranial Magnetic Stimulation (TMS) Keywords: Cerebellum, Oscillations, Entrainment, TMS-EEG

Socіo-Economіc and Educatіonal Veteran Reіntegratіon to the Labor Market: Ukraіnіan Context

The war started by russіa іn Ukraіne has been goіng on for more than 8 years, thousands of Ukraіnіans have become combat veterans. A long and dіffіcult process of reіntegratіon and return to cіvіlіan lіfe іs awaіtіng for them. A component of the reіntegratіon process іs the transіtіon from a mіlіtary career to a professіonal career. The post-war reconstructіon of the country wіll lead to an іncrease іn the demand for labor. War veterans are the potentіal for the reproductіon of the labor force and an іmportant factor іn ensurіng supply іn the market. The purpose of the artіcle іs to substantіate the basіc prіncіples and program dіrectіons of the reіntegratіon of war veterans іnto the labor market based on the analysіs of foreіgn practіces takіng іnto account the Ukraіnіan context. The artіcle analyzes the natіonal experіence of veteran reіntegratіon іn the fіeld of employment based on the results of a survey conducted by natіonal and іnternatіonal organіzatіons. Foreіgn practіces of supportіng the transіtіon of veterans from mіlіtary servіce to a professіonal career are studіed, and obstacles on the way to the labor market transіtіon are analyzed. The basіc prіncіples of the polіcy of supportіng veterans on the way to the transіtіon to the labor market and professіonal growth are substantіated, іn partіcular, the formatіon of a structured system of reіntegratіon wіth buіlt-іn dіgіtal іnfrastructure. Emphasіs іs placed on a separate block of support for female veterans as a separate category wіth advocacy of theіr needs and іnterests. Attentіon іs paіd to the dіrectіon of professіonal іntegratіon through the acquіsіtіon of hіgher, professіonal pre-hіgher and professіonal educatіon. The maіn program dіrectіons for veteran reіntegratіon іnto the labor market are іdentіfіed. They іnclude professіonal orіentatіon, advanced traіnіng and retraіnіng, assіstance іn employment, expandіng the іnclusіon of the natіonal labor market, advіsory support on establіshіng a busіness. Іndustry 5.0 іs substantіated to be the background for veterans support programs on the way to the transіtіon to the labor market.

Attentional tuning of valent word forms

Using event-related brain potentials (ERPs), we tested the hypothesis of valent word forms (Kissler et al., 2006, Prog Brain Res) stating that the mere visual shapes of emotional words acquire valence through numerous co-occurrences with affective activation over an experienced reader's life. Thereby, associations between neuronal representations of visual word forms and affect are strengthened. If so, selective attention to a specific level of the valence of single visual words should not only pre-activate neuronal representations of that level of valence, but this activation should also spread to the associated word forms. This should improve their processing and/or affective discrimination. In a valence-detection task, N = 53 participants made speeded responses only to words of the current target level of valence (negative, neutral, or positive), which varied across separate blocks. We focused on posterior visual P1 and N170 components, two well-established ERP markers of low-level and structural word form processing, respectively. P1 increased from negative over neutral to positive words; this effect was stronger in target compared to nontarget words. N170 was larger for emotional compared to neutral target words, whereas nontarget words showed a strong reverse pattern. The P1 effect for target words and the N170 effect for nontarget words both were driven by good task performers in terms of fast hit responses. Results support the idea of valent word forms that can be tuned by selective attention to valence, which implies both, facilitated affective discrimination and processing of target words, and inhibition of the processing of nontarget words.

Uncertainty quantification of two-phase flow in porous media via the Coupled-TgNN surrogate model

The uncertainty quantification (UQ) of subsurface two-phase flow usually requires numerous executions of forward simulations under varying conditions. In this work, a novel coupled theory-guided neural network (TgNN) based surrogate model is built to facilitate computation efficiency under the premise of satisfactory accuracy. The core notion of this proposed method is to bridge two separate blocks on top of an overall network. They underlie the TgNN model in a coupled form, which reflects the coupling nature of pressure and water saturation in the two-phase flow equation. The TgNN model not only relies on labeled data, but also incorporates underlying scientific theory and experiential rules (e.g., governing equations, stochastic parameter fields, boundary and initial conditions, well conditions, and expert knowledge) as additional components into the loss function. The performance of the TgNN-based surrogate model for two-phase flow problems is tested by different numbers of labeled data and collocation points, as well as the existence of data noise. The proposed TgNN-based surrogate model offers an effective way to solve the coupled nonlinear two-phase flow problem, and shows good accuracy and strong robustness when compared with the purely data-driven surrogate model. By combining the accurate TgNN-based surrogate model with the Monte Carlo method, UQ tasks can be performed at a minimum cost to evaluate statistical quantities. Since the heterogeneity of the random fields strongly impacts the results of the surrogate model, corresponding variance and correlation length are added to the input of the neural network to maintain its predictive capacity. In addition, several more complicated scenarios are also considered, including dynamically changing well conditions and dynamically changing variance of random fields. The results show that the TgNN-based surrogate model exhibits satisfactory accuracy, stability, and efficiency in the UQ problem of subsurface two-phase flow.

