Showing papers on "Architecture published in 2017"

Building Information Modelling (BIM) uptake: Clear benefits, understanding its implementation, risks and challenges

Abstract: Rapid advancement of technology continues to leverage change and innovation in the construction industry. Continued digitization of the industry offers the opportunity to totally reinvent contemporary construction design and delivery practice for future development. Building Information Modelling (BIM) within the context of Architecture, Engineering & Construction (AEC) has been developing since the early 2000s and is considered to be a key technology. Despite major technical advancements in BIM, it has not been fully adopted and its definitive benefits have not been fully capitalized upon by industry stakeholders. The lack of widespread uptake of BIM appears to be linked to the risks and challenges that are potentially impeding its effectiveness. This paper aims to discuss the reality of BIM, its widespread benefits and current level of uptake. The risks and challenges associated with the adoption of BIM, as well as recommendations regarding how future BIM adoption could be developed are also highlighted.

A Manufacturing Big Data Solution for Active Preventive Maintenance

Abstract: Industry 4.0 has become more popular due to recent developments in cyber-physical systems, big data, cloud computing, and industrial wireless networks. Intelligent manufacturing has produced a revolutionary change, and evolving applications, such as product lifecycle management, are becoming a reality. In this paper, we propose and implement a manufacturing big data solution for active preventive maintenance in manufacturing environments. First, we provide the system architecture that is used for active preventive maintenance. Then, we analyze the method used for collection of manufacturing big data according to the data characteristics. Subsequently, we perform data processing in the cloud, including the cloud layer architecture, the real-time active maintenance mechanism, and the offline prediction and analysis method. Finally, we analyze a prototype platform and implement experiments to compare the traditionally used method with the proposed active preventive maintenance method. The manufacturing big data method used for active preventive maintenance has the potential to accelerate implementation of Industry 4.0.

Hierarchical Representations for Efficient Architecture Search

Abstract: We explore efficient neural architecture search methods and show that a simple yet powerful evolutionary algorithm can discover new architectures with excellent performance. Our approach combines a novel hierarchical genetic representation scheme that imitates the modularized design pattern commonly adopted by human experts, and an expressive search space that supports complex topologies. Our algorithm efficiently discovers architectures that outperform a large number of manually designed models for image classification, obtaining top-1 error of 3.6% on CIFAR-10 and 20.3% when transferred to ImageNet, which is competitive with the best existing neural architecture search approaches. We also present results using random search, achieving 0.3% less top-1 accuracy on CIFAR-10 and 0.1% less on ImageNet whilst reducing the search time from 36 hours down to 1 hour.

A Framework for Designing the Architectures of Deep Convolutional Neural Networks

Abstract: Recent advances in Convolutional Neural Networks (CNNs) have obtained promising results in difficult deep learning tasks. However, the success of a CNN depends on finding an architecture to fit a given problem. A hand-crafted architecture is a challenging, time-consuming process that requires expert knowledge and effort, due to a large number of architectural design choices. In this article, we present an efficient framework that automatically designs a high-performing CNN architecture for a given problem. In this framework, we introduce a new optimization objective function that combines the error rate and the information learnt by a set of feature maps using deconvolutional networks (deconvnet). The new objective function allows the hyperparameters of the CNN architecture to be optimized in a way that enhances the performance by guiding the CNN through better visualization of learnt features via deconvnet. The actual optimization of the objective function is carried out via the Nelder-Mead Method (NMM). Further, our new objective function results in much faster convergence towards a better architecture. The proposed framework has the ability to explore a CNN architecture’s numerous design choices in an efficient way and also allows effective, distributed execution and synchronization via web services. Empirically, we demonstrate that the CNN architecture designed with our approach outperforms several existing approaches in terms of its error rate. Our results are also competitive with state-of-the-art results on the MNIST dataset and perform reasonably against the state-of-the-art results on CIFAR-10 and CIFAR-100 datasets. Our approach has a significant role in increasing the depth, reducing the size of strides, and constraining some convolutional layers not followed by pooling layers in order to find a CNN architecture that produces a high recognition performance.

Invited Talk: U-Net Convolutional Networks for Biomedical Image Segmentation

Abstract: In the last years, deep convolutional networks have outperformed the state of the art in many visual recognition tasks. A central challenge for its wide adoption in the bio-medical imaging field is the limited amount of annotated training images. In this talk, I will present our u-net for biomedical image segmentation. The architecture consists of an analysis path and a synthesis path with additional shortcut-connections.

