202 resultados para KNOWLEDGE-BASED ECONOMY


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The focus of knowledge management (KM) in the construction industry is moving towards capability building for value creation. The study reported by this paper is motivated by recent assertions about the genesis and evolution of knowledge management capability (KMC) in the strategic management field. It attempts to shed light on the governance of learning mechanisms that develop KMC within the context of construction firms. A questionnaire survey was administered to a sample of construction contractors operating in the very dynamic Hong Kong market to elicit opinions on the learning mechanisms and business outcomes of targeted firms. On the basis of a total of 149 usable responses, structural equation modeling (SEM) analysis identified relationships among knowledge-governance mechanisms, knowledge processes, and business performance, thereby supporting the existence of strategic learning loops. The study findings provide evidence from the construction context for capability assertions that knowledge-governance mechanisms and processes form learning mechanisms that carry out strategic learning to create value, effect performance outcomes, and ultimately drive the evolution of KMC. The findings imply that it is feasible for managing construction firms to govern learning mechanisms through managing the capability-based holistic KM system, thereby reconfiguring KMC to match needs in the dynamic market environment over time.

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Reasoning with uncertain knowledge and belief has long been recognized as an important research issue in Artificial Intelligence (AI). Several methodologies have been proposed in the past, including knowledge-based systems, fuzzy sets, and probability theory. The probabilistic approach became popular mainly due to a knowledge representation framework called Bayesian networks. Bayesian networks have earned reputation of being powerful tools for modeling complex problem involving uncertain knowledge. Uncertain knowledge exists in domains such as medicine, law, geographical information systems and design as it is difficult to retrieve all knowledge and experience from experts. In design domain, experts believe that design style is an intangible concept and that its knowledge is difficult to be presented in a formal way. The aim of the research is to find ways to represent design style knowledge in Bayesian net works. We showed that these networks can be used for diagnosis (inferences) and classification of design style. The furniture design style is selected as an example domain, however the method can be used for any other domain.

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With the growth in project management as a form of work organisation in many sectors of the economy has come the significant rise in the number of project managers and project team members. This change in work organisation brings issues in forging career paths and determining career support in work situations that are often dynamic, short lived and intense. In the relatively small but substantially robust Australian economy, a unique labour market and the tyranny of distance bring their own difficulties. Innovative and collaborative project structures and increasing prevalence of contract work provide both challenges and opportunities for new career pathways in many industries. A growing percentage of Australia's workforce is employed in project-based or project-oriented organisations, leading to the claim that Australia is a project-based economy. This provided a context for our research into the career paths and the issues of career management for project managers working in a project based economy. Using in-depth interviews with project managers from three industry areas we found generational and gender differences in experiences of work, workplace support and mentoring for career development. For a continued strong performance in this economy,organisations that employ project personnel will need to consider how they will ensure the supply of high quality project professionals into the future.

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Dynamic capability theory asserts that the learning capabilities of construction organisations influence the degree to which value-for-money (VfM) is achieved on collaborative projects. However, there has been little study conducted to verify this relationship. The evidence is particularly limited within the empirical context of infrastructure delivery in Australia. Primarily drawing on the theoretical perspectives of the resource-based view of the firm (e.g. Barney 1991), dynamic capabilities (e.g. Helfat et al. 2007), absorptive capacity (e.g. Lane et al. 2006) and knowledge management (e.g. Nonaka 1994), this paper conceptualises learning capability as a knowledge-based dynamic capability. Learning capability builds on the micro-foundations of high-order learning routines, which are deliberately developed by construction organisations for managing collaborative projects. Based on this conceptualisation of learning capability, an exploratory case study was conducted. The study investigated the operational and higher-order learning routines adopted by a project alliance team to successfully achieve VfM. The case study demonstrated that the learning routines of the alliance project were developed and modified by the continual joint learning activities of participant organisations. Project-level learning routines were found to significantly influence the development of organisational-level learning routines. In turn, the learning outcomes generated from the alliance project appeared to significantly influence the development of project management routines and contractual arrangements applied by the participant organisations in subsequent collaborative projects. The case study findings imply that the higher-order learning routines that underpin the learning capability of construction organisations have the potential to influence the VfM achieved on both current and future collaborative projects.

