30 resultados para Knowledge-based urban development


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The current rate of global biodiversity loss led many governments to sign the international agreement ‘Halting Biodiversity Loss by 2010 and beyond’ in 2001. The UK government was one of these and has a number of methods to tackle this, such as: commissioning specific technical guidance and supporting the UK Biodiversity Acton Plan (BAP) targets. However, by far the most effective influence the government has upon current biodiversity levels is through the town planning system. This is due to the control it has over all phases of a new development scheme’s lifecycle.There is an increasing myriad of regulations, policies and legislation, which deal with biodiversity protection and enhancement across the hierarchical spectrum: from the global and European level, down to regional and local levels. With these drivers in place, coupled with the promotion of benefits and incentives, increasing biodiversity value ought to be an achievable goal on most, if not all development sites. However, in the professional world, this is not the case due to a number of obstructions. Many of these tend to be ‘process’ barriers, which are particularly prevalent with ‘urban’ and ‘major’ development schemes, and is where the focus of this research paper lies.The paper summarises and discusses the results of a questionnaire survey, regarding obstacles to maximising biodiversity enhancements on major urban development schemes. The questionnaire was completed by Local Government Ecologists in England. The paper additionally refers to insights from previous action research, specialist interviews, and case studies, to reveal the key process obstacles.Solutions to these obstacles are then alluded to and recommendations are made within the discussion.

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Design of casting entails the knowledge of various interacting factors that are unique to casting process, and, quite often, product designers do not have the required foundry-specific knowledge. Casting designers normally have to liaise with casting experts in order to ensure the product designed is castable and the optimum casting method is selected. This two-way communication results in long design lead times, and lack of it can easily lead to incorrect casting design. A computer-based system at the discretion of a design engineer can, however, alleviate this problem and enhance the prospect of casting design for manufacture. This paper proposes a knowledge-based expert system approach to assist casting product designers in selecting the most suitable casting process for specified casting design requirements, during the design phase of product manufacture. A prototype expert system has been developed, based on production rules knowledge representation technique. The proposed system consists of a number of autonomous but interconnected levels, each dealing with a specific group of factors, namely, casting alloy, shape and complexity parameters, accuracy requirements and comparative costs, based on production quantity. The user interface has been so designed to allow the user to have a clear view of how casting design parameters affect the selection of various casting processes at each level; if necessary, the appropriate design changes can be made to facilitate the castability of the product being designed, or to suit the design to a preferred casting method.

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Inventory control in complex manufacturing environments encounters various sources of uncertainity and imprecision. This paper presents one fuzzy knowledge-based approach to solving the problem of order quantity determination, in the presence of uncertain demand, lead time and actual inventory level. Uncertain data are represented by fuzzy numbers, and vaguely defined relations between them are modeled by fuzzy if-then rules. The proposed representation and inference mechanism are verified using a large numbers of examples. The results of three representative cases are summarized. Finally a comparison between the developed fuzzy knowledge-based and traditional, probabilistic approaches is discussed.

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Automated negotiation systems can do better than human being in many aspects, and thus are applied into many domains ranging from business to computer science. However, little work about automating negotiation of complex business contract has been done so far although it is a kind of the most important negotiation in business. In order to address this issue, in this paper we developed an automated system for this kind of negotiation. This system is based on the principled negotiation theory, which is the most effective method of negotiation in the domain of business. The system is developed as a knowledge-based one because a negotiating agent in business has to be economically intelligent and capable of making effective decisions based on business experiences and knowledge. Finally, the validity of the developed system is shown in a real negotiation scenario where on behalf of human users, the system successfully performed a negotiation of a complex business contract between a wholesaler and a retailer. © 2013 Springer-Verlag Berlin Heidelberg.

