Showing papers on "Architecture published in 2021"

The Four Books of Architecture

Abstract: The Renaissance architect Andrea Palladio was one of the most influential figures that the field of architecture has ever produced. For classical architects, the term Palladian stands for a vocabulary of architectural forms embodying perfection and beauty. Of even greater significance than Palladio's buildings is his treatise I quattro libri dell'architettura (The Four Books On Architecture), the most successful architectural treatise of the Renaissance and one of the two or three most important books in the literature of architecture. First published in Italian in 1570, it has been translated into every major Western language.This is the first English translation of Palladio in over 250 years, making it the only translation available in modern English. Until now, English-language readers have had to rely mostly on a facsimile of Isaac Ware's 1738 translation and the eighteenth-century engravings prepared for that text. This new translation by Robert Tavernor and Richard Schofield contains Palladio's original woodcuts, reproduced in facsimile and positioned correctly, adjacent to the text. The book also contains a glossary that explains technical terms in their original context, a bibliography of recent Palladio research, and an introduction to Palladio and his times.The First Book discusses building materials and techniques, as well as the five orders of architecture: Tuscan, Doric, Ionic, Corinthian, and Composite. Palladio describes the characteristics of each order and illustrates them. The Second Book discusses private town houses and country estates, almost all designed by Palladio. The Third Book discusses streets, bridges, piazzas, and basilicas, most of ancient Roman origin. The Fourth Book discusses ancient Roman temples, including the Pantheon.

Diverse Part Discovery: Occluded Person Re-identification with Part-Aware Transformer

Abstract: Occluded person re-identification (Re-ID) is a challenging task as persons are frequently occluded by various obstacles or other persons, especially in the crowd scenario. To address these issues, we propose a novel end-to-end Part-Aware Transformer (PAT) for occluded person Re-ID through diverse part discovery via a transformer encoder-decoder architecture, including a pixel context based transformer encoder and a part prototype based transformer decoder. The proposed PAT model enjoys several merits. First, to the best of our knowledge, this is the first work to exploit the transformer encoder-decoder architecture for occluded person Re-ID in a unified deep model. Second, to learn part prototypes well with only identity labels, we design two effective mechanisms including part diversity and part discriminability. Consequently, we can achieve diverse part discovery for occluded person Re-ID in a weakly supervised manner. Extensive experimental results on six challenging benchmarks for three tasks (occluded, partial and holistic Re-ID) demonstrate that our proposed PAT performs favor-ably against stat-of-the-art methods.

A Survey on Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection

Abstract: As data privacy increasingly becomes a critical societal concern, federated learning has been a hot research topic in enabling the collaborative training of machine learning models among different organizations under the privacy restrictions. As researchers try to support more machine learning models with different privacy-preserving approaches, there is a requirement in developing systems and infrastructures to ease the development of various federated learning algorithms. Similar to deep learning systems such as PyTorch and TensorFlow that boost the development of deep learning, federated learning systems (FLSs) are equivalently important, and face challenges from various aspects such as effectiveness, efficiency, and privacy. In this survey, we conduct a comprehensive review on FLSs. To understand the key design system components and guide future research, we introduce the definition of FLSs and analyze the system components. Moreover, we provide a thorough categorization for FLSs according to six different aspects, including data distribution, machine learning model, privacy mechanism, communication architecture, scale of federation and motivation of federation. The categorization can help the design of FLSs as shown in our case studies. By systematically summarizing the existing FLSs, we present the design factors, case studies, and future research opportunities.

