Architectural Components Research Articles

Analytical examination of dynamic elements in modern architectural facades for advanced structural aesthetics

Introduction: The visual appeal and distinctiveness of a building’s external appearance can be enhanced by incorporating aesthetically pleasing and structurally coherent components, such as diagrids and external bracings. These components not only contribute to the building’s visual appeal but also communicate its structural logic. The aim of this research is to investigate how architectural surfaces can contribute to a building’s urban identity by integrating visually appealing and structurally sound structural systems.Methods: The research focuses on analyzing and understanding the formal structure, generating diverse patterns, and assessing their impact on stability. The goal is to develop architectural surface components that are both aesthetically pleasing and proficient in their application. The study involves analyzing architectural projects that address surfaces in alignment with structural connections and various connecting and modulating mechanisms. Significant architectural achievements from different historical periods were examined to construct a comprehensive knowledge framework.Results: The research conducted a detailed analytical and descriptive investigation into the intricate mechanisms of form surfaces within Modernity and Deconstruction architecture and their impact on structural relationships. The study revealed that by integrating structural connections and modulating mechanisms, it is possible to create architectural surface components that enhance a building’s visual appeal, artistic expression, and urban identity while maintaining structural stability and balance.Conclusion: The research concludes that integrating structural connections and modulating mechanisms into architectural surface components can significantly enhance a building’s visual appeal, artistic expression, and urban identity. By developing aesthetically pleasing and structurally sound elements, such as diagrids and external bracings, architects can create buildings that not only communicate their structural logic but also contribute to the overall urban fabric. This study provides valuable insights for architects and designers seeking to enhance the visual and structural qualities of their buildings.

Analysis of Pigments Unearthed from the Yungang Grottoes Archaeological Excavations

The Yungang Grottoes, excavated during the 5th to 6th centuries AD, stand as a pinnacle of Buddhist sculpture, representing a precious world cultural heritage. Since their excavation, the grottoes have undergone multiple phases of painting, with a significant amount of pigment still present on the surfaces of the stone carvings. Since the 1990s, two large-scale archaeological excavations have been conducted on both the front ground and the summit of Yungang Grottoes. During these excavations, various artifacts with accompanying pigments were unearthed, encompassing stone carvings, grinding tools, architectural components, fragments of murals, and remnants of clay sculptures, spanning the historical periods of the Northern Wei, Liao-Jin, and Ming-Qing dynasties. Using portable X-ray fluorescence spectrometry, portable microscopy, polarizing microscopy, scanning electron microscopy–energy dispersive X-ray spectroscopy, and confocal Raman microscopy, we conducted a comprehensive analysis of these painted elements. The investigation revealed the presence of hematite, vermilion, goethite, malachite, calcium carbonate, lead white, and ivory black pigments in the Northern Wei samples. The Liao-Jin samples exhibited hematite, while the Ming-Qing samples contained vermilion, minium, atacamite, lead white, and Prussian blue.

A real-time wearable AR system for egocentric vision on the edge

Real-time performance is critical for Augmented Reality (AR) systems as it directly affects responsiveness and enables the timely rendering of virtual content superimposed on real scenes. In this context, we present the DARLENE wearable AR system, analysing its specifications, overall architecture and core algorithmic components. DARLENE comprises AR glasses and a wearable computing node responsible for several time-critical computation tasks. These include computer vision modules developed for the real-time analysis of dynamic scenes supporting functionalities for instance segmentation, tracking and pose estimation. To meet real-time requirements in limited resources, concrete algorithmic adaptations and design choices are introduced. The proposed system further supports real-time video streaming and interconnection with external IoT nodes. To improve user experience, a novel approach is proposed for the adaptive rendering of AR content by considering the user’s stress level, the context of use and the environmental conditions for adjusting the level of presented information towards enhancing their situational awareness. Through extensive experiments, we evaluate the performance of individual components and end-to-end pipelines. As the proposed system targets time-critical security applications where it can be used to enhance police officers’ situational awareness, further experimental results involving end users are reported with respect to overall user experience, workload and evaluation of situational awareness.

