Application Architecture Research Articles

Orchestration Tools For Efficient Deployment of IoT Applications In Fog Computing: A Systematic Review

Internet of Things (IoT) is the developing technology that enables devices to communicate without human interaction. IoT utilizes cloud computing services to collect and process data for IoT devices and to manage the device remotely. Cloud computing is not efficient enough to handle the fast stream of data produced by the IoT, therefore scaling up IoT applications to meet demands of high peak becomes easier and highly automated in fog computing. Containers are mostly used as virtualization solutions for IoT in fog computing. It enables the execution of small microservices to large applications. However, the rise of many lightweight containers has resulted in new application architectures and fundamentally changing how applications are deployed and visualized. Due to this change, container orchestration tools were proposed. These tools allow users to coordinate and manage containers. However, container orchestration tools need to meet the requirements of IoT applications and constraints imposed on the nodes in fog. This paper presents a systematic literature review on the selection of orchestration tools for the efficient deployment of IoT applications in fog computing. Moreover, the performance of IoT applications must be considered by applying different metrics. This paper aims to propose potential research directions to address identified gaps in the selection of orchestration tools.

Utilizing Knowledge Graph to Build a Scientific and Technological Knowledge Management System for Grid Industry

Abstract Based on knowledge mapping, this paper designs the application architecture of the scientific and technological knowledge management system for the power grid industry and proposes the design of key modules such as knowledge extraction, knowledge fusion and cross-checking. In terms of knowledge fusion, this paper proposes the functional design of conflict detection, entity alignment based on deep learning, data fusion based on linking and cross-validation based on confidence assessment. In terms of cross-truth, this paper investigates the credibility calculation of candidate message sets, the representation of candidate message sets, and the construction of logic rules for cross-truth models. Finally, this paper evaluates the system’s term extraction, concept recognition, and performance. The results show that the average elapsed time for each function of graph visualization, keyword search, keyword search, advanced search, and advanced search in the knowledge management system to be executed 20 times is 1.33s, 1.27s, 3.14s, 1.47s, and 3.26s, respectively, and the average response time is only 2.1s. Therefore, the knowledge management system for grid industry science and technology presented in this paper is effective.

Implementation of Background Calibration for Redundant FLASH ADC

Flash converters are suitable analog-to-digital converter architectures for high-speed applications. However, the benefits in terms of the frequency of smaller technology nodes are hampered by variability, which necessitates the use of large transistors. Comparator redundancy was introduced to overcome this trade-off; the best comparators were selected upfront (either at start-up or in the factory), and the unused comparators could be switched off. This work studies the possibility of performing comparator selection in the background concurrently with normal conversion to increase the converter lifetime. Thus, the system can automatically recover its performance from drifts or failures due to aging, temperature, etc. This paper proposes an embedded solution that includes a calibration stimulus generator (which only requires some external passive elements) and develops system design requirements. In addition, mathematical equations and error sensitivities of the system elements were derived. A 6b flash converter is implemented in UMC180nm technology, and transistor-level simulations of the system are provided to demonstrate the feasibility of the proposed system.

Monolithic three-dimensional integration of RRAM-based hybrid memory architecture for one-shot learning

In this work, we report the monolithic three-dimensional integration (M3D) of hybrid memory architecture based on resistive random-access memory (RRAM), named M3D-LIME. The chip featured three key functional layers: the first was Si complementary metal-oxide-semiconductor (CMOS) for control logic; the second was computing-in-memory (CIM) layer with HfAlOx-based analog RRAM array to implement neural networks for feature extractions; the third was on-chip buffer and ternary content-addressable memory (TCAM) array for template storing and matching, based on Ta2O5-based binary RRAM and carbon nanotube field-effect transistor (CNTFET). Extensive structural analysis along with array-level electrical measurements and functional demonstrations on the CIM and TCAM arrays was performed. The M3D-LIME chip was further used to implement one-shot learning, where ~96% accuracy was achieved on the Omniglot dataset while exhibiting 18.3× higher energy efficiency than graphics processing unit (GPU). This work demonstrates the tremendous potential of M3D-LIME with RRAM-based hybrid memory architecture for future data-centric applications.