Energy Systems and Sustainability

Abstract: The only text to provide a fresh, contemporary perspective on energy and sustainability for an undergraduate audience - Includes extensive coverage of the important concepts and issues underpinning modern energy production - Gives detailed descriptions of the main methods used to produce energy today - Lavishly illustrated with full-colour photographs and diagrams - Boxes throughout the text present in-depth case studies and further explanation of more advanced topics - Written by an experienced and authoritative course team at the Open University Today energy and sustainability are areas of primary concern. Energy Systems and Sustainability provides a thorough introduction to the economic, social, environmental and policy issues raised by current systems of energy use, as well as describing their key physical and engineering features. The book begins with an introductory account of the present world energy situation. This is followed by chapters explaining basic energy concepts and describing the magnitudes and patterns of human energy needs. The central part of the book deals with the historical evolution and present status of the conventional fossil and nuclear fuelled energy systems that, along with hydropower and traditional biofuels, currently supply the majority of the world's commercial energy needs. A section on economics describes the basic methods by which the monetary costs of energy are calculated, and discusses the issue of the 'external' costs of energy production. The concluding sections then deal with the sustainability problems associated with both fossil and nuclear fuel use, and ways in which these might be ameliorated by various technological developments. The interdisciplinary approach of the book will appeal not only to specialists but also to non-specialist readers who wish to improve their understanding of these complex and increasingly important issues. This book will be an ideal companion to the forthcoming second edition of Renewable Energy by Godfrey Boyle, which deals with the different forms of renewable energy and how these can be utilised. Readership: Undergraduates and postgraduates taking courses in energy, sustainable development, environmental subjects and architecture. Also suitable for non-specialists. Contents: 1. Introductory Overview , Godfrey Boyle 2. Primary Energy , Janet Ramage 3. Energy Needs , Bob Everett and Janet Ramage 4. Forms of Energy , Janet Ramage 5. Coal , Janet Ramage 6. Heat to Motive Power , Janet Ramage and Bob Everett 7. Oil and Gas , David Crabbe 8. Engines and Turbines , Janet Ramage, Bob Everett, David Crabbe 9. The Rise of Electric Power , Janet Ramage and Bob Everett 10. Principles of Nuclear Power , Janet Ramage 11. The Future of Nuclear Power , David Elliott 12. Principles of Energy Costing , Bob Everett 13. Penalties , Janet Ramage, Bob Everett, Stephen Peake, Godfrey Boyle 14. Remedies , Godfrey Boyle

Agent architecture of an intelligent medical system based on federated learning and blockchain technology

Abstract: Multi-agent systems enable the division of complicated tasks into individual objects that can cooperate Such architecture can be useful in building solutions in the Internet of Medical Things (IoMT) In this paper, we propose an architecture of such a system that ensures the security of private data, as well as allows the addition and/or modification of the used classification methods The main advantages of the proposed system are based on the implementation of blockchain technology elements and threaded federated learning The individual elements are located on the agents who exchange information Additionally, we propose building an agent with a consortium mechanism for classification results from many machine learning solutions This proposal offers a new model of agents that can be implemented as a system for processing medical data in real-time Our proposition was described and tested to present advantages over other, existing state-of-the-art methods We show, that this proposition can improve the Internet of Medical Thing solutions by presenting a new idea of a multi-agent system that can separate different tasks like security, or classification and as a result minimize operation time and increase accuracy

Towards Long-Form Video Understanding

Abstract: Our world offers a never-ending stream of visual stimuli, yet today’s vision systems only accurately recognize patterns within a few seconds. These systems understand the present, but fail to contextualize it in past or future events. In this paper, we study long-form video understanding. We introduce a framework for modeling long-form videos and develop evaluation protocols on large-scale datasets. We show that existing state-of-the-art short-term models are limited for long-form tasks. A novel object-centric transformer-based video recognition architecture performs significantly better on 7 diverse tasks. It also outperforms comparable state-of-the-art on the AVA dataset.

A Survey on Evolutionary Neural Architecture Search.

Abstract: Deep neural networks (DNNs) have achieved great success in many applications. The architectures of DNNs play a crucial role in their performance, which is usually manually designed with rich expertise. However, such a design process is labor-intensive because of the trial-and-error process and also not easy to realize due to the rare expertise in practice. Neural architecture search (NAS) is a type of technology that can design the architectures automatically. Among different methods to realize NAS, the evolutionary computation (EC) methods have recently gained much attention and success. Unfortunately, there has not yet been a comprehensive summary of the EC-based NAS algorithms. This article reviews over 200 articles of most recent EC-based NAS methods in light of the core components, to systematically discuss their design principles and justifications on the design. Furthermore, current challenges and issues are also discussed to identify future research in this emerging field.

