995 resultados para Empirical Functions


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Knowledge is a commodity. It is a by-product of learning that involves the creation, sharing, processing and possible use of information in the mind of an individual. Knowledge management (KM) is, therefore, concerned with the effective implementation of such activities within the organisation. It is simply the process of leveraging organisational knowledge to deliver a long-term competitive advantage. This paper presents the results of an empirical research investigation into the interaction between different KM activities within the context of construction contracting organisations. The different KM activities include: responsiveness to the knowledge of business environment, knowledge acquisition, knowledge dissemination, and knowledge application. A questionnaire survey was administered to investigate the opinions of construction professionals regarding the intensity of activities currently implemented by their organisations to facilitate knowledge capturing, sharing and application. A total of 149 responses were then used to statistically examine the inter-relationships between the different KM activities as practised by contracting organisations in Hong Kong. The paper presents and discusses the survey findings and proposes recommendations for improving the effectiveness of current KM practices.

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X-ray microtomography (micro-CT) with micron resolution enables new ways of characterizing microstructures and opens pathways for forward calculations of multiscale rock properties. A quantitative characterization of the microstructure is the first step in this challenge. We developed a new approach to extract scale-dependent characteristics of porosity, percolation, and anisotropic permeability from 3-D microstructural models of rocks. The Hoshen-Kopelman algorithm of percolation theory is employed for a standard percolation analysis. The anisotropy of permeability is calculated by means of the star volume distribution approach. The local porosity distribution and local percolation probability are obtained by using the local porosity theory. Additionally, the local anisotropy distribution is defined and analyzed through two empirical probability density functions, the isotropy index and the elongation index. For such a high-resolution data set, the typical data sizes of the CT images are on the order of gigabytes to tens of gigabytes; thus an extremely large number of calculations are required. To resolve this large memory problem parallelization in OpenMP was used to optimally harness the shared memory infrastructure on cache coherent Non-Uniform Memory Access architecture machines such as the iVEC SGI Altix 3700Bx2 Supercomputer. We see adequate visualization of the results as an important element in this first pioneering study.

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Vehicle speed is an important attribute for the utility of a transport mode. The speed relationship between multiple modes of transport is of interest to the traffic planners and operators. This paper quantifies the relationship between bus speed and average car speed by integrating Bluetooth data and Transit Signal Priority data from the urban network in Brisbane, Australia. The method proposed in this paper is the first of its kind to relate bus speed and average car speed by integrating multi-source traffic data in a corridor-based method. Three transferable regression models relating not-in-service bus; in-service bus during peak; and in-service bus during off peak periods with average car are proposed. The models are cross-validated and the interrelationships are significant

