Architectural Engineering Research Articles

Covalent Organic Framework-Based Materials for Advanced Lithium Metal Batteries.

Lithium metal batteries (LMBs), with high energy densities, are strong contenders for the next generation of energy storage systems. Nevertheless, the unregulated growth of lithium dendrites and the unstable solid electrolyte interphase (SEI) significantly hamper their cycling efficiency and raise serious safety concerns, rendering LMBs unfeasible for real-world implementation. Covalent organic frameworks (COFs) and their derivatives have emerged as multifunctional materials with significant potential for addressing the inherent problems of the anode electrode of the lithium metal. This potential stems from their abundant metal-affine functional groups, internal channels, and widely tunable architecture. The original COFs, their derivatives, and COF-based composites can effectively guide the uniform deposition of lithium ions by enhancing conductivity, transport efficiency, and mechanical strength, thereby mitigating the issue of lithium dendrite growth. This review provides a comprehensive analysis of COF-based and derived materials employed for mitigating the challenges posed by lithium dendrites in LMB. Additionally, we present prospects and recommendations for the design and engineering of materials and architectures that can render LMBs feasible for practical applications.

Memristor In Non-Volatile Memory Technology and Computer Architecture

Memristor In Non-Volatile Memory Technology and Computer Architecture

BAOS-CNN: A novel deep neuroevolution algorithm for multispecies seagrass detection.

Deep learning, a subset of machine learning that utilizes neural networks, has seen significant advancements in recent years. These advancements have led to breakthroughs in a wide range of fields, from natural language processing to computer vision, and have the potential to revolutionize many industries or organizations. They have also demonstrated exceptional performance in the identification and mapping of seagrass images. However, these deep learning models, particularly the popular Convolutional Neural Networks (CNNs) require architectural engineering and hyperparameter tuning. This paper proposes a Deep Neuroevolutionary (DNE) model that can automate the architectural engineering and hyperparameter tuning of CNNs models by developing and using a novel metaheuristic algorithm, named 'Boosted Atomic Orbital Search (BAOS)'. The proposed BAOS is an improved version of the recently proposed Atomic Orbital Search (AOS) algorithm which is based on the principle of atomic model and quantum mechanics. The proposed algorithm leverages the power of the Lévy flight technique to boost the performance of the AOS algorithm. The proposed DNE algorithm (BAOS-CNN) is trained, evaluated and compared with six popular optimisation algorithms on a patch-based multi-species seagrass dataset. This proposed BAOS-CNN model achieves the highest overall accuracy (97.48%) among the seven evolutionary-based CNN models. The proposed model also achieves the state-of-the-art overall accuracy of 92.30% and 93.5% on the publicly available four classes and five classes version of the 'DeepSeagrass' dataset, respectively. This multi-species seagrass dataset is available at: https://ro.ecu.edu.au/datasets/141/.

The Effect of Applying Artificial Intelligence in Architecture College Developing Design Process

In the last 20 years, the world has seen increasing use of Artificial intelligence (AI) in many disciplines, one of these disciplines is Architecture. This research aims to study the effect of using AI in Architecture schools, especially design studios, in which phase, and in what percentage. The methodology of the research is applied for AI programs in four main design steps: The concept phase developing the design, coloring and developing the elevations, rendering phasing by using the AI, and distributing a survey to Design 7 students to register their responses using AI in Architecture design selected case studies from students work was selected to reflect the research works. The results from the survey show that the students achieved applying AI in concept development by 75%, in the development design process by 72.54%, in coloring by 50%, in rendering by 48%, sustainability by 70%, and in developing building form and structure by 72.3%. The conclusion of the research recommends applying AI in the whole design process including concept development, developing design process, coloring, rendering, form, and structure under the teacher's supervision, and recommends teaching AI as a course in architecture engineering colleges.

KLSD: a kinase database focused on ligand similarity and diversity.

Due to the similarity and diversity among kinases, small molecule kinase inhibitors (SMKIs) often display multi-target effects or selectivity, which have a strong correlation with the efficacy and safety of these inhibitors. However, due to the limited number of well-known popular databases and their restricted data mining capabilities, along with the significant scarcity of databases focusing on the pharmacological similarity and diversity of SMIKIs, researchers find it challenging to quickly access relevant information. The KLIFS database is representative of specialized application databases in the field, focusing on kinase structure and co-crystallised kinase-ligand interactions, whereas the KLSD database in this paper emphasizes the analysis of SMKIs among all reported kinase targets. To solve the current problem of the lack of professional application databases in kinase research and to provide centralized, standardized, reliable and efficient data resources for kinase researchers, this paper proposes a research program based on the ChEMBL database. It focuses on kinase ligands activities comparisons. This scheme extracts kinase data and standardizes and normalizes them, then performs kinase target difference analysis to achieve kinase activity threshold judgement. It then constructs a specialized and personalized kinase database platform, adopts the front-end and back-end separation technology of SpringBoot architecture, constructs an extensible WEB application, handles the storage, retrieval and analysis of the data, ultimately realizing data visualization and interaction. This study aims to develop a kinase database platform to collect, organize, and provide standardized data related to kinases. By offering essential resources and tools, it supports kinase research and drug development, thereby advancing scientific research and innovation in kinase-related fields. It is freely accessible at: http://ai.njucm.edu.cn:8080.