Biophilic design in architecture and its contributions to health, well-being, and sustainability: A critical review

Abstract: In the last ten years, ‘nature’ and biophilic design have received widespread attention in architecture, especially in response to growing environmental challenges. However, open questions and controversies remain regarding conceptualizing and addressing ‘nature’ in practice and research. This study conducts a literature review to discuss biophilic design as a theoretical framework to interpret ‘nature’ in architecture. The following questions are answered: (1) How has the concept of biophilic design emerged, and how can it be defined? (2) In what ways can biophilic design contribute to the goals of sustainable architecture? (3) What are the key design strategies in biophilic design? This review identifies and compares the key frameworks of biophilic design and explains their major elements. We then analyse the benefits (e.g. enhance health, well-being, productivity, biodiversity, and circularity) of biophilic design in achieving sustainability, as framed through the UN Sustainable Development Goals. The results indicate that biophilic design is more complex and richer than the mere application of vegetation in buildings; it broadens the variety through encompassing different types of nature from physical, sensory, metaphorical, morphological, material to spiritual. Moreover, knowledge gaps are identified to motivate future research and critical reflections on biophilic design practices.

FLEAM: A Federated Learning Empowered Architecture to Mitigate DDoS in Industrial IoT

Abstract: Due to resource constraints and working surroundings, many IIoT nodes are easily hacked and turn into zombies from which to launch attacks. It is challenging to detect such networked zombies. We combine federated learning (FL) and fog/edge computing to combat malicious codes. Our protocol trains a global optimized model based on distributed datasets of collaborators while removing the data and communication constraints. The FL-based detection protocol maximizes the value of distributed data samples, resulting in an accurate model timely. On top of the protocol, we place mitigation intelligence in a distributed and collaborative manner. Our approach improves accuracy, eliminates mitigation time, and enlarges attackers' expense. Comprehensive evaluations showcase that the attacking cost incurred is 2.5 times higher, the mitigation delay is about 72% lower, and the accuracy is 47% greater on average than classic solutions. Besides, the protocol evaluation shows the detection accuracy is approximately 98% in the FL.

Estimating Energy Consumption of Cloud, Fog and Edge Computing Infrastructures

Abstract: In order to improve locality aspects, new Cloud-related architectures such as Edge Computing have been proposed. Despite the growing popularity of these new architectures, their energy consumption has not been well investigated yet. To move forward on such a critical question, we first introduce a taxonomy of different Cloud-related architectures. From this taxonomy, we then present an energy model to evaluate their consumption. Unlike previous proposals, our model comprises the full energy consumption of the computing facilities, including cooling systems, and the energy consumption of network devices linking end users to Cloud resources. Finally, we instantiate our model on different Cloud-related architectures, ranging from fully centralized to completely distributed ones, and compare their energy consumption. The results show that a completely distributed architecture, because of not using intra-data center network and large-size cooling systems, consumes between 14% and 25% less energy than fully centralized and partly distributed architectures respectively. To the best of our knowledge, our work is the first one to propose a model that enables researchers to analyze and compare energy consumption of different Cloud-related architectures.

Co-evolution of platform architecture, platform services, and platform governance: Expanding the platform value of industrial digital platforms.

Abstract: Industrial manufacturers increasingly develop digital platforms in the business-to-business (B2B) context. This emergent form of digital platforms requires a profound yet little understood holistic perspective that encompasses the co-evolution of platform architecture, platform services, and platform governance. To address this research gap, our study examines multiple platform sponsors from an industrial manufacturing context. The study demarcates three platform archetypes: product platform, supply chain platform, and platform ecosystem. We argue that each platform archetype involves a gradual development of platform architecture, platform services, and platform governance, which mirror each other. We also find that each platform archetype is characterized by a specific innovation mechanism that contributes to the platform service discovery and expands the platform value. Our study extends the co-evolution perspective of platform ecosystem literature and digital servitization literature.

Computing over Space-Air-Ground Integrated Networks: Challenges and Opportunities

Abstract: Space-air-ground integrated networks (SAGINs) have gained significant attention and become a promising architecture for ubiquitous connectivity for SG-Advanced and 6G, enabling the integration of satellite networks, aerial networks, and terrestrial networks. This integration brings tremendous communication benefits, such as non-terrestrial networks, seamless global coverage, high flexibility, and augmented system capacity. Meanwhile, computing capability becomes an indispensable part of the SAGIN ecosystem. In SAGINs, limited and unbalanced computation and communication resources of different network segments make it challenging to provide strict quality-of-service (QoS) guarantees for specific traffic (e.g., delay-sensitive traffic and outage-sensitive traffic). To fully utilize available system resources in SAGINs, cooperative computing among different network segments is a promising technology. This article presents the fundamentals and applications of computing over SAGINs by introducing the system architecture and explaining the potential technical issues related to cooperative computing. Furthermore, the potential for cooperative computing over SAGINs is showcased with a preliminary performance evaluation. Finally, future research opportunities are discussed.