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Motivation: Influenza A viral heterogeneity remains a significant threat due to unpredictable antigenic drift in seasonal influenza and antigenic shifts caused by the emergence of novel subtypes. Annual review of multivalent influenza vaccines targets strains of influenza A and B likely to be predominant in future influenza seasons. This does not induce broad, cross protective immunity against emergent subtypes. Better strategies are needed to prevent future pandemics. Cross-protection can be achieved by activating CD8+ and CD4+ T cells against highly-conserved regions of the influenza genome. We combine available experimental data with informatics-based immunological predictions to help design vaccines potentially able to induce cross-protective T-cells against multiple influenza subtypes. Results: To exemplify our approach we designed two epitope ensemble vaccines comprising highly-conserved and experimentally-verified immunogenic influenza A epitopes as putative non-seasonal influenza vaccines; one specifically targets the US population and the other is a universal vaccine. The USA-specific vaccine comprised 6 CD8+ T cell epitopes (GILGFVFTL, FMYSDFHFI, GMDPRMCSL, SVKEKDMTK, FYIQMCTEL, DTVNRTHQY) and 3 CD4+ epitopes (KGILGFVFTLTVPSE, EYIMKGVYINTALLN, ILGFVFTLTVPSERG). The universal vaccine comprised 8 CD8+ epitopes: (FMYSDFHFI, GILGFVFTL, ILRGSVAHK, FYIQMCTEL, ILKGKFQTA, YYLEKANKI, VSDGGPNLY, YSHGTGTGY) and the same 3 CD4+ epitopes. Our USA-specific vaccine has a population protection coverage (portion of the population potentially responsive to one or more component epitopes of the vaccine, PPC) of over 96% and 95% coverage of observed influenza subtypes. The universal vaccine has a PPC value of over 97% and 88% coverage of observed subtypes.

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Purpose: This paper aims to explore the role of internal and external knowledgebased linkages across the supply chain in achieving better operational performance. It investigates how knowledge is accumulated, shared, and applied to create organization-specific knowledge resources that increase and sustain the organization's competitive advantage. Design/methodology/approach: This paper uses a single case study with multiple, embedded units of analysis, and the social network analysis (SNA) to demonstrate the impact of internal and external knowledge-based linkages across multiple tiers in the supply chain on the organizational operational performance. The focal company of the case study is an Italian manufacturer supplying rubber components to European automotive enterprises. Findings: With the aid of the SNA, the internal knowledge-based linkages can be mapped and visualized. We found that the most central nodes having the most connections with other nodes in the linkages are the most crucial members in terms of knowledge exploration and exploitation within the organization. We also revealed that the effective management of external knowledge-based linkages, such as buyer company, competitors, university, suppliers, and subcontractors, can help improve the operational performance. Research limitations/implications: First, our hypothesis was tested on a single case. The analysis of multiple case studies using SNA would provide a deeper understanding of the relationship between the knowledge-based linkages at all levels of the supply chain and the integration of knowledge. Second, the static nature of knowledge flows was studied in this research. Future research could also consider ongoing monitoring of dynamic linkages and the dynamic characteristic of knowledge flows. Originality/value: To the best of our knowledge, the phrase 'knowledge-based linkages' has not been used in the literature and there is lack of investigation on the relationship between the management of internal and external knowledge-based linkages and the operational performance. To bridge the knowledge gap, this paper will show the importance of understanding the composition and characteristics of knowledge-based linkages and their knowledge nodes. In addition, this paper will show that effective management of knowledge-based linkages leads to the creation of new knowledge and improves organizations' operational performance.

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Recent discussion of the knowledge-based economy draws increasingly attention to the role that the creation and management of knowledge plays in economic development. Development of human capital, the principal mechanism for knowledge creation and management, becomes a central issue for policy-makers and practitioners at the regional, as well as national, level. Facing competition both within and across nations, regional policy-makers view human capital development as a key to strengthening the positions of their economies in the global market. Against this background, the aim of this study is to go some way towards answering the question of whether, and how, investment in education and vocational training at regional level provides these territorial units with comparative advantages. The study reviews literature in economics and economic geography on economic growth (Chapter 2). In growth model literature, human capital has gained increased recognition as a key production factor along with physical capital and labour. Although leaving technical progress as an exogenous factor, neoclassical Solow-Swan models have improved their estimates through the inclusion of human capital. In contrast, endogenous growth models place investment in research at centre stage in accounting for technical progress. As a result, they often focus upon research workers, who embody high-order human capital, as a key variable in their framework. An issue of discussion is how human capital facilitates economic growth: is it the level of its stock or its accumulation that influences the rate of growth? In addition, these economic models are criticised in economic geography literature for their failure to consider spatial aspects of economic development, and particularly for their lack of attention to tacit knowledge and urban environments that facilitate the exchange of such knowledge. Our empirical analysis of European regions (Chapter 3) shows that investment by individuals in human capital formation has distinct patterns. Those regions with a higher level of investment in tertiary education tend to have a larger concentration of information and communication technology (ICT) sectors (including provision of ICT services and manufacture of ICT devices and equipment) and research functions. Not surprisingly, regions with major metropolitan areas where higher education institutions are located show a high enrolment rate for tertiary education, suggesting a possible link to the demand from high-order corporate functions located there. Furthermore, the rate of human capital development (at the level of vocational type of upper secondary education) appears to have significant association with the level of entrepreneurship in emerging industries such as ICT-related services and ICT manufacturing, whereas such association is not found with traditional manufacturing industries. In general, a high level of investment by individuals in tertiary education is found in those regions that accommodate high-tech industries and high-order corporate functions such as research and development (R&D). These functions are supported through the urban infrastructure and public science base, facilitating exchange of tacit knowledge. They also enjoy a low unemployment rate. However, the existing stock of human and physical capital in those regions with a high level of urban infrastructure does not lead to a high rate of economic growth. Our empirical analysis demonstrates that the rate of economic growth is determined by the accumulation of human and physical capital, not by level of their existing stocks. We found no significant effects of scale that would favour those regions with a larger stock of human capital. The primary policy implication of our study is that, in order to facilitate economic growth, education and training need to supply human capital at a faster pace than simply replenishing it as it disappears from the labour market. Given the significant impact of high-order human capital (such as business R&D staff in our case study) as well as the increasingly fast pace of technological change that makes human capital obsolete, a concerted effort needs to be made to facilitate its continuous development.