Synergistic Effects of SAP, Limestone Powder and White Cement on the Aesthetic and Mechanical Properties of Fair-Faced Concrete

In this investigation, a comprehensive assessment was conducted on the cooperative effects of Super Absorbent Polymers (SAP), limestone powder, and white cement within the realm of fair-faced concrete. We discerned that while white cement augments the color vibrancy of the concrete, its accelerated hydration rate potentially induced early-stage cracks and compromised performance. To mitigate these challenges, SAP was incorporated to regulate early hydration, and limestone powder was introduced as a fortifying agent to bolster the mechanical robustness of the concrete. Our findings highlighted not only the capability of SAP to enhance concrete workability and longevity but also the pivotal role of limestone powder in amplifying its mechanical attributes. Microscopic evaluations, undertaken via Scanning Electron Microscopy (SEM), unveiled the potential of both SAP and limestone powder in refining the microstructure of the concrete, thereby elevating its performance metrics. Synthesizing the research outcomes, we pinpointed an optimal amalgamation of SAP, limestone powder, and white cement in fair-faced concrete, offering a valuable reference for prospective architectural applications.

Optimization of Human, Technological, Administrative Resources for Decision-Making in Information Security Governance

Problems for decision-making in information security governance are persistent because there are no adequate models. The objective is to generate a model that optimizes human, technological and administrative resources for decision-making in the governance of Information Security. The deductive method and exploratory research were used. A resource optimization model with 95% reliability generated by Cronbach's Alpha resulted; the mathematical justification of the business, information and application architecture with 96.13%, 95.89% and 95.20% confidence respectively generated by the Pearson correlation; an enterprise architecture context diagram; and an algorithm expressed with flowchart techniques with 98.21% degree of association in its elements generated by the multiple correlation coefficient. It was concluded that with the proposed model, a company's resources can be optimized for information security governance; so that managers have adequate support for making decisions with a mathematical basis with simulations in quantities of components within the architectures; so that the function in business management becomes simpler by applying a general model that can be adapted to various types of companies to achieve success for decision making in security governance of information security.

Implementation of Model View Controller Architecture in Criticism and Suggestion Applications Using the Object Oriented Analysis and Design Method

STMIK Amik Riau is the first computer college in Riau, founded in 1996, and has produced thousands of graduates spread throughout Indonesia. Apart from the many achievements that have been achieved by this campus, in fact, there are still many problems that students often complain about. STMIK Amik Riau itself already has an assessment system, but it is still limited to an assessment of lecturers and services in general which are filled out once in one semester. Complaints submitted also cannot be seen and confirmed by other students so there is no benchmark that becomes a benchmark whether the complaint is worth prioritizing or not. Therefore an application system is needed that aims to provide criticism and suggestions in a transparent manner to improve the quality of the STMIK Amik Riau campus. This application will later provide a filtering feature that will display complaints based on the selected criteria using the Ascending and Descending concepts. MVC is a method used in designing applications with UML as a visual language based on the Software Development Life Cycle concept with an OOAD approach. The tools used in designing this application are Android Studio using the Flutter Framework with Dart as the main language.

The geometry of discrete asymptotic-geodesic 4-webs in isotropic 3-space

The geometry of webs has been investigated over more than a century driven by still open problems. In our paper we contribute to extending the knowledge on webs from the perspective of the geometry of webs on surfaces in three dimensional space. Our study of AGAG-webs is motivated by architectural applications of gridshell structures where four families of manufactured curves on a curved surface are realizations of asymptotic lines and geodesic lines. We describe all discrete AGAG-webs in isotropic space and propose a method to construct them. Furthermore, we prove that some sub-nets of an AGAG-web are timelike minimal surfaces in Minkowski space and can be embedded into a one-parameter family of discrete isotropic Voss nets.

Optimization of Tuff Stones Content in Lightweight Concrete Using Artificial Neural Networks

