941 resultados para Knowledge Structures


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Knowledge organization in the networked environment is guided by standards. Standards in knowledge organization are built on principles. For example, NISO Z39.19-1993 Guide to the Construction of Monolingual Thesauri (now undergoing revision) and NISO Z39.85- 2001 Dublin Core Metadata Element Set are two standards used in many implementations. Both of these standards were crafted with knowledge organization principles in mind. Therefore it is standards work guided by knowledge organization principles which can affect design of information services and technologies. This poster outlines five threads of thought that inform knowledge organization principles in the networked environment. An understanding of each of these five threads informs system evaluation. The evaluation of knowledge organization systems should be tightly linked to a rigorous understanding of the principles of construction. Thus some foundational evaluation questions grow from an understanding of stan dard s and pr inciples: on what pr inciples is this know ledge organization system built? How well does this implementation meet the ideal conceptualization of those principles? How does this tool compare to others built on the same principles?

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This paper considers the ethical concerns that surface around hierarchy as structure in knowledge organization systems. In order to do this, I consider the relationship between semantics and structure and argue for a separation of the two in design and critique of knowledge organization systems. The paper closes with an argument that agency and intention, as ethical concerns in knowledge organization, lead us to argue for a neutral stance on hierarchy.

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Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This final report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.

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Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This Industry focused report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.

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Purpose – The purpose of this paper is to provide a practicable systems-based approach to knowledge management (KM) in a project environment, to encourage organisations to unlock the value in their review processes. It relies on knowledge capture and storage at decision review points, to enrich individual, team and organisational learning during the project life cycle. The project's phases are typically represented horizontally with deliverables (objectives) or project "promises" as the desirable outcomes. The purpose of this paper is to give expression through introducing a vertical dimension to facilitate the KM process. A model is proposed that conceptualises project-specific knowledge drawing on and feeding into the organisation's knowledge management system (KMS) at tactical and strategic levels. Design/methodology/approach – This conceptual paper links concepts from systems theory with KM, to produce a model to identify, collate, and optimise project-based knowledge and integrate it into the management process. Findings – The application of the system theory approach enriches the knowledge generated by a project, and feeds it into the next phase of that project. At the same time, it contributes to the individual's and project team's KM, specifies possible courses of action, together with risks, costs and benefits and thus it expands the organisation's higher level KMS. Research limitations/implications – The concept suggests that the knowledge capture, storage and sharing process may best be undertaken holistically, in view of the systems relationships between the tasks. Systems theory structures this process. Research opportunities include studying the interfaces between levels of KM, in relation to the project's progress. Practical implications – Reconceptualisation of the project as a knowledge creation process may improve the project's progress as well as add to the individual's, project team's, and wider organisation's knowledge base. An example is given. Originality/value – This paper illuminates the broader potential of under-utilised opportunities in well-known management approaches to add dimension to the business project, of knowledge creation, storage and sharing.

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Reinforced concrete structures are susceptible to a variety of deterioration mechanisms due to creep and shrinkage, alkali-silica reaction (ASR), carbonation, and corrosion of the reinforcement. The deterioration problems can affect the integrity and load carrying capacity of the structure. Substantial research has been dedicated to these various mechanisms aiming to identify the causes, reactions, accelerants, retardants and consequences. This has improved our understanding of the long-term behaviour of reinforced concrete structures. However, the strengthening of reinforced concrete structures for durability has to date been mainly undertaken after expert assessment of field data followed by the development of a scheme to both terminate continuing degradation, by separating the structure from the environment, and strengthening the structure. The process does not include any significant consideration of the residual load-bearing capacity of the structure and the highly variable nature of estimates of such remaining capacity. Development of performance curves for deteriorating bridge structures has not been attempted due to the difficulty in developing a model when the input parameters have an extremely large variability. This paper presents a framework developed for an asset management system which assesses residual capacity and identifies the most appropriate rehabilitation method for a given reinforced concrete structure exposed to aggressive environments. In developing the framework, several industry consultation sessions have been conducted to identify input data required, research methodology and output knowledge base. Capturing expert opinion in a useable knowledge base requires development of a rule based formulation, which can subsequently be used to model the reliability of the performance curve of a reinforced concrete structure exposed to a given environment.

