Modeling videokeratoscopic height data with spherical harmonics

Purpose: All currently considered parametric models used for decomposing videokeratoscopy height data are viewercentered and hence describe what the operator sees rather than what the surface is. The purpose of this study was to ascertain the applicability of an object-centered representation to modeling of corneal surfaces. Methods: A three-dimensional surface decomposition into a series of spherical harmonics is considered and compared with the traditional Zernike polynomial expansion for a range of videokeratoscopic height data. Results: Spherical harmonic decomposition led to significantly better fits to corneal surfaces (in terms of the root mean square error values) than the corresponding Zernike polynomial expansions with the same number of coefficients, for all considered corneal surfaces, corneal diameters, and model orders. Conclusions: Spherical harmonic decomposition is a viable alternative to Zernike polynomial decomposition. It achieves better fits to videokeratoscopic height data and has the advantage of an object-centered representation that could be particularly suited to the analysis of multiple corneal measurements.

Section 46(1) and 46(1AA) of the TPA : the struggle of the small against the large

The purpose of this article is to highlight the conflict in the policy objectives of subs 46(1) and subs 46(1AA) of the Trade Practices Act 1974 (Cth) (TPA). The policy objective of subs 46(1) is to promote competition and efficient markets for the benefit of consumers (consumer welfare standard). It does not prohibit corporations with substantial market power using cost savings arising from efficiencies such economies of scale or scope, to undercut small business competitors The policy objective of 46(1AA), on the other hand, is to protect small business operators from price discounting by their larger competitors.. Unlike subs 46(1), it does not contain a ‘taking advantage’ element. It is argued that subs 46(1AA) may harm consumer welfare by having a chilling effect on price competition if this would harm small business competitors.

Communication of business process models via virtual environment simulations

Games and related virtual environments have been a much-hyped area of the entertainment industry. The classic quote is that games are now approaching the size of Hollywood box office sales [1]. Books are now appearing that talk up the influence of games on business [2], and it is one of the key drivers of present hardware development. Some of this 3D technology is now embedded right down at the operating system level via the Windows Presentation Foundations – hit Windows/Tab on your Vista box to find out... In addition to this continued growth in the area of games, there are a number of factors that impact its development in the business community. Firstly, the average age of gamers is approaching the mid thirties. Therefore, a number of people who are in management positions in large enterprises are experienced in using 3D entertainment environments. Secondly, due to the pressure of demand for more computational power in both CPU and Graphical Processing Units (GPUs), your average desktop, any decent laptop, can run a game or virtual environment. In fact, the demonstrations at the end of this paper were developed at the Queensland University of Technology (QUT) on a standard Software Operating Environment, with an Intel Dual Core CPU and basic Intel graphics option. What this means is that the potential exists for the easy uptake of such technology due to 1. a broad range of workers being regularly exposed to 3D virtual environment software via games; 2. present desktop computing power now strong enough to potentially roll out a virtual environment solution across an entire enterprise. We believe such visual simulation environments can have a great impact in the area of business process modeling. Accordingly, in this article we will outline the communication capabilities of such environments, giving fantastic possibilities for business process modeling applications, where enterprises need to create, manage, and improve their business processes, and then communicate their processes to stakeholders, both process and non-process cognizant. The article then concludes with a demonstration of the work we are doing in this area at QUT.

The measurement of perceived ontological deficiencies of conceptual modeling grammars

Over recent years, many scholars have studied the conceptual modeling of information systems based on a theory of ontological expressiveness. This theory offers four constructs that inform properties of modeling grammars in the form of ontological deficiencies, and their implications for development and use of conceptual modeling in IS practice. In this paper we report on the development of a valid and reliable instrument for measuring the perceptions that individuals have of the ontological deficiencies of conceptual modeling grammars. We describe a multi-stage approach for instrument development that incorporates feedback from expert and user panels. We also report on a field test of the instrument with 590 modeling practitioners. We further study how different levels of modeling experience influence user perceptions of ontological deficiencies of modeling grammars. We provide implications for practice and future research.