Mechanically robust and multifunctional Ti3C2Tx MXene composite aerogel for broadband EMI shielding

Because of its high electrical conductivity and low density, Ti3C2Tx MXene aerogel is thought to be a promising electromagnetic interference (EMI) shielding material. However, it is suffering from high reflection shielding and poor mechanical strength, which naturally hinders its practical application. Herein, we constructed PDMS-encapsulated Fe3O4/multi-walled carbon nanotubes (MWCNTs)/Ti3C2Tx MXene aerogel by combining the bi-directional freeze-drying technique with vacuum impregnation. The lamellar porous architecture and rational components endow the PDMS-encapsulated composite aerogel with superior EMI shielding properties in the X- and Ku-bands. Specifically, the optimal total shielding effectiveness (SET) of the PDMS-encapsulated composite aerogel (3 mm) could reach 43.6 dB, whereas the corresponding reflection shielding effectiveness (SER) is only 7 dB (approximately 16.7 % of SET). The shielding mechanism was also comprehensively disclosed. Simultaneously, contributed by the synergistic effect of lamellar porous structure and PDMS, the PDMS-encapsulated composite aerogel possesses satisfactory compressive strength (28.62 MPa) and tensile strength (1.67 MPa). Additionally, the PDMS-encapsulated composite aerogel also exhibits promising applications in thermal insulation.

Digital twin-based reinforcement learning framework: application to autonomous mobile robot dispatching

ABSTRACT This paper proposes a new framework for embedding an Intelligent Digital Twin (DT) in a production system with the objective of achieving more efficient real-time production planning and control. For that purpose, the Intelligence Layer is based on Reinforcement Leaning (RL) and Deep RL (DRL) algorithms. The use of this control instead of parametric simulation-based optimization approach allows to benefit from the separation between the training and execution phase. To ensure consistency and reusability, this work presents a standardized framework, based on a formal methodology, that specifies how the various components of the DT-based RL architecture interact over time to achieve essential real-time concurrency and synchronization aspects. Experiments are conducted in a small-scale production system where material handling operations are performed by an Autonomous Mobile Robot (AMR) in an Industry 4.0 Laboratory. Results showed how synchronized state updates between the Physical and Cyber World are used within the Decision Layer to ensure real-time response for the AMR dispatching requests. Finally, to deal with continuous and high-dimensional state spaces, the Deep Q-Network is implemented. The findings of an extensive computational study reveal that implementing the DT-based DRL solution leads to improved efficiency and robustness when compared to conventional dispatching rules.

Simultaneously improving accuracy and computational cost under parametric constraints in materials property prediction tasks

Modern data mining techniques using machine learning (ML) and deep learning (DL) algorithms have been shown to excel in the regression-based task of materials property prediction using various materials representations. In an attempt to improve the predictive performance of the deep neural network model, researchers have tried to add more layers as well as develop new architectural components to create sophisticated and deep neural network models that can aid in the training process and improve the predictive ability of the final model. However, usually, these modifications require a lot of computational resources, thereby further increasing the already large model training time, which is often not feasible, thereby limiting usage for most researchers. In this paper, we study and propose a deep neural network framework for regression-based problems comprising of fully connected layers that can work with any numerical vector-based materials representations as model input. We present a novel deep regression neural network, iBRNet, with branched skip connections and multiple schedulers, which can reduce the number of parameters used to construct the model, improve the accuracy, and decrease the training time of the predictive model. We perform the model training using composition-based numerical vectors representing the elemental fractions of the respective materials and compare their performance against other traditional ML and several known DL architectures. Using multiple datasets with varying data sizes for training and testing, We show that the proposed iBRNet models outperform the state-of-the-art ML and DL models for all data sizes. We also show that the branched structure and usage of multiple schedulers lead to fewer parameters and faster model training time with better convergence than other neural networks. Scientific contribution: The combination of multiple callback functions in deep neural networks minimizes training time and maximizes accuracy in a controlled computational environment with parametric constraints for the task of materials property prediction.