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Learning capability (LC) is a special dynamic capability that a firm purposefully builds to develop a cognitive focus, so as to enable the configuration and improvement of other capabilities (both dynamic and operational) to create and respond to market changes. Empirical evidence regarding the essential role of LC in leveraging operational manufacturing capabilities is, however, limited in the literature. This study takes a routine-based approach to understand capability, and focuses on demonstrating leveraging power of LC upon two essential operational capabilities within the manufacturing context, i.e., operational new product development capability (ONPDC), and operational supplier integration capability (OSIC). A mixed-methods research framework was used, which combines sources of evidence derived from a survey study and a multiple case study. This study identified high-level routines of LC that can be designed and controlled by managers and practitioners, to reconfigure underlying routines of ONPDC and OSIC to achieve superior performance in a turbulent environment. Hence, the study advances the notion of knowledge-based dynamic capabilities, such as LC, as routine bundles. It also provides an impetus for managing manufacturing operations from a capability-based perspective in the fast changing knowledge era.

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Particulate matter research is essential because of the well known significant adverse effects of aerosol particles on human health and the environment. In particular, identification of the origin or sources of particulate matter emissions is of paramount importance in assisting efforts to control and reduce air pollution in the atmosphere. This thesis aims to: identify the sources of particulate matter; compare pollution conditions at urban, rural and roadside receptor sites; combine information about the sources with meteorological conditions at the sites to locate the emission sources; compare sources based on particle size or mass; and ultimately, provide the basis for control and reduction in particulate matter concentrations in the atmosphere. To achieve these objectives, data was obtained from assorted local and international receptor sites over long sampling periods. The samples were analysed using Ion Beam Analysis and Scanning Mobility Particle Sizer methods to measure the particle mass with chemical composition and the particle size distribution, respectively. Advanced data analysis techniques were employed to derive information from large, complex data sets. Multi-Criteria Decision Making (MCDM), a ranking method, drew on data variability to examine the overall trends, and provided the rank ordering of the sites and years that sampling was conducted. Coupled with the receptor model Positive Matrix Factorisation (PMF), the pollution emission sources were identified and meaningful information pertinent to the prioritisation of control and reduction strategies was obtained. This thesis is presented in the thesis by publication format. It includes four refereed papers which together demonstrate a novel combination of data analysis techniques that enabled particulate matter sources to be identified and sampling site/year ranked. The strength of this source identification process was corroborated when the analysis procedure was expanded to encompass multiple receptor sites. Initially applied to identify the contributing sources at roadside and suburban sites in Brisbane, the technique was subsequently applied to three receptor sites (roadside, urban and rural) located in Hong Kong. The comparable results from these international and national sites over several sampling periods indicated similarities in source contributions between receptor site-types, irrespective of global location and suggested the need to apply these methods to air pollution investigations worldwide. Furthermore, an investigation into particle size distribution data was conducted to deduce the sources of aerosol emissions based on particle size and elemental composition. Considering the adverse effects on human health caused by small-sized particles, knowledge of particle size distribution and their elemental composition provides a different perspective on the pollution problem. This thesis clearly illustrates that the application of an innovative combination of advanced data interpretation methods to identify particulate matter sources and rank sampling sites/years provides the basis for the prioritisation of future air pollution control measures. Moreover, this study contributes significantly to knowledge based on chemical composition of airborne particulate matter in Brisbane, Australia and on the identity and plausible locations of the contributing sources. Such novel source apportionment and ranking procedures are ultimately applicable to environmental investigations worldwide.

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We introduce the use of Ingenuity Pathway Analysis to analyzing global metabonomics in order to characterize phenotypically biochemical perturbations and the potential mechanisms of the gentamicin-induced toxicity in multiple organs. A single dose of gentamicin was administered to Sprague Dawley rats (200 mg/kg, n = 6) and urine samples were collected at -24-0 h pre-dosage, 0-24, 24-48, 48-72 and 72-96 h post-dosage of gentamicin. The urine metabonomics analysis was performed by UPLC/MS, and the mass spectra signals of the detected metabolites were systematically deconvoluted and analyzed by pattern recognition analyses (Heatmap, PCA and PLS-DA), revealing a time-dependency of the biochemical perturbations induced by gentamicin toxicity. As result, the holistic metabolome change induced by gentamicin toxicity in the animal's organisms was characterized. Several metabolites involved in amino acid metabolism were identified in urine, and it was confirmed that gentamicin biochemical perturbations can be foreseen from these biomarkers. Notoriously, it was found that gentamicin induced toxicity in multiple organs system in the laboratory rats. The proof-of-knowledge based Ingenuity Pathway Analysis revealed gentamicin induced liver and heart toxicity, along with the previously known toxicity in kidney. The metabolites creatine, nicotinic acid, prostaglandin E2, and cholic acid were identified and validated as phenotypic biomarkers of gentamicin induced toxicity. Altogether, the significance of the use of metabonomics analyses in the assessment of drug toxicity is highlighted once more; furthermore, this work demonstrated the powerful predictive potential of the Ingenuity Pathway Analysis to study of drug toxicity and its valuable complementation for metabonomics based assessment of the drug toxicity.

