An approach to statistical lip modelling for speaker identification via chromatic feature extraction

This paper presents a novel technique for the tracking of moving lips for the purpose of speaker identification. In our system, a model of the lip contour is formed directly from chromatic information in the lip region. Iterative refinement of contour point estimates is not required. Colour features are extracted from the lips via concatenated profiles taken around the lip contour. Reduction of order in lip features is obtained via principal component analysis (PCA) followed by linear discriminant analysis (LDA). Statistical speaker models are built from the lip features based on the Gaussian mixture model (GMM). Identification experiments performed on the M2VTS¹ database, show encouraging results

Approximate Membership Localization within a Web-Based Join Framework

In this paper, we propose a search-based approach to join two tables in the absence of clean join attributes. Non-structured documents from the web are used to express the correlations between a given query and a reference list. To implement this approach, a major challenge we meet is how to efficiently determine the number of times and the locations of each clean reference from the reference list that is approximately mentioned in the retrieved documents. We formalize the Approximate Membership Localization (AML) problem and propose an efficient partial pruning algorithm to solve it. A study using real-word data sets demonstrates the effectiveness of our search-based approach, and the efficiency of our AML algorithm.

Evaluating multivariate volatility forecasts : how effective are statistical and economic loss functions?

Multivariate volatility forecasts are an important input in many financial applications, in particular portfolio optimisation problems. Given the number of models available and the range of loss functions to discriminate between them, it is obvious that selecting the optimal forecasting model is challenging. The aim of this thesis is to thoroughly investigate how effective many commonly used statistical (MSE and QLIKE) and economic (portfolio variance and portfolio utility) loss functions are at discriminating between competing multivariate volatility forecasts. An analytical investigation of the loss functions is performed to determine whether they identify the correct forecast as the best forecast. This is followed by an extensive simulation study examines the ability of the loss functions to consistently rank forecasts, and their statistical power within tests of predictive ability. For the tests of predictive ability, the model confidence set (MCS) approach of Hansen, Lunde and Nason (2003, 2011) is employed. As well, an empirical study investigates whether simulation findings hold in a realistic setting. In light of these earlier studies, a major empirical study seeks to identify the set of superior multivariate volatility forecasting models from 43 models that use either daily squared returns or realised volatility to generate forecasts. This study also assesses how the choice of volatility proxy affects the ability of the statistical loss functions to discriminate between forecasts. Analysis of the loss functions shows that QLIKE, MSE and portfolio variance can discriminate between multivariate volatility forecasts, while portfolio utility cannot. An examination of the effective loss functions shows that they all can identify the correct forecast at a point in time, however, their ability to discriminate between competing forecasts does vary. That is, QLIKE is identified as the most effective loss function, followed by portfolio variance which is then followed by MSE. The major empirical analysis reports that the optimal set of multivariate volatility forecasting models includes forecasts generated from daily squared returns and realised volatility. Furthermore, it finds that the volatility proxy affects the statistical loss functions’ ability to discriminate between forecasts in tests of predictive ability. These findings deepen our understanding of how to choose between competing multivariate volatility forecasts.

Towards a service framework for remote sales support via augmented reality

Real-time sales assistant service is a problematic component of remote delivery of sales support for customers. Solutions involving web pages, telephony and video support prove problematic when seeking to remotely guide customers in their sales processes, especially with transactions revolving around physically complex artefacts. This process involves a number of services that are often complex in nature, ranging from physical compatibility and configuration factors, to availability and credit services. We propose the application of a combination of virtual worlds and augmented reality to create synthetic environments suitable for remote sales of physical artefacts, right in the home of the purchaser. A high level description of the service structure involved is shown, along with a use case involving the sale of electronic goods and services within an example augmented reality application. We expect this work to have application in many sales domains involving physical objects needing to be sold over the Internet.

Developing a conceptual framework of strategic entrepreneurship

Purpose: This paper aims to examine the integration of entrepreneurship and strategy to develop a conceptual framework of strategic entrepreneurship. The framework is developed through an analysis of theory and refined through an examination of practice. Design/methodology/approach: This framework is considered in the context of potentially entrepreneurial and strategic activity undertaken by 12 of the 17 state-owned enterprises (SOEs) operating in New Zealand in 2006-2007. Based on a review of documents, observation, and interviews with SOE executives, cases of 12 SOE activities were analysed to compare and contrast strategic entrepreneurship in practice. Findings: The findings reveal distinct elements within the four activities classified as strategic entrepreneurship, activities, such as leveraging from core skills and resources from a strategic perspective, and innovation from an entrepreneurial perspective. Originality/value: This study is one of the first to examine the nature of strategic entrepreneurship in practice and the associated financial returns.