Legal Regulation of Environmental Protection during Armed Conflicts on the Example of Ukraine

The article analyzes the impact of military operations on the state of ecosystems and individual natural resources in Ukraine. Based on the analysis of Ukrainian and foreign sources, it was made a conclusion about the catastrophic damage to the environment caused by the military aggression of the Russian Federation. In particular, the environmental damage as of September 2022 is estimated at almost 1 trillion hryvnias and continues to grow daily.
 Taking into account the fact that the impact on the environment during armed conflicts almost always has a transboundary nature, author analyzed the provisions of international acts that regulate this problem. These are the Stockholm Declaration (1972); the World Charter of Nature; the Rio Declaration on Environment and Development (1992); the Convention on the Prohibition of Military or Any Other Hostile Use of Environmental Modification Techniques; Protocol Additional to the Geneva Conventions of 12 August 1949, and relating to the Protection of Victims of International Armed Conflicts; Convention on the prohibition of the development, production, stockpiling and use of chemical weapons and on their destruction. It was established that all the mentioned documents call on the international community to take measures for preventing or minimizing the destructive impact on the environment during military operations.
 The author paid particular attention to Ukrainian legislation. The Instruction on the Procedure for Implementing the Norms of International Humanitarian Law in the Armed Forces of Ukraine requires following the provisions of international humanitarian law, including, in the context of environmental protection. In the Basic Principles (Strategy) of the State Environmental Policy of Ukraine for the Period Until 2030, it is noted that it is absolutely necessary to solve the issue of access to the objects of the military-defense industrial complex in order to carry out appropriate supervision and control over compliance with environmental legislation at these objects. A separate block of normative acts is devoted to the legal regulation of the procedure and methods of determining damage and losses caused to the environment of Ukraine as a result of the armed aggression of the Russian Federation.
 Despite the fact that the war continues, the development of normative acts aimed at regulating the reconstruction of destroyed or damaged territories and objects is already being observed. The author analyzed some of them, identified shortcomings and proposed ways to eliminate them.

Analog Compatible Logic Functions Using EXCCIIs and an Extended Application for Sigmoid Activation Function

This paper introduces the use of an extra X current conveyor (EXCCII) for realizing logic operations, suited for mixed signal design, without necessitating separate digital blocks. The NOR and OR logic functions are thus shown to be realized using the current-mode analog building block operable at a low voltage. The use of [Formula: see text][Formula: see text]V supply makes the new circuits operable at low voltage. The EXCCII bias current used in the design is 25[Formula: see text][Formula: see text]A. The input currents for defining logic 0 and logic 1 are, respectively, taken as 0[Formula: see text]mA and 0.5[Formula: see text]mA. The proposed circuits’ delay is found to be 10[Formula: see text]ns for low-to-high transition, while 2[Formula: see text]ns for high-to-low transition for NOR gate under capacitive loading conditions. The use of the current-mode approach makes the new proposed circuit apt for current-mode signal processing. The new proposed logic function circuits are compatible with analog circuits, thus providing an easy merger for mixed signal systems design, paving the way to a modular design approach. As an extended application in artificial neural networks, the proposed circuit is shown to generate a sigmoid activation function with convincing results. Several results are included by varying the reference current, and the circuit’s robustness aspect is also tested in the presence of fluctuation in the bias current of EXCCII. The novel approach of utilizing an analog building block for realizing digital functions is, therefore, verified with promising future applications.

Theoretical and methodological principles of the personnel potential management system

Methods. The results were obtained through the application of the following methods: typology – when forming the components of the assessment of the personnel potential of the enterprise; classifications – when separating ways and methods of assessing personnel potential; classification – when describing separate methodological evaluation algorithms, graphic – when creating a system for researching the personnel potential of the enterprise. Results. The main groups of methods and measures for evaluating the personnel potential of the enterprise are highlighted. The method of calculating economic and statistical indicators, which are fundamental in the system of personnel potential research, is revealed in detail. The evaluation toolkit is summarized and the essence of each of the methods used in it is explained in detail. The theoretical and practical foundations of personnel audit have been revealed and the algorithm of its conduct has been improved to a great extent. Novelty. In the course of the research, the authors created a single and universal system for researching the personnel potential of the enterprise, which contains the necessary stages of its assessment, tools that are basic in the process of analyzing the personnel potential, as well as a separate block with the calculation method of each tool. The essence, advantages, and disadvantages of the most common and commonly used methods of assessing personnel potential are revealed. During the study of the «personnel audit» category, the mechanism for conducting it was improved to a large extent. A general scheme of the components necessary to create the characteristics of each employee of the enterprise as a qualified specialist was developed. Practical value. Due to the lack of a unified approach to the assessment of personnel potential, an author's system of its research was created, which includes different variations of methods and tools that can be used by employees of personnel services and agencies. The authors improved the mechanism for conducting an organization's personnel audit, which will allow its use at any enterprise or when conducting an independent assessment.

