Limited information estimation and evaluation of DSGE models

We advance the proposition that dynamic stochastic general equilibrium (DSGE) models should not only be estimated and evaluated with full information methods. These require that the complete system of equations be specified properly. Some limited information analysis, which focuses upon specific equations, is therefore likely to be a useful complement to full system analysis. Two major problems occur when implementing limited information methods. These are the presence of forward-looking expectations in the system as well as unobservable non-stationary variables. We present methods for dealing with both of these difficulties, and illustrate the interaction between full and limited information methods using a well-known model.

Accelerated Partial Breast Irradiation (APBI) : a review of available techniques

Breast conservation therapy (BCT) is the procedure of choice for the management of the early stage breast cancer. However, its utilization has not been maximized because of logistics issues associated with the protracted treatment involved with the radiation treatment. Accelerated Partial Breast Irradiation (APBI) is an approach that treats only the lumpectomy bed plus a 1-2 cm margin, rather than the whole breast. Hence because of the small volume of irradiation a higher dose can be delivered in a shorter period of time. There has been growing interest for APBI and various approaches have been developed under phase I-III clinical studies; these include multicatheter interstitial brachytherapy, balloon catheter brachytherapy, conformal external beam radiation therapy and intra-operative radiation therapy (IORT). Balloon-based brachytherapy approaches include Mammosite, Axxent electronic brachytherapy and Contura, Hybrid brachytherapy devices include SAVI and ClearPath. This paper reviews the different techniques, identifying the weaknesses and strength of each approach and proposes a direction for future research and development. It is evident that APBI will play a role in the management of a selected group of early breast cancer. However, the relative role of the different techniques is yet to be clearly identified.

Estimation of the depth focus from wavefront measurements

It is possible to estimate the depth of focus (DOF) of the eye directly from wavefront measurements using various retinal image quality metrics (IQMs). In such methods, DOF is defined as the range of defocus error that degrades the retinal image quality calculated from IQMs to a certain level of the maximum value. Although different retinal image quality metrics are used, currently there have been two arbitrary threshold levels adopted, 50% and 80%. There has been limited study of the relationship between these threshold levels and the actual measured DOF. We measured the subjective DOF in a group of 17 normal subjects, and used through-focus augmented visual Strehl ratio based on optical transfer function (VSOTF) derived from their wavefront aberrations as the IQM. For each subject, a VSOTF threshold level was derived that would match the subjectively measured DOF. Significant correlation was found between the subject’s estimated threshold level and the HOA RMS (Pearson’s r=0.88, p<0.001). The linear correlation can be used to estimate the threshold level for each individual subject, subsequently leading to a method for estimating individual’s DOF from a single measurement of their wavefront aberrations.

Australian data breach notification : avoiding the State/Federal overlap

Mandatory data breach notification has become a matter of increasing concern for law reformers. In Australia, this issue was recently addressed as part of a comprehensive review of privacy law conducted by the Australian Law Reform Commission (ALRC) which recommended a uniform national regime for protecting personal information applicable to both the public and private sectors. As in all federal systems, the distribution of powers between central and state governments poses problems for national consistency. In the authors’ view, a uniform approach to mandatory data breach notification has greater merit than a ‘jurisdiction specific’ approach epitomized by US state-based laws. The US response has given rise to unnecessary overlaps and inefficiencies as demonstrated by a review of different notification triggers and encryption safe harbors. Reviewing the US response, the authors conclude that a uniform approach to data breach notification is inherently more efficient.

Wavelet based approaches and high resolution methods for complex process models

Many industrial processes and systems can be modelled mathematically by a set of Partial Differential Equations (PDEs). Finding a solution to such a PDF model is essential for system design, simulation, and process control purpose. However, major difficulties appear when solving PDEs with singularity. Traditional numerical methods, such as finite difference, finite element, and polynomial based orthogonal collocation, not only have limitations to fully capture the process dynamics but also demand enormous computation power due to the large number of elements or mesh points for accommodation of sharp variations. To tackle this challenging problem, wavelet based approaches and high resolution methods have been recently developed with successful applications to a fixedbed adsorption column model. Our investigation has shown that recent advances in wavelet based approaches and high resolution methods have the potential to be adopted for solving more complicated dynamic system models. This chapter will highlight the successful applications of these new methods in solving complex models of simulated-moving-bed (SMB) chromatographic processes. A SMB process is a distributed parameter system and can be mathematically described by a set of partial/ordinary differential equations and algebraic equations. These equations are highly coupled; experience wave propagations with steep front, and require significant numerical effort to solve. To demonstrate the numerical computing power of the wavelet based approaches and high resolution methods, a single column chromatographic process modelled by a Transport-Dispersive-Equilibrium linear model is investigated first. Numerical solutions from the upwind-1 finite difference, wavelet-collocation, and high resolution methods are evaluated by quantitative comparisons with the analytical solution for a range of Peclet numbers. After that, the advantages of the wavelet based approaches and high resolution methods are further demonstrated through applications to a dynamic SMB model for an enantiomers separation process. This research has revealed that for a PDE system with a low Peclet number, all existing numerical methods work well, but the upwind finite difference method consumes the most time for the same degree of accuracy of the numerical solution. The high resolution method provides an accurate numerical solution for a PDE system with a medium Peclet number. The wavelet collocation method is capable of catching up steep changes in the solution, and thus can be used for solving PDE models with high singularity. For the complex SMB system models under consideration, both the wavelet based approaches and high resolution methods are good candidates in terms of computation demand and prediction accuracy on the steep front. The high resolution methods have shown better stability in achieving steady state in the specific case studied in this Chapter.