Tuff stones are volcanic sedimentary rocks formed by the consolidation of volcanic ash. They possess unique geological properties that make them attractive for a variety of construction and architectural applications. Considerable amounts and various types of Tuff stones exist in the eastern part of Jordan. However, the use of Tuff stones often requires experimental investigations that can significantly impact the accuracy of their physical and mechanical characteristics. To ensure consistent and predictable properties in their mix design, it is essential to minimize the effects of these experimental procedures. Artificial neural networks (ANNs) have emerged as a promising tool to address such challenges, leveraging their ability to analyze complex data and optimize concrete mix design. In this research, ANNs have been used to predict the optimum content of Tuff fine aggregate to produce structural lightweight concrete with a wide range (20 to 50 MPa) of compressive strength. Three different types of Tuff aggregates, namely gray, brown, and yellow Tuff, were experimentally investigated. A set of 68 mixes was produced by varying the fine-tuff aggregate content from 0 to 50%. Concrete cubes were cast and tested for their compressive strength. These samples were then used to form the input dataset and targets for ANN. ANN was created by incorporating the recent advancements in deep learning algorithms, and then it was trained, validated using data collected from the literature, and tested. Both experimental and ANN results showed that the optimum content of the various types of used Tuff fine aggregate ranges between 20 to 25%. The results revealed that there is a clear agreement between the predicted values using ANN and the experimental ones. The use of ANNs may help to cut costs, save time, and expand the applications of Tuff aggregate in lightweight concrete production. Doi: 10.28991/CEJ-2023-09-11-013 Full Text: PDF

GREEN ARCHITECTURE OF NAHDLATUL ULAMA YOGYAKARTA UNIVERSITY CAMPUS BUILDING FROM MATERIAL AND ENERGY ASPECTS

The use of Green Architecture in designing a building is a necessity in order to create the principle of sustainability. The campus as a place where education is carried out is a benchmark in creating the principle of sustainability. The Yogyakarta Nahdlatul Ulama University Campus Building tries to implement green architecture in its construction. The aim of the research is to investigate green architecture elements in the NU Yogyakarta Campus buildings. The method uses descriptive narrative by explaining in description the application of green architecture in buildings. Applications are specialized in the application of materials and energy. The research results show that some materials use green architecture principles, such as the use of a hollow roaster so that it can incorporate elements of light and wind and the use of solar panels to save energy

Nondestructive Analysis On 4D-Printed Hygroscopic Actuators Through Optical Flow-Based Displacement Measurements

The many advantages of additive manufacturing are particularly noticeable in the fabrication of 4D-printed actuators. Through the selection of specific printing properties and materials, hygroscopic wood polymer composites (WPCs) can be produced and their reaction to humidity can be preprogrammed to achieve the greatest deformations in the shortest time. This responsive behavior makes 4D-printed WPCs suitable for architectural applications, where they can act as passive airflow controllers to improve hygrometric conditions in indoor environments. Image analysis methods have been proven to be reliable to select the best combinations of materials and properties for hygroscopic WPCs but, in some cases, they provide only information on the curvature angles and the instrumentation and software can be expensive. This paper presents an optical flow method for tracking the displacements through a free and open-source software. Starting from a time-lapse video of the sample immersed in water, the analysis returns a matrix composed of the 3D displacement values for each pixel in consecutive frames and the velocity of the displacement, with their visual representation. Such image analysis techniques proved to be suitable to assess the different hygro-responsive behavior under water of 4D-printed WPCs through low-cost equipment without altering their configuration.

Overview of Chatbots with special emphasis on artificial intelligence-enabled ChatGPT in medical science.

The release of ChatGPT has initiated new thinking about AI-based Chatbot and its application and has drawn huge public attention worldwide. Researchers and doctors have started thinking about the promise and application of AI-related large language models in medicine during the past few months. Here, the comprehensive review highlighted the overview of Chatbot and ChatGPT and their current role in medicine. Firstly, the general idea of Chatbots, their evolution, architecture, and medical use are discussed. Secondly, ChatGPT is discussed with special emphasis of its application in medicine, architecture and training methods, medical diagnosis and treatment, research ethical issues, and a comparison of ChatGPT with other NLP models are illustrated. The article also discussed the limitations and prospects of ChatGPT. In the future, these large language models and ChatGPT will have immense promise in healthcare. However, more research is needed in this direction.

Evolution of dynamic architecture

The article discusses the first objects of dynamic architecture: from mobile, collapsible elementary mobile housing units of nomadic peoples to the first simplest mechanisms of sliding bridges of medieval castles, which served as an impetus for the emergence of a new style of architecture of the future - dynamic architecture. The origins of dynamic architecture originated at the time of the birth of the first civilizations. With the passage of time and the development of technology, the objects of dynamic architecture have undergone a functional purpose, appearance and element of dynamics. The possibilities of practical application of dynamic architecture have increased in the modern world, thanks to scientific and technological progress and dynamic lifestyle, which has led to changes in all spheres of human activity, including architecture.