Transformative Pedagogy in Architecture and Urbanism

Abstract: As a new round of pedagogical dialogue on architecture and urbanism it resets the stage for debating future visions of transformative pedagogy and its impact on design education. This is a forward looking effort that comes to amalgamate concerns, concepts, and practices that Ashraf M. Salama has explored and introduced over a period of two decades. It is about balancing the creative act required for creating responsive environments and the social and environmental responsibilities that should be embedded in this act. It is also about understanding how knowledge is produced, what the components of such knowledge are, and what are the learning processes and social practices that can be used to transmit it. Structured in five chapters the book presents a wide range of innovative and practical methodologies for teaching architectural and urban design. It traces the roots of architectural education and offers several contrasting ideas and strategies of design teaching practices. The book includes five chapters: 1) A New Theory for Transformative Pedagogy in Architecture and Urbanism 2) The Architect, the Profession, and Society 3) The Conventional Approach to Studio Teaching Practice 4) Against the Conventional Studio Pedagogy 5) Empowering Transformative Pedagogy.

Architecture Anti-Patterns: Automatically Detectable Violations of Design Principles

Abstract: In large-scale software systems, error-prone or change-prone files rarely stand alone. They are typically architecturally connected and their connections usually exhibit architecture problems causing the propagation of error-proneness or change-proneness. In this paper, we propose and empirically validate a suite of architecture anti-patterns that occur in all large-scale software systems and are involved in high maintenance costs. We define these architecture anti-patterns based on fundamental design principles and Baldwin and Clark’s design rule theory. We can automatically detect these anti-patterns by analyzing a project’s structural relationships and revision history. Through our analyses of 19 large-scale software projects, we demonstrate that these architecture anti-patterns have significant impact on files’ bug-proneness and change-proneness. In particular, we show that 1) files involved in these architecture anti-patterns are more error-prone and change-prone; 2) the more anti-patterns a file is involved in, the more error-prone and change-prone it is; and 3) while all of our defined architecture anti-patterns contribute to file’s error-proneness and change-proneness, Unstable Interface and Crossing contribute the most by far.

Industrial perspectives of 3D scanning: Features, roles and it's analytical applications

Abstract: 3D scanning is one of the lesser talked about technologies used for designing, inspection, and quality control. This non-contact measuring technology converts a physical model into digital 3D Computer-Aided Design (CAD) with the help of various scanning software's. It is becoming an essential tool for producers who need an accurate dimensional inspection, virtual image, analysis, and even physical prototype manufacturing. This paper aims to discuss the potential of 3D scanning for the Industrial Sphere. It will take up 3D Scanners for practical industrial support and develop the Work-Flow Process of 3D Scanners for Industrial requirements. Further, the paper identifies and discusses sixteen major applications of 3D scanning from an Industrial perspective. 3D scanners use sensors to sense the data of any product. This technology can easily capture the virtual image of a physical part, and the same can be analysed, modified, printed, and stored. It allows for careful preparation of production systems involving machinery placement, facilities, repair and human ergonomic interplay. It is a vital performance measure to ensure the initial vision has been realised as intended. The automobile sector ensures that the produced product fits as per the manufacturer's requirement and for quality control. 3D scanning is helpful for reverse engineering, analysis, designing and measuring complex curved surfaces, education, architecture, survey, healthcare, quality monitoring, prototyping, development of industrial tools and many more. This technology uses advanced software for accurate measurement, storage, analysis, which helps increase the process's flexibility and reliability.

Design, Monitoring, and Testing of Microservices Systems: The Practitioners' Perspective.

Abstract: Context: Microservices Architecture (MSA) has received significant attention in the software industry. However, little empirical evidence exists on design, monitoring, and testing of microservices systems. Objective: This research aims to gain a deep understanding of how microservices systems are designed, monitored, and tested in the industry. Method: A mixed-methods study was conducted with 106 survey responses and 6 interviews from microservices practitioners. Results: The main findings are: (1) a combination of domain-driven design and business capability is the most used strategy to decompose an application into microservices, (2) over half of the participants used architecture evaluation and architecture implementation when designing microservices systems, (3) API gateway and Backend for frontend patterns are the most used MSA patterns, (4) resource usage and load balancing as monitoring metrics, log management and exception tracking as monitoring practices are widely used, (5) unit and end-to-end testing are the most used testing strategies, and (6) the complexity of microservices systems poses challenges for their design, monitoring, and testing, for which there are no dedicated solutions. Conclusions: Our findings reveal that more research is needed to (1) deal with microservices complexity at the design level, (2) handle security in microservices systems, and (3) address the monitoring and testing challenges through dedicated solutions.

