Architectural Components Research Articles

ANALYZING THE COMMON FEATURES BETWEEN MOSQUE ARCHITECTURE, RITUAL MOVEMENTS OF PRAYER AND YOGA MOVEMENTS

An architectural work contains wide aspects and is not limited only to the body made of materials. What adds value to the building is the spirit breathed into this body. Prayer (Namaz) and Yoga are mental and physical activities that cause peace in body and soul. The purpose of this research is to analyze the common features between mosque architecture, ritual movements of prayer and yoga movements in order to achieve human mental and physical health. Therefore, the relationship between the physical movements of prayer and mosque architecture was analyzed, and the amount of movement in prayer was evaluated using the OWAS method. Then, based on the previous step's results, the relationship between body ergonomics in prayer and yoga movements was descriptively analyzed. Finally, the common features between mosque architecture, ritual movements of prayer and yoga movements are presented visually. The results show that there are common features between the architecture of mosque spaces, the ritual movements of prayer and yoga movements, and the shape of the body in prayer and yoga is similar to the shape of the architectural components of the mosque.

Component Recognition and Coordinate Extraction in Two-Dimensional Paper Drawings Using SegFormer

Within the domain of architectural urban informatization, the automated precision recognition of two-dimensional paper schematics emerges as a pivotal technical challenge. Recognition methods traditionally employed frequently encounter limitations due to the fluctuating quality of architectural drawings and the bounds of current image processing methodologies, inhibiting the realization of high accuracy. The research delineates an innovative framework that synthesizes refined semantic segmentation algorithms with image processing techniques and precise coordinate identification methods, with the objective of enhancing the accuracy and operational efficiency in the identification of architectural elements. A meticulously curated data set, featuring 13 principal categories of building and structural components, facilitated the comprehensive training and assessment of two disparate deep learning models. The empirical findings reveal that these algorithms attained mean intersection over union (MIoU) values of 96.44% and 98.01% on the evaluation data set, marking a substantial enhancement in performance relative to traditional approaches. In conjunction, the framework’s integration of the Hough Transform with SQL Server technology has significantly reduced the coordinate detection error rates for linear and circular elements to below 0.1% and 0.15%, respectively. This investigation not only accomplishes the efficacious transition from analog two-dimensional paper drawings to their digital counterparts, but also assures the precise identification and localization of essential architectural components within the digital image coordinate framework. These developments are of considerable importance in furthering the digital transition within the construction industry and establish a robust foundation for the forthcoming extension of data collections and the refinement of algorithmic efficacy.

PROBLEMS OF REGULATING ECO-POSITIVE CHANGES IN SMART CITY FORMATION PROCESSES

Architects, scientists of the Kharkiv National University of Urban Economy. O.M. Beketov conducts research focused on writing the terms of reference for the "Software package for modeling the city as a dynamic system". This development is devoted to the problem of improving SMART-oriented software and analytical tools based on working with large data arrays (BIG DATA) in architectural and urban planning management. The purpose of this toolkit is prognostics and monitoring of the architectural component of the city as a dynamic system. The relevance of its implementation lies in the optimization of the principles of functioning of the architectural component of the city with the calculation of its impact on the processes of functioning of other urban subsystems.
 As a development and improvement of this direction, a method for determining the optimal speed and acceleration of positive transformations of the architectural component of cities, based on the indicator "Ecological footprint of architecture", which is currently being developed, is proposed. It is a method of developing step-by-step strategies for the development of the architectural component of cities. The main problem is to determine the optimal pace of social, environmental and economic changes in the processes of achieving a sustainable state of the city. Too rapid changes will inevitably lead to an aggravation of the socio-economic crisis. Slow change has a negative impact on the sustainability and ecology of the region. For this reason, in this article, the authors have developed a concept for the formation of an indicator that determines the vector, speed and acceleration of modernization of the architectural component of the city. As a factor limiting the rate of change to a socially acceptable level, the indicator of "Sustainable accessibility of vital goods for the population" was chosen.