Mechanical and Thermal Characteristics of Concrete Reinforced with Crushed Glass and Glass Fiber: An Experimental Study

The incorporation of waste glass and glass fiber, as replacements for fine aggregate and cement respectively, offers a sustainable strategy to mitigate landfilling and virgin aggregate extraction. The present study delves into the influence of these waste derivatives on the mechanical and thermal attributes of concrete. Fine aggregate was substituted by crushed glass shards in a weight-to-weight ratio ranging from 5% to 30%, and cement was replaced by glass fiber in a weight-to-weight ratio of 1%. Mechanical attributes such as compressive, flexural, and splitting strength were evaluated, along with thermal characteristics of the concrete. A concrete mix ratio of 1:2:4 and a water/cement ratio of 0.45 were employed. The results revealed that concrete designated as Mcf20% demonstrated superior mechanical properties compared to the reference concrete. After 28 days, compressive strength of 51.2 MPa, flexural strength of 6.5 MPa, and splitting tensile strength of 3.78 MPa were recorded for Mcf20% concrete, signifying the beneficial effects of the combined use of glass fiber and crushed glass. Furthermore, an inverse relationship was observed between the percentage of waste additives and thermal conductivity. This investigation underscores the potential of recycling glass and glass fiber as eco-friendly additives in concrete, improving both mechanical properties and thermal performance, thus endorsing their use in structural and architectural concrete applications.

Predicting large comprehensive refrigeration performance of plastic crystals by compositing carbon architectures for room temperature application

Plastic crystals PE (pentaerythritol) possess colossal barocaloric effect (BCE) that is promising for solid-state refrigeration; however, the high phase transition temperature (> 400 K) and low thermal conductivity (<0.5 W·m−1·K−1) greatly hinder its practical application at room temperature. Here, we propose to complex plastic crystal (PC) with carbon nanotube/graphene architectures (CNT-Gra) to form [PC/CNT-Gra] composites and investigate the BCE based on molecular dynamics simulations. It is found that phase transition temperature of molecular order to disorder can be tuned by alloying PA (neopentane) or NPG (neopentyl glycol) into PE imbedded in CNT-Gra architectures. Importantly, we find that PE0.8PA0.2/CNT-Gra and PE0.75NPG0.25/CNT-Gra demonstrate both giant isothermal entropy changes ΔS (∼200 J·kg−1·K−1) and adiabatic temperature change ΔT (∼18 K) at room temperature. The large BCE mainly comes from the order–disorder transition of PC molecules imbedded in CNT-Gra architectures through analysis of the dynamic process of the composites. Importantly, the thermal conductivity of these campsites is as high as ∼10 W·m−1·K−1, enabling efficient thermal exchange that is vital for improving cooling performance of the cyclic refrigeration process. This work provides important insights for designing PC-based composites with optimized comprehensive cooling performance for potential room temperature refrigeration.

Multi-Dataset Comparison of Vision Transformers and Convolutional Neural Networks for Detecting Glaucomatous Optic Neuropathy from Fundus Photographs.

Glaucomatous optic neuropathy (GON) can be diagnosed and monitored using fundus photography, a widely available and low-cost approach already adopted for automated screening of ophthalmic diseases such as diabetic retinopathy. Despite this, the lack of validated early screening approaches remains a major obstacle in the prevention of glaucoma-related blindness. Deep learning models have gained significant interest as potential solutions, as these models offer objective and high-throughput methods for processing image-based medical data. While convolutional neural networks (CNN) have been widely utilized for these purposes, more recent advances in the application of Transformer architectures have led to new models, including Vision Transformer (ViT,) that have shown promise in many domains of image analysis. However, previous comparisons of these two architectures have not sufficiently compared models side-by-side with more than a single dataset, making it unclear which model is more generalizable or performs better in different clinical contexts. Our purpose is to investigate comparable ViT and CNN models tasked with GON detection from fundus photos and highlight their respective strengths and weaknesses. We train CNN and ViT models on six unrelated, publicly available databases and compare their performance using well-established statistics including AUC, sensitivity, and specificity. Our results indicate that ViT models often show superior performance when compared with a similarly trained CNN model, particularly when non-glaucomatous images are over-represented in a given dataset. We discuss the clinical implications of these findings and suggest that ViT can further the development of accurate and scalable GON detection for this leading cause of irreversible blindness worldwide.