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Abstract With the phenomenal growth of electronic data and information, there are many demands for the development of efficient and effective systems (tools) to perform the issue of data mining tasks on multidimensional databases. Association rules describe associations between items in the same transactions (intra) or in different transactions (inter). Association mining attempts to find interesting or useful association rules in databases: this is the crucial issue for the application of data mining in the real world. Association mining can be used in many application areas, such as the discovery of associations between customers’ locations and shopping behaviours in market basket analysis. Association mining includes two phases. The first phase, called pattern mining, is the discovery of frequent patterns. The second phase, called rule generation, is the discovery of interesting and useful association rules in the discovered patterns. The first phase, however, often takes a long time to find all frequent patterns; these also include much noise. The second phase is also a time consuming activity that can generate many redundant rules. To improve the quality of association mining in databases, this thesis provides an alternative technique, granule-based association mining, for knowledge discovery in databases, where a granule refers to a predicate that describes common features of a group of transactions. The new technique first transfers transaction databases into basic decision tables, then uses multi-tier structures to integrate pattern mining and rule generation in one phase for both intra and inter transaction association rule mining. To evaluate the proposed new technique, this research defines the concept of meaningless rules by considering the co-relations between data-dimensions for intratransaction-association rule mining. It also uses precision to evaluate the effectiveness of intertransaction association rules. The experimental results show that the proposed technique is promising.

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Knowledge has been recognised as a source of competitive advantage. Knowledge-based resources allow organisations to adapt products and services to the marketplace and deal with competitive challenges that enable them to compete more effectively. One factor critical to using knowledge-based resources is the ability to transfer knowledge as a dimension of the learning organisation. There are many elements that may influence whether knowledge transfer can be effectively achieved in an organisation such as leadership, problem-solving behaviours, support structures, change management capabilities, absorptive capacity and the nature of the knowledge. An existing framework was applied in a case study to explain how knowledge transfer can be managed effectively and to identify emerging issues or additional factors involved in the process. As a result, a refined framework is proposed that provides a better understanding for the effective management of knowledge transfer processes that can provide a competitive advantage.

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High density development has been seen as a contribution to sustainable development. However, a number of engineering issues play a crucial role in the sustainable construction of high rise buildings. Non linear deformation of concrete has an adverse impact on high-rise buildings with complex geometries, due to differential axial shortening. These adverse effects are caused by time dependent behaviour resulting in volume change known as ‘shrinkage’, ‘creep’ and ‘elastic’ deformation. These three phenomena govern the behaviour and performance of all concrete elements, during and after construction. Reinforcement content, variable concrete modulus, volume to surface area ratio of the elements, environmental conditions, and construction quality and sequence influence on the performance of concrete elements and differential axial shortening will occur in all structural systems. Its detrimental effects escalate with increasing height and non vertical load paths resulting from geometric complexity. The magnitude of these effects has a significant impact on building envelopes, building services, secondary systems, and lifetime serviceability and performance. Analytical and test procedures available to quantify the magnitude of these effects are limited to a very few parameters and are not adequately rigorous to capture the complexity of true time dependent material response. With this in mind, a research project has been undertaken to develop an accurate numerical procedure to quantify the differential axial shortening of structural elements. The procedure has been successfully applied to quantify the differential axial shortening of a high rise building, and the important capabilities available in the procedure have been discussed. A new practical concept, based on the variation of vibration characteristic of structure during and after construction and used to quantify the axial shortening and assess the performance of structure, is presented.

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This thesis explores a way to inform the architectural design process for contemporary workplace environments. It reports on both theoretical and practical outcomes through an exclusively Australian case study of a network enterprise comprised of collaborative, yet independent business entities. The internet revolution, substantial economic and cultural shifts, and an increased emphasis on lifestyle considerations have prompted a radical re-ordering of organisational relationships and the associated structures, processes, and places of doing business. The social milieu of the information age and the knowledge economy is characterised by an almost instantaneous flow of information and capital. This has culminated in a phenomenon termed by Manuel Castells as the network society, where physical locations are joined together by continuous communication and virtual connectivity. A new spatial logic encompassing redefined concepts of space and distance, and requiring a comprehensive shift in the approach to designing workplace environments for today’s adaptive, collaborative organisations in a dynamic business world, provides the backdrop for this research. Within the duality of space and an augmentation of the traditional notions of place, organisational and institutional structures pose new challenges for the design professions. The literature revealed that there has always been a mono-organisational focus in relation to workplace design strategies. The phenomenon of inter-organisational collaboration has enabled the identification of a gap in the knowledge relative to workplace design. This new context generated the formulation of a unique research construct, the NetWorkPlace™©, which captures the complexity of contemporary employment structures embracing both physical and virtual work environments and practices, and provided the basis for investigating the factors that are shaping and defining interactions within and across networked organisational settings. The methodological orientation and the methods employed follow a qualitative approach and an abductively driven strategy comprising two distinct components, a cross-sectional study of the whole of the network and a longitudinal study, focusing on a single discrete workplace site. The complexity of the context encountered dictated that a multi-dimensional investigative framework was required to be devised. The adoption of a pluralist ontology and the reconfiguration of approaches from traditional paradigms into a collaborative, trans-disciplinary, multi-method epistemology provided an explicit and replicatable method of investigation. The identification and introduction of the NetWorkPlace™© phenomenon, by necessity, spans a number of traditional disciplinary boundaries. Results confirm that in this context, architectural research, and by extension architectural practice, must engage with what other disciplines have to offer. The research concludes that no single disciplinary approach to either research or practice in this area of design can suffice. Pierre Bourdieau’s philosophy of ‘practice’ provides a framework within which the governance and technology structures, together with the mechanisms enabling the production of social order in this context, can be understood. This is achieved by applying the concepts of position and positioning to the corporate power dynamics, and integrating the conflict found to exist between enterprise standard and ferally conceived technology systems. By extending existing theory and conceptions of ‘place’ and the ‘person-environment relationship’, relevant understandings of the tensions created between Castells’ notions of the space of place and the space of flows are established. The trans-disciplinary approach adopted, and underpinned by a robust academic and practical framework, illustrates the potential for expanding the range and richness of understanding applicable to design in this context. The outcome informs workplace design by extending theoretical horizons, and by the development of a comprehensive investigative process comprising a suite of models and techniques for both architectural and interior design research and practice, collectively entitled the NetWorkPlace™© Application Framework. This work contributes to the body of knowledge within the design disciplines in substantive, theoretical, and methodological terms, whilst potentially also influencing future organisational network theories, management practices, and information and communication technology applications. The NetWorkPlace™© as reported in this thesis, constitutes a multi-dimensional concept having the capacity to deal with the fluidity and ambiguity characteristic of the network context, as both a topic of research and the way of going about it.

