Continuous Improvement Of Technology Research Articles

Advances in nutritional metabolic therapy to impede the progression of critical illness.

With the advancement of medical care and the continuous improvement of organ support technologies, some critically ill patients survive the acute phase of their illness but still experience persistent organ dysfunction, necessitating long-term reliance on intensive care and organ support, known as chronic critical illness. Chronic critical illness is characterized by prolonged hospital stays, high mortality rates, and significant resource consumption. Patients with chronic critical illness often suffer from malnutrition, compromised immune function, and poor baseline health, which, combined with factors like shock or trauma, can lead to intestinal mucosal damage. Therefore, effective nutritional intervention for patients with chronic critical illness remains a key research focus. Nutritional therapy has emerged as one of the essential components of the overall treatment strategy for chronic critical illness. This paper aims to provide a comprehensive review of the latest research progress in nutritional support therapy for patients with chronic critical illness.

Contemporary Trends of Digitalisation of Management Processes in Higher Education: Data Analytics, Cloud Technologies and Artificial Intelligence Authors

The continuous development, improvement and diversification of digital technologies cause the issue of rethinking their use in education, in particular, in the context of digitalisation of management processes at higher education institutions. It is important to understand the current state and trends of digital technologies, which become the basis for digitalisation of management processes in higher education. For this purpose, the article has analysed Ukrainian publications in the Google Scholar search engine to identify scientific works dealing with the digitalisation of management processes in higher education, using Scopus AI, the tool based on artificial intelligence, to obtain a conceptual map of digitalisation technologies of management processes in education, studied publications in the Scopus international scientometric database to determine the significance of digital technologies described in these publications. The article analyses digital technologies currently used for management tasks in higher education, namely: data analytics, cloud technologies, and artificial intelligence technologies. The main advantages of the digitalisation of management processes in higher education are highlighted: effective administration, improvement of the decision-making process, improvement of the provision of educational services, improvement of teaching. Challenges and difficulties accompanied by digitalisation of management processes in higher education are presented: insufficient financing of higher education; lack of understanding of the educational process by the participants (from students to managers) regarding processes taking place in the modern digital society, as well as emerging or changing technologies; the need for competent management and teaching staff, a high level of digitalisation of society at the national level, orientation of educational process participants in a large number of digital technologies. As a result of the study, the current trends in digitalisation of management processes in higher education are summarised (continuation of the process of introducing digital technologies into the educational process in general and management processes in higher education in particular; integration of these digital technologies into learning management systems; introduction of updated digital technologies into the teaching process; improvement of education through digital transformation of management processes.

Artificial Intelligence-Assisted Simulation Research on Intelligent Behavior of Film and Television 3D Animation Characters

Abstract With the continuous development of artificial intelligence technology, the continuous improvement of three-dimensional animation design technology has become an inevitable trend. This paper conducts a simulation study on the intelligent behavior of three-dimensional animation characters in film and television, using finite state machines as the basis. First, we look at the basic parts of the character behavior diagram design and behavior modeling. Then, we use the decision state of the finite state machine to define the intelligent behavior of a three-dimensional animation character. Finally, we combine the character behavior operation principle with the character action generator to finish building the character intelligent behavior model. Under the technical support of the film and television animation character behavior model of the finite state machine, Anima Studio is used to realize the construction of the film and television animation character simulation platform, and the platform of this paper is used to explore the simulation of intelligent behavior of animation characters. Upon exploration, we discover that the animated character, utilizing the finite state machine model, operates efficiently and consistently, thereby demonstrating the simulation effect of the film and television animation character simulation platform in a vivid and realistic manner.

Analysis of Strategies and Effectiveness of Big Data Technology for Business Decision Optimization

Abstract Business decision-making is a decision-making process that relies heavily on business data, and with the continuous improvement of information technology, the level of intelligence of business decision-making has been increasing. The paper suggests relevant optimization strategies for business decision-making and creates an intelligent business decision-making process that utilizes big data. This paper mainly applies the association rule mining algorithm based on big data to business decision-making, extracting valuable information for business decision-makers from a large database of business information systems. In order to verify the operational efficiency of the improved algorithm, the traditional Apriori algorithm, FP-Growth algorithm, HBE-Apriori algorithm, and the improved algorithm are compared at the same time, and the results of the experiments show that the improved algorithm’s operational efficiency in the process of finding the maximal frequent itemset is significantly improved compared with the other three algorithms, which provides a basis for the analysis of the effectiveness of the optimization of business decision-making. The example of optimization of business decisions through big data technology found that after the optimization of business decision optimization, the asset quality and solvency of the enterprise are improved, and the operating capacity is unchanged due to the low operating capacity of the total assets of the enterprise. This paper’s method for optimizing business decisions based on association rules is shown to be feasible.