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In most of the advanced economies, students are losing interest in careers especially in en¬gineering and related industries. Hence, western economies are confronting a critical skilled labour shortage in areas of technology, science and engineering. Decisions about career pathways are made as early as the primary years of schooling and hence cooperation be¬tween industry and schools to attract students to the professions is crucial. The aim of this paper is to document how the organisational and institutional elements of one industry-school partnerships initiative — The Gateway Schools Program — contribute to productive knowledge sharing and networking. In particular this paper focuses on an initiative of an Australian State government in response to a perceived crisis around the skills shortage in an economy transitioning from a localised to a global knowledge production economy. The Gateway Schools initiative signals the first sustained attempt in Australia to incorporate schools into production networks through strategic partnerships linking them to partner organisations at the industry level. We provide case examples of how four schools opera¬tionalise the partnerships with the minerals and energy industries and how these partner¬ships as knowledge assets impact the delivery of curriculum and capacity building among teachers. Our ultimate goal is to define those characteristics of successful partnerships that do contribute to enhanced interest and engagement by students in those careers that are currently experiencing critical shortages.

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The operation of the law rests on the selection of an account of the facts. Whether this involves prediction or postdiction, it is not possible to achieve certainty. Any attempt to model the operation of the law completely will therefore raise questions of how to model the process of proof. In the selection of a model a crucial question will be whether the model is to be used normatively or descriptively. Focussing on postdiction, this paper presents and contrasts the mathematical model with the story model. The former carries the normative stamp of scientific approval, whereas the latter has been developed by experimental psychologists to describe how humans reason. Neil Cohen's attempt to use a mathematical model descriptively provides an illustration of the dangers in not clearly setting this parameter of the modelling process. It should be kept in mind that the labels 'normative' and 'descriptive' are not eternal. The mathematical model has its normative limits, beyond which we may need to critically assess models with descriptive origins.

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In the legal domain, it is rare to find solutions to problems by simply applying algorithms or invoking deductive rules in some knowledge‐based program. Instead, expert practitioners often supplement domain‐specific knowledge with field experience. This type of expertise is often applied in the form of an analogy. This research proposes to combine both reasoning with precedents and reasoning with statutes and regulations in a way that will enhance the statutory interpretation task. This is being attempted through the integration of database and expert system technologies. Case‐based reasoning is being used to model legal precedents while rule‐based reasoning modules are being used to model the legislation and other types of causal knowledge. It is hoped to generalise these findings and to develop a formal methodology for integrating case‐based databases with rule‐based expert systems in the legal domain.

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Background Paramedic education has evolved in recent times from vocational post-employment to tertiary pre-employment supplemented by clinical placement. Simulation is advocated as a means of transferring learned skills to clinical practice. Sole reliance of simulation learning using mannequin-based models may not be sufficient to prepare students for variance in human anatomy. In 2012, we trialled the use of fresh frozen human cadavers to supplement undergraduate paramedic procedural skill training. The purpose of this study is to evaluate whether cadaveric training is an effective adjunct to mannequin simulation and clinical placement. Methods A multi-method approach was adopted. The first step involved a Delphi methodology to formulate and validate the evaluation instrument. The instrument comprised of knowledge-based MCQs, Likert for self-evaluation of procedural skills and behaviours, and open answer. The second step involved a pre-post evaluation of the 2013 cadaveric training. Results One hundred and fourteen students attended the workshop and 96 evaluations were included in the analysis, representing a return rate of 84%. There was statistically significant improved anatomical knowledge after the workshop. Students' self-rated confidence in performing procedural skills on real patients improved significantly after the workshop: inserting laryngeal mask (MD 0.667), oropharyngeal (MD 0.198) and nasopharyngeal (MD 0.600) airways, performing Bag-Valve-Mask (MD 0.379), double (MD 0.344) and triple (MD 0.326,) airway manoeuvre, doing 12-lead electrocardiography (MD 0.729), using McGrath(R) laryngoscope (MD 0.726), using McGrath(R) forceps to remove foreign body (MD 0.632), attempting thoracocentesis (MD 1.240), and putting on a traction splint (MD 0.865). The students commented that the workshop provided context to their theoretical knowledge and that they gained an appreciation of the differences in normal tissue variation. Following engagement in/ completion of the workshop, students were more aware of their own clinical and non-clinical competencies. Conclusions The paramedic profession has evolved beyond patient transport with minimal intervention to providing comprehensive both emergency and non-emergency medical care. With limited availability of clinical placements for undergraduate paramedic training, there is an increasing demand on universities to provide suitable alternatives. Our findings suggested that cadaveric training using fresh frozen cadavers provides an effective adjunct to simulated learning and clinical placements.