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Benchmarking exercises have become increasingly popular within the sphere of regional policy making. However, most exercises are restricted to comparing regions within a particular continental bloc or nation.This article introduces the World Knowledge Competitiveness Index (WKCI), which is one of the very few benchmarking exercises established to compare regions across continents.The article discusses the formulation of the WKCI and analyzes the results of the most recent editions.The results suggest that there are significant variations in the knowledge-based regional economic development models at work across the globe. Further analysis also indicates that Silicon Valley, as the highest ranked WKCI region, holds a unique economic position among the globe’s leading regions. However, significant changes in the sources of regional competitiveness are evolving as a result of the emergence of new regional hot spots in Asia. It is concluded that benchmarking is imperative to the learning process of regional policy making.

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Since much knowledge is tacit, eliciting knowledge is a common bottleneck during the development of knowledge-based systems. Visual interactive simulation (VIS) has been proposed as a means for eliciting experts’ decision-making by getting them to interact with a visual simulation of the real system in which they work. In order to explore the effectiveness and efficiency of VIS based knowledge elicitation, an experiment has been carried out with decision-makers in a Ford Motor Company engine assembly plant. The model properties under investigation were the level of visual representation (2-dimensional, 2½-dimensional and 3-dimensional) and the model parameter settings (unadjusted and adjusted to represent more uncommon and extreme situations). The conclusion from the experiment is that using a 2-dimensional representation with adjusted parameter settings provides the better simulation-based means for eliciting knowledge, at least for the case modelled.

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Knowledge elicitation is a well-known bottleneck in the production of knowledge-based systems (KBS). Past research has shown that visual interactive simulation (VIS) could effectively be used to elicit episodic knowledge that is appropriate for machine learning purposes, with a view to building a KBS. Nonetheless, the VIS-based elicitation process still has much room for improvement. Based in the Ford Dagenham Engine Assembly Plant, a research project is being undertaken to investigate the individual/joint effects of visual display level and mode of problem case generation on the elicitation process. This paper looks at the methodology employed and some issues that have been encountered to date. Copyright © 2007 Inderscience Enterprises Ltd.

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Purpose – The purpose of this paper is to analyze the way in which the knowledge competitiveness of regions is measured and further introduces the World Knowledge Competitiveness Index (WKCI) benchmarking tool. Design/methodology/approach – The methodology consists of an econometric analysis of key indicators relating to the concept of knowledge competitiveness for 125 regions from across the globe consisting of 55 representatives from North America, 45 from Europe and 25 from Asia and Oceania. Findings – The key to winning the super competitive race in the knowledge-based economy is investment in the future: research and development, and education and training. It is found that the majority of the high-performing regional economies in the USA have a knowledge competitive edge over their counterparts in Europe and Asia. Research limitations/implications – To an extent, the research is limited by the availability of comparable indicators and metrics at the regional level that extend across the globe. Whilst comparative data are often accessible at the national level, regional data sources remain underdeveloped. Practical implications – The WKCI has become internationally recognized as an important instrument for economic development policymakers and regional investment promotion agents as they create and refine their strategies and targets. In particular, it has provided a benchmark that allows regions to compare their knowledge competitiveness with other regions for around the world and not only their own nation or continent. Originality/value – The WKCI is the first composite and relative measure of the knowledge competitiveness of the globe's best performing regions.

