Detailed Architecture Research Articles

Revitalization of regular landscape compositions of the park-monument of landscape art «Sharivskyi»

Introduction. The perception of the landscape as a space for living has led to the formation and development of a special group of anthropogenic landscapes, namely garden and park landscapes, which are characterized by a wide range of functions from utilitarian to aesthetic and spiritual. Currently, approximately 30% of cultural heritage sites are in disrepair, and 80% require serious restoration work. Therefore, the revitalization of the landscape structure of historical garden and park landscapes is an urgent scientific problem and meets two sustainable development goals (goal 11 Sustainable cities and communities and goal 15 - Life on land). The purpose of article. To substantiate the concept of revitalization of regular landscape compositions of the park-monument of landscape gardening art of national importance "Sharivskyi" and to provide a graphic 3D model of architectural, planning and volumetric-spatial solutions of the proposed concept of revitalization of regular compositions of the studied landscape. Research methods. Method of historical analysis: with a focus on the period of the highest embodiment of the artistic compositional intent of the restored space, when the estate belonged to the successful sugar producer Leopold Koenig. The graphic presentation of architectural, planning, and three-dimensional solutions of the proposed revitalization concepts for the studied landscapes was achieved through the use of QGIS 3.28.3-Firenze 2022-08-31, Sketchup, and Realtime Landscaping Architect software tools. Main findings. In order to preserve the original idea and characteristics of the landscape compositions, the concept of revitalization of the White Garden was proposed, which was suggested by the "Genius loci" of the historical landscape of Sharivsky Park. Using the QGIS geographic information system, OSM standard map and Google Satellite Hybrid map, the 3D authentic relief of regular landscape compositions of the Sharivsky Palace and Park Complex was modeled. Using the Sketchup 2020 software tool, a graphical representation of the architectural, planning, and three-dimensional solutions of the studied historical landscape was made. The Sketchup 2020 software tool was also used for the graphic 3D reconstruction of numerous architectural details that adorn the palace, including balustrades, windows, doors, and towers decorated with ornaments. The dendrological plan was developed using species and cultivars of ornamental plants with identified historical and aesthetic value to ensure the continuity of new and preserved plant elements of landscape compositions. Scientific novelty and practical value. The proposed vision of preserving the sustainable features of the place, the selection of plants with identified historical and substantiated aesthetic value can be used in the complex reconstruction of regular garden and park landscapes of the Sharivskyi Park, a monument of landscape gardening art of national importance.

Innovative synthesis strategies for Rambutan-shaped CuNiO2 electrodes in high-performance supercapacitors

The shape/morphology of materials is critical for energy storage, especially in supercapacitors, as it affects their efficiency. The unique Rambutan-shaped CuNiO2 material shows promise for supercapacitors due to its tailored properties. This study stands out for synthesizing the Rambutan-like CuNiO2 structure, further improved by adding Mn, which changes its composition. Using a single-step hydrothermal technique, Mn-doped CuNiO2 (Mn–CuNiO2) is successfully made, with X-ray diffraction (XRD) used to identify phases. High-Resolution Transmission Electron Microscopy (HRTEM) reveals the detailed hexagonal-like architecture of Mn–CuNiO2, shedding light on its nano structural attributes. Brunauer-Emmett-Teller (BET) analysis adds insights into the material's surface characteristics. The electrochemical performance of the Mn–CuNiO2 electrode is thoroughly examined through galvanostatic charge/discharge experiments and cyclic voltammetry, demonstrating its high specific capacitance. Remarkably, the electrode shows a specific capacitance of 1870 F/g at a current density of 1 A/g, highlighting its effectiveness in energy storage. Additionally, the electrode material displays commendable cyclic stability, maintaining superior performance over 10,000 cycles. This durability emphasizes the importance of improving electrode materials to enhance the efficiency and lifespan of supercapacitors, meeting the growing demand for sustainable energy storage solutions.

Human Umbilical Vein Endothelial Cells as a Versatile Cellular Model System in Diverse Experimental Paradigms: An Ultrastructural Perspective.