ClimMob: Software to support experimental citizen science in agriculture

Experimental citizen science offers new ways to organize on-farm testing of crop varieties and other agronomic options. Its implementation at scale requires software that streamlines the process of experimental design, data collection and analysis, so that different organizations can support trials. This article considers ClimMob software developed to facilitate implementing experimental citizen science in agriculture. We describe the software design process, including our initial design choices, the architecture and functionality of ClimMob, and the methodology used for incorporating user feedback. Initial design choices were guided by the need to shape a workflow that is feasible for farmers and relevant for farmers, breeders and other decision-makers. Workflow and software concepts were developed concurrently. The resulting approach supported by ClimMob is triadic comparisons of technology options (tricot), which allows farmers to make simple comparisons between crop varieties or other agricultural technologies tested on farms. The software was built using Component-Based Software Engineering (CBSE), to allow for a flexible, modular design of software that is easy to maintain. Source is open-source and built on existing components that generally have a broad user community, to ensure their continuity in the future. Key components include Open Data Kit, ODK Tools, PyUtilib Component Architecture. The design of experiments and data analysis is done through R packages, which are all available on CRAN. Constant user feedback and short communication lines between the development teams and users was crucial in the development process. Development will continue to further improve user experience, expand data collection methods and media channels, ensure integration with other systems, and to further improve the support for data-driven decision-making.

REVISITING THE MECHANISMS OF FUNCTIONING OF THE ARTISTIC SPACE OF AN OLD EGYPTIAN PRIVATE TOMB

This paper examines the mechanism of functioning of the artistic space of the Egyptian noble tomb of the Old Kingdom period as a system of pictorial and architectural components. The purpose of the burial and the mechanism of functioning of the system to a great extent determined the themes and content of the plots, which contributes a special relevance to the study. A systematic analysis of reliefs from more than a hundred burials of the necropolises of Giza and Saqqara is used, with a focus on the design of the large tombs of Yasen and Chi. The paper emphasizes the fact that the universal mechanism for the functioning of the level system “a large image of the owner – a nearby scene” is a stable correlation between the elements of the attribute set of the nobleman and the content of the plots. Moreover, a large image of the nobleman is valuable not only as an image itself, but also as a set of necessary attributes that allow one to engage in “contemplating” on the images corresponding to these attributes. A new unusual variant of correlation has been identified by depicting a nobleman without the required attribute, however in a certain pose in which this attribute is usually present. Thus, the combination of the necessary insignia, combined with the pose of the depicted nobleman, endowed the large image of the owner with additional functions, allowing it to correlate with several plots and scenes of different content.

Advances in Modeling and Interpretability of Deep Neural Sleep Staging: A Systematic Review

Sleep staging has a very important role in diagnosing patients with sleep disorders. In general, this task is very time-consuming for physicians to perform. Deep learning shows great potential to automate this process and remove physician bias from decision making. In this study, we aim to identify recent trends on performance improvement and the causes for these trends. Recent papers on sleep stage classification and interpretability are investigated to explore different modeling and data manipulation techniques, their efficiency, and recent advances. We identify an improvement in performance up to 12% on standard datasets over the last 5 years. The improvements in performance do not appear to be necessarily correlated to the size of the models, but instead seem to be caused by incorporating new architectural components, such as the use of transformers and contrastive learning.

FORMATION OF CITY IDENTITY BY MEANS OF GRAPHIC DESIGN (THE EXAMPLE OF SAINT PETERSBURG)

The article considers the problems of forming and development of visual environment of a large European city on the example of Saint Petersburg. Human interaction with architectural and graphic components of urban space is analysed in context of visual perception. The peculiarities of the impact of urban visual information objects on human perception of urban environment are revealed. Particular attention is paid to the influence of the visual information environment on the formation of the aesthetic image of the city. The specifics of legislative regulation of the quality of visual information environment in Saint Petersburg are highlighted.