Deep Neural Architectures for Medical Image Semantic Segmentation: Review

Abstract: Deep learning has an enormous impact on medical image analysis. Many computer-aided diagnostic systems equipped with deep networks are rapidly reducing human intervention in healthcare. Among several applications, medical image semantic segmentation is one of the core areas of active research to delineate the anatomical structures and other regions of interest. It has a significant contribution to healthcare and provides guided interventions, radiotherapy, and improved radiological diagnostics. The underlying article provides a brief overview of deep convolutional neural architecture, the platforms and applications of deep neural networks, metrics used for empirical evaluation, state-of-the-art semantic segmentation architectures based on a foundational convolution concept, and a review of publicly available medical image datasets highlighting four distinct regions of interest. The article also analyzes the existing work and provides open-ended potential research directions in deep medical image semantic segmentation.

Architecture, urbanism and health in a post-pandemic virtual world

Abstract: Purpose: The highly contagious coronavirus and the rapid spread of COVID-19 disease have generated a global public health crisis Crises are being addressed at various local and global scales through social distancing measures and guidelines, emerging working and living patterns and the utilisation of technology to partially replace physical learning environments The purpose of this article is to capture the key messages of the contributions published in this special edition of Archnet-IJAR: International Journal of Architectural Research, Volume 15, Issue 1, March 2021 Reviewing more than 70 submissions, 15 articles have been identified that are contributed by 35 scholars, educators and practitioners from 12 countries The article calls for the need to embed trans-disciplinarity in current and future built environment research Design/methodology/approach: Driven by the fact that architecture, urban design and planning and built environment studies interact and have direct correlation with public health and virus spread The approach to develop and present the key messages of the contributions is premised on three areas: (a) the pandemic condition as it relates to the built environment, (b) analytical reflections on the emerging themes and (c) the diversity and complexity embedded in these themes Findings: While some contributions speak to the particularities of their contexts, others address regional or global parameters The enquiry into architectural research, architectural education and architectural design indicates some of the important methods and tools to address the accelerated adoption, adaption and redesign needed to create a new and better normal which embeds flexibility, adaptability and continuous learning The papers represent brilliant investiture to address the momentous insinuations the COVID-19 condition has on the built environment Research limitations/implications: The diversity of implications reveals potential alternative futures for urbanity and society and the associated education and practice of future built environment professions While the contributions invite us to critically envisage possibilities for future research and collective action, critical fast-track empirical research is needed to address how health is an integral component in the production of architecture and urban environments Originality/value: The diversity, complexity, depth and breadth of the contribution convey important insights on people, health and the spatial environments that accommodate both Trans-disciplinarity, as it relates to research and action and to the production of urban environments, is viewed as a form of learning involving co-operation among different parts of society, professionals and academia in order to meet complex challenges of society such this pandemic condition This approach has enabled the identification of three future research areas in architecture urbanism that include implications of virus spread on urban environments, how spatial and social distancing measures and protocols are altering our understanding of spatial design © 2021, Emerald Publishing Limited

Interaction Relational Network for Mutual Action Recognition

Abstract: Person-person mutual action recognition (also referred to as interaction recognition) is an important research branch of human activity analysis. Current solutions in the field are mainly dominated by CNNs, GCNs and LSTMs. These approaches often consist of complicated architectures and mechanisms to embed the relationships between the two persons on the architecture itself, to ensure the interaction patterns can be properly learned. In this paper, we propose a more simple yet very powerful architecture, named Interaction Relational Network (IRN), which utilizes minimal prior knowledge about the structure of the human body. We drive the network to identify by itself how to relate the body parts from the individuals interacting. In order to better represent the interaction, we define two different relationships, leading to specialized architectures and models for each. These multiple relationship models will then be fused into a single and special architecture, in order to leverage both streams of information for further enhancing the relational reasoning capability. Furthermore we define important structured pair-wise operations to extract meaningful extra information from each pair of joints -- distance and motion. Ultimately, with the coupling of an LSTM, our IRN is capable of paramount sequential relational reasoning. These important extensions we made to our network can also be valuable to other problems that require sophisticated relational reasoning. Our solution is able to achieve state-of-the-art performance on the traditional interaction recognition datasets SBU and UT, and also on the mutual actions from the large-scale dataset NTU RGB+D. Furthermore, it obtains competitive performance in the NTU RGB+D 120 dataset interactions subset.