Exploiting Linked Data and Knowledge Graphs in Large Organisations

Abstract: This book addresses the topic of exploiting enterprise-linked data with a particularfocus on knowledge construction and accessibility within enterprises. It identifies thegaps between the requirements of enterprise knowledge consumption and standarddata consuming technologies by analysing real-world use cases, and proposes theenterprise knowledge graph to fill such gaps. It provides concrete guidelines for effectively deploying linked-data graphs withinand across business organizations. It is divided into three parts, focusing on the keytechnologies for constructing, understanding and employing knowledge graphs. Part 1 introduces basic background information and technologies, and presents asimple architecture to elucidate the main phases and tasks required during the lifecycleof knowledge graphs. Part 2 focuses on technical aspects; it starts with state-of-theart knowledge-graph construction approaches, and then discusses exploration andexploitation techniques as well as advanced question-answering topics concerningknowledge graphs. Lastly, Part 3 demonstrates examples of successful knowledgegraph applications in the media industry, healthcare and cultural heritage, and offersconclusions and future visions.

Real-time Convolutional Neural Networks for Emotion and Gender Classification

Abstract: In this paper we propose an implement a general convolutional neural network (CNN) building framework for designing real-time CNNs. We validate our models by creating a real-time vision system which accomplishes the tasks of face detection, gender classification and emotion classification simultaneously in one blended step using our proposed CNN architecture. After presenting the details of the training procedure setup we proceed to evaluate on standard benchmark sets. We report accuracies of 96% in the IMDB gender dataset and 66% in the FER-2013 emotion dataset. Along with this we also introduced the very recent real-time enabled guided back-propagation visualization technique. Guided back-propagation uncovers the dynamics of the weight changes and evaluates the learned features. We argue that the careful implementation of modern CNN architectures, the use of the current regularization methods and the visualization of previously hidden features are necessary in order to reduce the gap between slow performances and real-time architectures. Our system has been validated by its deployment on a Care-O-bot 3 robot used during RoboCup@Home competitions. All our code, demos and pre-trained architectures have been released under an open-source license in our public repository.

Forensic Architecture: Violence at the Threshold of Detectability

Abstract: This is the first, in depth book on the work of Forensic Architecture, a field of study which the author established. It is conceived as the inaugural book of a new academic field providing an introduction to the history, practice, assumptions, potentials, and double binds of FA. Across its 376 pages, it includes both theoretical and methodological reflections was well as dozens of investigations (in Pakistan, the West Bank, Syria, Gaza and Guatemala), original maps, images, models and diagrams (that are themselves research products). The book demonstrates how architecture can be used an analytical framework to investigate armed conflicts and environmental destruction, as well as to cross-reference a variety of evidence sources, such as new media, remote sensing, material analysis, witness testimony, and crowd-sourcing. Forensic Architecture calls for a transformative politics in which architecture as a field of knowledge and a mode of interpretation exposes and confronts ever-new forms of state violence and secrecy.

Foregrounding Sociomaterial Practice in Our Understanding of Affordances: The Skilled Intentionality Framework.

Abstract: Social coordination and affordance perception always take part in concrete situations in real life. Nonetheless, the different fields of ecological psychology studying these phenomena do not seem to make this situated nature an object of study. To integrate both fields and extend the reach of the ecological approach, we introduce the Skilled Intentionality Framework (SIF) that situates both social coordination and affordance perception within the human form of life and its rich landscape of affordances. We argue that in the human form of life the social and the material are intertwined and best understood as sociomateriality. Taking the form of life as our starting point foregrounds sociomateriality in each perspective we take on engaging with affordances. Using ethnographical examples we show how sociomateriality shows up from three different perspectives we take on affordances in a real-life situation. One perspective shows us a landscape of affordances that the sociomaterial environment offers. Zooming in on this landscape to the perspective of a local observer, we can focus on an individual coordinating with affordances offered by things and other people situated in this landscape. Finally, viewed from within this unfolding activity, we arrive at the person’s lived perspective: a field of relevant affordances solicits activity. The Skilled Intentionality Framework offers a way of integrating social coordination and affordance theory by drawing attention to these complementary perspectives. We end by showing a real-life example from the practice of architecture that suggests how this situated view that foregrounds sociomateriality can extend the scope of ecological psychology to forms of so-called “higher” cognition.

Microservices: How To Make Your Application Scale

Abstract: The microservice architecture is a style inspired by service-oriented computing that has recently started gaining popularity and that promises to change the way in which software is perceived, conceived and designed. In this paper, we describe the main features of microservices and highlight how these features improve scalability.

