970 resultados para Local productive arrangement
Resumo:
More recently, lifespan development psychology models of adaptive development have been applied to the workforce to investigate ageing worker and lifespan issues. The current study uses the Learning and Development Survey (LDS) to investigate employee selection and engagement of learning and development goals and opportunities and constraints for learning at work in relation to demographics and career goals. It was found that mature age was associated with perceptions of preferential treatment of younger workers with respect to learning and development. Age was also correlated with several career goals. Findings suggest that younger workers’ learning and development options are better catered for in the workplace. Mature aged workers may compensate for unequal learning opportunities at work by studying for an educational qualification or seeking alternate job opportunities. The desire for a higher level job within the organization or educational qualification was linked to engagement in learning and development goals at work. It is suggested that an understanding of employee perceptions in the workplace in relation to goals and activities may be important in designing strategies to retain workers.
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Robust, affine covariant, feature extractors provide a means to extract correspondences between images captured by widely separated cameras. Advances in wide baseline correspondence extraction require looking beyond the robust feature extraction and matching approach. This study examines new techniques of extracting correspondences that take advantage of information contained in affine feature matches. Methods of improving the accuracy of a set of putative matches, eliminating incorrect matches and extracting large numbers of additional correspondences are explored. It is assumed that knowledge of the camera geometry is not available and not immediately recoverable. The new techniques are evaluated by means of an epipolar geometry estimation task. It is shown that these methods enable the computation of camera geometry in many cases where existing feature extractors cannot produce sufficient numbers of accurate correspondences.
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We propose new bounds on the error of learning algorithms in terms of a data-dependent notion of complexity. The estimates we establish give optimal rates and are based on a local and empirical version of Rademacher averages, in the sense that the Rademacher averages are computed from the data, on a subset of functions with small empirical error. We present some applications to classification and prediction with convex function classes, and with kernel classes in particular.
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Urban expansion continues to encroach on existing or newly implemented sewerage infrastructure. In this context, legislation and guidelines, both national and international, provide limited direction to the amenity allocation of appropriate buffering distances for land use planners and infrastructure providers. A review of published literature suggests the dominant influences include topography, wind speed and direction, temperature, humidity, existing land uses and vegetation profiles. A statistical criteria review of these factors against six years of sewerage odour complaint data was undertaken to ascertain their influence and a complaint severity hierarchy was established. These hierarchical results suggested the main criteria were: topographical location, elevation relative to the odour source and wind speed. Establishing a justifiable criterion for buffer zone allocations will assist in analytically determining a basis for buffer separations and will assist planners and infrastructure designers in assessing lower impact sewerage infrastructure locations.
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This paper adopts an epistemic community framework to explicate the dual role of epistemic communities as influencers of accounting policy within regulatory space and as implementers who effect change within the domain of accounting. The context is the adoption and implementation of fair value accounting within local government in New South Wales (NSW). The roles and functions of Australian local government are extensive, and include the development and maintenance of infrastructure, provision of recreational facilities, certain health and community services, buildings, cultural facilities, and in some cases, water and sewerage (Australian Local Government Association, 2009). The NSW state Department of Local Government (DLG) is responsible for legislation and policy development to ensure that local councils are able to deliver ‘quality services to their communities in a sustainable manner’ (DLG, 2008c). These local councils receive revenue from various sources including property rates, government grants and user-pays service provision. In July 2006 the DLG issued Circular 06-453 to councils (DLG, 2006c), mandating the staged adoption of fair value measurement of infrastructure assets. This directive followed the policy of NSW State Treasury (NSW Treasury, 2007),4 and an independent inquiry into the financial sustainability of local councils (LGSA, 2006). It was an attempt to resolve the inconsistency in public sector asset valuation in NSW Local Governments, and to provide greater usefulness and comparability of financial statements.5 The focus of this study is the mobilization of accounting change by the DLG within this wider political context. When a regulatory problem arises, those with political power seek advice from professionals with relevant skill and expertise (Potter, 2005). This paper explores the way in which professionals diffuse accounting ‘problems’ and the associated accounting solutions ‘across time and space’ (Potter, 2005, p. 277). The DLG’s fair value accounting policy emanated from a ‘regulatory space’ (Hancher and Moran, 1989)6 as a result of negotiations between many parties, including accounting and finance professionals. Operating within the local government sector, these professionals were identified by the DLG as being capable of providing helpful input. They were also responsible for the implementation of the new olicy within local councils. Accordingly they have been dentified as an pistemic community with the ability to ranslate regulatory power by changing he domain of ccounting (Potter, 2005, p. 278).7 The paper is organised as follows. The background to the LG’s decision to require the introduction of fair value accounting for infrastructure assets is explored. Following this, the method of the study is described, and the epistemic community framework outlined. In the next sections, evidence of the influencing and implementing roles of epistemic groups is provided. Finally, conclusions are drawn about the significance of these groups both within regulatory space in developing accounting regulation, and in embedding change within the domain of accounting.