Digital transformations in arts and entertainment

This paper examines a series of digital transformations in arts and entertainment focused creative industries ( television, recorded music, live concerts, museums, computer games) impacted by digital innovations arising within these industries. Our paper demonstrates how continuous improvement in semiconductor technology (based on the doubling of chip density every two years as predicted by Moore’s law) has fostered advances in digital device capabilities, speed, portability, cost reduction and device integration that has made possible an array of innovative digital products, services and methods of engaging arts and entertainment audiences. Our analysis focuses on six innovative transformations: the digitization of the television set and transformation of television viewing and services, MP3 sound compression transformation of the recorded music industry, video streaming transformation of television programming, 3 D holography and hologram transformation of live concerts, multimedia, augmented reality (AR) and virtual reality (VR) transformation of museum audience engagement, and eSports transformation of video game industry participation and audience engagement. We also note the creative destructive impacts on non-digitized (analog) elements of some of these industries and identify transformational trends shaping the futures of these industries.

Artificial Intelligence Technology Helps Inform the Sports Industry

Abstract The continuous development and improvement of information technology and the arrival of the knowledge economy have injected new vitality into the development of the sports industry. In the context of artificial intelligence, this paper constructs a graph convolutional neural network model. It applies it to the field of sports teaching, creating an adjacency matrix based on image information to optimize the information processing speed of the neural network model. The standardized way is used to recognize and guide the various sports movements performed by students in the classroom. Through effectiveness analysis and FMS experiments, it was found that the graph convolutional neural network has a high recognition rate, and the matching rate for each section of the movement is above 70%. The mean values of angle features of students with very different body sizes remained at the same level with minimal differences under the same shooting angle. From the perspective of students’ sports performance, in the fourth week of the middle and late experimental period, the results of the experimental group and the control group students were 82.39±2.10 and 73.64±3.62, respectively, which was a difference of nearly 10 points. The results of the control group students had already lagged behind the experimental group students substantially from the perspective of the score, and the difference was significant at P=0.000<0.05. The convolutional neural network can effectively improve sports movement standardization, which in turn enhances the performance of students in physical education and promotes the information development of the sports industry.

Research on Target Detection and Recognition Algorithms in Remote Sensing Images

Abstract With the continuous improvement of computer vision and deep learning technology, the target detection methods of remote sensing images are also expanding and diversifying. In view of the shortcomings of the current object detection and recognition algorithms in terms of accuracy and versatility, this paper introduces the reverse scale transfer layer and feature pyramid (FPN) modules and applies the attention models of channel attention mechanism and spatial attention mechanism to each module of the convolutional neural network, so that the feature layer can obtain accurate and comprehensive prediction information, and finally proposes a remote sensing image object detection algorithm DCYOLOv7 with high accuracy. Compared with the benchmark model, the accuracy of the algorithm on small, medium, and large targets is improved by 14.69%, 4.14%, and 5.19%, respectively. The DC-YOLOv7 algorithm is improved by 10.15%, 12.16%, 13.18%, and 14.8% compared with the mAP, AP50, AP75, and AR100 of the benchmark algorithm, respectively. DC-YOLOv7 has a better detection application effect than the classical algorithm in the military aspect. The effectiveness and versatility of the target detection and recognition algorithm in the remote sensing images presented in this paper have been verified.

Orbital Eccentricity of Celestial Motion—from Stars to Planets

The orbital eccentricity is one of the key parameters to describe the orbit of celestial bodies, which can provide important clues to reveal their dynamical evolution, and thus help to understand their formation and evolution processes along with the physical mechanisms behind them. The continuous improvement of observational technologies, enable us to explore the orbit of celestial bodies beyond the solar system, i.e., from stellar systems to planetary systems. Focusing on the orbital eccentricity of celestial bodies, this paper reviews the progress in stellar systems (including the main sequence stars, brown dwarfs, and compact stars) and planetary systems (including gas-giants, low-mass exoplanets such as “super-Earth” and “sub-Neptune”), and summarizes several similarities and issues among the investigations of orbital eccentricity under different scales. Finally, based on the ongoing and future astronomical facilities and missions, we discuss the future prospect on eccentricity studies of stellar systems, extra-solar planetary systems, and even extra-solar satellite systems.

