209 resultados para Knowledge-based industry


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Reforms to the national research and research training system by the Commonwealth Government of Australia sought to effectively connect research conducted in universities to Australia's national innovation system. Research training has a key role in ensuring an adequate supply of highly skilled people for the national innovation system. During their studies, research students produce and disseminate a massive amount of new knowledge. Prior to this study, there was no research that examined the contribution of research training to Australia's national innovation system despite the existence of policy initiatives aiming to enhance this contribution. Given Australia's below average (but improving) innovation performance compared to other OECD countries, the inclusion of Finland and the United States provided further insights into the key research question. This study examined three obvious ways that research training contributes to the national innovation systems in the three countries: the international mobility and migration of research students and graduates, knowledge production and distribution by research students, and the impact of research training as advanced human capital formation on economic growth. Findings have informed the concept of a research training culture of innovation that aims to enhance the contribution of research training to Australia's national innovation system. Key features include internationally competitive research and research training environments; research training programs that equip students with economically-relevant knowledge and the capabilities required by employers operating in knowledge-based economies; attractive research careers in different sectors; a national commitment to R&D as indicated by high levels of gross and business R&D expenditure; high private and social rates of return from research training; and the horizontal coordination of key organisations that create policy for, and/or invest in research training.

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Artificial neural network (ANN) learning methods provide a robust and non-linear approach to approximating the target function for many classification, regression and clustering problems. ANNs have demonstrated good predictive performance in a wide variety of practical problems. However, there are strong arguments as to why ANNs are not sufficient for the general representation of knowledge. The arguments are the poor comprehensibility of the learned ANN, and the inability to represent explanation structures. The overall objective of this thesis is to address these issues by: (1) explanation of the decision process in ANNs in the form of symbolic rules (predicate rules with variables); and (2) provision of explanatory capability by mapping the general conceptual knowledge that is learned by the neural networks into a knowledge base to be used in a rule-based reasoning system. A multi-stage methodology GYAN is developed and evaluated for the task of extracting knowledge from the trained ANNs. The extracted knowledge is represented in the form of restricted first-order logic rules, and subsequently allows user interaction by interfacing with a knowledge based reasoner. The performance of GYAN is demonstrated using a number of real world and artificial data sets. The empirical results demonstrate that: (1) an equivalent symbolic interpretation is derived describing the overall behaviour of the ANN with high accuracy and fidelity, and (2) a concise explanation is given (in terms of rules, facts and predicates activated in a reasoning episode) as to why a particular instance is being classified into a certain category.

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Together with hard and soft networks tangible and intangible regional assets play an important role in the knowledge-based development of competing city-regions. The aim of this paper, therefore, is to investigate the best ways of managing invaluable tangible and intangible assets of city-regions. The paper explores the importance of asset management of city-regions by giving special emphasis on their knowledge asset base. This paper develops and introduces a theoretical framework to conceptualise a new approach to articulate the strategic planning mechanism, so called the 6K1C framework. The 6K1C framework is part of the strategic planning process of continuous improvement of overall public sector performance. The framework provides a proactive check-list approach integrated for managing and harnessing tangible and intangible assets of the post-industrial city-regions.