Human umbilical vein endothelial cells (HUVECs) are primary cells isolated from the vein of an umbilical cord, extensively used in cardiovascular studies and medical research. These cells, retaining the characteristics of endothelial cells in vivo, serve as a valuable cellular model system for understanding vascular biology, endothelial dysfunction, pathophysiology of diseases such as atherosclerosis, and responses to different drugs or treatments. Transmission electron microscopy (TEM) has been a cornerstone in revealing the detailed architecture of multiple cellular model systems including HUVECs, allowing researchers to visualize subcellular organelles, membrane structures, and cytoskeletal elements. Among them, the endoplasmic reticulum, Golgi apparatus, mitochondria, and nucleus can be meticulously examined to recognize alterations indicative of cellular responses to various stimuli. Importantly, Weibel-Palade bodies are characteristic secretory organelles found in HUVECs, which can be easily distinguished in the TEM. These distinctive structures also dynamically react to different factors through regulated exocytosis, resulting in complete or selective release of their contents. This detailed review summarizes the ultrastructural features of HUVECs and highlights the utility of TEM as a pivotal tool for analyzing HUVECs in diverse research frameworks, contributing valuable insights into the comprehension of HUVEC behavior and enriching our knowledge into the complexity of vascular biology.

Intelligent Transportation System Technologies, Challenges and Security

Intelligent Transportation Systems (ITS) first appeared in 1868 with traffic lights. With developing technology, the need to bring a smart approach to transportation applications within the scope of speed and environmental protection has emerged. Protecting ITS infrastructure against cyber attacks has become a matter of reputation for states. It is essential to provide the necessary technological infrastructure for the integrated operation of the systems used in ITS, especially geographical location, communication, and mapping. These technological developments bring cyber attacks, risks, and many dangers that should be avoided, especially on the systems used. This study examines ITS architecture, applications, communication technologies, and new trend technologies in detail. This study includes contributing to studies in the field of ITS and preventing attacks and incidents that may occur in terms of cyber security. The most important cyber attacks that may occur in ITS applications are included. In addition, the minimum security requirements that can be taken in ITS applications and infrastructures against these attacks are included.

DIAR: a blockchain-based system for generation and verification of academic diplomas

Nowadays, the centralized systems used in higher education institutions are sophisticated and have high security mechanisms, offering secure data transfer and real-time encryption. Despite the prevalent usage of centralized systems in many institutions, particularly those within the realm of higher education, some unresolved concerns persist pertaining to privacy, potential abuse, transparency, and the limited capacity to digitize numerous services. Blockchain systems are considered as a potential solution for addressing these constraints. This study begins by highlighting the significance of implementing blockchain systems in higher education institutions, while also outlining the obstacles encountered by researchers in this domain. Centralized systems and blockchain systems are distinguished, with a description of the challenges related to data transfer and adaptation to different platforms. A thorough explanation of the proposed blockchain system begins with a presentation of the conceptual model, followed by a detailed architecture of the processes that would be executed by the system, with particular emphasis on the generation and authentication of academic credentials. Additionally, an analysis is provided on the significance of smart contracts in the programming of blockchain systems. This includes a detailed explanation of the main smart contract architecture used in the proposed blockchain system. This article aims to explore the development of a proposed blockchain system and its practical implementation for testing purposes using specific scenarios and data in the foreseeable future.

Architectural Detail in Sustainable Architecture: Formal and Aesthetic Connotations

Contemporary architecture is shaped by the paradigm of sustainability and is characteristic of many solutions determined by a relevant set of principles related to shaping the environment based on the ecology of systems focused on the flow of energy. These design principles concern gaining energy from renewable resources, protection against the loss of thermal energy from buildings, protection against the excess of thermal energy in buildings, and proper distribution of thermal energy in buildings. This paper presents a proposal for a method to analyze some building components used as sustainability-related elements given their formal similarity to historic architectural details or some artworks integrated with buildings. It aims to emphasize the potential of a different perspective from which to perceive and assess buildings, and specifically their architectural details, given their spatial and aesthetic values associated with sustainable technical solutions. This study is based on a few differentiated examples. It proves the relations mentioned above true, given the sustainability paradigm epitomized in technical solutions to contemporary buildings and the related aesthetic features characterizing the relevant architectural detailing. Such a perception of buildings is intended to promote unconventional viewing and assessment of them by the public and professionals in the area of architecture and art. It would make them discover new types of aesthetic values, which are usually invisible.