Realizing Intrinsically Stretchable Transparent Electrodes via Silver Nanowires/PEDOT:PSS/Polyvinyl Alcohol Composites on the Polyurethane Substrate

AbstractStretchable transparent electrodes (STEs) have garnered considerable attention as a fundamental architectural component in the realm of conformable and wearable electronics. This study presents a novel approach utilizing composite inks based on silver nanowires to fabricate STEs, with the incorporation of a conductive polymer as the leveling agent and polyvinyl alcohol as the bonding agent. The resulting STE demonstrates several desirable properties, including low sheet resistance (15.6 Ω sq−1) and surface roughness facilitated by poly(3,4‐ethylenedioxythiophene) polystyrene sulfonate. Moreover, the STE demonstrates strong adhesive strength to various plastic substrates, high transparency (>80%), and remarkable stretchability of up to 100%. Notably, the STE exhibits exceptional thermal stability under thermal stress at 200 °C for extended durations of up to 300 min. As a result, flexible organic solar cells employing this composite STE achieve outstanding performance in terms of high efficiency, robust mechanical durability, and remarkable thermal stability.

Explaining the role of physical components of architecture in medical centers on the reduction of stress in patients before surgery

Explaining the role of physical components of architecture in medical centers on the reduction of stress in patients before surgery

Identification of QTLs for plant height and branching related traits in cultivated peanut

Plant height (PH), primary lateral branch length (PBL) and branch number (BN) are architectural components impacting peanut pod yield, biomass production and adaptivity to mechanical harvesting. In this study, a recombinant inbred population consisting of 181 individual lines was used to determine genetic controls of PH, PBL and BN across three environments. Phenotypic data collected from the population demonstrated continuous distributions and transgressive segregation patterns. Broad-sense heritability of PH, PBL and BN was found to be 0.87, 0.88 and 0.92, respectively. Unconditional individual environmental analysis revealed 35 additive QTLs with phenotypic variation explained (PVE) ranging from 4.57 to 21.68%. A two-round meta-analysis resulted in 24 consensus and 17 unique QTLs. Five unique QTLs exhibited pleiotropic effects and their genetic bases (pleiotropy or tight linkage) were evaluated. Joint analysis was performed to estimate the QTL by environment interaction (QEI) effects on PH, PBL and BN, which collectively explained phenotypic variations of 10.80, 11.02, and 7.89%, respectively. We identified 3 major and stable QTL regions (uq9-3, uq10-2 and uq16-1) on chromosomes 9, 10 and 16, spanning 1.43-1.53 Mb genomic regions. Candidate genes involved in phytohormones biosynthesis, signaling and cell wall development were proposed to regulate these morphological traits. These results provide valuable information for further genetic studies and development of molecular markers applicable for peanut architecture improvement.

Modelling local and general quantum mechanical properties with attention-based pooling

Atom-centred neural networks represent the state-of-the-art for approximating the quantum chemical properties of molecules, such as internal energies. While the design of machine learning architectures that respect chemical principles has continued to advance, the final atom pooling operation that is necessary to convert from atomic to molecular representations in most models remains relatively undeveloped. The most common choices, sum and average pooling, compute molecular representations that are naturally a good fit for many physical properties, while satisfying properties such as permutation invariance which are desirable from a geometric deep learning perspective. However, there are growing concerns that such simplistic functions might have limited representational power, while also being suboptimal for physical properties that are highly localised or intensive. Based on recent advances in graph representation learning, we investigate the use of a learnable pooling function that leverages an attention mechanism to model interactions between atom representations. The proposed pooling operation is a drop-in replacement requiring no changes to any of the other architectural components. Using SchNet and DimeNet++ as starting models, we demonstrate consistent uplifts in performance compared to sum and mean pooling and a recent physics-aware pooling operation designed specifically for orbital energies, on several datasets, properties, and levels of theory, with up to 85% improvements depending on the specific task.

Development of digital twin ecosystem and ontology in medicine

Summary: Providing citizens with high-quality and safe medical services, providing information support for medical research and continuous medical education, making both doctor’s decisions and management decisions necessitated the provision of tools to ensure complex digitization of healthcare. To achieve these goals, a wide range of modern technologies have emerged. One such technology is digital twin technology.
 Modern medicine, being formed in the environment of Health 4.0, includes not only the treatment of patients, but also the management of healthcare, the prevention of diseases and the processes of health restoration. With the increasing popularity of information communication technologies, people’s demand for health services is shifting from offline service to new online models. Currently, the field of online medicine is not developed enough to serve the elderly, chronically ill people and the people with infectious diseases. Using the advantages of digital twins in solving these problems can give positive results.
 The article describes the nature, capabilities and applications of digital twin technology. The principles of the formation of the medical digital twin ecosystem are developed to ensure citizens’ accessibility to medical services and to make both medical and managerial decisions. The architecture and structural components of the digital twin ecosystem providing the connection between physical medical objects (patient, hospital, doctor, etc.) and their virtual images are shown. An ontological model for the staged construction and functionalization of the general DT of healthcare is proposed and its hierarchical architecture is established