Теоретические аспекты формирования и развития кадров управления: эволюция подходов

The development of an organization operating in the field of high technologies must take into account modern approaches and methods for the formation and development of management personnel. This is true for both small businesses and large companies, especially those that produce complex products or operate in high-tech businesses. In such conditions, where there is high competition and strict requirements for management and organization of activities, the desire for continuous development and technological improvement is especially important. This article defines the main methods for managing the formation and development of IT management personnel in companies.

Оценка факторов риска развития интраоперационного синдрома девиации инфузионных потоков с учетом анатомо-топографических особенностей переднего отрезка

Relevance. Despite continuous improvement in cataract surgery technology, intraoperative fluid misdirection syndrome remains an underestimated problem. Purpose. To evaluate intraoperative fluid misdirection syndrome clinical manifestation in patients with pseudoexfoliation syndrome (PXS) and without it; to assess intraoperative fluid misdirection syndrome risk factors according to anatomical and topographical features of anterior segment. Material and methods. There were two groups of patients who underwent phacoemulsification in the prospective study. Study group (50 eyes) included patients with complicated cataract, PXS and drug-induced mydriasis less than 6 mm. Control group (50 eyes) included patients with senile cataract, no PXS and drug-induced mydriasis more than 6 mm were enrolled in the control group. Clinical examination of patients included optical biometry, pupillometry using rotational Scheimpflug imaging, ultrasound biomicroscopy for evaluation of iris thickness and sectional area of posterior chamber under drug-induced mydriasis. Results. The average pupil diameter in 1 hour after instillation of mydriatics was 5.46±0.46 mm in the study group and 6.6±0.43 mm in the control group. The sectional area of posterior chamber was 0.67±0.28 mm² and iris thickness – 0.53±0.05 mm in the study group. The sectional area of posterior chamber was 0.43±0.15 mm² and iris thickness – 0.64±0.07 mm in the control group. The results revealed positive correlation between pupil diameter and iris thickness, and negative correlation between pupil diameter, iris thickness and sectional area of posterior chamber. Lens floaters were determined after phacoemulsification in 9 eyes (18%) in the study group and in 3 eyes (6%) in the control group. The results showed statistically significant difference between groups (p≤0.05). Conclusion. Lens floaters in the retrolental space as one of the main manifestations of the intraoperative fluid misdirection syndrome were observed in 18% patients of study group and in 6% patients of control group (p≤0.05). Combination of PXS and drug-induced mydriasis less than 6 mm is considered to be the predictive factor of intraoperative fluid misdirection syndrome. Key words: intraoperative fluid misdirection syndrome, pseudoexfoliation syndrome, anterior vitreous face

EVALUATION OF THE ADEQUACY OF WRITTEN SPECIALIZED TEXTS MACHINE TRANSLATION

Machine translation has become critical for overcoming language differences in the age of global communication, especially in specialized fields. This article discusses the complex process of evaluating the adequacy of machine translation for written specialized literature. The study analyzes the mistakes made by Google Translate (GT) and DeepL Translate (DT) when translating biology textbooks. The paper emphasizes that specialized texts require not only terminological accuracy but also context preservation, which makes machine translation in this field extremely challenging. Several evaluation approaches have been considered in previous work, emphasizing the need for human editing alongside machine translation systems. Machine translation errors, ranging from terminological and semantic mistakes to stylistic and grammatical errors, emphasize the importance of thorough post-editing. The results of the study showed that despite the correct translation of commonly used terminology, its use in complex sentences caused difficulties. Both systems often failed to recognize details, leading to distorted interpretations. Stylistic mistakes, such as word-for-word translation disregarding context, further weakened the translated sentences. The translation was also accompanied by grammatical errors that demonstrate the complexity of syntactic structures in specialized topics. The study revealed minimal differences between GT and DT, with GT translating terminology better and DT demonstrating more efficient grammatical structures. However, both systems used word-for-word translation, which resulted in stylistic errors and inaccurate word choice. This paper emphasizes the need for human editing to ensure the correct translation of specialized materials, as well as the need for continuous improvement of machine translation technology to ensure the accuracy of terminology and preserve context in specialized texts.