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This chapter reports on a project in which university researchers’ expertise in architecture, literacy and communications enabled two teachers in one school to expand the forms of literacy that primary school children engaged in. Starting from the school community’s concerns about an urban renewal project in their neighbourhood, participants collaborated to develop a curriculum of spatial literacies with real-world goals and outcomes. We describe how the creative re-design of curriculum and pedagogy by classroom teachers, in collaboration with university academics and students, allowed students aged 8 to 12 years to appropriate semiotic resources from their local neighbourhood, home communities, and popular culture to make a difference to their material surrounds. We argue that there are productive possibilities for educators who integrate critical and place-based approaches to the design and teaching of the literacy curriculum with work in other learning areas such as society and environment, technology and design and the arts. The student production of expansive and socially significant texts enabled by such approaches may be especially necessary in contemporary neoconservative policy contexts that tend to limit and constrain what is possible in schools.
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This article presents a two-stage analytical framework that integrates ecological crop (animal) growth and economic frontier production models to analyse the productive efficiency of crop (animal) production systems. The ecological crop (animal) growth model estimates "potential" output levels given the genetic characteristics of crops (animals) and the physical conditions of locations where the crops (animals) are grown (reared). The economic frontier production model estimates "best practice" production levels, taking into account economic, institutional and social factors that cause farm and spatial heterogeneity. In the first stage, both ecological crop growth and economic frontier production models are estimated to calculate three measures of productive efficiency: (1) technical efficiency, as the ratio of actual to "best practice" output levels; (2) agronomic efficiency, as the ratio of actual to "potential" output levels; and (3) agro-economic efficiency, as the ratio of "best practice" to "potential" output levels. Also in the first stage, the economic frontier production model identifies factors that determine technical efficiency. In the second stage, agro-economic efficiency is analysed econometrically in relation to economic, institutional and social factors that cause farm and spatial heterogeneity. The proposed framework has several important advantages in comparison with existing proposals. Firstly, it allows the systematic incorporation of all physical, economic, institutional and social factors that cause farm and spatial heterogeneity in analysing the productive performance of crop and animal production systems. Secondly, the location-specific physical factors are not modelled symmetrically as other economic inputs of production. Thirdly, climate change and technological advancements in crop and animal sciences can be modelled in a "forward-looking" manner. Fourthly, knowledge in agronomy and data from experimental studies can be utilised for socio-economic policy analysis. The proposed framework can be easily applied in empirical studies due to the current availability of ecological crop (animal) growth models, farm or secondary data, and econometric software packages. The article highlights several directions of empirical studies that researchers may pursue in the future.