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Universities are more and more challenged by the emerging global higher education market, facilitated by advances in Information and Communication Technologies (ICT). This requires them to reconsider their mission and direction in order to function effectively and efficiently, and to be responsive to changes in their environment. In the face of increasing demands and competitive pressures, Universities like other companies, seek to continuously innovate and improve their performance. Universities are considering co-operating or sharing, both internally and externally, in a wide range of areas to achieve cost effectiveness and improvements in performance. Shared services are an effective model for re-organizing to reduce costs, increase quality and create new capabilities. Shared services are not limited to the Higher Education (HE) sector. Organizations across different sectors are adopting shared services, in particular for support functions such as Finance, Accounting, Human Resources and Information Technology. While shared services has been around for more than three decades, commencing in the 1970’s in the banking sector and then been adopted by other sectors, it is an under researched domain, with little consensus on the most fundamental issues even as basic as defining what shared services is. Moreover, the interest in shared services within Higher Education is a global phenomenon. This study on shared services is situated within the Higher Education Sector of Malaysia, and originated as an outcome resulting from a national project (2005 – 2007) conducted by the Ministry of Higher Education (MOHE) entitled "Knowledge, Information Communication Technology Strategic Plan (KICTSP) for Malaysian Public Higher Education"- where progress towards more collaborations via shared services was a key recommendation. The study’s primary objective was to understand the nature and potential for ICT shared services, in particular in the Malaysian HE sector; by laying a foundation in terms of definition, typologies and research agenda and deriving theoretically based conceptualisations of the potential benefits of shared services, success factors and issues of pursuing shared services. The study embarked on this objective with a literature review and pilot case study as a means to further define the context of the study, given the current under-researched status of ICT shared services and of shared services in Higher Education. This context definition phase illustrated a range of unaddressed issues; including a lack of common understanding of what shared services are, how they are formed, what objectives they full fill, who is involved etc. The study thus embarked on a further investigation of a more foundational nature with an exploratory phase that aimed to address these gaps, where a detailed archival analysis of shared services literature within the IS context was conducted to better understand shared services from an IS perspective. The IS literature on shared services was analysed in depth to report on the current status of shared services research in the IS domain; in particular definitions, objectives, stakeholders, the notion of sharing, theories used, and research methods applied were analysed, which provided a firmer base to this study’s design. The study also conducted a detailed content analysis of 36 cases (globally) of shared services implementations in the HE sector to better understand how shared services are structured within the HE sector and what is been shared. The results of the context definition phase and exploratory phase formed a firm basis in the multiple case studies phase which was designed to address the primary goals of this study (as presented above). Three case sites within the Malaysian HE sector was included in this analysis, resulting in empirically supported theoretical conceptualizations of shared services success factors, issues and benefits. A range of contributions are made through this study. First, the detailed archival analysis of shared services in Information Systems (IS) demonstrated the dearth of research on shared services within Information Systems. While the existing literature was synthesised to contribute towards an improved understanding of shared services in the IS domain, the areas that are yet under-developed and requires further exploration is identified and presented as a proposed research agenda for the field. This study also provides theoretical considerations and methodological guidelines to support the research agenda; to conduct better empirical research in this domain. A number of literatures based a priori frameworks (i.e. on the forms of sharing and shared services stakeholders etc) are derived in this phase, contributing to practice and research with early conceptualisations of critical aspects of shared services. Furthermore, the comprehensive archival analysis design presented and executed here is an exemplary approach of a systematic, pre-defined and tool-supported method to extract, analyse and report literature, and is documented as guidelines that can be applied for other similar literature analysis, with particular attention to supporting novice researchers. Second, the content analysis of 36 shared services initiatives in the Higher Education sector presented eight different types of structural arrangements for shared services, as observed in practice, and the salient dimensions along which those types can be usefully differentiated. Each of the eight structural arrangement types are defined and demonstrated through case examples, with further descriptive details and insights to what is shared and how the sharing occurs. This typology, grounded on secondary empirical evidence, can serve as a useful analytical tool for researchers investigating the shared services phenomenon further, and for practitioners considering the introduction or further development of shared services. Finally, the multiple case studies conducted in the Malaysian Higher Education sector, provided further empirical basis to instantiate the conceptual frameworks and typology derived from the prior phases and develops an empirically supported: (i) framework of issues and challenges, (ii) a preliminary theory of shared services success, and (iii) a benefits framework, for shared services in the Higher Education sector.

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Robust hashing is an emerging field that can be used to hash certain data types in applications unsuitable for traditional cryptographic hashing methods. Traditional hashing functions have been used extensively for data/message integrity, data/message authentication, efficient file identification and password verification. These applications are possible because the hashing process is compressive, allowing for efficient comparisons in the hash domain but non-invertible meaning hashes can be used without revealing the original data. These techniques were developed with deterministic (non-changing) inputs such as files and passwords. For such data types a 1-bit or one character change can be significant, as a result the hashing process is sensitive to any change in the input. Unfortunately, there are certain applications where input data are not perfectly deterministic and minor changes cannot be avoided. Digital images and biometric features are two types of data where such changes exist but do not alter the meaning or appearance of the input. For such data types cryptographic hash functions cannot be usefully applied. In light of this, robust hashing has been developed as an alternative to cryptographic hashing and is designed to be robust to minor changes in the input. Although similar in name, robust hashing is fundamentally different from cryptographic hashing. Current robust hashing techniques are not based on cryptographic methods, but instead on pattern recognition techniques. Modern robust hashing algorithms consist of feature extraction followed by a randomization stage that introduces non-invertibility and compression, followed by quantization and binary encoding to produce a binary hash output. In order to preserve robustness of the extracted features, most randomization methods are linear and this is detrimental to the security aspects required of hash functions. Furthermore, the quantization and encoding stages used to binarize real-valued features requires the learning of appropriate quantization thresholds. How these thresholds are learnt has an important effect on hashing accuracy and the mere presence of such thresholds are a source of information leakage that can reduce hashing security. This dissertation outlines a systematic investigation of the quantization and encoding stages of robust hash functions. While existing literature has focused on the importance of quantization scheme, this research is the first to emphasise the importance of the quantizer training on both hashing accuracy and hashing security. The quantizer training process is presented in a statistical framework which allows a theoretical analysis of the effects of quantizer training on hashing performance. This is experimentally verified using a number of baseline robust image hashing algorithms over a large database of real world images. This dissertation also proposes a new randomization method for robust image hashing based on Higher Order Spectra (HOS) and Radon projections. The method is non-linear and this is an essential requirement for non-invertibility. The method is also designed to produce features more suited for quantization and encoding. The system can operate without the need for quantizer training, is more easily encoded and displays improved hashing performance when compared to existing robust image hashing algorithms. The dissertation also shows how the HOS method can be adapted to work with biometric features obtained from 2D and 3D face images.

