Architectural Engineering Research Articles

Analysis of the Construction of a Practical Teaching System for Architectural Engineering Technology Major in Vocational Colleges

Analysis of the Construction of a Practical Teaching System for Architectural Engineering Technology Major in Vocational Colleges

DYNAMIC FIREWALL CONFIGURATION FOR VIRTUAL NETWORKS: A COMPREHENSIVE AUTOMATION FRAMEWORK

In recent years, segment routing has emerged as a revolutionary traffic engineering architecture. Segment routing, however, results in control overheads since more packet headers need to be included. When segment headers get excessively long, the overheads can significantly lower the forwarding efficiency for a big network. We suggest the intelligent routing scheme for traffic engineering (IRTE), which can provide load balancing with minimal control overheads, in order to meet the better of two goals. We first frame the problem as a mapping problem that maps various flows to important diversion sites in order to obtain optimal performance. Second, by reducing the problem to a k-dense subgraph problem, we demonstrate that it is nondeterministic polynomial (NP)-hard. We create improved ant colony optimisation (IACO), a popular ant colony optimisation technique for network optimisation problems, to address this issue. We also develop and examine the theoretical performance of the load balancing algorithm with diversion routing (LBA-DR). Ultimately, we test the IRTE in various real-world topologies, and the findings demonstrate that the IRTE works better than previous algorithms. For example, while testing on Bell Canada topology, the maximum bandwidth is 24.6% less than that of traditional algorithms. Keywords: Segment Routing, Traffic Engineering, Control Overheads, Packet Headers, Forwarding Efficiency, Intelligent Routing Scheme.

A Thorough Analysis of the Address Corrector: Improving Validity of Data and Reliability

Abstract : This paper explores the creation of the Shatam Address Corrector, a complex system based on contemporary technologies like Java, Jetty, AWT, and Docker for robust backend development, HTML, CSS, and JavaScript for smooth frontend implementation, and Lucene for effective data indexing and searching. Fundamentally, the system is built to parse more than 10,000 addresses in ten seconds or less, demonstrating its fast processing power. The main goal of this project is to provide an intuitive user interface that will enable users to accurately and systematically arrange their address data in an easy-to-use manner. This system seeks to optimize address rectification by utilizing state-of-the-art technology design concepts. It focuses on improving accuracy and efficiency for addresses in the United States and Canada. This paper explains the broad objectives of the project, goes into great detail on the complex technological architecture of the Shatam Address Corrector, and emphasizes how crucial this system is to transforming the address correction industry. This research clarifies the critical role that the Shatam Address Corrector plays in developing address correction techniques for the present day by thoroughly examining its goals, design, and relevance.

Data science in economy and finance: A central bank perspective

Data science is fundamentally different from traditional data analysis, as it typically applies to large, complex and/or unstructured information sets. The role of data scientists, hence, lies at the intersection of three areas. The first is IT: central banks are increasingly aware that a modern technological architecture is crucial to reliably and securely deal with data. The second relates to the use of mathematical and statistical techniques to deal with the raw data at hand. This paper analyses how many different approaches can help support central banks’ operations, especially in the monetary policy and micro- and macroprudential areas, as well tasks related to the functioning of the payment system, financial inclusion, consumer protection and anti-money laundering. It presents how, in addition, the use of the new techniques could transform the whole production chain of official statistics, making it potentially more efficient, resilient and user-friendly. The third key area is to ensure close cooperation between data specialists and subject-matter experts involved in data science projects. Analysing statistics calls for an awareness of the way they have been compiled as well as of the complex factors that drive them — which are essential elements for transforming data into knowledge and taking informed policy decisions.