New variational Bayesian approaches for statistical data mining : with applications to profiling and differentiating habitual consumption behaviour of customers in the wireless telecommunication industry

This thesis investigates profiling and differentiating customers through the use of statistical data mining techniques. The business application of our work centres on examining individuals’ seldomly studied yet critical consumption behaviour over an extensive time period within the context of the wireless telecommunication industry; consumption behaviour (as oppose to purchasing behaviour) is behaviour that has been performed so frequently that it become habitual and involves minimal intentions or decision making. Key variables investigated are the activity initialised timestamp and cell tower location as well as the activity type and usage quantity (e.g., voice call with duration in seconds); and the research focuses are on customers’ spatial and temporal usage behaviour. The main methodological emphasis is on the development of clustering models based on Gaussian mixture models (GMMs) which are fitted with the use of the recently developed variational Bayesian (VB) method. VB is an efficient deterministic alternative to the popular but computationally demandingMarkov chainMonte Carlo (MCMC) methods. The standard VBGMMalgorithm is extended by allowing component splitting such that it is robust to initial parameter choices and can automatically and efficiently determine the number of components. The new algorithm we propose allows more effective modelling of individuals’ highly heterogeneous and spiky spatial usage behaviour, or more generally human mobility patterns; the term spiky describes data patterns with large areas of low probability mixed with small areas of high probability. Customers are then characterised and segmented based on the fitted GMM which corresponds to how each of them uses the products/services spatially in their daily lives; this is essentially their likely lifestyle and occupational traits. Other significant research contributions include fitting GMMs using VB to circular data i.e., the temporal usage behaviour, and developing clustering algorithms suitable for high dimensional data based on the use of VB-GMM.

Applying a social justice framework to ensure good practice in monitoring student learning engagement

A current Australian Learning and Teaching Council (ALTC) funded action research project aims to provide a set of practical resources founded on a social justice framework, to guide good practice for monitoring student learning engagement (MSLE) in higher education. The project involves ten Australasian institutions, eight of which are engaged in various MSLE type projects. A draft framework, consisting of six social justice principles which emerged from the literature has been examined with reference to the eight institutional approaches for MSLE in conjunction with the personnel working on these initiatives during the first action research cycle. The cycle will examine the strategic and operational implications of the framework in each of the participating institutions. Cycle 2 will also build capacity to embed the principles within the institutional MSLE program and will identify and collect examples and resources that exemplify the principles in practice. The final cycle will seek to pilot the framework to guide new MSLE initiatives. In its entirety, the project will deliver significant resources to the sector in the form of a social justice framework for MSLE, guidelines and sector exemplars for MSLE. As well as increasing the awareness amongst staff around the criticality of transition to university (thereby preventing attrition) and the significance of the learning and teaching agenda in enhancing student engagement, the project will build leadership capacity within the participating institutions and provide a knowledge base and institutional capacity for the Australasian HE sector to deploy the deliverables that will safeguard student learning engagement At this early stage of the project the workshop session provides an opportunity to discuss and examine the draft set of social justice principles and to discuss their potential value for the participants’ institutional contexts. Specifically, the workshop will explore critical questions associated with the principles.

Developing a social justice framework to ensure good practice in higher education

The concept of student engagement is a key factor in student achievement and retention and Australasian universities have a range of initiatives aimed at monitoring and intervening with students who are at risk of disengaging. Given the aspirations about widening participation, it is absolutely critical that these initiatives are designed to enable success for all students, particularly those for whom social and cultural disadvantage have been a barrier. Consequently, these types of initiatives must be consistent with the concept of social justice and a set of principles would provide this philosophical foundation for the sector. An Australian Learning and Teaching Council (ALTC) project that involves ten Australasian universities, is designing of a suite of resources for the sector which will include: (1) a set of principles for good practice in MSLE, (2) a good practice guide for the design and implementation of institutional MSLE policy and practice, and (3) a collection of resources for and exemplars of good practice to be taken up by the sector. This workshop session will provide an opportunity for participants to examine the draft set of principles and to discuss their potential value for the participants’ institutional contexts. Australian Learning and Teaching Council Competitive Grant CG10-1730 2010-2012: Good practice for safeguarding student learning engagement in higher education institutions.