Tumor formation at ileocecal junction associated with interleukin-1β upregulation in aryl hydrocarbon receptor-deficient mouse.

Aryl hydrocarbon receptor (AhR) is a ligand-dependent transcription factor. We previously reported spontaneous ileocecal tumorigenesis in AhR-deficient mice after the age of 10 weeks, which originated in the confined area between ileum and cecum. This study aimed to investigate the underlying mechanism that causes tumor development at this particular location. To observe mucosal architecture in detail, tissues of ileocecal region were stained with methylene blue. Gene expression profile in the ileocecal tissue was compared with cecum. Immunohistochemical analysis was performed with ileocecal tissues using antibodies against ileum-specific Reg3β or cecum-specific Pitx2. In AhR+/+ mice and AhR+/- mice, that do not develop lesions, methylene blue staining revealed the gradually changing shape and arrangement of villi from ileum to cecum. It was also observed in AhR-deficient mice before developing lesions. Microarray-based analysis revealed abundant antimicrobial genes, such as Reg3, in the ileocecal tissue while FGFR2 and Pitx2 were specific to cecum. Immunohistochemical analysis of AhR-deficient mice indicated that lesions originated from the ileocecal junction, a boundary area between different epithelial types. Site-specific gene expression analysis revealed higher expression of IL-1β at the ileocecal junction compared with the ileum or cecum of 9-11-week-old AhR-deficient mice. These findings indicate that AhR plays a vital function in the ileocecal junction. Regulating AhR activity can potentially manage the stability of ileocecal tissue possessing cancer-prone characteristics. This investigation contributes to understanding homeostasis in different epithelial transitional tissues, frequently associated with pathological states.

The Factors of Religious Architecture Influencing Students' Perception of Beauty and Art: Evidence from Hanoi, Vietnam

This study explores the impact of religious architecture on the aesthetic perceptions of elementary school students in Hanoi, Vietnam, focusing on students majoring in fine arts. Employing regression analysis, the research assesses the influence of six key dimensions: architectural design and details, cultural and historical context, spiritual symbolism, emotional impact, context and setting, and students' perceptions of beauty and art. Data were collected through a structured questionnaire developed from a thorough literature review and expert consultations and administered to a randomly selected sample during Vietnam's Lunar New Year in January 2024. The results revealed that each dimension significantly contributes to students' perceptions of beauty, with context and setting having the most pronounced effect. The reliability of the questionnaire was confirmed via Cronbach's alpha, indicating high internal consistency across all scales. The regression analysis validated the theoretical framework, establishing that religious buildings' architectural and contextual elements significantly shape students' aesthetic judgments. These findings underscore the importance of integrating architectural aesthetics into educational curricula, highlighting how environmental and cultural contexts influence educational outcomes in art and aesthetics. This research contributes to filling a significant gap in understanding the academic impact of cultural heritage, offering significant implications for educational practices and policies in culturally diverse settings.

Application of Simulation-Based Metrics to Improve the Daylight Performance of a Secondary School, An Approach for Green Building Designers and Architects

Visual comfort affects the quality of classrooms as well as student learning. A practice-oriented approach discovers how the gap between academic research and its application in building design can be addressed. Nevertheless, the physical characteristics design of daylighting systems, including window sizes, shapes, dimensions, and materials, are considered fundamental challenges for their practicability. In this study, the physical characteristics design of daylighting systems, including window sizes, shapes, dimensions, and materials, are considered in a designed sample school, and the daylight metrics were analyzed to achieve more trustworthy and applicable daylighting systems. Grasshopper (Honeybee-Ladybug), as a parametric control method, was applied to simulate the daylighting quality for various educational spaces in a secondary school in Sanandaj City, based on average ‘Daylight Factor’, ‘Daylight Autonomy’, ‘Useful Daylight Illuminance’, and ‘Annual Sunlight Exposure’. These metrics were examined to discover the relationship between window size and positions on visual comfort. The results indicate daylighting assessments are a solid approach to revising the architectural design mistakes at the primary designing phase. Architects and other building designers or energy consumption assessors can apply the design improvement process to present more sufficient and successful architectural details. This is a fundamental step toward the implementation of green buildings.