SUSTAINABLE ARCHITECTURE – CONTRADICTIONS AND CONFLICTS

The problems of sustainable architecture are considered through the prism of creating architectural buildings and urban environments that provide environmental, economic and socio-cultural sustainability. In order to understand the complexity and nature of the permanence of architecture, it should be considered as a fragment of the overall open dynamic system of the city. At the same time, all components of such a system are interconnected by the general dynamics of functioning and often develop in conditions of internal systemic contradictions. The intra-system contradictions of the city as an open dynamic system should be understood as a situation where the attempts of any element of the system to achieve the conditions of optimal functioning are limited or suppressed by other elements of the system. Architecture, as an artificial environment in which these systemic contradictions arise, is forced to respond flexibly to them. The purpose of this work is to identify the systemic contradictions that arise in the process of functioning of the architectural component of the city as an open dynamic system, and to generalize these contradictions. 
 In the development of any system, stability and instability, adaptation and maladaptation are equally necessary. An absolutely unstable system is devoid of the ability to adapt and quickly collapses, while an ultra-stable system, suppressing any fluctuations, retains its structure and behavior, is not able to change qualitatively, that is, it is deprived of the possibility of development, and its destruction becomes only a matter of time. Both types of systems descend into chaos, the difference between them being the time it takes for entropy to explode. 
 The change in the evolutionary and revolutionary stages of the development of systems, their stability and instability forms dynamic cycles in time. Each system has not only cyclical processes due to its nature, but also cycles dictated by the environment. Moreover, the "external" cycles are more stable and stable, while the cycles of internal origin can change under their influence as a result of synchronization - the properties of systems of a diverse nature to produce a single rhythm of coexistence, despite the sometimes extremely weak interconnection.

Factors affecting chicken bone strength

Purpose: to study the accumulated data on the genetic determinism of the Kostyak fortress and discuss the possibility of their use to improve poultry farming.In both meat-type and egg-type poultry, bone strength is an important characteristic of animal welfare, on which largely depends the economic efficiency. The lack of strength is expressed by bone fragility, deformations or fractures occurring both at certain technologies of animal housing and at processing of poultry products, which is accompanied by economic losses. The quality and strength of bone tissue is formed, in addition to housing conditions, by a complex set of interactions of structural, physiological, nutritional and architectural components. The study of poultry bone strength is also complicated by reproduction peculiarities. Egg laying determines some features of osteogenesis, including medullary bone formation, which deposit calcium for eggshell formation. To date, the actual assessment of bone strength occurs postmortem, by measuring bone mineral density and breaking strength. Both methods do not allow using the evaluated animals in breeding to improve bone strength, therefore the study of genetic determinants of this trait is a relevant research task. The use of modern information analysis based on DNA technologies is a necessary step for identification of candidate genes controlling bone strength, because of their ability to increase selection efficiency in poultry. This review discusses the available results of genome-wide association studies (GWAS) for bone strength in birds, as well as existing data on the relationship of bone strength with traits such as egg production and age at first lay.

Solar-induced on-site H2O2 generation and tandem Fenton-like reaction on NiCo2S4/In2S3 triphase interface for naphthalene degradation