Challenges of Digital Education in India

During this pandemic situation across the world, the education system has completely changed. The internet and distant learning, which is commonly referred to as online instruction, are important components of the country's educational architecture. It is undeniable that online education provides sufficient benefits to young children. When all is said and done, there are numerous disadvantages to online education. The few disadvantages of online schooling are restricted cooperative learning, schedule expansion, and exertion. But considering the situation across the world we should move. Under consideration of problems discussing some suggestions for solving the problems caused. The main objective of this review is about electricity, network and conceptual understanding problems of students by digital education and how the system changed by this pandemic.

Exploring Challenges Faced by Engineering Students in Graphic Preparations of Perspective Geometry

Perspective geometry is a fundamental, challenging, and captivating subject within the engineering bachelor's degree program. It holds significant importance in developing graphic skills, analytical abilities, sketching proficiency, and comprehension of drawings. Moreover, it plays a crucial role in organizing the architectural components of a bachelor's thesis. However, the teaching and learning of perspective geometry often reveal various difficulties and shortcomings. Moreover, one of the various systems of symbols and languages created by global cultures is the graphical language, which is an exceptional and unparalleled language for understanding scientific and technical information. This language is considered the oldest international language. Every visual piece of information in various processes of human life has been formed through the graphical language, which is composed of various geometric shapes. In this research, data has been gathered from the perspectives of first-year students from the 2013 batch regarding the difficulties encountered in perspective geometry. A questionnaire was distributed to collect their opinions, and three graphical tasks with different levels of complexity were given to the students. The results obtained from this study indicate that employing suitable teaching methods and providing adequate resources can alleviate most of the learning difficulties associated with graphic skills. Instructors also play a pivotal role in resolving learning obstacles. Therefore, efforts should be made to enhance the quality of teaching graphic subjects by updating the content and curriculum of educational programs and improving teaching methods through the use of technology. In higher education institutions, conditions for fostering students' professional knowledge, enhancing their ability to draw maps and create technical documents can be facilitated through computer graphics education. Updating the teaching methods plays a crucial role in improving the quality of graphic education. The mentioned factors provide a suitable environment for the growth of graphic knowledge and the implementation of projects related to professional subjects.

Transformation of an Industrial Zone Into an Urban Park: Reconstruction of Buildings

Statement of the problem. To solve the problem of shortage of land resources in the territory of modern cities, a promising direction is the redevelopment of derelict manufacturing plants, including the reuse of unexploited industrial buildings for cultural and commercial purposes. The main task of the Changchun Vanke Blue Mountain project (Jilin Province, China) presented in this article was to maximize the preservation of cultural heritage and the unique atmosphere of the industrial zone while creating an entertainment park. Results. The article describes the technical solutions that made it possible to implement this concept as part of the buildings’ reconstruction of the gear wheel manufacturer and the stamping shop with the technical office. Not only the preservation of ruins was implemented, but also the maximum possible rehabilitation of buildings using original building materials, along with the addition of new annexes built in a modern style. The features of the main street design with an emphasis on the architectural components of reconstructed buildings are provided. Conclusions. The implementation of the Changchun Vanke Blue Mountain project made it possible to popularize the history of the former plant, to show its crucial role in the formation of the city. At the same time, it was possible to create original architectural solutions using modern methods of architectural reconstruction of industrial facilities.

Sustainable Optimizing Performance and Energy Efficiency in Proof of Work Blockchain: A Multilinear Regression Approach

The energy-intensive characteristics of the computations performed by graphics processing units (GPUs) in proof-of-work (PoW) blockchain technology are readily apparent. The optimization of GPU feature configuration is a complex subject that significantly impacts a system’s energy consumption and performance efficiency. The primary objectives of this study are to examine and improve the energy consumption characteristics of GPUs, which play a crucial role in the functioning of blockchains and the mining of cryptocurrencies. This study examines the complex relationship between GPU configurations and system architecture components and their effects on energy efficiency and sustainability. The methodology of this study conducts experiments involving various GPU models and mining software, evaluating their effectiveness across various configurations and environments. Multilinear regression analysis is used to study the complex relationships between critical performance indicators like power consumption, thermal dynamics, core speed, and hash rate and their effects on energy efficiency and performance. The results reveal that strategically adjusting GPU hardware, software, and configuration can preserve substantial energy while preserving computational efficiency. GPU core speed, temperature, core memory speed, ETASH algorithms, fan speed, and energy usage significantly affected the dependent computational-efficiency variable (p = 0.000 and R2 = 0.962) using multilinear regression analysis. GPU core speed, temperature, core memory speed, fan speed, and energy usage significantly affected efficient energy usage (p = 0.000 and R2 = 0.989). The contributions of this study offer practical recommendations for optimizing the feature configurations of GPUs to reduce energy consumption, mitigate the environmental impacts of blockchain operations, and contribute to the current research on performance in PoW blockchain applications.