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Many cities worldwide face the prospect of major transformation as the world moves towards a global information order. In this new era, urban economies are being radically altered by dynamic processes of economic and spatial restructuring. The result is the creation of ‘informational cities’ or its new and more popular name, ‘knowledge cities’. For the last two centuries, social production had been primarily understood and shaped by neo-classical economic thought that recognized only three factors of production: land, labor and capital. Knowledge, education, and intellectual capacity were secondary, if not incidental, factors. Human capital was assumed to be either embedded in labor or just one of numerous categories of capital. In the last decades, it has become apparent that knowledge is sufficiently important to deserve recognition as a fourth factor of production. Knowledge and information and the social and technological settings for their production and communication are now seen as keys to development and economic prosperity. The rise of knowledge-based opportunity has, in many cases, been accompanied by a concomitant decline in traditional industrial activity. The replacement of physical commodity production by more abstract forms of production (e.g. information, ideas, and knowledge) has, however paradoxically, reinforced the importance of central places and led to the formation of knowledge cities. Knowledge is produced, marketed and exchanged mainly in cities. Therefore, knowledge cities aim to assist decision-makers in making their cities compatible with the knowledge economy and thus able to compete with other cities. Knowledge cities enable their citizens to foster knowledge creation, knowledge exchange and innovation. They also encourage the continuous creation, sharing, evaluation, renewal and update of knowledge. To compete nationally and internationally, cities need knowledge infrastructures (e.g. universities, research and development institutes); a concentration of well-educated people; technological, mainly electronic, infrastructure; and connections to the global economy (e.g. international companies and finance institutions for trade and investment). Moreover, they must possess the people and things necessary for the production of knowledge and, as importantly, function as breeding grounds for talent and innovation. The economy of a knowledge city creates high value-added products using research, technology, and brainpower. Private and the public sectors value knowledge, spend money on its discovery and dissemination and, ultimately, harness it to create goods and services. Although many cities call themselves knowledge cities, currently, only a few cities around the world (e.g., Barcelona, Delft, Dublin, Montreal, Munich, and Stockholm) have earned that label. Many other cities aspire to the status of knowledge city through urban development programs that target knowledge-based urban development. Examples include Copenhagen, Dubai, Manchester, Melbourne, Monterrey, Singapore, and Shanghai. Knowledge-Based Urban Development To date, the development of most knowledge cities has proceeded organically as a dependent and derivative effect of global market forces. Urban and regional planning has responded slowly, and sometimes not at all, to the challenges and the opportunities of the knowledge city. That is changing, however. Knowledge-based urban development potentially brings both economic prosperity and a sustainable socio-spatial order. Its goal is to produce and circulate abstract work. The globalization of the world in the last decades of the twentieth century was a dialectical process. On one hand, as the tyranny of distance was eroded, economic networks of production and consumption were constituted at a global scale. At the same time, spatial proximity remained as important as ever, if not more so, for knowledge-based urban development. Mediated by information and communication technology, personal contact, and the medium of tacit knowledge, organizational and institutional interactions are still closely associated with spatial proximity. The clustering of knowledge production is essential for fostering innovation and wealth creation. The social benefits of knowledge-based urban development extend beyond aggregate economic growth. On the one hand is the possibility of a particularly resilient form of urban development secured in a network of connections anchored at local, national, and global coordinates. On the other hand, quality of place and life, defined by the level of public service (e.g. health and education) and by the conservation and development of the cultural, aesthetic and ecological values give cities their character and attract or repel the creative class of knowledge workers, is a prerequisite for successful knowledge-based urban development. The goal is a secure economy in a human setting: in short, smart growth or sustainable urban development.

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Where a city or a country aspires to be in a decade or two from now on? How its social, economic and urban structures would be shaped by then? These are very complex two questions to answer precisely, just as it is not possible to accurately predict, especially in the wake of the recent global financial crisis, what a city or a country would be transformed into over the next decades. Under this uncertainly, the incredible speed of the knowledge that is generated, marketed, exchanged and applied in all parts of our lives – society, economy, environment – provides a hope for furthering the development of our cities and countries (Carrillo, 2006). This is to say, in today’s global knowledge economy knowledge and talent are continued to be seen as prerequisites for success as it was always the case in the course of history.

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Background: A State-based industry in Australia is in the process of developing a programme to prevent AOD impairment in the workplace. The objective of this study was to determine whether the Theory of Planned Behaviour can help explain the mechanisms by which behaviour change occurs with regard to AOD impairment in the workplace. ---------- Method: A survey of 1165 employees of a State-based industry in Australia was conducted, and a response rate of 98% was achieved. The survey included questions relevant to the Theory of Planned Behaviour: behaviour; behavioural intentions; attitude; perceptions of social pressure; and perceived behavioural control with regard to workplace AOD impairment. ---------- Findings: Less than 3% of participants reported coming to work impaired by AODs. Fewer than 2% of participants reported that they intended to come to work impaired by AODs. The majority of participants (over 80%) reported unfavourable attitudes toward AOD impairment at work. Logistic regression analyses suggest that, consistent with the theory of planned behaviour: attitudes, perceptions of social pressure, and perceived behavioural control with regard to workplace AOD impairment, all predict behavioural intentions (P < .001); and behavioural intentions predict (self-reported) behaviour regarding workplace AOD impairment (P < .001). ---------- Conclusions: The Theory of Planned Behaviour appears to assist with understanding the mechanisms by which behaviour change occurs with regard to AOD impairment in the workplace. An occupational AOD programme which targets those mechanisms for change may improve its impact in preventing workplace AOD impairment.