Modeling corneal surfaces with three-dimensional basis functions

Purpose: To ascertain the effectiveness of object-centered three-dimensional representations for the modeling of corneal surfaces. Methods: Three-dimensional (3D) surface decomposition into series of basis functions including: (i) spherical harmonics, (ii) hemispherical harmonics, and (iii) 3D Zernike polynomials were considered and compared to the traditional viewer-centered representation of two-dimensional (2D) Zernike polynomial expansion for a range of retrospective videokeratoscopic height data from three clinical groups. The data were collected using the Medmont E300 videokeratoscope. The groups included 10 normal corneas with corneal astigmatism less than −0.75 D, 10 astigmatic corneas with corneal astigmatism between −1.07 D and 3.34 D (Mean = −1.83 D, SD = ±0.75 D), and 10 keratoconic corneas. Only data from the right eyes of the subjects were considered. Results: All object-centered decompositions led to significantly better fits to corneal surfaces (in terms of the RMS error values) than the corresponding 2D Zernike polynomial expansions with the same number of coefficients, for all considered corneal surfaces, corneal diameters (2, 4, 6, and 8 mm), and model orders (4th to 10th radial orders) The best results (smallest RMS fit error) were obtained with spherical harmonics decomposition which lead to about 22% reduction in the RMS fit error, as compared to the traditional 2D Zernike polynomials. Hemispherical harmonics and the 3D Zernike polynomials reduced the RMS fit error by about 15% and 12%, respectively. Larger reduction in RMS fit error was achieved for smaller corneral diameters and lower order fits. Conclusions: Object-centered 3D decompositions provide viable alternatives to traditional viewer-centered 2D Zernike polynomial expansion of a corneal surface. They achieve better fits to videokeratoscopic height data and could be particularly suited to the analysis of multiple corneal measurements, where there can be slight variations in the position of the cornea from one map acquisition to the next.

Why adopt now? Multiple case studies and survey studies comparing small, medium and large firms

While a number of factors have been highlighted in the innovation adoption literature, little is known about the key triggers of innovation adoption across differently-sized firms. This study compares case studies of small, medium and large manufacturing firms who recently decided to adopt a process innovation. We also employ organizational surveys from 134 firms investigating the factors which influence innovation adoption. The quantitative results support the qualitative findings that the external pressures are a trigger among small to medium firms, while the larger firm’s adoption was associated with internal causes.

Addressing issues in sparseness, ecological bias and formulation of the adjacency matrix in Bayesian spatio-temporal analysis of disease counts

The main objective of this PhD was to further develop Bayesian spatio-temporal models (specifically the Conditional Autoregressive (CAR) class of models), for the analysis of sparse disease outcomes such as birth defects. The motivation for the thesis arose from problems encountered when analyzing a large birth defect registry in New South Wales. The specific components and related research objectives of the thesis were developed from gaps in the literature on current formulations of the CAR model, and health service planning requirements. Data from a large probabilistically-linked database from 1990 to 2004, consisting of fields from two separate registries: the Birth Defect Registry (BDR) and Midwives Data Collection (MDC) were used in the analyses in this thesis. The main objective was split into smaller goals. The first goal was to determine how the specification of the neighbourhood weight matrix will affect the smoothing properties of the CAR model, and this is the focus of chapter 6. Secondly, I hoped to evaluate the usefulness of incorporating a zero-inflated Poisson (ZIP) component as well as a shared-component model in terms of modeling a sparse outcome, and this is carried out in chapter 7. The third goal was to identify optimal sampling and sample size schemes designed to select individual level data for a hybrid ecological spatial model, and this is done in chapter 8. Finally, I wanted to put together the earlier improvements to the CAR model, and along with demographic projections, provide forecasts for birth defects at the SLA level. Chapter 9 describes how this is done. For the first objective, I examined a series of neighbourhood weight matrices, and showed how smoothing the relative risk estimates according to similarity by an important covariate (i.e. maternal age) helped improve the model’s ability to recover the underlying risk, as compared to the traditional adjacency (specifically the Queen) method of applying weights. Next, to address the sparseness and excess zeros commonly encountered in the analysis of rare outcomes such as birth defects, I compared a few models, including an extension of the usual Poisson model to encompass excess zeros in the data. This was achieved via a mixture model, which also encompassed the shared component model to improve on the estimation of sparse counts through borrowing strength across a shared component (e.g. latent risk factor/s) with the referent outcome (caesarean section was used in this example). Using the Deviance Information Criteria (DIC), I showed how the proposed model performed better than the usual models, but only when both outcomes shared a strong spatial correlation. The next objective involved identifying the optimal sampling and sample size strategy for incorporating individual-level data with areal covariates in a hybrid study design. I performed extensive simulation studies, evaluating thirteen different sampling schemes along with variations in sample size. This was done in the context of an ecological regression model that incorporated spatial correlation in the outcomes, as well as accommodating both individual and areal measures of covariates. Using the Average Mean Squared Error (AMSE), I showed how a simple random sample of 20% of the SLAs, followed by selecting all cases in the SLAs chosen, along with an equal number of controls, provided the lowest AMSE. The final objective involved combining the improved spatio-temporal CAR model with population (i.e. women) forecasts, to provide 30-year annual estimates of birth defects at the Statistical Local Area (SLA) level in New South Wales, Australia. The projections were illustrated using sixteen different SLAs, representing the various areal measures of socio-economic status and remoteness. A sensitivity analysis of the assumptions used in the projection was also undertaken. By the end of the thesis, I will show how challenges in the spatial analysis of rare diseases such as birth defects can be addressed, by specifically formulating the neighbourhood weight matrix to smooth according to a key covariate (i.e. maternal age), incorporating a ZIP component to model excess zeros in outcomes and borrowing strength from a referent outcome (i.e. caesarean counts). An efficient strategy to sample individual-level data and sample size considerations for rare disease will also be presented. Finally, projections in birth defect categories at the SLA level will be made.