Parametric design and daylighting: A literature review

Abstract: In the history, architecture was exploited to the human being to protect him from unsteady environmental conditions. In the past centuries, architecture was pioneer art which has special features such as; simplicity, organization, clear style, accurate decoration, material assembly, and so on. However, modern buildings become complex products that have so many parts which have to fulfil different functions. Therefore, new computational ways and techniques have been developed to facilitate the design of modern complicated buildings and to create a convenient quantitative relationship between the environment and the envelope, putting into consideration the obstacles which influence on the building design. This has therefore formed the concept of parametric design in architecture, in order to deal with complex designs and gain more accurate results. Modern architects claim that parametric design is the most creative way to understand the development and complexity of the new era of architectural trends [1]. Meanwhile, it is really hard to deal with sophisticated details in buildings using our brains to imagine, or conventional ways to design [2]. In addition, building technologies nowadays are integrated and containing many disciplines in the same time, and each discipline is dependent on the other disciplines in a very complex vast connections. Hence, they should be organized in a database container, and this container could be managed parametrically using parametric design as an advanced way to explore and understand these sophisticated relations [3]. This paper hence presents a literature review on parametric design in architecture practice and put a focus on its applications in daylighting and solar radiation, which can have an essential impact on improving daylight availability and energy saving.

Clean Architecture: A Craftsman's Guide to Software Structure and Design

Abstract: Components You may find it strange that we would create a component—in this example, UService—that contains nothing but an interface. Such a component contains no executable code! It turns out, however, that this is a very common, and necessary, tactic when using statically typed languages like Java and C#. These abstract components are very stable and, therefore, are ideal targets for less stable components to depend on. When using dynamically typed languages like Ruby and Python, these abstract components don’t exist at all, nor do the dependencies that would

A survey of big data architectures and machine learning algorithms in healthcare

Abstract: Big Data has gained much attention from researchers in healthcare, bioinformatics, and information sciences. As a result, data production at this stage will be 44 times greater than that in 2009. Hence, the volume, velocity, and variety of data rapidly increase. Hence, it is difficult to store, process and visualise this huge data using traditional technologies. Many organisations such as Twitter, LinkedIn, and Facebook are used big data for different use cases in the social networking domain. Also, implementations of such architectures of the use cases have been published worldwide. However, a conceptual architecture for specific big data application has been limited. The intention of this paper is application-oriented architecture for big data systems, which is based on a study of published big data architectures for specific use cases. This paper also provides an overview of the state-of-the-art machine learning algorithms for processing big data in healthcare and other applications.

Buildings, Beauty, and the Brain: A Neuroscience of Architectural Experience

Abstract: A burgeoning interest in the intersection of neuroscience and architecture promises to offer biologically inspired insights into the design of spaces. The goal of such interdisciplinary approaches to architecture is to motivate construction of environments that would contribute to peoples' flourishing in behavior, health, and well-being. We suggest that this nascent field of neuroarchitecture is at a pivotal point in which neuroscience and architecture are poised to extend to a neuroscience of architecture. In such a research program, architectural experiences themselves are the target of neuroscientific inquiry. Here, we draw lessons from recent developments in neuroaesthetics to suggest how neuroarchitecture might mature into an experimental science. We review the extant literature and offer an initial framework from which to contextualize such research. Finally, we outline theoretical and technical challenges that lie ahead.

Blockchain-based platform architecture for industrial IoT

Abstract: The development of robotics, the Internet of Things concept, big data processing techniques, automation, and distributed digital ledgers leads to the fourth industrial revolution. One of the main issues of new industry is interaction between the "smart factory" components both internally and with other factories based on the Internet of Things. This interaction should provide trust between the participants of the Internet of Things; control over the distribution of resources (such as maintenance time, energy, etc.) and finished products. The paper describes one of the possible ways of integrating Internet of Things and blockchain technologies to solve these issues. For this purpose, an architecture has been developed that combines Smart-M3 information sharing platform and blockchain platform. One of the main features of the proposed architecture is the use of smart contracts for processing and storing information related to the interaction between smart space components.