MEDICAL DATA EXTRACTION

The proposed system is a user-friendly and efficient Data Extraction software for Medical Documents and Images, integrating advanced technologies such as PHP, Android, database, ML-Kit, retrofit, recycler views. The application facilitates efficient user registration, user login, insurance claims, and management of claimed users. The system aims to enhance the accessibility and accuracy of medical data extraction, thereby optimizing insurance procedures for agents, Also This paper outlines the technical architecture, functionalities, and implementation details of the application, highlighting its potential to revolutionize insurance operations within the healthcare industry. Keywords: - Machine Learning Kit(ML-Kit)

Machine Learning-Based Predictive Models for Patients with Venous Thromboembolism: A Systematic Review.

Venous thromboembolism (VTE) is a chronic disorder with a significant health and economic burden. Several VTE-specific clinical prediction models (CPMs) have been used to assist physicians in decision-making but have several limitations. This systematic review explores if machine learning (ML) can enhance CPMs by analyzing extensive patient data derived from electronic health records. We aimed to explore ML-CPMs' applications in VTE for risk stratification, outcome prediction, diagnosis, and treatment. Three databases were searched: PubMed, Google Scholar, and IEEE electronic library. Inclusion criteria focused on studies using structured data, excluding non-English publications, studies on non-humans, and certain data types such as natural language processing and image processing. Studies involving pregnant women, cancer patients, and children were also excluded. After excluding irrelevant studies, a total of 77 studies were included. Most studies report that ML-CPMs outperformed traditional CPMs in terms of receiver operating area under the curve in the four clinical domains that were explored. However, the majority of the studies were retrospective, monocentric, and lacked detailed model architecture description and external validation, which are essential for quality audit. This review identified research gaps and highlighted challenges related to standardized reporting, reproducibility, and model comparison. ML-CPMs show promise in improving risk assessment and individualized treatment recommendations in VTE. Apparently, there is an urgent need for standardized reporting and methodology for ML models, external validation, prospective and real-world data studies, as well as interventional studies to evaluate the impact of artificial intelligence in VTE.

An Open-Source Supervisory Control and Data Acquisition Architecture for Photovoltaic System Monitoring Using ESP32, Banana Pi M4, and Node-RED

To overcome the issues of the existing properties and the non-configurable supervisory control and data acquisition (SCADA) architecture, this paper proposes an IoT-centered open-source SCADA system for monitoring photovoltaic (PV) systems. The system consists of three voltage sensors and three current sensors for data accumulation from the PV panel, the battery, and the load. As a part of the system design, a relay is used that controls the load remotely. An ESP32-E microcontroller transmits the collected data to a Banana Pi M4 Berry (BPI-M4 Berry) through the Message Queuing Telemetry Transport (MQTT) protocol over a privately established communication channel using Wi-Fi. The ESP32-E is configured as the MQTT publisher and the BPI-M4 Berry serves as the MQTT broker. Locally installed on the BPI-M4 Berry, the Node-RED platform creates highly customizable dashboards as human–machine interfaces (HMIs) to achieve real-time monitoring of the PV system. The proposed system was successfully tested to collect the PV system voltage/current/power data and to control the load in a supervisory way under a laboratory setup. The complete SCADA architecture details and test results for the PV system data during the total eclipse on 8 April 2024 and another day are presented in this paper.

The Way of the Detail in Japanese Design

When considering the growing interest in the ideas of internationalisation and globalisation, the phrase ‘Japanese Design’ has always captured the inspirational pulse of designers. This paradoxical world of Japan provides the impetus for vast and varied design outcomes. These outcomes range from the traditional design of tearooms, to the youth fashion phenomena in Harajuku. Design in Japan demonstrates a controlled approach to the subtle nuances that express the design spectrum between excess and austerity. This paper explores the idea of the intricacy of Japanese design as not only being a clear expression of their masterful handling of material and form, but also a demonstration of the amalgamation of cultural paradigms displayed in these various design outcomes. This is no more clearly expressed than in the examination of details used within Japanese design, in particular, the details in traditional Japanese architecture. The methodology involved with this research is mainly focussed on literature reviews of text and journal articles, as well as, review of appropriate exhibitions. But the original journey began years ago with my own education and exposure to the ideas of Japanese design and architecture. Numerous travel tours and design tours to Japan helped to reinforce the connection and unfold their paradoxical world.