Actionable Driver Events in Small Cell Lung Cancer.

Small cell lung cancer (SCLC) stands out as the most aggressive form of lung cancer, characterized by an extremely high proliferation rate and a very poor prognosis, with a 5-year survival rate that falls below 7%. Approximately two-thirds of patients receive their diagnosis when the disease has already reached a metastatic or extensive stage, leaving chemotherapy as the remaining first-line treatment option. Other than the recent advances in immunotherapy, which have shown moderate results, SCLC patients cannot yet benefit from any approved targeted therapy, meaning that this cancer remains treated as a uniform entity, disregarding intra- or inter-tumoral heterogeneity. Continuous efforts and technological improvements have enabled the identification of new potential targets that could be used to implement novel therapeutic strategies. In this review, we provide an overview of the most recent approaches for SCLC treatment, providing an extensive compilation of the targeted therapies that are currently under clinical evaluation and inhibitor molecules with promising results in vitro and in vivo.

Trace Sample Proteome Quantification by Data-Dependent Acquisition without Dynamic Exclusion.

Despite continuous technological improvements in sample preparation, mass-spectrometry-based proteomics for trace samples faces the challenges of sensitivity, quantification accuracy, and reproducibility. Herein, we explored the applicability of turboDDA (a method that uses data-dependent acquisition without dynamic exclusion) for quantitative proteomics of trace samples. After systematic optimization of acquisition parameters, we compared the performance of turboDDA with that of data-dependent acquisition with dynamic exclusion (DEDDA). By benchmarking the analysis of trace unlabeled human cell digests, turboDDA showed substantially better sensitivity in comparison with DEDDA, whether for unfractionated or high pH fractionated samples. Furthermore, through designing an iTRAQ-labeled three-proteome model (i.e., tryptic digest of protein lysates from yeast, human, and E. coli) to document the interference effect, we evaluated the quantification interference, accuracy, reproducibility of iTRAQ labeled trace samples, and the impact of PIF (precursor intensity fraction) cutoff for different approaches (turboDDA and DEDDA). The results showed that improved quantification accuracy and reproducibility could be achieved by turboDDA, while a more stringent PIF cutoff resulted in more accurate quantification but less peptide identification for both approaches. Finally, the turboDDA strategy was applied to the differential analysis of limited amounts of human lung cancer cell samples, showing great promise in trace proteomics sample analysis.

The Use of Virtual Reality and Augmented Reality in Enhancing the Sports Viewing Experience

Purpose: The main aim of this study was to investigate the use of Virtual Reality and AugmentedReality in enhancing the sports viewing experience.Methodology: The study adopted a desktop research methodology. Desk research refers to secondarydata or that which can be collected without fieldwork. Desk research is basically involved in collectingdata from existing resources hence it is often considered a low cost technique as compared to fieldresearch, as the main cost is involved in executive’s time, telephone charges and directories. Thus, thestudy relied on already published studies, reports and statistics. This secondary data was easilyaccessed through the online journals and library.Findings: The findings revealed that there exists a contextual and methodological gap relating to theuse of Virtual Reality and Augmented Reality in enhancing the sports viewing experience. Preliminaryempirical review revealed that both Virtual Reality (VR) and Augmented Reality (AR) have a profoundpositive impact on the sports viewing experience. VR offers fans the opportunity to be virtually presentat sporting events, providing an unparalleled level of immersion, personalization, and interactivity.This heightened engagement contributes significantly to fan satisfaction and a deeper emotionalconnection to the game. In light of the consistent and compelling findings, it is clear that VR and ARare not just novelties but powerful tools that can shape the future of sports viewing. Sportsorganizations, broadcasters, and marketers should continue to invest in and explore these technologiesto meet the evolving expectations of fans, elevate the viewing experience, and unlock newopportunities for revenue generation.Unique Contribution to Theory, Practice and Policy: The Uses and Gratifications theory,Technology Acceptance Model (TAM) and the Flow theory may be used to anchor future studies onthe use of Virtual Reality and Augmented Reality in enhancing the sports viewing experience. Thestudy recommended that sports organizations and broadcasters to embrace and invest in Virtual Reality(VR) and Augmented Reality (AR) technologies to create immersive and interactive sports viewingexperiences; fan education and training on how to use VR and AR applications should be a priority.Many potential users may be unfamiliar with these technologies, and clear instructions and tutorialsshould be provided to enhance user adoption and for continuous innovation and improvement in VRand AR content and technology are essential. This includes refining the quality of VR headsets andAR devices, enhancing the realism of simulations, and developing new applications and features thatcater to specific sports and fan preferences.