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Relevance Feedback (RF) has been proven very effective for improving retrieval accuracy. Adaptive information filtering (AIF) technology has benefited from the improvements achieved in all the tasks involved over the last decades. A difficult problem in AIF has been how to update the system with new feedback efficiently and effectively. In current feedback methods, the updating processes focus on updating system parameters. In this paper, we developed a new approach, the Adaptive Relevance Features Discovery (ARFD). It automatically updates the system's knowledge based on a sliding window over positive and negative feedback to solve a nonmonotonic problem efficiently. Some of the new training documents will be selected using the knowledge that the system currently obtained. Then, specific features will be extracted from selected training documents. Different methods have been used to merge and revise the weights of features in a vector space. The new model is designed for Relevance Features Discovery (RFD), a pattern mining based approach, which uses negative relevance feedback to improve the quality of extracted features from positive feedback. Learning algorithms are also proposed to implement this approach on Reuters Corpus Volume 1 and TREC topics. Experiments show that the proposed approach can work efficiently and achieves the encouragement performance.

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Stormwater pollution has been recognised as one of the main causes of aquatic ecosystem degradation and poses a significant threat to both the goal of ecological sustainable development as well as human health and wellbeing. In response, water sensitive urban design (WSUD) practices have been put forward as a strategy to mitigate the detrimental impacts of urban stormwater runoff quality and to safeguard ecosystem functions. However, despite studies that support its efficiency in urban stormwater management, the mainstreaming of WSUD remains a significant challenge. This paper proposes that viewing WSUD through the lens of the integrated urban metabolism framework which encourages an interdisciplinary approach and facilitates dialogue through knowledge transfer is a strategy in which the implementation of WSUD can be mainstreamed.

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High fidelity simulation as a teaching and learning approach is being embraced by many schools of nursing. Our school embarked on integrating high fidelity (HF) simulation into the undergraduate clinical education program in 2011. Low and medium fidelity simulation has been used for many years, but this did not simplify the integration of HF simulation. Alongside considerations of how and where HF simulation would be integrated, issues arose with: student consent and participation for observed activities; data management of video files; staff development, and conceptualising how methods for student learning could be researched. Simulation for undergraduate student nurses commenced as a formative learning activity, undertaken in groups of eight, where four students undertake the ‘doing’ role and four are structured observers, who then take a formal role in the simulation debrief. Challenges for integrating simulation into student learning included conceptualising and developing scenarios to trigger students’ decision making and application of skills, knowledge and attitudes explicit to solving clinical ‘problems’. Developing and planning scenarios for students to ‘try out’ skills and make decisions for problem solving lay beyond choosing pre-existing scenarios inbuilt with the software. The supplied scenarios were not concept based but rather knowledge, skills and technology (of the manikin) focussed. Challenges lay in using the technology for the purpose of building conceptual mastery rather than using technology simply because it was available. As we integrated use of HF simulation into the final year of the program, focus was on building skills, knowledge and attitudes that went beyond technical skill, and provided an opportunity to bridge the gap with theory-based knowledge that students often found difficult to link to clinical reality. We wished to provide opportunities to develop experiential knowledge based on application and clinical reasoning processes in team environments where problems are encountered, and to solve them, the nurse must show leadership and direction. Other challenges included students consenting for simulations to be videotaped and ethical considerations of this. For example if one student in a group of eight did not consent, did this mean they missed the opportunity to undertake simulation, or that others in the group may be disadvantaged by being unable to review their performance. This has implications for freely given consent but also for equity of access to learning opportunities for students who wished to be taped and those who did not. Alongside this issue were the details behind data management, storage and access. Developing staff with varying levels of computer skills to use software and undertake a different approach to being the ‘teacher’ required innovation where we took an experiential approach. Considering explicit learning approaches to be trialled for learning was not a difficult proposition, but considering how to enact this as research with issues of blinding, timetabling of blinded groups, and reducing bias for testing results of different learning approaches along with gaining ethical approval was problematic. This presentation presents examples of these challenges and how we overcame them.

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It is a big challenge to guarantee the quality of discovered relevance features in text documents for describing user preferences because of the large number of terms, patterns, and noise. Most existing popular text mining and classification methods have adopted term-based approaches. However, they have all suffered from the problems of polysemy and synonymy. Over the years, people have often held the hypothesis that pattern-based methods should perform better than term- based ones in describing user preferences, but many experiments do not support this hypothesis. This research presents a promising method, Relevance Feature Discovery (RFD), for solving this challenging issue. It discovers both positive and negative patterns in text documents as high-level features in order to accurately weight low-level features (terms) based on their specificity and their distributions in the high-level features. The thesis also introduces an adaptive model (called ARFD) to enhance the exibility of using RFD in adaptive environment. ARFD automatically updates the system's knowledge based on a sliding window over new incoming feedback documents. It can efficiently decide which incoming documents can bring in new knowledge into the system. Substantial experiments using the proposed models on Reuters Corpus Volume 1 and TREC topics show that the proposed models significantly outperform both the state-of-the-art term-based methods underpinned by Okapi BM25, Rocchio or Support Vector Machine and other pattern-based methods.