Benefits of collaborative ICT adoption for building project management

Purpose : Effective flow of data and communication at every stage of a construction project is essential for achieving required coordination and collaboration between the project participants, leading to successful management of the projects. In present scenario, when project participants are geographically separated, adoption of information communication technology (ICT) enables such effective communication. Thus, the purpose of this paper is to focus on ICT adoption for building project management.---------- Design/methodology/approach : It is difficult to quantitatively evaluate the benefits of ICT adoption in the multiple enterprise scenario of building project management. It requires qualitative analysis based on the perceptions of the construction professionals. The paper utilizes interpretive structural modeling (ISM) technique to assess importance of perceived benefits and their driving power and dependence on other benefits.---------- Findings : The developed ISM model shows that all the categories of benefits, i.e. benefits related to projects, team management, technology, and organization are inter-related and cannot be achieved in isolation. But, organization- and technology-related benefits have high-driving power and these are “strategic benefits” for the project team organizations. Thus, organizations are required to give more attention on strategically increasing these benefits from application of ICT. Originality/value – This analysis provides a road map to managers or project management organizations to decide that if they are planning ICT adoption for achieving certain benefits then which are the other driving benefits that should be achieved prior to that and also which are the dependent benefits that would be achieved by default.

Framework and processes for enhancing sustainability deliverables in Australian road infrastructure projects

Road and highway infrastructure provides the backbone for a nation’s economic growth. The versatile dispersion of population in Australia and its resource boom, coupled with improved living standards and growing societal expectations, calls for continuing development and improvement of road infrastructure under the current local, state and federal governments’ policies and strategic plans. As road infrastructure projects involve huge resources and mechanisms, achieving sustainability not only on economic scales but also through environmental and social responsibility becomes a crucial issue. While sustainability is a logical link to infrastructure development, literature study and consultation with the industry found that there is a lack of common understanding on what constitutes sustainability in the infrastructure context. Its priorities are often interpreted differently among multiple stakeholders. For road infrastructure projects which typically span over long periods of time, achieving tangible sustainability outcomes during the lifecycle of development remains a formidable task. Sustainable development initiatives often remain ideological as in macro-level policies and broad-based concepts. There were little elaboration and exemplar cases on how these policies and concepts can be translated into practical decision-making during project implementation. In contrast, there seemed to be over commitment on research and development of sustainability assessment methods and tools. Between the two positions, there is a perception-reality gap and mismatch, specifically on how to enhance sustainability deliverables during infrastructure project delivery. Review on past research in this industry sector also found that little has been done to promote sustainable road infrastructure development; this has wide and varied potential impacts. This research identified the common perceptions and expectations by different stakeholders towards achieving sustainability in road and highway infrastructure projects. Face to face interviews on selected representatives of these stakeholders were carried out in order to select and categorize, confirm and prioritize a list of sustainability performance targets identified through literature and past research. A Delphi study was conducted with the assistance of a panel of senior industry professionals and academic experts, which further considered the interrelationship and influence of the sustainability indicators, and identified critical sustainability indicators under ten critical sustainability criteria (e.g. Environmental, Health & Safety, Resource Utilization & Management, Social & Cultural, Economic, Public Governance & Community Engagement, Relations Management, Engineering, Institutional and Project Management). This presented critical sustainability issues that needed to be addressed at the project level. Accordingly, exemplar highway development projects were used as case studies to elicit solutions for the critical issues. Through the identification and integration of different perceptions and priority needs of the stakeholders, as well as key sustainability indicators and solutions for critical issues, a set of decision-making guidelines was developed to promote and drive consistent sustainability deliverables in road infrastructure projects.