Paper Invoice Dilemma and Electronic Invoice Solution

This paper will start from the definition and purpose of paper invoice, analyze the shortcomings and problems in the use of paper invoice, and introduce the definition, advantages and purpose of electronic invoice, in order to solve the dilemma faced by the use of paper invoice. As a traditional form of bill, paper invoice plays an important role in commercial transactions, but there are some problems in its use. First of all, paper invoices are prone to damage, loss or tampering, increasing the risk and uncertainty of transactions. Secondly, the preservation and management of paper invoices requires a lot of time, space and labor costs, which brings no small burden to enterprises. In addition, because the paper invoice cannot realize real-time information sharing and tracking, resulting in the information process is not smooth and inefficient. In order to solve these problems of paper invoice, electronic invoice came into being. Electronic invoice is a new form of bill based on electronic data exchange and digital signature technology. It has the following advantages: First, electronic invoice does not need paper carrier, reduces the cost of use and management, and is not easy to be damaged, lost or tampered with, improving the reliability and security of transactions. Secondly, electronic invoices can realize real-time information sharing and tracking, which improves the efficiency and convenience of transactions. In addition, the electronic invoice can also be seamlessly connected with the enterprise's financial management system, to achieve automated accounting processing, reducing manual operations and errors. In short, there are a series of shortcomings and problems in the use of paper invoices, such as easy loss, difficult management, not easy to share information and so on. As a solution, electronic invoice has been more and more widely used and promoted by virtue of its advantages of eliminating paper carrier, improving transaction security and reliability, and realizing real-time information sharing and tracking. In the future, with the continuous development and improvement of technology, electronic invoices will become the mainstream form of business transactions, and promote the process of paper invoices to electronic transformation.

Frontier development and prospect trend of HCCI engine

Nowadays, with the rapid development of information technology, the level of science and technology is constantly improving. All fields are developing rapidly. In recent years, the development of the automotive engine industry has been particularly rapid. To cope with increasingly strict environmental requirements and the impact of electric motors on the market, a new engine model is gradually being valued. Homogeneous Charge Compression Ignition (HCCI) internal combustion engine is a new type of engine. It has the technical advantages of traditional diesel and gasoline engines. This combustion mode greatly improves the emission of pollutants and the engine’s overall efficiency. However, there are still certain challenges to this technology at present. But with the continuous improvement and optimization of related technologies. HCCI engines are bound to have broad development prospects. This article elaborates on the current status and development trends of HCCI engines from four perspectives: basic principles, combustion characteristics, emission characteristics, and the latest developments.

Development of an algorithm for the reasoned selection of machines for leather garments manufacturing

The technology of processing clothing elements is very mobile and changes with the appearance of new materials and equipment. The selected design and technological solutions that ensure the conformity of aesthetic properties and requirements can be satisfied through continuous improvement of sewing production technologies. This study aims to develop an algorithm for choosing the optimal equipment, taking into account the material parameters and the permissible requirements for the technological process of manufacturing sewing products from artificial leather. As a result of the analysis of the range of sewing machines and manufacturing companies, Juki sewing machines were chosen to build a complex matrix of machine equipment. A morphological scheme of the selection process and a mathematical description of the two-dimensional matrix of elements have been developed. That has made it possible to reflect the simultaneous consideration of all process components and their influence on the technological parameters of the machine. The database of the parameters of the equipment selection system was built in the form of matrix elements: a matrix of the type of operations, a matrix of material coatings, a matrix of the base of materials, a matrix of machine assignments, and a matrix of qualifications. Each matrix is a production rule for making a decision at a separate selection stage. The operation matrix was constructed using the TechLab mobile application, which includes 50 processing schemes for artificial leather products. The analysis of the schemes has made it possible to determine the frequency of occurrence of types of seams for processing artificial leather products: 1.01.01 (28.75 %), 2.01.01 (16.75 %), 1.06.02 (11.00 %), 2.02.01 (15.50 %), 5.01.01 (24.25 %), 6.02.01 (3.75 %). The mathematical notation of the algorithm for choosing the optimal machine equipment has made it possible to visualize the structure of the process using a graph. The graph was built using Gephi. Such a notation takes into account the qualification of the worker, the type of technological operation, and the material’s properties, including the material’s thickness, coating, and base.