Crash risk estimation and assessment tool

Currently in Australia, there are no decision support tools for traffic and transport engineers to assess the crash risk potential of proposed road projects at design level. A selection of equivalent tools already exists for traffic performance assessment, e.g. aaSIDRA or VISSIM. The Urban Crash Risk Assessment Tool (UCRAT) was developed for VicRoads by ARRB Group to promote methodical identification of future crash risks arising from proposed road infrastructure, where safety cannot be evaluated based on past crash history. The tool will assist practitioners with key design decisions to arrive at the safest and the most cost -optimal design options. This paper details the development and application of UCRAT software. This professional tool may be used to calculate an expected mean number of casualty crashes for an intersection, a road link or defined road network consisting of a number of such elements. The mean number of crashes provides a measure of risk associated with the proposed functional design and allows evaluation of alternative options. The tool is based on historical data for existing road infrastructure in metropolitan Melbourne and takes into account the influence of key design features, traffic volumes, road function and the speed environment. Crash prediction modelling and risk assessment approaches were combined to develop its unique algorithms. The tool has application in such projects as road access proposals associated with land use developments, public transport integration projects and new road corridor upgrade proposals.

V2V/V2I augmented maps : state-of-the-art and contribution to real-time crash risk assessment

A number of advanced driver assistance systems (ADAS) are currently being released on the market, providing safety functions to the drivers such as collision avoidance, adaptive cruise control or enhanced night-vision. These systems however are inherently limited by their sensory range: they cannot gather information from outside this range, also called their “perceptive horizon”. Cooperative systems are a developing research avenue that aims at providing extended safety and comfort functionalities by introducing vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) wireless communications to the road actors. This paper presents the problematic of cooperative systems, their advantages and contributions to road safety and exposes some limitations related to market penetration, sensors accuracy and communications scalability. It explains the issues of how to implement extended perception, a central contribution of cooperative systems. The initial steps of an evaluation of data fusion architectures for extended perception are exposed.

Strategic entrepreneurship in New Zealand's state-owned enterprises : underlying elements and financial implications

The concept of strategic entrepreneurship has received increased attention over the past ten yeras. Viewed as the intersection of entrepreneurship and strategy this field of research is populated by conceptual studies which focus mainly on the nature and perceived benefits of strategic entrepreneurship. Similarly the study of entrepreneurship in a public sector context has gained increasing support in recent years but also remains underexplored. To address these gaps this thesis considers : what are the underlying elements and financial implications of strategic entrepreneurship in New Zealand's state-owned enterprises, New Zealand's SOE sector comprising 17 government-owned,commercially focused organisations, is considered to be a prime subject for this research. Well known for their implementation of new public management, many New Zealand SOEs have also been publicly recognised as both innovative and entrepreneurial. The research question is addressed by first developing a preliminary framework of strategic entrepreneurship from literature on entrepreneurhsip and strategy. The framework is then examined in the context of case studies on activity.

Enabling 21st century learning spaces : practical interpretations of the MCEETYA Learning Spaces Framework at Bounty Boulevard State School, Queensland, Australia

While the Queensland and Australian Governments have recognised the importance of new spaces for teaching and learning, particularly with the Rudd Government's Building the Education Revolution, the practical implementation of new spaces is largely left to schools and even individual teachers. This article proposes a theory for the consideration of 21st century learning spaces in relation to the learner, desired knowledge and understanding, digital technology and digital pedagogy. New and emerging learning spaces at Bounty Boulevard State School are analysed and critiqued through an analysis of the guiding principles offered by the 'Learning in an Online World: Learning Spaces Framework' (MCEETYA, 2008) publication, including flexibility, inclusivity, collaboration, creativity and efficiency. The argument put forward in this article is that 21st century learning spaces can be enabled while acknowledging barriers of resourcing and current ICT infrastructure.

Estimation of parameters for macroparasite population evolution using approximate Bayesian computation

We estimate the parameters of a stochastic process model for a macroparasite population within a host using approximate Bayesian computation (ABC). The immunity of the host is an unobserved model variable and only mature macroparasites at sacrifice of the host are counted. With very limited data, process rates are inferred reasonably precisely. Modeling involves a three variable Markov process for which the observed data likelihood is computationally intractable. ABC methods are particularly useful when the likelihood is analytically or computationally intractable. The ABC algorithm we present is based on sequential Monte Carlo, is adaptive in nature, and overcomes some drawbacks of previous approaches to ABC. The algorithm is validated on a test example involving simulated data from an autologistic model before being used to infer parameters of the Markov process model for experimental data. The fitted model explains the observed extra-binomial variation in terms of a zero-one immunity variable, which has a short-lived presence in the host.