Motivating construction organisations through incentives : a case study for client-side project managers

Client-side project managers face challenges in motivating project organisations to pursue exceptional design and construction performance. One approach to improving the motivation of project organisations is by offering a financial incentive reward for the achievement of voluntary performance standards above the minimum required standard. However, little investigation has been undertaken into the features of a successful incentive system as a part of an overall procurement strategy. In response to a lack of information available to client-side project managers tasked with the initial design of an incentive system, the paper explores motivation under a successful incentive and identifies key learnings for client-side project managers to consider when designing incentives. Our findings are based on the results of a large Australian case study which is interpreted against a conceptual framework based on both economic and psychological perspectives of motivation. The results suggest that motivation towards incentive goals is influenced by the value the project organisations place on the incentive reward as a commercial opportunity to increase their profit margins. However, perhaps more important are the relationship management processes that promote commitment to the project; and pride in the achievement of project goals. In the case study, these processes intensified the direct motivational effect of the incentive reward on offer. The findings also highlight the importance of ensuring that incentive goals and performance measurement processes remain relevant to the organisations throughout a project to continuously encourage motivation under changing project conditions.

Engaging students in large classes using Elluminate

The advancement of online teaching environments during the past several years presents an exciting opportunity to extend existing teaching methodologies. The software package known as Elluminate is one example of a virtual classroom, facilitating the provision of real time interaction, collaboration and group meetings. This paper will examine the use of Elluminate in the teaching of large classes. The use of such technology for large classes is of particular interest, as large classes are often, unfairly, associated with a reputation for being impersonal as well as notions of conveyor belt learning. In this paper the potential to extend teaching and learning opportunities using Elluminate, in the context of large classes, will be explored. It will be shown that the use of technology such as Elluminate can assist in providing students with a more flexible means of accessing academic support, as well as allowing for a customised delivery of course content so as to focus learning outcomes.

Collaborative business process modeling using 3D virtual environments

Process modeling is a complex organizational task that requires many iterations and communication between the business analysts and the domain specialists involved in the process modeling. The challenge of process modeling is exacerbated, when the process of modeling has to be performed in a cross-organizational, distributed environment. Some systems have been developed to support collaborative process modeling, all of which use traditional 2D interfaces. We present an environment for collaborative process modeling, using 3D virtual environment technology. We make use of avatar instantiations of user ego centres, to allow for the spatial embodiment of the user with reference to the process model. We describe an innovative prototype collaborative process modeling approach, implemented as a modeling environment in Second Life. This approach leverages the use of virtual environments to provide user context for editing and collaborative exercises. We present a positive preliminary report on a case study, in which a test group modelled a business process using the system in Second Life.

On the usage of labels and icons in business process modeling

The value of business process models is dependent not only on the choice of graphical elements in the model, but also on their annotation with additional textual and graphical information. This research discusses the use of text and icons for labeling the graphical constructs in a process model. We use two established verb classification schemes to examine the choice of activity labels in process modeling practice. Based on our findings, we synthesize a set of twenty-five activity label categories. We propose a systematic approach for graphically representing these label categories through the use of graphical icons, such that the resulting process models are easier and more readily understandable by end users. Our findings contribute to an ongoing stream of research investigating the practice of process modeling and thereby contribute to the body of knowledge about conceptual modeling quality overall.

Modeling multivariate autoregressive conditional heteroskedasticity with the double smooth transition conditional correlation GARCH Model

In this paper, we propose a multivariate GARCH model with a time-varying conditional correlation structure. The new double smooth transition conditional correlation (DSTCC) GARCH model extends the smooth transition conditional correlation (STCC) GARCH model of Silvennoinen and Teräsvirta (2005) by including another variable according to which the correlations change smoothly between states of constant correlations. A Lagrange multiplier test is derived to test the constancy of correlations against the DSTCC-GARCH model, and another one to test for another transition in the STCC-GARCH framework. In addition, other specification tests, with the aim of aiding the model building procedure, are considered. Analytical expressions for the test statistics and the required derivatives are provided. Applying the model to the stock and bond futures data, we discover that the correlation pattern between them has dramatically changed around the turn of the century. The model is also applied to a selection of world stock indices, and we find evidence for an increasing degree of integration in the capital markets.