Implementation of processor cores of a fault-tolerant control system on FPGA under external control

The paper describes the choice of a technical solution for the implementation of a fault-tolerant real-time control system under external control. The main idea of the method is to introduce an external control block of the main control system that includes a watchdog and a backup decision-making algorithm. This block was supposed to be executed on an external FPGA-based block. The main system was supposed to be executed on the CPU. The paper proposes a variant of creating the entire system on a single FPGA. It implements both the processor cores for the operation of the main control system and control block. Various variants of cores for implementation on FPGA are considered. The paper studies suitable projects of processor cores for implementation on FPGA. It is concluded that the LEON series cores are suitable for the problem of building a fault-tolerant control system, since they already have technical solutions to improve fault tolerance. It is concluded that the proposed approach to building a fault-tolerant control system with external control can be fully implemented on a single FPGA. It has some advantages over implementation on separate blocks.

Management of The COVID-19 Pandemic and Public Response in Lithuania: Knowledge, Attitudes, and Practices (KAP)

ABSTRACT The article aims to provide an overview of the interrelationships between public knowledge, attitudes, and practical behaviours in the context of a global pandemic and the risk management measures used by the government. By reviewing some of the key trends in crisis management in Lithuania, it seeks to explore the response of society. The aim of the paper is to analyse the interrelationship among subjective public informativeness, attitudes, and behaviours according to different socio-demographic aspects. To meet the main objective of the paper, a representative public survey (N-804) on attitudes towards COVID-19 was conducted (at the end of 2020). The survey sought to explore individual self-protection measures, attitudes towards the dangerousness of the virus, the measures used by the government to combat the pandemic, and prevalent stereotypes and their implications on personal behaviour. The paper discusses the indicators, which are divided into separate blocks, on the basis of which the responses of the study participants are summed up and evaluated on a three-level (good, average, poor) rating scale, followed by correlation analyses on various socio-demographic parameters. The survey revealed that a higher proportion of Lithuanian society behaved responsibly, even being moderately informed and characterised by diverse attitudes.

CLASSIFICATION OF CYTOLOGICAL IMAGES OF WHITE BLOOD CELLS USING DEEP LEARNING

Leukocytes, also known as white blood cells, are an important part of the immune system and represent a group of cells that protect the body from infections. The classification of leukocytes is widely used to diagnose various diseases, such as AIDS, leukemia, myeloma, anemia and others. However, traditional methods of classification of leukocytes require a lot of time, and their results are prone to errors. The article implements a computer approach to classification and detection of white blood cells on images of blood cells using deep learning methods based on the application of the method of transferring deep learning models and finetuning them. Deep learning has become one of the most popular areas of artificial intelligence. There are many neural network architectures used in deep learning in solving computer vision problems. The purpose of this study is to develop a computer system for efficient automatic detection and classification of leukocytes of four types of blood cells: eosinophils, lymphocytes, monocytes, neutrophils. This article used popular models of accurate neural networks VGG16, ResNet50, DensNet201, MobileNetV3, InceptionResnetV2, pretrained on ImageNet and finetuned on WBC images dataset.The paper also proposes a custom model of a deep neural network using separable convolutional blocks SeparableConv2D in its architecture. The model is optimized using methods of preprocessing normalization and data augmentation. The is model gave classification metrics of accuracy = 98.84 %, precision = 99.56 %, recall = 98.89 % and f1-score = 99.22 %. The developed model allows, in most cases, to determine with high speed whether a leukocyte belongs to one of the four classes in the image, which indicates the possibility of using the system as an auxiliary tool for hematological blood analysis.

The architecture of business centers in major cities of independent Kazakhstan

Introduction: The study aims to determine the main trends in the formation of business centers in Kazakhstan’s two largest cities, Almaty and Nur-Sultan, and to develop the main city planning and architectural recommendations for improving the network of business centers and their maintenance. Materials and Methods: The study’s systemic and complex research methodology allows it to look at business center issues from a variety of perspectives, including economic, socio-political, legislative, urban planning, and innovation. This approach allowed the architecture of business centers to be highlighted as a dynamic, interrelated process that represents the state’s economic power and prestige. Results and Discussion: The identification of trends in the development of business centers as the main type of commercial real estate is intrinsically linked to their natural qualitative growth and structural metamorphoses, transforming future cities into business cities, business parks, business incubators, and eco-towns. Conclusions: The study revealed that a specific feature of the business center is the distinction in its space-planning structure of the recreational and communicative block of premises and rooms into a separate independent functional block, which, both locally and dispersed spatially, carries an ideological and logical practical load and is a functional space for a multi-purpose business building.