Resumo:
The Queensland University of Technology (QUT) allows the presentation of a thesis for the Degree of Doctor of Philosophy in the format of published or submitted papers, where such papers have been published, accepted or submitted during the period of candidature. This thesis is composed of seven published/submitted papers, of which one has been published, three accepted for publication and the other three are under review. This project is financially supported by an Australian Research Council (ARC) Discovery Grant with the aim of proposing strategies for the performance control of Distributed Generation (DG) system with digital estimation of power system signal parameters. Distributed Generation (DG) has been recently introduced as a new concept for the generation of power and the enhancement of conventionally produced electricity. Global warming issue calls for renewable energy resources in electricity production. Distributed generation based on solar energy (photovoltaic and solar thermal), wind, biomass, mini-hydro along with use of fuel cell and micro turbine will gain substantial momentum in the near future. Technically, DG can be a viable solution for the issue of the integration of renewable or non-conventional energy resources. Basically, DG sources can be connected to local power system through power electronic devices, i.e. inverters or ac-ac converters. The interconnection of DG systems to power system as a compensator or a power source with high quality performance is the main aim of this study. Source and load unbalance, load non-linearity, interharmonic distortion, supply voltage distortion, distortion at the point of common coupling in weak source cases, source current power factor, and synchronism of generated currents or voltages are the issues of concern. The interconnection of DG sources shall be carried out by using power electronics switching devices that inject high frequency components rather than the desired current. Also, noise and harmonic distortions can impact the performance of the control strategies. To be able to mitigate the negative effect of high frequency and harmonic as well as noise distortion to achieve satisfactory performance of DG systems, new methods of signal parameter estimation have been proposed in this thesis. These methods are based on processing the digital samples of power system signals. Thus, proposing advanced techniques for the digital estimation of signal parameters and methods for the generation of DG reference currents using the estimates provided is the targeted scope of this thesis. An introduction to this research – including a description of the research problem, the literature review and an account of the research progress linking the research papers – is presented in Chapter 1. One of the main parameters of a power system signal is its frequency. Phasor Measurement (PM) technique is one of the renowned and advanced techniques used for the estimation of power system frequency. Chapter 2 focuses on an in-depth analysis conducted on the PM technique to reveal its strengths and drawbacks. The analysis will be followed by a new technique proposed to enhance the speed of the PM technique while the input signal is free of even-order harmonics. The other techniques proposed in this thesis as the novel ones will be compared with the PM technique comprehensively studied in Chapter 2. An algorithm based on the concept of Kalman filtering is proposed in Chapter 3. The algorithm is intended to estimate signal parameters like amplitude, frequency and phase angle in the online mode. The Kalman filter is modified to operate on the output signal of a Finite Impulse Response (FIR) filter designed by a plain summation. The frequency estimation unit is independent from the Kalman filter and uses the samples refined by the FIR filter. The frequency estimated is given to the Kalman filter to be used in building the transition matrices. The initial settings for the modified Kalman filter are obtained through a trial and error exercise. Another algorithm again based on the concept of Kalman filtering is proposed in Chapter 4 for the estimation of signal parameters. The Kalman filter is also modified to operate on the output signal of the same FIR filter explained above. Nevertheless, the frequency estimation unit, unlike the one proposed in Chapter 3, is not segregated and it interacts with the Kalman filter. The frequency estimated is given to the Kalman filter and other parameters such as the amplitudes and phase angles estimated by the Kalman filter is taken to the frequency estimation unit. Chapter 5 proposes another algorithm based on the concept of Kalman filtering. This time, the state parameters are obtained through matrix arrangements where the noise level is reduced on the sample vector. The purified state vector is used to obtain a new measurement vector for a basic Kalman filter applied. The Kalman filter used has similar structure to a basic Kalman filter except the initial settings are computed through an extensive math-work with regards to the matrix arrangement utilized. Chapter 6 proposes another algorithm based on the concept of Kalman filtering similar to that of Chapter 3. However, this time the initial settings required for the better performance of the modified Kalman filter are calculated instead of being guessed by trial and error exercises. The simulations results for the parameters of signal estimated are enhanced due to the correct settings applied. Moreover, an enhanced Least Error Square (LES) technique is proposed to take on the estimation when a critical transient is detected in the input signal. In fact, some large, sudden changes in the parameters of the signal at these critical transients are not very well tracked by Kalman filtering. However, the proposed LES technique is found to be much faster in tracking these changes. Therefore, an appropriate combination of the LES and modified Kalman filtering is proposed in Chapter 6. Also, this time the ability of the proposed algorithm is verified on the real data obtained from a prototype test object. Chapter 7 proposes the other algorithm based on the concept of Kalman filtering similar to those of Chapter 3 and 6. However, this time an optimal digital filter is designed instead of the simple summation FIR filter. New initial settings for the modified Kalman filter are calculated based on the coefficients of the digital filter applied. Also, the ability of the proposed algorithm is verified on the real data obtained from a prototype test object. Chapter 8 uses the estimation algorithm proposed in Chapter 7 for the interconnection scheme of a DG to power network. Robust estimates of the signal amplitudes and phase angles obtained by the estimation approach are used in the reference generation of the compensation scheme. Several simulation tests provided in this chapter show that the proposed scheme can very well handle the source and load unbalance, load non-linearity, interharmonic distortion, supply voltage distortion, and synchronism of generated currents or voltages. The purposed compensation scheme also prevents distortion in voltage at the point of common coupling in weak source cases, balances the source currents, and makes the supply side power factor a desired value.