Calibration of simulation model to analyze hospital building energy performance

This research paper addresses the calibration of an energy simulation model for a naturally ventilated hospital building located in Mangalore, Karnataka, India, in a warm, humid climatic zone. The study aims to enhance the accuracy of energy consumption calculations through a calibration process by developing the energy model of a reference hospital building using EnergyPlus software. The required architectural design data, construction details, occupancy and schedule data and services are collected through documents, energy audits and documentation, measured drawings, and semi-structured interviews. Calibration parameters are systematically identified and adjusted through an iterative process. The monthly electricity bill is used to validate the simulation model. The simulation model reached during the validation process has an excellent Coefficient of Variation-Root Mean Squared Error of 4.24% and a Normalized Mean Bias Error of −4.42%, both of which meet the ASHRAE-approved accuracy standards. The paper also discusses the challenges and emphasizes the need for a nuanced approach to modeling healthcare facilities. Notwithstanding the challenges faced, the study offers insightful information about how to calibrate simulation models for hospital energy usage with the significant influence of scheduling for artificial lighting and equipment usage. By pioneering a manual calibration approach tailored to hospital simulation models in the warm humid climate of India, this paper offers a novel and practical solution to address the challenges of energy performance analysis in resource-constrained environments. The calibrated simulation model presented in this study is a valuable tool for assessing and improving the energy performance of naturally ventilated healthcare facilities. By creating alternative space layouts, the research findings aim to foster the development of hospital infrastructure that is both ecologically friendly and energy-efficient in a specific climatic context. This research is assured to make a substantial contribution to the advancement of sustainable hospital design in warm-humid climates, with implications for both academia and industry.

Harnessing large language models over transformer models for detecting Bengali depressive social media text: A comprehensive study

In an era where the silent struggle of underdiagnosed depression pervades globally, our research delves into the crucial link between mental health and social media. This work focuses on early detection of depression, particularly in extroverted social media users, using LLMs such as GPT 3.5, GPT 4 and our proposed GPT 3.5 fine-tuned model DepGPT, as well as advanced Deep learning models(LSTM, Bi-LSTM, GRU, BiGRU) and Transformer models(BERT, BanglaBERT, SahajBERT, BanglaBERT-Base). The study categorized Reddit and X datasets into “Depressive” and “Non-Depressive” segments, translated into Bengali by native speakers with expertise in mental health, resulting in the creation of the Bengali Social Media Depressive Dataset (BSMDD). Our work provides full architecture details for each model and a methodical way to assess their performance in Bengali depressive text categorization using zero-shot and few-shot learning techniques. Our work demonstrates the superiority of SahajBERT and Bi-LSTM with FastText embeddings in their respective domains also tackles explainability issues with transformer models and emphasizes the effectiveness of LLMs, especially DepGPT (GPT 3.5 fine-tuned), demonstrating flexibility and competence in a range of learning contexts. According to the experiment results, the proposed model, DepGPT, outperformed not only Alpaca Lora 7B in zero-shot and few-shot scenarios but also every other model, achieving a near-perfect accuracy of 0.9796 and an F1-score of 0.9804, high recall, and exceptional precision. Although competitive, GPT-3.5 Turbo and Alpaca Lora 7B show relatively poorer effectiveness in zero-shot and few-shot situations. The work emphasizes the effectiveness and flexibility of LLMs in a variety of linguistic circumstances, providing insightful information about the complex field of depression detection models.