An integrated framework to assess financial reward systems in construction projects

Motivation is a major driver of project performance. Despite team member ability to deliver successful project outcomes if they are not positively motivated to pursue joint project goals, then performance will be constrained. One approach to improving the motivation of project organizations is by offering a financial reward for the achievement of set performance standards above a minimum required level. However, little investigation has been undertaken into the features of successful incentive systems as a part of an overall delivery strategy. With input from organizational management literature, and drawing on the literature covering psychological and economic theories of motivation, this paper presents an integrated framework that can be used by project organizations to assess the impact of financial reward systems on motivation in construction projects. The integrated framework offers four motivation indicators which reflect key theoretical concepts across both psychological and economic disciplines. The indicators are: (1) Goal Commitment, (2) Distributive Justice, (3) Procedural Justice, and (4) Reciprocity. The paper also interprets the integrated framework against the results of a successful Australian social infrastructure project case study and identifies key learning’s for project organizations to consider when designing financial reward systems. Case study results suggest that motivation directed towards the achievement of incentive goals is influenced not only by the value placed on the financial reward for commercial benefit, but also driven by the strength of the project initiatives that encourage just and fair dealings, supporting the establishment of trust and positive reciprocal behavior across a project team. The strength of the project relationships was found to be influenced by how attractive the achievement of the goal is to the incentive recipient and how likely they were to push for the achievement of the goal. Interestingly, findings also suggested that contractor motivation is also influenced by the fairness of the performance measurement process and their perception of the trustworthiness and transparency of their client. These findings provide the basis for future research on the impact of financial reward systems on motivation in construction projects. It is anticipated that such research will shed new light on this complex topic and further define how reward systems should be designed to promote project team motivation. Due to the unique nature of construction projects with high levels of task complexity and interdependence, results are expected to vary in comparison to previous studies based on individuals or single-entity organizations.

Sustainability and urban settlements: urban metabolism as a framework for achieving sustainable development

Urban settlements, with their role as economic and governance nerve centres, are rapidly expanding in size and in consumption of resources, and consequently have significant impacts on the environment. The transition to an ‘eco-city’ - an urban settlement that adopts the goals and principles in the urban metabolism model - needs to occur to meet the challenges posed by a multitude of pressures including population growth, climate change and resource depletion. Thus, the adoption and integration of ‘sustainable development’ into the management of urban growth is one of the most critical governance issues for urban settlements. A framework in which sustainable development can be achieved is through the lenses of the established theoretical concept of ‘urban metabolism’. The key facet of the proposed ‘Integrated Urban Metabolism Framework’ is the provision of a platform whereby different fields can appreciate, absorb and learn from other areas, to increase the understanding of where each and every one of the pieces fit together in order to create a larger, holistic approach to the currently stagnant problem of unsustainable development.

Assessment of requirements for establishment of a framework to enhance implementation of quality practices in building projects

Quality, in construction projects should be regarded as the fulfillment of expectation of those contributors involved in such projects. Although a significant amount of quality practices have been introduced within the industry, attainment of reasonable levels of quality in construction projects continues to be an ongoing problem. To date, some research into the introduction and improvement of quality practices and stakeholder management has been undertaken, but so far no major studies have been completed that comprehensively examine how greater consideration of stakeholders’ perspectives of quality can be used to contribute to final project quality outcomes. This paper aims to examine the requirements for development of a framework leading to more effective involvement of stakeholders in quality planning and practices thus ultimately contributing to higher quality outcomes for construction projects. Through an extensive literature review it highlights various perceptions of quality, categorizes quality issues with particular focus on benefits and shortcomings and also examines the viewpoints of major stakeholders on project quality. It proposes a set of criteria to be used as a basis for a quality practice improvement framework, which will provide project managers and owners with the required information and strategic direction to achieve their own and their stakeholders’ targets for implementation of quality practices leading to the achievement of improved quality outcomes on future projects.

Evaluation framework for focused link discovery

Information has no value unless it is accessible. Information must be connected together so a knowledge network can then be built. Such a knowledge base is a key resource for Internet users to interlink information from documents. Information retrieval, a key technology for knowledge management, guarantees access to large corpora of unstructured text. Collaborative knowledge management systems such as Wikipedia are becoming more popular than ever; however, their link creation function is not optimized for discovering possible links in the collection and the quality of automatically generated links has never been quantified. This research begins with an evaluation forum which is intended to cope with the experiments of focused link discovery in a collaborative way as well as with the investigation of the link discovery application. The research focus was on the evaluation strategy: the evaluation framework proposal, including rules, formats, pooling, validation, assessment and evaluation has proved to be efficient, reusable for further extension and efficient for conducting evaluation. The collection-split approach is used to re-construct the Wikipedia collection into a split collection comprising single passage files. This split collection is proved to be feasible for improving relevant passages discovery and is devoted to being a corpus for focused link discovery. Following these experiments, a mobile client-side prototype built on iPhone is developed to resolve the mobile Search issue by using focused link discovery technology. According to the interview survey, the proposed mobile interactive UI does improve the experience of mobile information seeking. Based on this evaluation framework, a novel cross-language link discovery proposal using multiple text collections is developed. A dynamic evaluation approach is proposed to enhance both the collaborative effort and the interacting experience between submission and evaluation. A realistic evaluation scheme has been implemented at NTCIR for cross-language link discovery tasks.