26‐1: Embedded a‐Si Photo‐Transistor Sensors Integration in Remote Optical Touch‐input Panel Using Four‐Mask Process Architecture Technology

An optical type touch‐input flat panel is designed. The driving system is based on the passive pixel sensor (PPS) array with amorphous silicon (a‐Si) TFT technology. The embedded sensing structure of the optical sensor is using the a‐Si TFT phototransistor and four‐mask process architecture technology. This paper presents a primary optical pixel sensor circuit that utilizes hydrogenated amorphous silicon photo‐transistor sensor. The a‐Si TFT phototransistor sensor is high reliability by using Multi‐N+ layer in the a‐Si TFT structure.

Predictive modeling of wide-shallow RC beams shear strength considering stirrups effect using (FEM-ML) approach

This paper presents an analysis and prediction of the shear strength of wide-shallow reinforced concrete beams, utilizing Finite Element Analysis (FEA) and machine learning techniques. The methodology involves validating a detailed Finite Element Model (FEM) against experimental results, conducting a parametric study, and developing three Machine Learning prediction equations. The FEM captures concrete and steel behaviors, including cracking and crushing for concrete and linear isotropic properties for steel reinforcement. Loading and boundary conditions are defined for accuracy and validated against 13 experimental specimens, exhibiting a maximum 8% and 12% difference in loads and deflections, respectively. A parametric study generates a dataset of 77 wide beam configurations, exploring variations in beam widths, concrete strengths, compression rebars, and shear reinforcement. This dataset is used to develop machine learning models, including “Genetic Programming (GP)”, “Evolutionary Polynomial Regression (EPR)”, and “Artificial Neural Network (ANN)”. Comparative analysis reveals GP and EPR models with over 95% correlation, while the ANN model outperforms with 99% accuracy. Sensitivity analysis underscores the significant influence of concrete strength and beam aspect ratio on shear strength. In conclusion, the study demonstrates the potential of FEA and machine learning models to predict shear strength in wide-shallow reinforced concrete beams, providing valuable insights for architectural design and engineering practices and emphasizing the role of concrete strength and beam geometry in shear behavior.

5G- Analysis and Characteristics in Comparison with Previous Generations

This paper explores the architecture and remarkable advantages of 5G technology in the current industry of wireless communication. The paper covers details of the recently developed 5th generation of networks and how its benefits overpower its drawbacks, majorly being its impact on health and environment. This study helps understanding 5G and highlights how this recent advancement has better chances of helping with wide area network connectivity, latency, economic growth, enhanced security features etc. While advancements in the cellular network technology continue to be one of the most important developments in the economic, telecom and healthcare sector among many others, many common beliefs about 5G which can be listed as its “drawbacks” have been brought to people’s attention recently, and with proper facts and studies, it can be easily proved how 5G, till this date, has no significant harm to any area, and simply has a few complexities which are natural with any advancement in technology. The paper covers the characteristics of the 5G network, and addresses common misconceptions and concerns surrounding health, security, and infrastructure.

The importance of first-principles tools for safety enhancement in the design of passenger ships in the case of flooding events

The design of a passenger ship is a complex process covering multiple aspects of naval architecture and marine engineering to address performance, functionality safety, and cost as primary objectives. Between them, safety is a key element focusing on the people on board. In this sense, ship safety in the case of flooding events needs proper estimation from the first stages of the design process employing an appropriate metric. To this end, safety can be evaluated as a risk by calculating the Potential Loss of Life. Thanks to a multi-level framework developed during project FLARE, it is possible to calculate the risk associated with an accident, increasing the level of reliability as the design process advances. The framework aims at employing first-principles tools from the early stages of the design process, abandoning static calculations and empirical formulae as soon as data is available to set up advanced calculation techniques. Then, the framework adopts rigid-body time-domain calculations for the flooding simulations, advanced evacuation analysis tools, and direct crash simulation to evaluate collision damages. The process allows for testing alternative design solutions for the ship to enhance safety. Investigating risk control options is also possible, considering active or passive systems such as fixed foam installations, deployable barriers, or crashworthiness. Such an approach allows for evaluating safer solutions, respecting other design constraints and cost-related aspects. The present work describes the risk assessment framework for the case of flooding events, together with the different levels of accuracy that can be achieved, showing the improvements that could be reached by employing alternative risk control options.

