831 resultados para Formal Methods. Component-Based Development. Competition. Model Checking
Resumo:
Maximisation of Knowledge-Based Development (KBD) benefits requires effective dissemination and utilisation mechanisms to accompany the initial knowledge creation process. This work highlights the potential for interactions between Supply Chains (SCs) and Small and Medium sized Enterprise Clusters (SMECs), (including via ‘junction’ firms which are members of both networks), to facilitate such effective dissemination and utilisation of knowledge. In both these network types there are firms that readily utilise their relationships and ties for ongoing business success through innovation. The following chapter highlights the potential for such beneficial interactions between SCs and SMECs in key elements of KBD, particularly knowledge management, innovation and technology transfer. Because there has been little focus on the interactions between SCs and SMECs, particularly when firms simultaneously belong to both, this chapter examines the conduits through which information and knowledge can be transferred and utilised. It shows that each network type has its own distinct advantages in the types of information searched for and transferred amongst network member firms. Comparing and contrasting these advantages shows opportunities for both networks to leverage the knowledge sharing strengths of each other, through these ‘junctions’ to address their own weaknesses, allowing implications to be drawn concerning new ways of utilising relationships for mutual network gains.
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Modern computer graphics systems are able to construct renderings of such high quality that viewers are deceived into regarding the images as coming from a photographic source. Large amounts of computing resources are expended in this rendering process, using complex mathematical models of lighting and shading. However, psychophysical experiments have revealed that viewers only regard certain informative regions within a presented image. Furthermore, it has been shown that these visually important regions contain low-level visual feature differences that attract the attention of the viewer. This thesis will present a new approach to image synthesis that exploits these experimental findings by modulating the spatial quality of image regions by their visual importance. Efficiency gains are therefore reaped, without sacrificing much of the perceived quality of the image. Two tasks must be undertaken to achieve this goal. Firstly, the design of an appropriate region-based model of visual importance, and secondly, the modification of progressive rendering techniques to effect an importance-based rendering approach. A rule-based fuzzy logic model is presented that computes, using spatial feature differences, the relative visual importance of regions in an image. This model improves upon previous work by incorporating threshold effects induced by global feature difference distributions and by using texture concentration measures. A modified approach to progressive ray-tracing is also presented. This new approach uses the visual importance model to guide the progressive refinement of an image. In addition, this concept of visual importance has been incorporated into supersampling, texture mapping and computer animation techniques. Experimental results are presented, illustrating the efficiency gains reaped from using this method of progressive rendering. This visual importance-based rendering approach is expected to have applications in the entertainment industry, where image fidelity may be sacrificed for efficiency purposes, as long as the overall visual impression of the scene is maintained. Different aspects of the approach should find many other applications in image compression, image retrieval, progressive data transmission and active robotic vision.
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This paper introduces an event-based traffic model for railway systems adopting fixed-block signalling schemes. In this model, the events of trains' arrival at and departure from signalling blocks constitute the states of the traffic flow. A state transition is equivalent to the progress of the trains by one signalling block and it is realised by referring to past and present states, as well as a number of pre-calculated look-up tables of run-times in the signalling block under various signalling conditions. Simulation results are compared with those from a time-based multi-train simulator to study the improvement of processing time and accuracy.
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The impact of what has been broadly labelled the knowledge economy has been such that, even in the absence of precise measurement, it is the undoubted dynamo of today’s global market, and an essential part of any global city. The socio-economic importance of knowledge production in a knowledge economy is clear, and it is an emerging social phenomenon and research agenda in geographical studies. Knowledge production, and where, how and by whom it is produced, is an urban phenomenon that is poorly understood in an era of strong urbanisation. This paper focuses on knowledge community precincts as the catalytic magnet infrastructures impacting on knowledge production in cities. The paper discusses the increasing importance of knowledge-based urban development within the paradigm of the knowledge economy, and the role of knowledge community precincts as instruments to seed the foundation of knowledge production in cities. This paper explores the knowledge based urban development, and particularly knowledge community precinct development, potentials of Sydney, Melbourne and Brisbane, and benchmarks this against that of Boston, Massachusetts.
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A new approach that is slowly replacing neoclassical models of economic growth and commodity based industrial activities, knowledge based urban development (KBUD) aims to provide opportunities for citiesw to foster knowledge creation, exchange and innovation, and is based on the concepts of both sustainable urban development and economic prosperity; sustainable uses and protection of natural resources are therefore integral parts of KBUD. As such, stormwater, which has been recognised as one of the main culprits of aquatic ecosystem pollution and as therefore a significant threat to the goal of sustainable urban development, needs to be managed in a manner that produces ecologically sound outcomes. Water sensitive urban design (WSUD) is one of the key responses to the need to better management urban stormwater runoff and supports KBUD by providing an alternative, innovative and effective strategy to traditional stormwater management.