The Creation of “Sacred Place” through the “Sense of Place” of the Daci’en Wooden Buddhist Temple, Xi’an, China

After the Industrial Revolution, new technologies and architectural forms gradually replaced China’s wooden construction system, which had lasted for thousands of years. The architectural narrative also turned a new page. As pieces of architectural and cultural heritage and as the residence of “gods”, wooden Buddhist temples carry the indelible imprints of history and religion and have become a healing place or spiritual home for people living in urban areas. In order to preserve the local cultural context and explore the creation of a spiritual “sacred place”, this study traces the spiritual and cultural value of Xi’an’s wooden Buddhist temple through ethnographic qualitative methods of text analysis, observation and interviews. The case study examines the metaphorical symbolism of the architecture’s “sense of place” and religion in terms of architectural structure and components, and the advantages of creating a “sacred place” are examined based on the characteristics of wooden materials. The results show that the design elements of wooden Buddhist temples connect cultural identity and collective memory, which are inseparable from religion, and because of the material properties of wood, they sublimate the sacred atmosphere of religion. Moreover, identifying the “sense of place” and the atmosphere of sacred spaces through the structure, components, and material characteristics of wooden temple architecture offers a new perspective that focuses on architectural emotions and creates a new topic of “sacred places”. Such temples have the potential to enhance human spiritual health and well-being.

An image encryption algorithm based on multi-layered chaotic maps and its security analysis

This study introduces a novel symmetric image encryption algorithm that employs a multi-layered architecture of chaotic maps, incorporating both confusion and diffusion components. The selected chaotic maps, namely Aizawa, Ricker, Sine-Circle, and Chirikov, have been well-established as effective sources of chaos in the existing literature. Within the proposed algorithm, these chaotic maps are strategically utilised in distinct layers to enhance the security of the encrypted image. The algorithm demonstrates applicability to real-world scenarios, distinguished by its simplicity, high-speed performance, and low computational complexity. The efficacy of the method is underlined by its dependence on both original images and secret keys, rendering it resilient against brute force and differential attacks. Rigorous experimentation, encompassing correlation, histogram analysis, NBCR, NPCR, UACI, PSNR, and NIST values, establishes the proposed encryption algorithm's robustness and security against diverse attack modalities, including differential and statistical approaches. These findings position the algorithm as a compelling solution for safeguarding sensitive information in various practical applications.

Identification and empowerment of capabilities and potentials in urban tourism with an approach to enhancing brand image and personality: A case study of Tabriz City

<p>This research focuses on identifying and enhancing the capabilities and potentials of urban tourism with the aim of improving the brand image and personality in Tabriz City. The research methodology, given its practical nature, is based on the analytical-survey method. The statistical population includes all city managers and experts in the tourism sector of Tabriz City. The data were analyzed using SPSS software, and the ANP and TOPSIS Fuzzy decision-making models were employed for prioritizing criteria. The results indicate that Tabriz City possesses exceptional tourism power, capacity, and potential. The examination of urban tourism capabilities and potentials in Tabriz demonstrates that its tourism capacity is particularly pronounced in the social, cultural, traditional, historical, and architectural domains. The social and cultural identity index of the city (celebrities, music) with a normalized weight of 0.0277, the presence of historical entities in the city with a normalized weight of 0.0274, the old context with traditional architecture (houses, mosques, etc.) with a normalized weight of 0.0272, great variety in souvenirs and food products with a normalized weight of 0.0271, creating a sense of belonging to a neighborhood among residents with a normalized weight of 0.0270, and special customs in the city (food styles, etc.) with a normalized weight of 0.0270 are among the most important indicators. Therefore, city managers and officials in the tourism sector of Tabriz should pay special attention to the social and cultural capacities and historical and architectural components to introduce Tabriz as a cultural and historical city at both the national and international levels. The tourism planning for Tabriz should be based on the city's cultural, architectural, and historical attractions.<strong></strong></p>