Design and Implementation of 3D Hologram using Machine Learning

Holographic means “entire recording” and originates from the Greek words “holo” (“whole”) and “graphic” (“message”). “Entire” refers to the recording of both the intensity and the phase of the object, as opposed to conventional photography, where only the intensity profile of the object is recorded. In a new stage in the organisation and control of the industrial value chain, interchangeably with the fourth industrial revolution. It has a broad vision with well-defined frameworks and reference designs, focusing on bridging physical infrastructure and digital technology in so- called cyber-physical systems. Apart from the other essential technologies, Holography is considered a new innovative technology that can completely transform the vision of Industry 4.0. In industrial applications, holographic technology is used for quality control in manufacturing and fracture testing, such as holographic nondestructive testing. Holography has a wide range of applications in medicine, the military, weather forecasting, virtual reality, digital art, and security. The fourth industrial revolution aims to provide automated asset monitoring, decision-making for corporate operations, and real-time network connectivity. This paper explores holography and its significant benefits through various development processes, features, and applications, where the focus is on ‘holography for Industry 4.0'. Hologram technology is a new industry trend and can impact multiple domains of Industry 4.0. Furthermore, the adoption of holographic technologies may improve the efficiency of existing products and services in other technology sectors such as architecture, 3D modelling, mechatronics, robotics, and healthcare and medical engineering

Review of Studies on Performance of Dowel Connections Loaded Perpendicular to Grain

Wood as a sustainable building material demonstrates significant advantages in terms of environmental protection, economy and functionality. Studies showed that adding 1.0m3 of wood could absorb 1.0kg of carbon dioxide, produce 730kg of oxygen, and fix 270kg of carbon, which plays an important role in ecological environment protection. In addition, in addition, wood has good thermal insulation performance, can adjust indoor humidity, beneficial to human health.China's wooden structure architecture has a long history. As an important technology in China's traditional architecture, mortise and tenon connection technology constitutes an important part of Chinese traditional architectural heritage through the insertion of wood components. As a prefabricated building form, modern wood structure has a history of more than 100 years in developed countries. The main forms include heavy wood structure, light wood structure, square wood wood structure and wood mixed structure. In recent years, wood structure architecture has attracted wide attention in scientific research and application in China. Whether for new construction or large-scale reconstruction projects, wood structure buildings are widely adopted because of their design flexibility, high strength and aesthetics, as shown in Figure 1.1. Modern wood structure buildings show the advantages of energy conservation and environmental protection, good earthquake resistance, convenient construction and safety and comfort, and its development is fully in line with the national sustainable development strategy.

Application of Landscape Smart Lighting in Construction Projects

Currently, to effectively construct high-quality smart cities and achieve comprehensive governance goals, various industries must embrace the transformation and upgrading of traditional management methods through the integration of new technologies. Among these, landscape smart lighting serves as a crucial tool for advancing smart city development. By judiciously applying this technology, it is possible to enhance traditional lighting methods and offer people novel experiences in their daily lives. Recognizing this importance, this article analyzes and organizes the content of landscape smart lighting, delves into its system characteristics, and summarizes its principles and practices in the field of architectural engineering as practical references for application scenarios.

Problems and Employability of Architectural Drafting Technology Students of Surigao Norte State University

This article entails the problems meet and employability of architectural drafting students of Surigao Norte State University (SNSU) under the College of Technology (COT). The faculty members in architectural drafting courses are more experienced and qualified to teach in this field. The enrolment in architectural drafting courses is increasing. On the other hand, the partners of SNSU in the OJT of the students are much established companies in the field of architecture and engineering. Instructors are having problems concerning facilities and acquisition of teaching materials. Students are considering facilities as their most problematic concern. The architectural drafting students in SSCT possess the necessary skills to be employed in architectural engineering works. Female architectural drafting students are more employable in terms of work ethics and technical skills compared to males. As problems on either facilities, curriculum, teacher, or administration/supervision become more prevalent, the employability of the students are affected..