An integrated knowledge management framework for managing sustainability knowledge in the Australian infrastructure sector

In Australia, it has been increasingly accepted that sustainability needs to be at the top of the agenda when contemplating infrastructure development. In practice however, many companies struggle to find effective ways to embrace sustainable ideas and implement them in real projects beyond minimum compliance. One of the reasons is the lack of underpinning knowledge and evidence to demonstrate and measure the linkage between sustainability implementations and the relevant outcomes. This is compounded by the fact that very often there are no common understandings between the stakeholders on sustainability and there is a big divide between research advancement and real-life applications. Therefore it is both feasible and timely to develop and expand the body of sustainability knowledge on infrastructure development and investigate better ways of communicating with and managing it within the infrastructure sector. Although knowledge management (KM) is a relatively new and emerging discipline, it has shown its value and promise in existing applications in the construction industry. Considering the existing KM mechanisms and tools employed in practice, this research is aimed at establishing a specific KM approach to facilitate sustainability knowledge identification, acquisition, sharing, maintenance and application within the infrastructure sector, and promote integrated decision-making for sustainable infrastructure development. A triangulation of questionnaire survey, semi-structured interviews and case studies was employed in this research to collect required qualitative and quantitative data. The research studied the unique characteristics of the infrastructure sector, the nature of sustainability knowledge, and evaluated and validated the critical elements, key processes, and priority issues of KM for the Australian infrastructure sector. A holistic KM framework was developed to set the overall context for managing sustainability knowledge in the infrastructure sector by outlining (1) the main aims and outcomes of managing sustainability knowledge, (2) the key knowledge activities, (3) effective KM strategies and instruments, and (4) KM enablers. Because of the highly project-oriented nature of the infrastructure sector, knowledge can only add value when it is being used in real projects. Implementation guidelines were developed to help the industry practitioners and project teams to apply sustainability knowledge and implement KM in infrastructure project scenarios. This research provides the Australian infrastructure sector with tools to better understand KM, helps the industry practitioners to prioritize attention on relevant sustainability issues, and recommends effective practices to manage sustainability knowledge, especially in real life implementation of infrastructure projects.

Relationship management as a strategy for supply chain engagement in the civil engineering construction industry

Many studies into construction procurement methods reveal evidence of a need to change the culture and attitude in the construction industry, transition from traditional adversarial relationships to cooperative and collaborative relationships. At the same time there is also increasing concern and discussion on alternative procurement methods, involving a movement away from traditional procurement systems. Relational contracting approaches, such as partnering and relationship management, are business strategies that align the objectives of clients, commercial participants and stakeholders. It provides a collaborative environment and a framework for all participants to adapt their behaviour to project objectives and allows for engagement of those subcontractors and suppliers down the supply chain. The efficacy of relationship management in the client and contractor groups is proven and well documented. However, the industry has a history of slow implementation of relational contracting down the supply chain. Furthermore, there exists little research on relationship management conducted in the supply chain context. This research aims to explore the association between relational contracting structures and processes and supply chain sustainability in the civil engineering construction industry. It endeavours to shed light on the practices and prerequisites for relationship management implementation success and for supply sustainability to develop. The research methodology is a triangulated approach based on Cheung.s (2006) earlier research where questionnaire survey, interviews and case studies were conducted. This new research includes a face-to-face questionnaire survey that was carried out with 100 professionals from 27 contracting organisations in Queensland from June 2008 to January 2009. A follow-up survey sub-questionnaire, further examining project participants. perspectives was sent to another group of professionals (as identified in the main questionnaire survey). Statistical analysis including multiple regression, correlation, principal component factor analysis and analysis of variance were used to identify the underlying dimensions and test the relationships among variables. Interviews and case studies were conducted to assist in providing a deeper understanding as well as explaining findings of the quantitative study. The qualitative approaches also gave the opportunity to critique and validate the research findings. This research presents the implementation of relationship management from the contractor.s perspective. Findings show that the adaption of relational contracting approach in the supply chain is found to be limited; contractors still prefer to keep the suppliers and subcontractors at arm.s length. This research shows that the degree of match and mismatch between organisational structuring and organisational process has an impact on staff.s commitment level and performance effectiveness. Key issues affecting performance effectiveness and relationship effectiveness include total influence between parties, access to information, personal acquaintance, communication process, risk identification, timely problem solving and commercial framework. Findings also indicate that alliance and Early Contractor Involvement (ECI) projects achieve higher performance effectiveness at both short-term and long-term levels compared to projects with either no or partial relationship management adopted.

Analysis of productive performance of crop and animal production systems : an integrated analytical framework

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.