Penerapan Konsep Arsitektur Regionalisme pada Bangunan Kampus Universitas Medan Area

Indonesia has a distinctive array of architectural styles. Architecture that is rooted in regionalism offers a platform for the revival of traditional design elements in modern structures. One of North Sumatra's first private campuses is that of Medan Area University. The architecture and culture in this region are extremely varied. There is no prevailing architectural style like there is in Riau, West Sumatra, or Java. This campus uses conventional architecture in its construction as it is a university with an architectural study program. The scope of the use of regional architecture on a multicultural campus environment is investigated in this study. Several regional architectural applications have been made using the technique of observation and research of traditional architectural theories of the tribes living in North Sumatra.

Construction of highly efficient CuS/CdS nanostructure for enhanced solar H2 evolution

The fabrication of efficient photocatalytic system for enhanced production of hydrogen is exceptionally thought-provoking.To address this issue herein we fabricated the CuS/CdS heterostructures by ultrasonication for photocatalytic H2 production. The structural integrity of the produced heterostructure is confirmed by the aid of analytical tools such as X-ray diffraction studies (XRD), Ultraviolet–Visible Diffuse Reflectance Spectroscopy (UV–vis DRS), scanning electron microscopy (SEM), High-Resolution Transmission Electron Microscopy (HRTEM) and X-ray photoelectron spectroscopy (XPS). The fabricated CuS/CdS sample exhibited the highest H2 production rate (824 μmol/g) than CuS (67 μmol/g) and CdS (135 μmol/g) under simulated solar illumination. The hydrogen output is noticeably enhanced due to improved absorption of visible light and competent charge carrier partition. It was confirmed by UV–vis diffuse reflectivity and photoluminescence spectra (PL) as charge carrier parting was effective as absorption of visible light was enhanced. A plausible photocatalytic H2 reaction mechanism has been elucidated from increased charge carrier division and visible light absorptivity. This work depicts a new approach for greatly resourceful nano architecture for energy-related applications.

Design and implementation of hybrid low power wide area network architecture for IoT applications

The rapid proliferation of Internet of Things (IoT) devices and applications has resulted in an increasing demand for Low Power and Wide Area Network (LPWAN) solutions. The adoption of IoT networks still faces several challenges, despite the rapid advancement of low-power communication technology. Homogenizing this sector requires allowing interoperability between many technologies, which is now one of the largest obstacles. In this article, we present the design and implementation of the hybrid LPWAN architecture that can accomplish wide-area communication coverage and low-power consumption for IoT applications by leveraging two LPWAN technologies, Wireless Smart Ubiquitous Network (Wi-SUN) and Long Range (LoRa). In particular, LoRa is used for long-range communication, and Wi-SUN for a low-latency mesh network. Additionally, we implemented smart street light controlling system as a real-world deployment at the university campus to showcase the efficiency of the hybrid network. Our results demonstrate that the hybrid LPWAN architecture provides a better coverage and capacity while consuming less power than that of the LoRa or Wi-SUN network. The results of this study demonstrate the effectiveness of the proposed hybrid LPWAN architecture as a viable solution for next-generation IoT applications.

Architectural Patterns for Blockchain Systems and Application Design

Blockchain technology has gained popularity in various applications, including finance transactions and beyond. However, developing blockchain application systems is challenging due to stringent quality requirements, such as performance, scalability, and security. Software architecture plays a critical role in realizing key quality requirements. Nonetheless, little work has been performed on software architectures for blockchain applications since blockchain application development is still a new field. This paper proposes twelve architectural patterns for blockchain application software architectures based on 400 cross-industry real-world applications available on the Internet. We determine the key components of each application guided by a blockchain application taxonomy we developed. We then identify typical architectural patterns from the interactions of these components guided by well-known software patterns, such as peer-to-peer, layered, pipe-filter, and access control. Based on the roles of these patterns, we organize them into four architectural views comprising four structural, two interactional, four transactional, and two security patterns. We describe each pattern in detail using a standard form and demonstrate the patterns through a real-world blockchain application. The use of patterns can be valuable in addressing blockchain’s unique challenges, but creativity remains essential in crafting innovative solutions. Mixing architectural patterns according to varying requirements can help developers communicate effectively.