Architectural technology and labour organisation at the late Neolithic Liangzhu City, Yangtze Delta region, China

Building the UNESCO World Cultural Heritage site of Liangzhu City and its hinterlands was an enormous undertaking that required an unprecedented level of architectural innovations, clever logistic planning, and sophisticated labour organisation. We draw on environmental, archaeological and experimental data on the preparation and construction of grass-wrapped clay blocks at the Liangzhu City and investigate the importance of technological innovations to understand architectural energetics and labour organisation behind the unprecedented urbanisation at Liangzhu and beyond in prehistoric Yangtze Delta region. We estimate that each clay block took only around 5 min to prepare by 2–4 workers. Considering digging and other tasks, a small group of 3–4 workers would have been the most efficient arrangement in the preparation of grass-wrapped clay blocks. We reproduced different types of clay blocks, classified their sizes, and identified the standard sized (45x15 × 15cm) clay blocks that match with archaeological finds. Our results also show that standard-sized clay blocks had a more optimal grass-earth ratio which increased the drainage efficiency of the built clay-blocked structures and their resistance to weathering in wet conditions. The different architectural technologies applied by the Liangzhu builders constituted the Liangzhu builders’ earth-building toolkit. To maximize the efficiency, labour was divided and organised according to different construction tasks. The clay-blocked structures and stone beddings were mostly built by smaller groups, who were responsible for the preparation, transportation and construction tasks. Mobilization and division of labour during these construction activities might not follow the classical top-down process. Instead, the need to apply different architectural technologies, each restrained by availability of resources, convenience of transportation, and/or intrinsic engineering properties, at construction sites in a predominantly aquatic environment, prompted a creative form of labour organisation. Our study therefore provides fresh insights into understanding labour organisation, social structure and power relations at the Liangzhu Civilisation.

A digital twin model of the axial temperature field of a DC cable for millisecond calculations

The most important features of digital twin technology for transmission and transformation equipment are symbiotic evolution and state prediction. In constructing the digital twin model for DC cables, the transient and steady-state temperature fields need to be considered comprehensively in the modeling process to consider the multi-physical field coupling, mathematical model, operational data, and environmental conditions in specific cases, which makes it difficult to satisfy the real-time requirements of the digital twin. To solve this problem, in this paper, a digital twin technology architecture for DC cables is proposed, and a neural network learning model is constructed to minimize the latency due to the complexity of the model simulation. Moreover, an efficient digital twin model that is based on the model-driven approach is developed for the fast computation of the axial temperature field of DC cables. The use of the Sequence-to-Sequence residual neural network algorithm for the reduced-order multi-physics field coupling modeling reduces the computational time and ensures as much accuracy as possible up to the finite element model simulation. The simulation results show that the use of the digital twin model reduces the simulation time from 275 s to 0.56 s, and the relative error between the accuracy of the digital twin model and the finite element model for the axial temperature field of the DC cable is 0.46 %. Finally, verification of the reasonableness and feasibility of the proposed method is carried out via an experimental platform according to the standard of CIGRE TB496. In particular, the maximum value of the DC cable temperature is verified to have a small error compared with the result of the Sequence-to-Sequence calculation under specific working conditions.