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Design for Manufacturing (DFM) is a highly integral methodology in product development, starting from the concept development phase, with the aim of improving manufacturing productivity. It is used to reduce manufacturing costs in complex production environments, while maintaining product quality. While Design for Assembly (DFA) is focusing on elimination or combination of parts with other components, which in most cases relates to performing a function and manufacture operation in a simpler way, DFM is following a more holistic approach. Common consideration for DFM are standard components, manufacturing tool inventory and capability, materials compatibility with production process, part handling, logistics, tool wear and process optimization, quality control complexity or Poka-Yoke design. During DFM, the considerable background work required for the conceptual phase is compensated for by a shortening of later development phases. Current DFM projects normally apply an iterative step-by-step approach and eventually transfer to the developer team. The study is introducing a new, knowledge based approach to DFM, eliminating steps of DFM, and showing implications on the work process. Furthermore, a concurrent engineering process via transparent interface between the manufacturing engineering and product development systems is brought forward.

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This fourth edition of Communication, Cultural and Media Studies: The Key Concepts is an indispensible guide to the most important terms in the field. It offers clear explanations of the key concepts, exploring their origins, what they’re used for and why they provoke discussion. The author provides a multi-disciplinary explanation and assessment of the key concepts, from ‘authorship’ to ‘censorship’; ‘creative industries’ to ‘network theory’; ‘complexity’ to ‘visual culture’. The new edition of this classic text includes: * Over 200 entries including 50 new entries * All entries revised, rewritten and updated * Coverage of recent developments in the field * Insight into interactive media and the knowledge-based economy * A fully updated bibliography with 400 items and suggestions for further reading throughout the text

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Globalisation and the emergence of knowledge-based economies have forced many countries to reform their education system. The enhancement of human capital to meet modern day demands of a knowledge economy, and equip the new generation with the capacity to meet the challenges of the 21st Century has become a priority. This change is particularly necessary in economies typical of countries, such as Kuwait, which have been dependent on the exploitation of non-renewable natural resources. Transiting from a resource-based economy to an economy based on knowledge and intellectual skills poses a key challenge for an education system. Significant in the development of this new economy has been the expansion of Information Communication Technology (ICT). In education, in particular, ICT is a tool for transforming the education setting. However, transformation is only successful where there are effective change management strategies and appropriate leadership. At the school level, rapid changes have affected the role that principals take particularly in relation to leading the change process. Therefore, this study investigated the leadership practices of school principals for embedding ICT into schools. The case study assessed two Kuwaiti secondary schools; both schools had well established ICT programs. The mode of data collection used a mixed-methods design, to address the purpose of the study, namely, to examine the leadership practices of school principals when managing the change processes associated with embedding ICT in the context of Kuwait. A theoretical model of principal leadership, developed, from the literature, documented and analysed the practices of the respective school principals. The study used the following five data sources: (a) face to face interviews (with each school principal), and two focus group interviews (with five teachers and five students, from each school); (b) school documents (related to the implementation and embedding of ICT); (c) one survey (of all teachers in each school); (d) an open-ended questionnaire (of participating principals and teachers); and (e) the observation of ICT activities (PD ICT activities and instruction meetings). The study revealed a range of strategies used by the principals and aligned with the theoretical perspective. However, these strategies needed to be refined and selectively used to fit the Kuwait context, both culturally and organisationally. The principals of Schools A and B employed three key strategies to maximise the impact on the teaching staff incorporating ICT into their teaching and learning practices. These strategies were: (a) encouragement for teaching staff to implement ICT in their teaching; (b) support to meet the material and human needs of teaching staff using ICT; and (c) provision of instructions and guidance for teaching staff in how and why such behaviours and practices should be performed. The strategies provided the basic leadership practices required to construct a successful ICT embedded implementation process. Hence, a revised model of leadership that has applicability in the adoption of ICT in Kuwait was developed. The findings provide a better understanding of how a school principal’s leadership practices impact upon the ICT embedding process. Hence, the outcome of this study informs emerging countries, which are also undergoing major change related to ICT, for example, other members of the Cooperation Council for the Arab States of the Gulf. From an educational perspective, this knowledge has the potential to support ICT-based learning environments that will help educational practitioners to effectively integrate ICT into teaching and learning that will facilitate students’ ICT engagement, and prepare them for the ICT development challenges that are associated with the new economy; this is achieved by increasing students’ knowledge and performance. Further, the study offers practical strategies that have been shown to work for school principals leading ICT implementation in Kuwait. These strategies include how to deal with the shortage in schools’ budgets, and the promotion of the ICT vision, as well as developing approaches to build collaborative culture in the schools.