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The research work reported in this thesis is concerned with the development and application of an urban scale sampling methodology for measuring and assessing background levels of heavy metal soil contamination in large and varied urban areas. The policy context of the work is broadly the environmental health problems posed by contaminated land and their implications for urban development planning. Within this wider policy context, the emphasis in the research has been placed on issues, related to the determination and application of 'guidelines' for assessing the significance of contaminated land for environmental planning. In concentrating on background levels of land contamination, the research responds to the need for additional techniques which address both the problems of measuring soil contamination at the urban scale and which are also capable of providing detailed information for use in the assessment of contaminated sites. Therefore, a key component of the work has been the development of a land-use based sampling framework for generating spatially comprehensive data on heavy metals in soil. The utility of the information output of the sampling method is demonstrated in two alternative ways. Firstly, it has been used to map the existing pattern of typical levels of heavy metals in urban soils. Secondly, it can be used to generate both generalised data in the form of 'reference levels' from which the overall significance of .background contamination may be assessed and detailed data, termed 'normal limit levels' for use in the assessment of site specific investigation data. The fieldwork was conducted in the West Midlands Metropolitan County and surface soil has been sampled and analysed for a measure of plant-available' and 'total' lead cadmium, copper and zinc. The research contrasts with much of the previous work on contaminated land which has generally concentrated on either the detailed investigation of individual sites suspected of being contaminated or the appraisal of land contamination resulting from specific point sources.

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The research described here concerns the development of metrics and models to support the development of hybrid (conventional/knowledge based) integrated systems. The thesis argues from the point that, although it is well known that estimating the cost, duration and quality of information systems is a difficult task, it is far from clear what sorts of tools and techniques would adequately support a project manager in the estimation of these properties. A literature review shows that metrics (measurements) and estimating tools have been developed for conventional systems since the 1960s while there has been very little research on metrics for knowledge based systems (KBSs). Furthermore, although there are a number of theoretical problems with many of the `classic' metrics developed for conventional systems, it also appears that the tools which such metrics can be used to develop are not widely used by project managers. A survey was carried out of large UK companies which confirmed this continuing state of affairs. Before any useful tools could be developed, therefore, it was important to find out why project managers were not using these tools already. By characterising those companies that use software cost estimating (SCE) tools against those which could but do not, it was possible to recognise the involvement of the client/customer in the process of estimation. Pursuing this point, a model of the early estimating and planning stages (the EEPS model) was developed to test exactly where estimating takes place. The EEPS model suggests that estimating could take place either before a fully-developed plan has been produced, or while this plan is being produced. If it were the former, then SCE tools would be particularly useful since there is very little other data available from which to produce an estimate. A second survey, however, indicated that project managers see estimating as being essentially the latter at which point project management tools are available to support the process. It would seem, therefore, that SCE tools are not being used because project management tools are being used instead. The issue here is not with the method of developing an estimating model or tool, but; in the way in which "an estimate" is intimately tied to an understanding of what tasks are being planned. Current SCE tools are perceived by project managers as targetting the wrong point of estimation, A model (called TABATHA) is then presented which describes how an estimating tool based on an analysis of tasks would thus fit into the planning stage. The issue of whether metrics can be usefully developed for hybrid systems (which also contain KBS components) is tested by extending a number of "classic" program size and structure metrics to a KBS language, Prolog. Measurements of lines of code, Halstead's operators/operands, McCabe's cyclomatic complexity, Henry & Kafura's data flow fan-in/out and post-release reported errors were taken for a set of 80 commercially-developed LPA Prolog programs: By re~defining the metric counts for Prolog it was found that estimates of program size and error-proneness comparable to the best conventional studies are possible. This suggests that metrics can be usefully applied to KBS languages, such as Prolog and thus, the development of metncs and models to support the development of hybrid information systems is both feasible and useful.

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There is a growing awareness in the UK and mainland Europe of the importance of higher education to the development of a knowledge-based economy. European universities are increasingly required to produce highly mobile graduates able to respond to the ever-changing needs of the contemporary workplace. Following the Bologna Declaration (19991. 19 June 1999 . “The European Higher Education Area” (Bologna Declaration), Joint Declaration of the European Ministers of Education, Bologna, higher education across Europe has expanded rapidly. This has resulted in questions being raised about the quality of the graduate labour market and the ability of graduates to meet the needs of employers. This paper analyses graduate and employer perspectives of graduate employability in four European countries (UK, Austria, Slovenia and Romania). In doing so it adds to current debates in this area.