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Occupational segregation is a major source of labour market rigidity and economic inefficiency due to a waste of human resources. Organisations are repeatedly recognised as gendered constructs exhibiting sustained work segregation, income and status inequality, as well as cultural and individual images of gender, and these are perpetuated through their processes, practices and pressures (Acker, 1990). A large percentage of Australia’s workforce is now employed in project-based or project-oriented organisations, leading to the claim that Australia is a project-based economy. For a continued strong performance in this economy, organisations that employ project personnel will need to consider how they address inclusivity and equality in diversity in project based temporary organisations to ensure the supply of high quality project professionals into the future. This paper investigates the inclusion processes experienced and exercised by men and women working in temporary organisations in project situations through a review of reports on the inclusion processes experienced by 60 project managers and project workers in three project based industries in Australia. Results indicate that temporary organisations are not implementing equality and diversity management strategies at the macro level and project workers are accepting this lack of recognition. However inclusivity and equality at the micro level of the team is seen as vital.

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Background: For medical and allied health students, bioscience knowledge underpins the successful scaffolding of learning in their developmental and advanced level units. Many of these students complete theory-based Bioscience units, followed by a unit in Pharmacology, which specifically requires knowledge of anatomy, physiology and microbiology. In general, studies of recall report relatively large losses over short retention intervals (months), which accumulate, but level off, for longer retention intervals (years) (Custers, 2010). However, there are no studies that specifically test the recall of bioscience knowledge by allied health students. Methods: We are tracking the recall of bioscience in nursing students prior to, and during, their Pharmacology unit. In each semester, students complete short, basic, knowledge-based MCQ quizzes on concepts from (i) the gastrointestinal system and (ii) fundamental microbiology. Students were given 5 days warning about the microbiology quizzes but were given no warning prior to the gastrointestinal system quiz. Performance in these quizzes was compared to individual student’s results in the final examination on these topics in the first semester of their degree. Results: At the start of the study, the nursing students performed better in the exam MCQs on the gastrointestinal system than on microbiology. In the exam, the students’ mean marks for the gastrointestinal system ranged from 69–83%, and this was successively reduced to 63%, 53% and 49% after 4, 9 and 16 months, respectively. The mean exam marks for microbiology was 48–58%, and this did not change significantly after 4 (63%), 9 (59%) or 16 months (47%). This suggests that warning the nursing students that they were to be quizzed on microbiology may have helped their recall. However, after 16 months regardless of the subject, the nursing students undertaking the Pharmacology unit recalled less than half of the bioscience quiz answers. Conclusions: Nursing students may not have the recall of bioscience necessary to study pharmacology, and this may limit their success in pharmacology. Reference: Custers, E. J. F. M. (2010). Long-term retention of basic science knowledge: a review study. Advances in Health Science Education, 15, 109–128.

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In this paper conditional hidden Markov model (HMM) filters and conditional Kalman filters (KF) are coupled together to improve demodulation of differential encoded signals in noisy fading channels. We present an indicator matrix representation for differential encoded signals and the optimal HMM filter for demodulation. The filter requires O(N3) calculations per time iteration, where N is the number of message symbols. Decision feedback equalisation is investigated via coupling the optimal HMM filter for estimating the message, conditioned on estimates of the channel parameters, and a KF for estimating the channel states, conditioned on soft information message estimates. The particular differential encoding scheme examined in this paper is differential phase shift keying. However, the techniques developed can be extended to other forms of differential modulation. The channel model we use allows for multiplicative channel distortions and additive white Gaussian noise. Simulation studies are also presented.