On the History of the Development of Daylighting and Light-Conducting Systems in the History of Architecture

The history of the development of human civilization shows us how the use of daylighting could influence the development of world architecture. In the article, the author tried to show how in different eras daylight influenced not only civil architecture, but also how light became an important sacred component of religious architecture. The article examines the influence of daylight on architecture throughout history, in certain historical periods and architectural techniques using daylighting.

THE ROLE OF INTERNATIONAL TRANSPORT LOGISTICS IN OPTIMIZING TRANSPORT INFRASTRUCTURE ARCHITECTURES

Nowadays, transport infrastructure is a crucial component of any social and economic system. The arrangement of infrastructure is a top priority in economic activity due to the globalization of international logistics. This study aims to comprehensively analyse the transport infrastructure system regarding architectural objects. It also seeks to identify the main issues of the management paradigm in the industry and options for solving them. The research employed general scientific methods of cognition, including logical and structural analysis, comparison, theoretical modelling, abstraction, induction, and deduction, as well as statistical methods, specification, generalization, and formalization. The article examines innovative approaches to developing transport infrastructure in the international logistics system. The authors analysed the main issues, challenges, and achievements of managing the architectural component of transport infrastructure. The paper concludes that the effective use of transport infrastructure capabilities is essential for increasing the productivity of economic processes. The authors also identified the position and role of architectural objects in the international logistics system.

Empowering Edge Intelligence: A Comprehensive Exploration of Fog Computing in the Era of Real-time Data Processing and the Internet of Things

Fog computing, a paradigm that extends cloud computing closer to the edge of the network, has emerged as a transformative solution to address the growing demands of latency-sensitive applications and the massive influx of data from the Internet of Things (IoT). Unlike traditional cloud computing, which centralizes data processing and storage in distant data centers, fog computing leverages a distributed architecture, bringing computation, storage, and networking resources closer to the end-users and devices. This abstract explores the key concepts, principles, and advantages of fog computing. By distributing computing resources across a continuum from the cloud to the edge, fog computing minimizes latency, enhances efficiency, and optimizes network bandwidth. The seamless integration of edge devices into the computing infrastructure facilitates real-time processing of data, enabling timely decision-making and improved user experiences in applications ranging from autonomous vehicles to smart cities. Furthermore, the abstract delves into the architectural components of fog computing, including fog nodes, gateways, and the interaction with cloud resources. The dynamic nature of fog environments allows for scalable and flexible deployments, catering to the diverse requirements of modern applications. Security and privacy concerns are also addressed, emphasizing the need for robust mechanisms to protect data integrity and user confidentiality in decentralized computing environments. As the digital landscape continues to evolve, fog computing emerges as a pivotal enabler of edge intelligence, empowering organizations to harness the benefits of real-time data processing and analysis at the edge of the network. The adoption of fog computing signifies a paradigm shift in the way we approach data management and processing, opening new avenues for innovation and efficiency in the era of the Internet of Things. Keywords: IOT, Fog Computing, Autonomous Vehicles.

A chromosome arm from Thinopyrum intermedium × Thinopyrum ponticum hybrid confers increased tillering and yield potential in wheat