Context-Aware System for Information Flow Management in Factories of the Future

The trends of the 21st century are challenging the traditional production process due to the reduction in the life cycle of products and the demand for more complex products in greater quantities. Industry 4.0 (I4.0) was introduced in 2011 and it is recognized as the fourth industrial revolution, with the aim of improving manufacturing processes and increasing the competitiveness of industry. I4.0 uses technological concepts such as Cyber-Physical Systems, Internet of Things and Cloud Computing to create services, reduce costs and increase productivity. In addition, concepts such as Smart Factories are emerging, which use context awareness to assist people and optimize tasks based on data from the physical and virtual world. This article explores and applies the capabilities of context-aware applications in industry, with a focus on production lines. In specific, this paper proposes a context-aware application based on a microservices approach, intended for integration into a context-aware information system, with specific application in the area of manufacturing. The manuscript presents a detailed architecture for structuring the application, explaining components, functions and contributions. The discussion covers development technologies, integration and communication between the application and other services, as well as experimental findings, which demonstrate the applicability and advantages of the proposed solution.

Research on VR e-learning based on load balancing algorithm in intelligent music education system

This paper aims to explore the application of virtual reality (VR) electronic learning based on load balancing algorithm in the simulation of intelligent music education system. This paper designs and implements an intelligent music education system simulation, which uses load balancing algorithm and virtual reality (VR) technology to provide the convenience of e-learning and personalized learning experience. The load balancing algorithm allocates and manages multiple tasks or requests in the system to ensure the balanced utilization of resources and the efficient operation of the system. In the intelligent music education system, the load balancing algorithm can be used to manage user requests, allocate appropriate resources and services, and ensure that the system can respond quickly and provide a stable learning environment. This paper introduces the architecture and implementation details of the system, including the design and optimization of load balancing algorithm and the application of VR technology. The results show that we point out that VR e-learning based on load balancing algorithm has potential in the simulation of intelligent music education system, which can provide high-quality personalized music learning experience and provide useful enlightenment for innovation in the field of music education.

A Kotlin and Firebase Based Project Discovery Platform with Cosine Similarity-Based Recommendation

Abstract: In today's interconnected world, mobile applications have become integral to our daily lives, revolutionizing how we communicate, work, and collaborate. we present an Android application utilizing Kotlin, Firebase, and a cosine-based recommendation system to address the challenge of project collaboration and discovery. The application aims to provide users with a seamless and personalized experience, empowering them to discover, collaborate on, and contribute to projects aligned with their interests and expertise. By integrating Firebase, the application ensures real-time data synchronization, secure authentication, and cloud storage capabilities, enhancing user experience. The implementation of a cosine-based recommendation system further enhances project discovery by analyzing user profiles and project data to generate personalized recommendations. This paper offers insights into the architecture, methodology, and implementation details of the Android application, highlighting its innovative features and technologies for collaborative project management.

Real Time Chat Application using React and Firebase

Abstract: This paper presents the development of a real-time chat application leveraging modern web technologies, including React for front-end development, Tailwind CSS for styling, and Firebase for backend services. The chat application addresses the need for seamless communication among users in various contexts. We discuss the architectural design, implementation details, and performance evaluation of the application. Our findings demonstrate the effectiveness and scalability of the proposed solution, paving the way for future enhancements and applications in real-time communication systems.

Virtual reality technology for learning detailed design in landscape architecture

There is much interest in employing computer technology in design professions and education. However, few attempts have been made to apply immersive visualization technology to learn design details in landscape architecture. This study aims to illuminate how virtual reality (VR) technology helps students with design details in landscape architecture. Students were given a course project to create 3D models such as boardwalk structures located in residential pond areas. Based on their 3D models, we asked 16 research participants to answer survey questionnaires about the perception of realism, scale, and effectiveness of using computer technology in semi-immersive environments (e.g., monitor display-based) as opposed to fully immersive environments (e.g., VR head-mounted display-based). The results of our study showed that students had a higher realism in fully immersive environments compared to semi-immersive environments. In terms of perception of scale, participants perceived the height of the simulated model to be higher than they had anticipated in fully immersive environments. While there were no statistically significant findings regarding the effectiveness of design evaluation in the two modalities, students mentioned that VR technology can effectively assist in creating design details, as it provides them with a better understanding of the spatial characteristics of models.