Local Rademacher complexities

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.

Learning the Kernel Matrix with Semi-Definite Programming

Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is performed implicitly, by specifying the inner products between each pair of points in the embedding space. This information is contained in the so-called kernel matrix, a symmetric and positive definite matrix that encodes the relative positions of all points. Specifying this matrix amounts to specifying the geometry of the embedding space and inducing a notion of similarity in the input space -- classical model selection problems in machine learning. In this paper we show how the kernel matrix can be learned from data via semi-definite programming (SDP) techniques. When applied to a kernel matrix associated with both training and test data this gives a powerful transductive algorithm -- using the labelled part of the data one can learn an embedding also for the unlabelled part. The similarity between test points is inferred from training points and their labels. Importantly, these learning problems are convex, so we obtain a method for learning both the model class and the function without local minima. Furthermore, this approach leads directly to a convex method to learn the 2-norm soft margin parameter in support vector machines, solving another important open problem. Finally, the novel approach presented in the paper is supported by positive empirical results.

Development of a sewerage infrastructure buffer assessment tool for local authorities

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.

The causes and consequences of corruption

This thesis comprehensively studies the causes and consequences of corruption in both crosscountry and within-country contexts, mainly focusing on China. The thesis commences by extensively investigating the causes of corruption. Using the standard economic approach, this study finds that in China regions with more anti-corruption efforts, higher education attainment, Anglo-American historic influence, higher openness, more access to media, higher relative wages of government employees, and a greater representation of women in legislature are markedly less corrupt; while the social heterogeneity, deregulation and abundance of resources, substantially breed regional corruption. Moreover, fiscal decentralization is discovered to depress corruption significantly. This study also observes a positive relationship between corruption and the economic development in current China that is mainly driven by the transition to a market economy. Focusing on the influence of political institutions on corruption, the thesis then provides evidence that a high level of political interest helps to reduce corruption within a society, while the effect of democracy upon corruption depends on property rights protection and income distribution. With the social economic approach, however, the thesis presents both cross-country and within-country evidence that the social interaction plays an important role in determining corruption. The thesis then continues by comprehensively evaluating the consequences of corruption in China. The study provides evidence that corruption can simultaneously have both positive and negative effects on economic development. And it also observes that corruption considerably increases the income inequality in China. Furthermore this study finds that corruption in China significantly distorts public expenditures. Local corruption is also observed to substantially reduce FDI in Chinese regions. Finally the study documents that corruption substantially aggravates pollution probably through a loosening of the environmental regulation, and that it also modifies the effects of trade openness and FDI on the stringency of environmental policy. Overall, this thesis adds to the current literature by a number of novel findings concerning both the causes and the consequences of corruption.

Spatially stratified sampling using auxiliary information for geostatistical mapping

This paper presents a method of spatial sampling based on stratification by Local Moran’s I i calculated using auxiliary information. The sampling technique is compared to other design-based approaches including simple random sampling, systematic sampling on a regular grid, conditional Latin Hypercube sampling and stratified sampling based on auxiliary information, and is illustrated using two different spatial data sets. Each of the samples for the two data sets is interpolated using regression kriging to form a geostatistical map for their respective areas. The proposed technique is shown to be competitive in reproducing specific areas of interest with high accuracy.