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Density functional theory (DFT) is a powerful approach to electronic structure calculations in extended systems, but suffers currently from inadequate incorporation of long-range dispersion, or Van der Waals (VdW) interactions. VdW-corrected DFT is tested for interactions involving molecular hydrogen, graphite, single-walled carbon nanotubes (SWCNTs), and SWCNT bundles. The energy correction, based on an empirical London dispersion term with a damping function at short range, allows a reasonable physisorption energy and equilibrium distance to be obtained for H2 on a model graphite surface. The VdW-corrected DFT calculation for an (8, 8) nanotube bundle reproduces accurately the experimental lattice constant. For H2 inside or outside an (8, 8) SWCNT, we find the binding energies are respectively higher and lower than that on a graphite surface, correctly predicting the well known curvature effect. We conclude that the VdW correction is a very effective method for implementing DFT calculations, allowing a reliable description of both short-range chemical bonding and long-range dispersive interactions. The method will find powerful applications in areas of SWCNT research where empirical potential functions either have not been developed, or do not capture the necessary range of both dispersion and bonding interactions.

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This thesis investigated the viability of using Frequency Response Functions in combination with Artificial Neural Network technique in damage assessment of building structures. The proposed approach can help overcome some of limitations associated with previously developed vibration based methods and assist in delivering more accurate and robust damage identification results. Excellent results are obtained for damage identification of the case studies proving that the proposed approach has been developed successfully.

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Information and communications technologies are a significant component of the healthcare domain and electronic health records play a major role within it. As a result, it is important that they are accepted en masse by healthcare professionals. How healthcare professionals perceive the usefulness of electronic health records and their attitudes towards them have been shown to have significant effects on their overall acceptance. This paper investigates the role of perceived usefulness and attitude on the intention to use electronic health records by future healthcare professionals using polynomial regression with response surface analysis. Results show that the relationship is more complex than predicted in prior research. The paper concludes that the predicting properties of the above determinants must be further investigated to clearly understand their role in predicting the intention to use electronic health records and in designing systems that are better adopted by healthcare professionals of the future.

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Australian TV News: New Forms, Functions, and Futures examines the changing relationships between television, politics and popular culture. Drawing extensively on qualitative audience research and industry interviews, this book demonstrates that while ‘infotainment’ and satirical programmes may not follow the journalism orthodoxy (or, in some cases, reject it outright), they nevertheless play an important role in the way everyday Australians understand what is happening in the world. This therefore throws into question some longstanding assumptions about what form TV news should take, the functions it ought to serve, and the future prospects of the fourth estate.

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Whether to keep products segregated (e.g., unbundled) or integrate some or all of them (e.g., bundle) has been a problem of profound interest in areas such as portfolio theory in finance, risk capital allocations in insurance and marketing of consumer products. Such decisions are inherently complex and depend on factors such as the underlying product values and consumer preferences, the latter being frequently described using value functions, also known as utility functions in economics. In this paper, we develop decision rules for multiple products, which we generally call ‘exposure units’ to naturally cover manifold scenarios spanning well beyond ‘products’. Our findings show, e.g. that the celebrated Thaler's principles of mental accounting hold as originally postulated when the values of all exposure units are positive (i.e. all are gains) or all negative (i.e. all are losses). In the case of exposure units with mixed-sign values, decision rules are much more complex and rely on cataloging the Bell number of cases that grow very fast depending on the number of exposure units. Consequently, in the present paper, we provide detailed rules for the integration and segregation decisions in the case up to three exposure units, and partial rules for the arbitrary number of units.

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We define a pair-correlation function that can be used to characterize spatiotemporal patterning in experimental images and snapshots from discrete simulations. Unlike previous pair-correlation functions, the pair-correlation functions developed here depend on the location and size of objects. The pair-correlation function can be used to indicate complete spatial randomness, aggregation or segregation over a range of length scales, and quantifies spatial structures such as the shape, size and distribution of clusters. Comparing pair-correlation data for various experimental and simulation images illustrates their potential use as a summary statistic for calibrating discrete models of various physical processes.

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Background The Achenbach problem behaviour scales (CBCL/YSR) are widely used. The DSM-oriented anxiety and depression scales have been created to improve concordance between Achenbach’s internalising scales and DSM-IV depression and anxiety. To date no study has examined the concurrent utility of the young adult (YASR) internalising scales, either the empirical or newly developed DSM-oriented depressive or anxiety scales. Methods A sample of 2,551 young adults, aged 18–23 years, from an Australian cohort study. The association between the empirical and DSM-oriented anxiety and depression scales were individually assessed against DSMIV depression and anxiety diagnoses derived from structured interview. Odds ratios, ROC analyses and diagnostic efficiency tests (sensitivity, specificity, positive and negative predictive values) were used to report findings. Results YASR empirical internalising scale predicted DSM-IV mood disorders (depression OR = 6.9, 95% CI 5.0–9.5; anxiety OR = 5.1, 95% CI 3.8–6.7) in the previous 12 months. DSM-oriented depressive or anxiety scales did not appear to improve the concordance with DSM-IV diagnosed depression or anxiety. The internalising scales were much more effective at identifying those with comorbid depression and anxiety, with Ors between 10.1 and 21.7 depending on the internalising scale used. Conclusion DSM-oriented scales perform no better than the standard internalising in identifying young adults with DSM-IV mood or anxiety disorder.