Effective Management of Energy Internet in Renewable Hybrid Microgrids: A Secured Data Driven Resilient Architecture

Abstract: This paper proposes a two-layer in-depth secured management architecture for the optimal operation of energy internet in hybrid microgrids considering wind turbines, photovoltaics, fuel cell unit, and microturbines. In the physical layer of the proposed architecture, the operation of the grid is formulated as a single objective problem that is solved using teacher learning-based optimization (TLBO). Regarding the cyber layer of the proposed architecture, a two-level intrusion detection system (IDS) is proposed to detect various cyber-attacks (i.e. Sybil attacks, spoofing attacks, false data injection attacks) on wireless-based advanced metering infrastructures. The sequential probability ratio testing (SPRT) approach is utilized in both levels of the proposed IDS to detect cyber-attacks based on a sequence of anomalies rather than only one piece of evidence. The feasibility and performance of the proposed architecture are examined on IEEE 33-bus test system and the results are provided for both islanded and grid-connected operation modes.

Surface Value: Ways of Seeing Decoration in Architecture

Abstract: The long 18th century was a period of intense investment in elite architecture in Britain which sustained an extensive craft culture in carving, modelling, and joinery. Yet decoration is largely marginalised or ignored by architectural historians. This antipathy to the enrichment of buildings is not particular to Britain and reflects a wider discourse on the architecture of many periods and places. By situating past and present attitudes to 18th-century decoration in Britain within a wider historiography, this paper reveals the prejudices which still attend the discussion of ornament and craft production in architecture. Conversely, it explores revisionist perspectives on craft and decoration and considers how they can inform architectural history and contribute to a more holistic understanding of building production. Despite a recent, widespread revival of interest in ornament, however, scholarship continues to privilege conceptual issues over the material practices of decoration. Disciplinary boundaries have militated against an integrated approach to architecture and decoration and historians of sculpture and architecture have overlooked significant common ground. Lacunae in the historiography of decoration in 18th-century British architecture call for approaches which integrate the analytical and methodological tools of architectural and sculpture history.

Cognitive Service Architecture for 6G Core Network

Abstract: 5G communication is making much progress in achieving the Internet of Things and improving the quality of user experience in large bandwidth scenarios. By introducing a variety of new technologies, the performance of 5G has been greatly improved. However, emerging applications put forward more stringent requirements in terms of latency, reliability, peak data rate, service continuity, etc. Communication technology still needs to be further developed. In this article, the next generation of core networks is conceptualized. Inspired by the nervous system of the octopus, we propose a new cognitive service architecture. Cognitive service architecture is a new architecture designed for the 6G core network. It is proposed to enhance the core network so that it is qualified for the increasingly high requirement for quality of service and complicated scenarios. We first give a short vision of the 6G core network. Then cognitive service architecture is demonstrated in detail. A case study is demonstrated to show how cognitive service architecture enhances the performance of the system. Enabling technologies for 6G cognitive service architecture are discussed at last.

Lightweight Multi-Branch Network For Person Re-Identification

Abstract: Person Re-Identification aims to retrieve person identities from images captured by multiple cameras or the same cameras in different time instances and locations. Because of its importance in many vision applications from surveillance to human-machine interaction, person re-identification methods need to be reliable and fast. While more and more deep architectures are proposed for increasing performance, those methods also increase overall model complexity. This paper proposes a lightweight network that combines global, part-based, and channel features in a unified multi-branch architecture that builds on the resource-efficient OSNet backbone. Using a well-founded combination of training techniques and design choices, our final model achieves state-of-the-art results on CUHK03 labeled, CUHK03 detected, and Market-1501 with 85.1% mAP / 87.2% rank1, 82.4% mAP / 84.9% rank1, and 91.5% mAP / 96.3% rank1, respectively.

Generative systems in the architecture, engineering and construction industry: A systematic review and analysis:

Abstract: Researchers have been extensively exploring the employment of generative systems to support design practices in the architecture, engineering and construction industry since the 1970s. More than ha...