SIPHON: Towards Scalable High-Interaction Physical Honeypots

Abstract: In recent years, the emerging Internet-of-Things (IoT) has led to rising concerns about the security of networked embedded devices. In this work, we propose the SIPHON architecture---a Scalable high-Interaction Honeypot platform for IoT devices. Our architecture leverages IoT devices that are physically at one location and are connected to the Internet through so-called \emph{wormholes} distributed around the world. The resulting architecture allows exposing few physical devices over a large number of geographically distributed IP addresses. We demonstrate the proposed architecture in a large scale experiment with 39 wormhole instances in 16 cities in 9 countries. Based on this setup, five physical IP cameras, one NVR and one IP printer are presented as 85 real IoT devices on the Internet, attracting a daily traffic of 700MB for a period of two months. A preliminary analysis of the collected traffic indicates that devices in some cities attracted significantly more traffic than others (ranging from 600 000 incoming TCP connections for the most popular destination to less than 50 000 for the least popular). We recorded over 400 brute-force login attempts to the web-interface of our devices using a total of 1826 distinct credentials, from which 11 attempts were successful. Moreover, we noted login attempts to Telnet and SSH ports some of which used credentials found in the recently disclosed Mirai malware.

Data-Driven News Generation for Automated Journalism

Abstract: Despite increasing amounts of data and ever improving natural language generation techniques, work on automated journalism is still relatively scarce. In this paper, we explore the field and challenges associated with building a journalistic natural language generation system. We present a set of requirements that should guide system design, including transparency, accuracy, modifiability and transferability. Guided by the requirements, we present a data-driven architecture for automated journalism that is largely domain and language independent. We illustrate its practical application in the production of news articles about the 2017 Finnish municipal elections in three languages, demonstrating the successfulness of the data-driven, modular approach of the design. We then draw some lessons for future automated journalism.

RAN revolution with NGFI (xHaul) for 5G

Abstract: From "Rethinking Ring and Young" in 2011 to proposing NGFI (xHaul) in 2014, the RAN revolutionary path to meet ambitious 5G demands has been charted out. Traditional fronthaul solutions fell short both in required bandwidth and architecture flexibility. Next generation fronthaul interface (NGFI, aka xHaul) proposed by China Mobile targeting a packet-based, traffic-dependent, and antenna scale-independent interface will be central to the 5G RAN revolution. This paper presents its latest progress. Specifically, a two-level NGFI architecture will be highlighted, and the function split options with associated requirements in, e.g. latency, bandwidth and synchronization will be presented. In addition, challenges for NGFI realization will be discussed.

Big Data Analytics Embedded Smart City Architecture for Performance Enhancement through Real-Time Data Processing and Decision-Making

Abstract: The concept of the smart city is widely favored, as it enhances the quality of life of urban citizens, involving multiple disciplines, that is, smart community, smart transportation, smart healthcare, smart parking, and many more. Continuous growth of the complex urban networks is significantly challenged by real-time data processing and intelligent decision-making capabilities. Therefore, in this paper, we propose a smart city framework based on Big Data analytics. The proposed framework operates on three levels: data generation and acquisition level collecting heterogeneous data related to city operations, data management and processing level filtering, analyzing, and storing data to make decisions and events autonomously, and application level initiating execution of the events corresponding to the received decisions. In order to validate the proposed architecture, we analyze a few major types of dataset based on the proposed three-level architecture. Further, we tested authentic datasets on Hadoop ecosystem to determine the threshold and the analysis shows that the proposed architecture offers useful insights into the community development authorities to improve the existing smart city architecture.

Persistent memcached: bringing legacy code to byte-addressable persistent memory

Abstract: We report our experience building and evaluating pmemcached, a version of memcached ported to byte-addressable persistent memory. Persistent memory is expected to not only improve overall performance of applications' persistence tier, but also vastly reduce the "warm up" time needed for applications after a restart. We decided to test this hypothesis on memcached, a popular key-value store. We took the extreme view of persisting memcached's entire state, resulting in a virtually instantaneous warm up phase. Since memcached is already optimized for DRAM, we expected our port to be a straightforward engineering effort. However, the effort turned out to be surprisingly complex during which we encountered several non-trivial problems that challenged the boundaries of memcached's architecture. We detail these experiences and corresponding lessons learned.

The Silent Complicity of Architecture

Abstract: We experience architecture primarily in states of distraction; we live in it first and look at it second. Our contemplative gaze falls upon ‘architecture’ within a spatial world we have already silently imbibed and embodied. How do we reconcile this unreflexive embodiment with the production of architectural imagery; everyday life with architecture as discourse? This is a key task for architectural theory and Bourdieu can be a useful ally.