Predicting residue-wise contact orders in proteins by support vector regression

Background The residue-wise contact order (RWCO) describes the sequence separations between the residues of interest and its contacting residues in a protein sequence. It is a new kind of one-dimensional protein structure that represents the extent of long-range contacts and is considered as a generalization of contact order. Together with secondary structure, accessible surface area, the B factor, and contact number, RWCO provides comprehensive and indispensable important information to reconstructing the protein three-dimensional structure from a set of one-dimensional structural properties. Accurately predicting RWCO values could have many important applications in protein three-dimensional structure prediction and protein folding rate prediction, and give deep insights into protein sequence-structure relationships. Results We developed a novel approach to predict residue-wise contact order values in proteins based on support vector regression (SVR), starting from primary amino acid sequences. We explored seven different sequence encoding schemes to examine their effects on the prediction performance, including local sequence in the form of PSI-BLAST profiles, local sequence plus amino acid composition, local sequence plus molecular weight, local sequence plus secondary structure predicted by PSIPRED, local sequence plus molecular weight and amino acid composition, local sequence plus molecular weight and predicted secondary structure, and local sequence plus molecular weight, amino acid composition and predicted secondary structure. When using local sequences with multiple sequence alignments in the form of PSI-BLAST profiles, we could predict the RWCO distribution with a Pearson correlation coefficient (CC) between the predicted and observed RWCO values of 0.55, and root mean square error (RMSE) of 0.82, based on a well-defined dataset with 680 protein sequences. Moreover, by incorporating global features such as molecular weight and amino acid composition we could further improve the prediction performance with the CC to 0.57 and an RMSE of 0.79. In addition, combining the predicted secondary structure by PSIPRED was found to significantly improve the prediction performance and could yield the best prediction accuracy with a CC of 0.60 and RMSE of 0.78, which provided at least comparable performance compared with the other existing methods. Conclusion The SVR method shows a prediction performance competitive with or at least comparable to the previously developed linear regression-based methods for predicting RWCO values. In contrast to support vector classification (SVC), SVR is very good at estimating the raw value profiles of the samples. The successful application of the SVR approach in this study reinforces the fact that support vector regression is a powerful tool in extracting the protein sequence-structure relationship and in estimating the protein structural profiles from amino acid sequences.

Neo-planning: Location-based social media to engage Australia’s new digital locals

Community engagement with time poor and seemingly apathetic citizens continues to challenge local governments. Capturing the attention of a digitally literate community who are technology and socially savvy adds a new quality to this challenge. Community engagement is resource and time intensive, yet local governments have to manage on continually tightened budgets. The benefits of assisting citizens in taking ownership in making their community and city a better place to live in collaboration with planners and local governments are well established. This study investigates a new collaborative form of civic participation and engagement for urban planning that employs in-place digital augmentation. It enhances people’s experience of physical spaces with digital technologies that are directly accessible within that space, in particular through interaction with mobile phones and public displays. The study developed and deployed a system called Discussions in Space (DIS) in conjunction with a major urban planning project in Brisbane. Planners used the system to ask local residents planning-related questions via a public screen, and passers-by sent responses via SMS or Twitter onto the screen for others to read and reflect, hence encouraging in-situ, real-time, civic discourse. The low barrier of entry proved to be successful in engaging a wide range of residents who are generally not heard due to their lack of time or interest. The system also reflected positively on the local government for reaching out in this way. Challenges and implications of the short-texted and ephemeral nature of this medium were evaluated in two focus groups with urban planners. The paper concludes with an analysis of the planners’ feedback evaluating the merits of the data generated by the system to better engage with Australia’s new digital locals.

An epistemic community as influencer and implementer in local government accounting in Australia

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.

Engaging middle school students in context-based science : One teacher's approach

In Australia, there is a crisis in science education with students becoming disengaged with canonical science in the middle years of schooling. One recent initiative that aims to improve student interest and motivation without diminishing conceptual understanding is the context-based approach. Contextual units that connect the canonical science with the students’ real world of their local community have been used in the senior years but are new in the middle years. This ethnographic study explored the learning transactions that occurred in one 9th grade science class studying an Environmental Science unit for 11 weeks. Data were derived from field notes, audio and video recorded conversations, interviews, student journals and classroom documents with a particular focus on two selected groups of students. Data were analysed qualitatively through coding for emergent themes. This paper presents an outline of the program and discussion of three assertions derived from the preliminary analysis of the data. Firstly, an integrated, coherent sequence of learning experiences that included weekly visits to a creek adjacent to the school enabled the teacher to contextualise the science in the students’ local community. Secondly, content was predominantly taught on a need-to-know basis and thirdly, the lesson sequence aligned with a model for context-based teaching. Research, teaching and policy implications of these results for promoting the context-based teaching of science in the middle years are discussed.

To have your caveat and claim it, too : steps to take to protect an interest in land or water allocation

Caveats as protection for unregistered interests - lapsing and non-lapsing caveats - caveator - use only in appropriate circumstances