Research and analysis of FIFO related working principles

An asynchronous FIFO is a classic circuit device used for caching data and accommodating the frequency of asynchronous signals. With the continuous improvement of technology, the advantages of this device in real-time transmission, multi-core processing, and data acquisition have become more apparent. As a result, the original structure has been optimized and extended using algorithm and design techniques to achieve greater efficiency and applicability in various academic and industrial applications. This article discusses several methods for optimizing FIFO in different aspects and examines how an unlocked FIFO queue is applied in a CAN bus data acquisition system, as well as its use in data hybrid framing technology. The findings show that FIFO performs exceptionally well as a cache structure, particularly in situations involving large amounts of data acquisition and real-time procession. The various optimization techniques discussed in this article include using pipeline registers, implementing a dual-clock FIFO, and employing Gray-code-based pointers. These techniques can increase the speed and reduce the power consumption of FIFO, thereby improving its overall efficiency. In addition, the article introduces the unlocked FIFO queue, which provides more flexibility than conventional locked FIFOs. Unlocked FIFO queues allow multiple cores to access the buffer simultaneously, which makes them ideal for high-performance systems. Finally, the article explores the application of FIFO in CAN bus data acquisition systems, where it is utilized as a buffer between the bus and other devices. Additionally, the use of FIFO in data hybrid framing technology is discussed, where it is essential for maintaining the integrity of the data stream.

Application of artificial intelligence technology in the digital transformation of small and medium-sized enterprises in China

With the development of a new round of scientific and technological revolution, big data, cloud computing, and other information technologies have injected new momentum into the research of artificial intelligence. The continuous improvement of artificial intelligence technology has had an impact on social life that cannot be ignored. In the wave of digital transformation of global enterprises, the low level of digital construction and blocked digital transformation of small and medium-sized enterprises (SMEs) in China are still prominent. How to seize the opportunities brought by the development of artificial intelligence and effectively apply artificial intelligence to promote the transformation and upgrading of SMEs? To clarify this issue, this paper first uses crawling technology to get the annual reports of SMEs from 2017 to 2021 and analyses how much emphasis SMEs place on AI through Python. Then, this paper analyses the transformation difficulties faced by Chinese SMEs and systematically sorts out the technical means of artificial intelligence that could embed into the main functions of enterprises. Finally, this paper puts forward specific measures for Chinese SMEs to actively apply artificial intelligence for digital transformation and provides suggestions for SMEs to better integrate into the era of the digital economy.

КОМПОЗИЦІЙНО-МИСТЕЦЬКІ ОСОБЛИВОСТІ ЕВОЛЮЦІЇ СУЧАСНИХ ІНДИВІДУАЛЬНИХ ЖИТЛОВИХ БУДИНКІВ

The article is devoted to the study of artistic features and specifics of the functioning of individual residential buildings. Examples of well-known, iconic objects designed and built at the beginning of the 20-21 centuries are considered. Research directions are conditionally divided into artistic-aesthetic, cultural-semiotic and functional. The main attention is paid to the composition and stylistic features of individual residential buildings, the description of conceptual-artistic, functional and constructive approaches used in the design and construction of these buildings. Examples of well-known architectural objects with analysis of various compositional techniques and stylistic directions are provided as illustrations. The first most famous object is the villa "Savoy", architect Le Corbusier. The villa is designed taking into account the 5 main principles developed by Corbusier for modern buildings, the main structural scheme of which is a reinforced concrete frame. The second object that defined an entire direction in the architecture of the last third of the 20th century is the "Vanna House", architect Robert Venturi. It is with this building that the emergence and development of a new architectural style - "postmodernism" - is connected. The third building is Villa "Soravia" by the well-known Coop Himmelb(l)au architectural office. Two more objects are examples of economy-class housing using the latest achievements in the field of new technologies. These are residential buildings designed by architects Tadao Ando and Renzo Piano. The continuous and purposeful improvement of building technologies and building structures, as well as the constant change and development of aesthetic views, stimulate the emergence of new stylistic concepts and artistic generalizations in modern architecture.