Transformative Impact of Technology in Landscape Architecture on Landscape Research: Trends, Concepts and Roles

The role of technology in landscape architecture (TLA) has significantly evolved since the 19th century, increasingly integrating with digital tools and technologies in the 21st century. Despite its growing importance, there is a notable deficiency in the scholarly literature regarding the progression of TLA trends and their interplay with the core domains and research themes within landscape research. The influence of TLA on landscape research remains ambiguous, especially concerning its ability to generate new knowledge and impact design and sustainability practices. Furthermore, there is a critical need to delineate how TLA differs from allied general digital technology tools and to identify specific specializations that are emerging within the TLA field. To explore the above gaps, this study utilized a mixed methods approach involving secondary data from peer-reviewed publications, primary data from the archival research of winning projects, and expert interviews based on the two major research types of “Research through Design (RTD)” and “Research for Design (RFD)” to explore the TLA’s contribution. This research is significant as it: (1) identified the trend of TLA; (2) conceptualized the TLA, and (3) identified its role in relation to the core domains and research themes of landscape research.

Institutional investor heterogeneity and green innovation in China: Does digital transformation matter?

This paper examines how different categories of institutional investors influence green innovation for Chinese-listed companies and investigates the impact of digital transformation on this relationship. Results show that pressure-insensitive investors significantly improve corporate green innovation, while pressure-sensitive institutions have no effect. Further evidence suggests this is due to the negative impact of long-term pressure-sensitive investors on green innovation. We further analyze whether digital transformation affects the relationship between institutional ownership heterogeneity and green innovation. Consistent with the view that digital transformation promotes timely information dissemination and alleviates information asymmetry, our findings demonstrate that both pressure-insensitive institutional investors and short-term pressure-sensitive institutional investors promote green innovation in firms with higher levels of digital transformation. Further analyses reveal that digital transformation at the city level amplifies the influence of institutional investors on green innovation, and the underlying technology architecture provides more value to the institutional ownership heterogeneity−green innovation nexus.

Synchronous Regulation of Hydrophobic Molecular Architecture and Interface Engineering for Robust WORM‐Type Memristor

AbstractIn the context of human active response to exponentially increasing data volumes, memristors have emerged as a focal point in systematic problem‐solving approaches. Particularly, organic memristors, characterized by excellent scalability, flexibility, and 3D stacking capabilities, have shown its tremendous potential in innovative electronic applications. However, the modulation of molecular assembly and interface interaction at the electrode surface poses a challenging task, despite their crucial role in determining the memristive performance. Herein, a collaborative method involving hydrophobic molecular design and interface engineering is proposed to generate high‐quality nanofilms with optimal photoelectric and electrochemical properties. By subjecting the bottom electrode to O2 plasma treatment and chemical modification using a hydrophobic ionic liquid poly(diallyldimethylammonium) bis(trifluoromethanesulfonyl)imide (PTFSI), the hydrophobic compound DN demonstrates exceptional affinity and stronger intermolecular interactions with the electrode surface. Consequently, the two‐terminal device array comprising Al/DN@PTFSI/ITO exhibits robust non‐volatile write‐once‐read‐many times (WORM) memory behavior, resulting in a tripling production yield from 30% to 92% along with a lower threshold voltage of 1.5 V, higher ON/OFF current ratio of 103 and excellent stability. This study presents a versatile approach to optimize the film assembly and material/electrode interface, thereby accelerating the development of organic memristors toward future applications.

Improving non-destructive testing methods for detecting cavity damage and internal defects in stone cultural relics: A focus on ultrasonic testing and acoustic tapping technology

This study employs advanced ultrasonic tomography and Grasshopper software to investigate the internal anomalies within stone materials. We aim to enhance the non-destructive testing (NDT) methods with potential applications extending to modern architecture and stone engineering. Cavity damage and internal defects threaten the structural stability of stone cultural relics. Traditional non-destructive testing methods, while practical, have limitations in assessing these relics comprehensively. This paper proposes an enhanced ultrasonic testing method based on mathematical analysis to accurately detect cavity damage in stone cultural relics. We also investigate imaging techniques for internal defects, combining ultrasonic testing with Grasshopper software for efficient and accurate defect characterization. Additionally, we introduce an acoustic tapping method for detecting internal defects in ancient building stones. Verified through field tests and data analysis, this method is non-invasive, accurate, and fast. The process of detecting stone defects using this technology, along with data analysis methods, experimental results, and application effects, are detailed. This research contributes to the improved preservation and restoration of ancient buildings and extends to other fields, such as modern architecture and stone engineering, highlighting its significance in cultural heritage conservation.