An Appraisal of Employable Content of the National Diploma in Architectural Technology Program in North East Nigeria

The study was designed to determine the applicability of knowledge and skill content of the National diploma in Architectural Technology (NDAT) Program. The study involves 4 Polytechnics in the North East zone of Nigeria are involved, Namely Federal Polytechnic Mubi, Bauchi, and Damaturu along with Ramat Polytechnic, Maiduguri. The respondents are from stakeholders of the NDAT Operating departments at the listed institutions. They include lecturers (54), Instructors (14), Technologist (9), Technicians (26), Higher National Diploma (HND) Architectural Technology Student (44) and NDAT graduating Class Student (33). A total population of 192 respondents. To guide the study, research questions touched on which occupations can be associated with type of knowledge and skill content of the NDAT program. A structured questionnaire containing twenty occupations that require core, Linkage or general knowledge or skills as those in NDAT training was administered. The data collected was cumulated and analyzed using sample percentage as statistics tool, the result showed that all occupations scored more than 50%, 3 had scores between 50-59%, 3 between 60-69%, 7 scored 70-79%, 6 had 80-89% while 1 recorded over 90% acceptance of its applicability to knowledge and skill sets in the NDAT, the responses indicate a level of acceptance that the NDAT courses carry knowledge and skills that are similar to those applied in the occupations listed. These findings suggest that the researchers recommend that application and applicabilityof courses be clearly explained along with other objectives of the courses in the training. With a target of preparing the potential NDAT Graduate to develop flair for aspects of the training leading to practice, specialty and employment has assumed calls for need to increase a graduates’ chance by being multi skilled, or even trans- Occupational, might well be considered and attitude of the graduate must radiate dignity of labour and humility.

Knowledge sharing technologies for rice farmers: A perspective from the Eastern Region of Ghana

This article investigates technologies used for knowledge sharing among rice farmers in the Eastern Region of Ghana and suggests ways by which the use of technologies may be enhance rice farming. The research was underpinned by the pragmatic paradigm where a concurrent triangulation mixed method design was adopted. The data was drawn from 101 survey respondents and nine interview participants, consisting of rice farmers, farm managers and extension officers. The findings revealed elementary use of technologies, tools and systems for knowledge sharing among the rice farmers. The main social media platform used for knowledge sharing was WhatsApp. The platforms that were used the least were Twitter, Facebook, LinkedIn, Imo and Instagram. Findings have implications for integrating various tools, technologies and systems into knowledge sharing among rice farmers. There is a need to address the challenges in structural-level technological infrastructures, architecture and functionalities, in order to build the technological competence of rice farmers. Farmers’ knowledge of technology is influenced by training, motivation, and personal experiences. Previous studies on use of technologies in knowledge sharing focused on organisation. This article examines technology within the context of rice farming.

Li-Fi Technology for Vehicle-To-Vehicle

The integration of Light Fidelity (Li-Fi) technology within Smart Cities to enhance vehicle-to-vehicle (V2V) communication systems. Highlighting the limitations of traditional radio frequency (RF) methods in managing increasing traffic and potential ecosystem impacts, the abstract introduces Li-Fi as a promising alternative. Li-Fi utilizes visible light to achieve high-speed data transfer rates, offering advantages such as enhanced efficiency, reduced latency, improved reliability, and heightened security. The objectives of implementing Li-Fi in V2V communication are delineated, emphasizing its potential to facilitate real-time data exchange crucial for autonomous driving and safety applications. The abstract further details the methodology and architecture of Li-Fi technology, illustrating its utilization of LED bulbs and photo detectors for data transmission and reception. Practical implementation strategies for integrating Li-Fi into V2V communication systems, including sensor-based distance measurement and automated collision avoidance mechanisms, are discussed. Ultimately, the abstract concludes by emphasizing Li-Fi's potential as a cost-effective solution to mitigate traffic accidents and enhance communication efficiency in Smart Cities. Keywords — Li-Fi, Illumination, Wi-Fi, LED, Photo Diode, Radio Frequency

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..