An analysis of parliamentary questions raised by Opposition in the Uttar Pradesh (India) State Legislative Assembly

The use of parliamentary questions is the most popular and visible tool in the hands of the Opposition as a means to make government accountable. Their main purpose is to seek information or press for action. Contemporary parliamentary literature from the UK, Canada, and Australia, however, suggests that parliamentary questions have lost their effectiveness. The literature points out that Question Time in parliaments has become a battle ground between Ruling and Opposition parties in their fight to gain maximum political advantage. In this context, the effectiveness of parliamentary questions in the Indian state legislatures has not been investigated. The aim of this study, therefore, is to analyse the use, purpose and effectiveness of parliamentary questions in the State Legislative Assembly of Uttar Pradesh (India) to explore differences, if any, between Ruling and Opposition parties. In this study, 4023 parliamentary questions asked in the Uttar Pradesh State Legislative Assembly were analysed. The effectiveness of answers was also analysed qualitatively. The results show that half of the total members of the Assembly used this device, out of which 60% of the questions were asked by the Opposition party members. 31% of the questions from the Opposition were seeking information and 69% were pressing for action. The government provided the required information in 96% of the questions in the former category and took action in only 35% of the latter category. Furthermore, 60% of the questions raised by the Opposition were related to constituency matters and the remaining 40% were related to policy issues or public welfare. Comparing the data with the ruling party, the results indicate that the use,purpose and effectiveness of parliamentary questions were similar to that of the Opposition except some minor differences. Surprisingly, there was no evidence of any ‘Dorothy Dix’ questions. The study concludes parliamentary question is an effective device in the Indian state of Uttar Pradesh.

Customers behaving badly : a state of the art review, research agenda and implications for practitioners

The purpose of this paper is to highlight important issues in the study of dysfunctional customer behavior and to provide a research agenda to inspire, guide, and enthuse. Through a critical evaluation of existing research, the aim is to highlight key issues and to present potentially worthy avenues for future study.

Unaided stereo vision based pose estimation

This paper presents the development of a low-cost sensor platform for use in ground-based visual pose estimation and scene mapping tasks. We seek to develop a technical solution using low-cost vision hardware that allows us to accurately estimate robot position for SLAM tasks. We present results from the application of a vision based pose estimation technique to simultaneously determine camera poses and scene structure. The results are generated from a dataset gathered traversing a local road at the St Lucia Campus of the University of Queensland. We show the accuracy of the pose estimation over a 1.6km trajectory in relation to GPS ground truth.

An evidence-based approach to professional development planning in large state educational systems

This paper presents a systems-level approach for adjudicating the prioritization, selection, and planning of inservcie professional development (PD) for teachers. We present a step-by-step model for documenting and assessing system-wide 'bids' for professional development programs

Vision only pose estimation and scene reconstruction on airborne platforms

We aim to demonstrate unaided visual 3D pose estimation and map reconstruction using both monocular and stereo vision techniques. To date, our work has focused on collecting data from Unmanned Aerial Vehicles, which generates a number of significant issues specific to the application. Such issues include scene reconstruction degeneracy from planar data, poor structure initialisation for monocular schemes and difficult 3D reconstruction due to high feature covariance. Most modern Visual Odometry (VO) and related SLAM systems make use of a number of sensors to inform pose and map generation, including laser range-finders, radar, inertial units and vision [1]. By fusing sensor inputs, the advantages and deficiencies of each sensor type can be handled in an efficient manner. However, many of these sensors are costly and each adds to the complexity of such robotic systems. With continual advances in the abilities, small size, passivity and low cost of visual sensors along with the dense, information rich data that they provide our research focuses on the use of unaided vision to generate pose estimates and maps from robotic platforms. We propose that highly accurate (�5cm) dense 3D reconstructions of large scale environments can be obtained in addition to the localisation of the platform described in other work [2]. Using images taken from cameras, our algorithm simultaneously generates an initial visual odometry estimate and scene reconstruction from visible features, then passes this estimate to a bundle-adjustment routine to optimise the solution. From this optimised scene structure and the original images, we aim to create a detailed, textured reconstruction of the scene. By applying such techniques to a unique airborne scenario, we hope to expose new robotic applications of SLAM techniques. The ability to obtain highly accurate 3D measurements of an environment at a low cost is critical in a number of agricultural and urban monitoring situations. We focus on cameras as such sensors are small, cheap and light-weight and can therefore be deployed in smaller aerial vehicles. This, coupled with the ability of small aerial vehicles to fly near to the ground in a controlled fashion, will assist in increasing the effective resolution of the reconstructed maps.