Tiller number is a key component of wheat plant architecture having a direct impact on grain yield. Because of their viability, biotic resistance, and abiotic stress tolerance, wild relative species are a valuable gene source for increasing wheat genetic diversity, including yield potential. Agropyron glael, a perennial hybrid of Thinopyrum intermedium and Th. ponticum, was created in the 1930s. Recent genome analyses identified five evolutionarily distinct subgenomes (J, Jst, Jvs, Jr, and St), making A. glael an important gene source for transferring useful agronomical traits into wheat. During a bread wheat × A. glael crossing program, a genetically stable translocation line, WT153397, was developed. Sequential in situ hybridizations (McGISH) with J-, St-, and D-genomic DNA probes and pSc119.2, Afa family, pTa71, and (GAA)7 DNA repeats, as well as molecular markers specific for the wheat 6D chromosome, revealed the presence of a 6DS.6Jvs Robertsonian translocation in the genetic line. Field trials in low-input and high-input breeding nurseries over four growing seasons demonstrated the Agropyron chromosome arm’s high compensating ability for the missing 6DL, as spike morphology and fertility of WT153397 did not differ significantly from those of wheat parents, Mv9kr1 and ‘Mv Karizma.’ Moreover, the introgressed 6Jvs chromosome arm significantly increased the number of productive tillers, resulting in a significantly higher grain yield potential compared to the parental wheat cultivars. The translocated chromosome could be highly purified by flow cytometric sorting due to the intense fluorescent labeling of (GAA)7 clusters on the Thinopyrum chromosome arm, providing an opportunity to use chromosome genomics to identify Agropyron gene variant(s) responsible for the tillering capacity. The translocation line WT153397 is an important genetic stock for functional genetic studies of tiller formation and useful breeding material for increasing wheat yield potential. The study also discusses the use of the translocation line in wheat breeding.

Effect of 6G Network in our Environment

The ongoing deployment of 5G cellular systems is continuously exposing the inherent limitations of this system, compared to its original premise as an enabler for Internet of Everything applications. These 5G drawbacks are spurring worldwide activities focused on defining the next-generation 6G wireless system that can truly integrate far-reaching applications ranging from autonomous systems to extended reality. Despite recent 6G initiatives1, the fundamental architectural and performance components of 6G remain largely undefined. In this paper, we present a holistic, forward-looking vision that defines the tenets of a 6G system. We opine that 6G will not be a mere exploration of more spectrum at high-frequency bands, but it will rather be a convergence of upcoming technological trends driven by exciting, underlying services. In this regard, we first identify the primary drivers of 6G systems, in terms of applications and accompanying technological trends. Then, we propose a new set of service classes and expose their target 6G performance requirements. We then identify the enabling technologies for the introduced 6G services and outline a comprehensive research agenda that leverages those technologies. We conclude by providing concrete recommendations for the roadmap toward 6G. Ultimately, the intent of this article is to serve as a basis for stimulating more out-of-the-box research around 6G.

Comprehensive Study of SDC Memristors for Resistive RAM Applications

Memristors have garnered considerable attention within the scientific community as devices for emerging construction of Very Large Scale Integration (VLSI) systems. Owing to their inherent properties, they appear to be promising candidates for pivotal components in computational architectures, offering alternatives to the conventional von Neumann architectures. This work has focused on exploring potential applications of Self-Directed Channel (SDC) memristors as novel RRAM memory cells. The introductory section of the study is dedicated to evaluating the repeatability of the tested memristors. Subsequently, a detailed account of the binary programming testing process for memristors is provided, along with illustrative characteristics depicting the impact of programming pulses on a memory cell constructed from a memristor. A comprehensive data analysis was then conducted, comparing memristors with varying types of doping. The results revealed that SDC memristors exhibit a high level of switching, certainty between the Low Resistance State (LRS) and High Resistance State (HRS), suggesting their capability to facilitate the storage of multiple bits within a single memory cell.

Building Maintenance Priority Decision Support System Using the Method Profile Matching

Along with the increasing age of a building, maintenance activities become things that need to be done to minimize damage that occurs such as damage to the ceiling or ceramics. Therefore, this study aims to determine the priority of building elements in the treatment of architectural components in buildings A and B ITK campus using Profile Matching method. Based on the results of analysis and observations in the field, the elements that are the main priority in the architectural component of Building A are ceiling elements, the second priority element is sanitary elements, the third priority element is floor elements and door and window elements, the fourth priority element is painting elements, and the last priority element is Wall pair elements. Whereas in the architectural component of Building B, the main priority elements are ceiling elements and sanitary elements, the second priority element is the wall pair element, the third priority element is the floor element and the door and window element, and the last priority element is the painting element.