The formal and informal tools of design governance

Abstract: This paper takes a typological exploration of the ‘tools’ of ‘design governance’. It begins by exploring the generic literature that focuses on the range of instruments, approaches and actions ‒ the tools ‒ that policy makers deploy in order to steer public and private actors towards particular policy outcomes. Subsequently, how the notion of tools relates to practices of design governance is examined: first, encompassing three ‘formal’ categories of design governance tools ‒ guidance, incentive and control ‒ and second, by drawing on the work of the former Commission for Architecture and the Built Environment (CABE) in England to introduce five categories of ‘informal’ design governance tools ‒ evidence, knowledge, promotion, evaluation and assistance. The result, and the key contribution of this paper, is a new and comprehensive (albeit evolving), design governance toolbox that extends from formal to informal tools and far beyond that which most policy makers recognize or use.

The travelling business of sustainable urbanism: International consultants as norm-setters:

Abstract: This paper examines the international travels of ideas about sustainable urban planning and design through a focus on private sector architecture, planning and engineering consultants. These consul ...

Towards a Functional System Architecture for Automated Vehicles.

Abstract: This paper presents a functional system architecture for an automated vehicle. It provides an overall, generic structure that is independent of a specific implementation of a particular vehicle project. Yet, it has been inspired and cross-checked with a real world automated driving implementation in the Stadtpilot project at the Technische Universitat Braunschweig. The architecture entails aspects like environment and self perception, planning and control, localization, map provision, Vehicle-To-X-communication, and interaction with human operators.

Glimpse: A Programmable Early-Discard Camera Architecture for Continuous Mobile Vision

Abstract: We consider the problem of continuous computer-vision based analysis of video streams from mobile cameras over extended periods. Given high computational demands, general visual processing must currently be offloaded to the cloud. To reduce mobile battery and bandwidth consumption, recent proposals offload only "interesting" video frames, discarding the rest. However, determining what to discard is itself typically a power-hungry computer vision calculation, very often well beyond what most mobile devices can afford on a continuous basis. We present the Glimpse system, a re-design of the conventional mobile video processing pipeline to support such "early discard" flexibly, efficiently and accurately. Glimpse is a novel architecture that gates wearable vision using low-power vision modalities. Our proposed architecture adds novel sensing, processing, algorithmic and programming-system components to the camera pipeline to this end. We present a complete implementation and evaluation of our design. In common settings, Glimpse reduces mobile power and data usage by more than one order of magnitude relative to earlier designs, and moves continuous vision on lightweight wearables to the realm of the practical.

The Icon Project: Architecture, Cities, and Capitalist Globalization

Abstract: In the last quarter century, a new form of iconic architecture has appeared throughout the world's major cities. Typically designed by globe-trotting "starchitects" or by a few large transnational architectural firms, these projects are almost always funded by the private sector in the service of private interests. Whereas in the past monumental architecture often had a strong public component, the urban ziggurats of today are emblems and conduits of capitalist globalization. In The Icon Project, Leslie Sklair focuses on ways in which capitalist globalization is produced and represented all over the world, especially in globalizing cities. Sklair traces how the iconic buildings of our era — elaborate shopping malls, spectacular museums, and vast urban megaprojects — constitute the triumphal "Icon Project" of contemporary global capitalism, promoting increasing inequality and hyperconsumerism. Two of the most significant strains of iconic architecture — unique icons recognized as works of art, designed by the likes of Gehry, Foster, Koolhaas, and Hadid, as well as successful, derivative icons that copy elements of the starchitects' work — speak to the centrality of hyperconsumerism within contemporary capitalism. Along with explaining how the architecture industry organizes the social production and marketing of iconic structures, he also shows how corporations increasingly dominate the built environment and promote the trend towards globalizing, consumerist cities. The Icon Project, Sklair argues, is a weapon in the struggle to solidify capitalist hegemony as well as reinforce transnational capitalist control of where we live, what we consume, and how we think.

Author and Audience in Vitruvius' De architectura

Abstract: Vitruvius' De architectura is the only extant classical text on architecture, and its impact on Renaissance masters including Leonardo da Vinci is well-known. But what was the text's purpose in its own time (ca. 20s BCE)? In this book, Marden Fitzpatrick Nichols reveals how Vitruvius pitched the Greek discipline of architecture to his Roman readers, most of whom were undoubtedly laymen. The inaccuracy of Vitruvius' architectural rules, when compared with surviving ancient buildings, has knocked Vitruvius off his pedestal. Nichols argues that the author never intended to provide an accurate view of contemporary buildings. Instead, Vitruvius crafted his authorial persona and remarks on architecture to appeal to elites (and would-be elites) eager to secure their positions within an expanding empire. In this major new analysis of De architectura from archaeological and literary perspectives, Vitruvius emerges as a knowing critic of a social landscape in which the house made the man.