Studying the phenomenon of self-compassion in the context of preventing academic procrastination

Introduction. Currently, the presence of procrastination causes contradictions in modern conditions of society, which places special demands on the independence, initiative, motivation and responsibility of the individual. Scientific research describes in sufficient detail the factors that cause procrastination. There is less research on the relationship between procrastination and such an aspect of personality as self-compassion. The purpose of our study is to examine the relationship between procrastination and self-compassion among university students. Materials and methods. The sample consisted of 157 students of the St. Petersburg State University of Architecture and Civil Engineering, of which 77 boys and 80 girls aged 19 to 22 years. The assumption that procrastination depends on self-compassion and self-esteem was tested using the Self-Compassion Scale by K. Neff, adapted by K.A. Chistopolskaya et al., test «Degree of severity of procrastination» (SVP) by M.A. Kiseleva, N.E. Shustova, O.V. Karina and the test «Personal Self-Esteem» by O.I. Motkova. The obtained empirical results were verified using the Kolmogorov–Smirnov test, Student's t-test, Pearson correlation analysis, and regression analysis. Results. It was revealed that 28% of students have a high level of self-compassion, 69% have an average level, 3% do not show self-compassion. The level of self-compassion among girls was significantly higher (79.3±10.0) than among boys (75.5±12.2). There is a negative relationship between indicators of self-compassion and indicators of procrastination: with a high level of self-compassion in a student, motivational insufficiency (r=- 0.24; p≤0.05), procrastination (r=-0.21; p≤0.05), anxiety (r=-0.31; p≤0.05). A positive relationship between self-compassion and self-esteem indicators was found. As a result of regression analysis, two components of self-compassion influencing procrastination were identified: self-isolation (B = -0.44) and excessive identification with negative emotions (B = -0.24). Conclusion. The results obtained show the need to develop self-compassion as a factor reducing personal procrastination.

High Rates of Eye Surgery Cancellation in Veterans Related to Mental Health.

Approximately 9 million veterans receive health care at the Veterans Health Administration, many of whom have psychiatric illnesses. The military continues to have higher rates of psychiatric illness compared to the civilian population. Having a diagnosis such as posttraumatic stress disorder or depression may create challenges in using health care services, such as surgery. The aim of this study was to evaluate eye surgery cancellation, risk factors for cancellation, and areas for intervention within the VA. This was a single-center retrospective cohort study. The Veteran Health Information Systems and Technology Architecture were queried to identify all surgical requests at the West Los Angeles VA in 2019. Data collection included sociodemographic information and comorbid medical conditions, including psychiatric illness. Exploratory analyses using univariate logistic regression were used to evaluate factors associated with surgery cancellation. A total of 1,115 surgical requests were identified with a cancellation rate of 23.7% (n = 270). Sociodemographic factors were similar between those with completed and cancelled surgery. However, having a psychiatric diagnosis correlated with surgery cancellation. For all subspecialties, patients with schizophrenia were more likely to have cancellation (odds ratio [OR], 2.53, P = .04). For retina surgery, patients with posttraumatic stress disorder were more likely to have cancellation (OR, 4.23, P = .01). Glaucoma patients with anxiety (OR, 5.78, P = .05) and depression (OR, 4.05, P = .04) were more likely to have cancellation. There was a significant amount of eye surgery cancellations in veterans with variation by subspecialty and comorbid conditions. Having a psychiatric illness was correlated with increased rates of surgery cancellation amongst veterans. Areas to improve surgical utilization include risk stratification and increased support of vulnerable patients before surgery.