In this work, a hierarchical flower-like 2D/3D NiCo2S4/In2S3 Schottky junction containing S vacancies with excellent photocatalytic performance was elaborately designed and synthesized. The high redox ability of 2D/3D NiCo2S4/In2S3 is not only ascribed to the regulation of architectural morphology, components and heterostructure, but also the systematic optimization of charge transfer, abundant catalytic active sites, and the exceptional synergistic effect of S vacancies defect and Schottky-junction. A solid–liquid-gas triphase reaction interface was constructed by immobilizing NiCo2S4/In2S3 on poly(vinylidene fluoride)-modified melamine sponge (PVDF/MS). The H2O2 production rate can reach 842.7 μmol gcat−1 h−1 through dual channels at the triphase interface by overcoming the mass-transfer limitation of oxygen in water and high concentration naphthalene degradation efficiency is over 70% within 180 min visible light irradiation, which was better than that of diphase toward naphthalene with same amount of catalyst. The triphase system provides a simple strategy for reducing oxygen transport limitation, enhancing easy circulation and high stability for catalytic applications. This research provides a viable avenue for designing H2O2 photosynthesis and naphthalene photodegradation.

DINNRS: A Distributed In-Network Name Resolution System for information-centric networks

Information-Centric Networking (ICN) is a promising network paradigm designed to address the challenges arising from the inherent ambiguity of IP addresses. ICN prioritizes the content itself as the main factor in network transmission. The Name Resolution System (NRS) is the primary component of the ICN architecture, relying on flat naming. Unfortunately, existing NRS frequently encounters scalability and performance issues. In this paper, we present the Distributed In-Network Name Resolution System (DINNRS), an NRS that leverages the software-defined networking and ICN paradigm. DINNRS offers global-scale name-based routing with high scalability and minimal request delay. Additionally, we propose a modular control domain architecture for easy implementation and an enhanced marked cuckoo filter for fast resolving. Simulation experiments using the ICN emulator demonstrate that our methods result in significant performance gains, with a 61.2% reduction in data acquire latency and a 55.2% lower link load control overhead compared to MDHT.

Data fabric and digital twins: An integrated approach for data fusion design and evaluation of pervasive systems

Recent technological improvements have made it possible for pervasive computing intelligent environments, augmented by sensors and actuators, to offer services that support society's aims for a wide variety of applications. This requires the fusion of data gathered from multiple sensors to convert them into information to obtain valuable knowledge. Poor implementation of data fusion hinders the appropriate actions from being taken and offering the appropriate support to users and environment needs, particularly relevant in the healthcare domain. Data fusion poses challenges that are mainly related to the quality of the data or data sources, the definition of a data fusion process and evaluating the data fusion carried out. There is also a lack of holistic engineering frameworks to address these challenges. These frameworks should be able to support automated methods of extracting knowledge from information, selecting algorithms and techniques, assessing information and evaluating information fusion systems in an automatic and standardized manner. This work proposes a holistic framework to improve data fusion in pervasive systems, addressing the issues identified by means of two processes: the first of which guides the design of the system architecture and focuses on data management. It is based on a previous proposal that integrated aspects of Data Fabric and Digital Twins to solve data management and data contextualization and representation issues, respectively. The extension of the previous proposal presented here was mainly defined by integrating aspects and techniques from different well-known multi-sensor data fusion models. The previous proposal identified high-level data processing activities and was intended to facilitate their traceability to components in the system architecture. However, the previously defined stages are not completely adequate in a data fusion process and the data processing tasks to be performed in each stage are not described in detail, especially in the data fusion stages. The second process of the framework deals with evaluating data fusion systems and is based on international standards to ensure the quality of the data fusion tasks performed by such systems. This process also offers guidelines for designing the architecture of an evaluation subsystem to automatically perform data fusion evaluation in runtime as part of the system. To illustrate the proposal, a system for preventing the spread of COVID-19 in nursing homes is described that was developed using the proposed guidelines It is also illustrated by a description of how the data fusion tasks it supports are evaluated by the proposed evaluation process. The overall evaluation of the data fusion performed by this system was considered satisfactory, which indicates that the proposal facilitates the design and development of data fusion systems and helps to achieve the necessary quality requirements.

An Automated Electronic System in a Motorized Wheelchair for Telemonitoring: Mixed Methods Study Based on Internet of Things.