Resumo:
Over the past twenty years, the conventional knowledge management approach has evolved into a strategic management approach that has found applications and opportunities outside of business, in society at large, through education, urban development, governance, and healthcare, amongst others. Knowledge-Based Development for Cities and Socieities: Integrated Multi-Level Approaches enlightens the concepts and challenges of knowledge management for both urban environments and entire regions, enhancing the expertise and knowledge of scholars, resdearchers, practitioners, managers and urban developers in the development of successful knowledge-based development policies, creation of knowledte cities and prosperous knowledge societies. This reference creates large knowledge base for scholars, managers and urban developers and increases the awareness of the role of knowledge cities and knowledge socieiteis in the knowledge era, as well as of the challenges and opportunities for future research.
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Urban development in the first decade of the 21st century has faced many challenges ranging from rapid to shrinking urbanisation, from emerging knowledge economy to global division of labour and from globalisation to climate change. Along with these challenges new concepts, such as essentialism, environmentalism and dematerialism, are emerged and started to influence the way urban development plans are prepared and visions for the development of cities are made. Beyond this, scholars, practitioners and decision-makers have also started to discuss the need for an new urban planning and development approach in order to achieve a development that is sustainable and knowledge-based. Limited successful examples of alternative planning and development approaches showcased potentials of moving towards a new plan-making mindset in the era of knowledge economy. This paper presents a new urban planning and development approach that is taking application ground in many parts of the globe, namely knowledge-based urban development. After providing the theoretical foundation and conceptual framework of knowledge-based urban development the paper discusses whether knowledge-based development of cities is a myth or a reality.
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In recent years, ocean scientists have started to employ many new forms of technology as integral pieces in oceanographic data collection for the study and prediction of complex and dynamic ocean phenomena. One area of technological advancement in ocean sampling if the use of Autonomous Underwater Vehicles (AUVs) as mobile sensor plat- forms. Currently, most AUV deployments execute a lawnmower- type pattern or repeated transects for surveys and sampling missions. An advantage of these missions is that the regularity of the trajectory design generally makes it easier to extract the exact path of the vehicle via post-processing. However, if the deployment region for the pattern is poorly selected, the AUV can entirely miss collecting data during an event of specific interest. Here, we consider an innovative technology toolchain to assist in determining the deployment location and executed paths for AUVs to maximize scientific information gain about dynamically evolving ocean phenomena. In particular, we provide an assessment of computed paths based on ocean model predictions designed to put AUVs in the right place at the right time to gather data related to the understanding of algal and phytoplankton blooms.
Resumo:
Trajectory design for Autonomous Underwater Vehicles (AUVs) is of great importance to the oceanographic research community. Intelligent planning is required to maneuver a vehicle to high-valued locations for data collection. We consider the use of ocean model predictions to determine the locations to be visited by an AUV, which then provides near-real time, in situ measurements back to the model to increase the skill of future predictions. The motion planning problem of steering the vehicle between the computed waypoints is not considered here. Our focus is on the algorithm to determine relevant points of interest for a chosen oceanographic feature. This represents a first approach to an end to end autonomous prediction and tasking system for aquatic, mobile sensor networks. We design a sampling plan and present experimental results with AUV retasking in the Southern California Bight (SCB) off the coast of Los Angeles.
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Urban development in the 21st decade of the 21st century has faced many challenges ranging from rapid to shrinking urbanisation, from emerging knowledge economy to global division of labour and from globalisation to climate change. Along with with these challenges new concepts, such as essentialism, environmentalism and dematerialism, are emerged and started to influence the way urban development plans are prepared and visions for the development of cities are made. Beyond this, scholars, practitioners and decision-makers have also started to discuss the need for an new urban planning and development approach in order to achieve a development that is sustainable and knowledge-based. Limited successful examples of alternative planning and development approaches showcased potentials of moving towards a new plan-making mindset in the era of knowledge economy. This paper presents a new urban planning and development approach that is taking application ground in many parts of the globe, namely knowledge-based urban development. After providing the theoretical foundation and conceptual framework of knowledge-based urban development the paper discusses whether knowledge-based development of cities is a myth or a reality.