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Following an epistemic frame advanced by Elliott Eisner (2002), it is argued that the tradition of the arts and perspectives from artists have the potential to yield refreshing and interesting insights for the field of educational leadership. Moreover, it is argued that Eisner’s work on tacit knowledge which he advanced as an example of connoisseurship has important implications and posits the possibility of developing a more discerning “eye” in describing the work of educational leaders. To assess these assertions, the paper reports on two stages of interviews with nine former and current artists from Australia in order to understand the processes in which they engaged when they create art and how they encountered and managed barriers. The implications of this preliminary investigation are explored in this paper as they related to how leadership is defined and the issues pertaining to claims that leadership studies must be “scientific” to have currency and credibility. The article begins by making an argument for the value of the arts to advanced a more nuanced view of leadership, considers the importance of connoisseurship as a frame for understanding it, and then explores the cognitive functions performed by the arts before turning to the study at hand.

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Currently, mass spectrometry-based metabolomics studies extend beyond conventional chemical categorization and metabolic phenotype analysis to understanding gene function in various biological contexts (e.g., mammalian, plant, and microbial). These novel utilities have led to many innovative discoveries in the following areas: disease pathogenesis, therapeutic pathway or target identification, the biochemistry of animal and plant physiological and pathological activities in response to diverse stimuli, and molecular signatures of host-pathogen interactions during microbial infection. In this review, we critically evaluate the representative applications of mass spectrometry-based metabolomics to better understand gene function in diverse biological contexts, with special emphasis on working principles, study protocols, and possible future development of this technique. Collectively, this review raises awareness within the biomedical community of the scientific value and applicability of mass spectrometry-based metabolomics strategies to better understand gene function, thus advancing this application's utility in a broad range of biological fields

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Osteocyte cells are the most abundant cells in human bone tissue. Due to their unique morphology and location, osteocyte cells are thought to act as regulators in the bone remodelling process, and are believed to play an important role in astronauts’ bone mass loss after long-term space missions. There is increasing evidence showing that an osteocyte’s functions are highly affected by its morphology. However, changes in an osteocyte’s morphology under an altered gravity environment are still not well documented. Several in vitro studies have been recently conducted to investigate the morphological response of osteocyte cells to the microgravity environment, where osteocyte cells were cultured on a two-dimensional flat surface for at least 24 hours before microgravity experiments. Morphology changes of osteocyte cells in microgravity were then studied by comparing the cell area to 1g control cells. However, osteocyte cells found in vivo are with a more 3D morphology, and both cell body and dendritic processes are found sensitive to mechanical loadings. A round shape osteocyte’s cells support a less stiff cytoskeleton and are more sensitive to mechanical stimulations compared with flat cellular morphology. Thus, the relative flat and spread shape of isolated osteocytes in 2D culture may greatly hamper their sensitivity to a mechanical stimulus, and the lack of knowledge on the osteocyte’s morphological characteristics in culture may lead to subjective and noncomprehensive conclusions of how altered gravity impacts on an osteocyte’s morphology. Through this work empirical models were developed to quantitatively predicate the changes of morphology in osteocyte cell lines (MLO-Y4) in culture, and the response of osteocyte cells, which are relatively round in shape, to hyper-gravity stimulation has also been investigated. The morphology changes of MLO-Y4 cells in culture were quantified by measuring cell area and three dimensionless shape features including aspect ratio, circularity and solidity by using widely accepted image analysis software (ImageJTM). MLO-Y4 cells were cultured at low density (5×103 per well) and the changes in morphology were recorded over 10 hours. Based on the data obtained from the imaging analysis, empirical models were developed using the non-linear regression method. The developed empirical models accurately predict the morphology of MLO-Y4 cells for different culture times and can, therefore, be used as a reference model for analysing MLO-Y4 cell morphology changes within various biological/mechanical studies, as necessary. The morphological response of MLO-Y4 cells with a relatively round morphology to hyper-gravity environment has been investigated using a centrifuge. After 2 hours culture, MLO-Y4 cells were exposed to 20g for 30mins. Changes in the morphology of MLO-Y4 cells are quantitatively analysed by measuring the average value of cell area and dimensionless shape factors such as aspect ratio, solidity and circularity. In this study, no significant morphology changes were detected in MLO-Y4 cells under a hyper-gravity environment (20g for 30 mins) compared with 1g control cells.