Wheelchair positioning systems can prevent postural deficits and pressure injuries. However, a more effective professional follow-up is needed to assess and monitor positioning according to the specificities and clinical conditions of each user. This study aims to present the concept of an electronic system embedded in a motorized wheelchair, based on the Internet of Things (IoT), for automated positioning as part of a study on wheelchairs and telemonitoring. We conducted a mixed methods study with a user-centered design approach, interviews with 16 wheelchair users and 66 professionals for the development of system functions, and a formative assessment of 5 participants with descriptive analysis to design system concepts. We presented a new wheelchair system with hardware and software components developed based on coparticipation with singular components in an IoT architecture. In an IoT solution, the incorporation of sensors from the inertial measurement unit was crucial. These sensors were vital for offering alternative methods to monitor and control the tilt and recline functions of a wheelchair. This monitoring and control could be achieved autonomously through a smartphone app. In addition, this capability addressed the requirements of real users. The technologies presented in this system can benefit telemonitoring and favor real feedback, allowing quality provision of health services to wheelchair users. User-centered development favored development with specific functions to meet the real demands of users. We emphasize the importance of future studies on the correlation between diagnoses and the use of the system in a real environment to help professionals in treatment.

THE ECOLOGICAL FOOTPRINT COEFFICIENT OF ARCHITECTURE AS A FACTOR IN THE FORMATION OF NATIONAL GREEN STANDARDS

The article is an attempt to generalize and adapt to architectural science the cycles of research devoted to the problem of national green standards formation in the context of the exit of cities and adjacent regions “beyond growth”. This approach is based on cycles of research on sustainable functioning principles of Ukrainian cities, conducted by specialists of the Department of Innovative Technologies in the Design of the Architectural Environment of O.M. Beketov Kharkiv National University of Urban Economy. Results of these researches was the authors' conviction that the existing methods and tools for adapting the architectural component of Ukrainian cities to global challenges do not fully meet the requirements of the time. In particular, the existing world rating systems for assessing the impact of architecture on the environment in terms of content and form are a very powerful factor in the formation of eco-positive architecture, but do not reflect the whole picture of its impact on the ecological systems of regions. For this reason, we have launched research aimed at the formation of a national system of voluntary environmental buildings’ certification, based on the “Coefficient of the Ecological Footprint of Architecture”. This coefficient is compiled as the sum of the coefficients for all elements of an architectural object and reflects the dynamics of its functioning during the life cycle – from production to disposal. Thanks to such a change in the lending system, it becomes possible to determine the “Environmental deficit of the region” and, through it, the level of negative and positive impact of architectural objects on the environment.

Generative Adversarial Network with Convolutional Wavelet Packet Transforms for Automated Speaker Recognition and Classification

Speech is an effective mode of communication that always conveys abundant and pertinent information, such as the gender, accent, and other distinguishing characteristics of the speaker. These distinctive characteristics allow researchers to identify human voices using artificial intelligence (AI) techniques, which are useful for forensic voice verification, security and surveillance, electronic voice eavesdropping, mobile banking, and mobile purchasing. Deep learning (DL) and other advances in hardware have piqued the interest of researchers studying automatic speaker identification (SI). In recent years, Generative Adversarial Networks (GANs) have demonstrated exceptional ability in producing synthetic data and improving the performance of several machine learning tasks. The capacity of Convolutional Wavelet Packet Transform (CWPT) and Generative Adversarial Networks are combined in this paper to propose a novel way of enhancing the accuracy and robustness of Speaker Recognition and Classification systems. Audio signals are dissected using the Convolutional Wavelet Packet Transform into a multi-resolution, time-frequency representation that faithfully preserves local and global characteristics. The improved audio features better precisely describe speech traits and handle pitch, tone, and pronunciation variations that are frequent in speaker recognition tasks. Using GANs to create synthetic speech samples, our suggested method GAN-CWPT enriches the training data and broadens the dataset's diversity. The generator and discriminator components of the GAN architecture have been tweaked to produce realistic speech samples with attributes quite similar to genuine speaker utterances. The new dataset enhances the Speaker Recognition and Classification system's robustness and generalization, even in environments with little training data. We conduct extensive tests on standard speaker recognition datasets to determine how well our method works. The findings demonstrate that, compared to conventional methods, the GAN-CWPTs combination significantly improves speaker recognition, classification accuracy, and efficiency. Additionally, the suggested model GAN-CWPT exhibits stronger generalization on unknown speakers and excels even with loud and poor audio inputs.