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This paper investigates the Cooroy Mill community precinct (Sunshine Coast, Queensland), as a case study, seeking to understand the way local dynamics interplay and work with the community strengths to build a governance model of best fit. As we move to an age of ubiquitous computing and creative economies, the definition of public place and its governance take on new dimensions, which – while often utilizing models of the past – will need to acknowledge and change to the direction of the future. This paper considers a newly developed community precinct that has been built on three key principles: to foster creative expression with new media, to establish a knowledge economy in a regional area, and to subscribe to principles of community engagement. The study involved qualitative interviews with key stakeholders and a review of common practice models of governance along a spectrum from community control to state control. The paper concludes with a call for governance structures that are locally situated and tailored, inclusive, engaging, dynamic and flexible in order to build community capacity, encourage creativity, and build knowledge economies within emerging digital media cityscapes.

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It is increasingly understood that learning and thus innovation often occurs via highly interactive, iterative, network-based processes. Simultaneously, economic development policy is increasingly focused on small and medium-sized enterprises (SMEs) as a means of generating growth, creating a clear research issue in terms of the roles and interactions of government policy, universities, and other sources of knowledge, SMEs, and the creation and dissemination of innovation. This paper analyses the contribution of a range of actors in an SME innovation creation and dissemination framework, reviewing the role of various institutions therein, exploring the contribution of cross-locality networks, and identifying the mechanisms required to operationalise such a framework. Bivariate and multivariate (regression) techniques are employed to investigate both innovation and growth outcomes in relation to these structures; data are derived from the survey responses of over 450 SMEs in the UK. Results are complex and dependent upon the nature of institutions involved, the type of knowledge sought, and the spatial level of the linkages in place but overall highlight the value of cross-locality networks, network governance structures, and certain spillover effects from universities. In general, we find less support for the factors predicting SME growth outcomes than is the case for innovation. Finally, we outline an agenda for further research in the area.

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This paper presents the outcome of investigations and studies of the vibratioon characteristics and response of low frequency structural systems for a composite concrete steel floor plate and a reverse profiled cable tensioned foot bridge. These highly dynamic and slender structure are the engineering response to planning, aesthetic and environmental influences, but are prone to excessive and complex vibration. A number of design codes and practice guides provided information to engineers for vibration mitigation However, they are limited to very simple load function applied to a few uncoupled translational modes of excitation. Motivated by the need to address the knowledge gaps in this area, the investigations described in this paper focused on synchronous multi-modal and coupled excitation of the floor plate and footbridge with considerations for torsinal effects. The results showed the potential for adverse dynamic response from multi-modal and coupled excitation influenced by patterned loading, structure geometry, stiffness distribution, directional effects, forcing functions based on activity frequency and duration of foot contact, and modal participation. It was also shown that higher harmonics of the load frequency can excite higher modes in the composite floor structure. Such responsive behaviour is prevalent mainly in slender and lightweight construction and not in stiffer and heavier structural systems. The analytical techniques and methods used in these investigations can supplement the current limited code and best practice provisions for mitigating the impact of human induced vibrations in slender structural systems.