Human resource behaviour simulation in business processes

The structure and dynamics of a modern business environment are very hard to model using traditional methods. Such complexity raises challenges to effective business analysis and improvement. The importance of applying business process simulation to analyze and improve business activities has been widely recognized. However, one remaining challenge is the development of approaches to human resource behavior simulation. To address this problem, we describe a novel simulation approach where intelligent agents are used to simulate human resources by performing allocated work from a workflow management system. The behavior of the intelligent agents is driven a by state transition mechanism called a Hierarchical Task Network (HTN). We demonstrate and validate our simulator via a medical treatment process case study. Analysis of the simulation results shows that the behavior driven by the HTN is consistent with design of the workflow model. We believe these preliminary results support the development of more sophisticated agent-based human resource simulation systems.

Investigation of stereotactic radiotherapy dose using dosimetry film and Monte Carlo simulations

This study uses dosimetry film measurements and Monte Carlo simulations to investigate the accuracy of type-a (pencil-beam) dose calculations for predicting the radiation doses delivered during stereotactic radiotherapy treatments of the brain. It is shown that when evaluating doses in a water phantom, the type-a algorithm provides dose predictions which are accurate to within clinically relevant criteria, gamma(3%,3mm), but these predictions are nonetheless subtly different from the results of evaluating doses from the same fields using radiochromic film and Monte Carlo simulations. An analysis of a clinical meningioma treatment suggests that when predicting stereotactic radiotherapy doses to the brain, the inaccuracies of the type-a algorithm can be exacerbated by inadequate evaluation of the effects of nearby bone or air, resulting in dose differences of up to 10% for individual fields. The results of this study indicate the possible advantage of using Monte Carlo calculations, as well as measurements with high-spatial resolution media, to verify type-a predictions of dose delivered in cranial treatments.

The politics of technology adoption : Water metering in Progressive Era Chicago

This paper examines the interactions between knowledge and power in the adoption of technologies central to municipal water supply plans, specifically investigating decisions in Progressive Era Chicago regarding water meters. The invention and introduction into use of the reliable water meter early in the Progressive Era allowed planners and engineers to gauge water use, and enabled communities willing to invest in the new infrastructure to allocate costs for provision of supply to consumers relative to use. In an era where efficiency was so prized and the role of technocratic expertise was increasing, Chicago’s continued failure to adopt metering (despite levels of per capita consumption nearly twice that of comparable cities and acknowledged levels of waste nearing half of system production) may indicate that the underlying characteristics of the city’s political system and its elite stymied the implementation of metering technologies as in Smith’s (1977) comparative study of nineteenth century armories. Perhaps, as with Flyvbjerg’s (1998) study of the city of Aalborg, the powerful know what they want and data will not interfere with their conclusions: if the data point to a solution other than what is desired, then it must be that the data are wrong. Alternatively, perhaps the technocrats failed adequately to communicate their findings in a language which the political elite could understand, with the failure lying in assumptions of scientific or technical literacy rather than with dissatisfaction in outcomes (Benveniste 1972). When examined through a historical institutionalist perspective, the case study of metering adoption lends itself to exploration of larger issues of knowledge and power in the planning process: what governs decisions regarding knowledge acquisition, how knowledge and power interact, whether the potential to improve knowledge leads to changes in action, and, whether the decision to overlook available knowledge has an impact on future decisions.

Interactive image manipulation for surgical planning

The Australian e-Health Research Centre in collaboration with the Queensland University of Technology's Paediatric Spine Research Group is developing software for visualisation and manipulation of large three-dimensional (3D) medical image data sets. The software allows the extraction of anatomical data from individual patients for use in preoperative planning. State-of-the-art computer technology makes it possible to slice through the image dataset at any angle, or manipulate 3D representations of the data instantly. Although the software was initially developed to support planning for scoliosis surgery, it can be applied to any dataset whether obtained from computed tomography, magnetic resonance imaging or any other imaging modality.

Optical non-destructive evaluation of articular cartilage integrity : a review

This paper reviews the current status of the application of optical non-destructive methods, particularly infrared (IR) and near infrared (NIR), in the evaluation of the physiological integrity of articular cartilage. It is concluded that a significant amount of work is still required in order to achieve specificity and clinical applicability of these methods in the assessment and treatment of dysfunctional articular joints.

Defining and mapping teacher practice in technology classrooms

The indecision surrounding the definition of Technology extends to the classroom as not knowing what a subject “is” affects how it is taught. Similarly, its relative newness – and consequent lack of habitus in school settings - means that it is still struggling to find its own place in the curriculum as well as resolve its relationship with more established subject domains, particularly Science and Mathematics. The guidance from syllabus documents points to open-ended student-directed projects where extant studies indicate a more common experience of teacher –directed activities and an emphasis on product over process. There are issues too for researchers in documenting classroom observations and in analysing teacher practice in new learning environments. This paper presents a framework for defining and mapping classroom practice and for attempting to describe the social practice in the Technology classroom. The framework is a bricolage which draws on contemporary research. More formally, the development of the framework is consonant with the aim of design-based research to develop a flexible, adaptive and generalisable theory to better understanding a teaching domain where promise is not seen to match current reality. The framework may also inform emergent approaches to STEM (Science, Technology, Education and Mathematics) in education.

Designing disruption : linking participatory design and design thinking in technology orientated industries

A vast proportion of companies nowadays are looking to design and are focusing on the end users as a means of driving new projects. However still many companies are drawn to technological improvements which drive innovation within their industry context. The Australian livestock industry is no different. To date the adoption of new products and services within the livestock industry has been documented as being quite slow. This paper investigates how disruptive innovation should be a priority for these technologically focused companies and demonstrates how the use of design led innovation can bring about a higher quality engagement between end user and company alike. A case study linking participatory design and design thinking is presented. Within this, a conceptual model of presenting future scenarios to internal and external stakeholders is applied to the livestock industry; assisting companies to apply strategy, culture and advancement in meaningful product offerings to consumers.

Probability distributed time delays: integrating spatial effects into temporal models

Background In order to provide insights into the complex biochemical processes inside a cell, modelling approaches must find a balance between achieving an adequate representation of the physical phenomena and keeping the associated computational cost within reasonable limits. This issue is particularly stressed when spatial inhomogeneities have a significant effect on system's behaviour. In such cases, a spatially-resolved stochastic method can better portray the biological reality, but the corresponding computer simulations can in turn be prohibitively expensive. Results We present a method that incorporates spatial information by means of tailored, probability distributed time-delays. These distributions can be directly obtained by single in silico or a suitable set of in vitro experiments and are subsequently fed into a delay stochastic simulation algorithm (DSSA), achieving a good compromise between computational costs and a much more accurate representation of spatial processes such as molecular diffusion and translocation between cell compartments. Additionally, we present a novel alternative approach based on delay differential equations (DDE) that can be used in scenarios of high molecular concentrations and low noise propagation. Conclusions Our proposed methodologies accurately capture and incorporate certain spatial processes into temporal stochastic and deterministic simulations, increasing their accuracy at low computational costs. This is of particular importance given that time spans of cellular processes are generally larger (possibly by several orders of magnitude) than those achievable by current spatially-resolved stochastic simulators. Hence, our methodology allows users to explore cellular scenarios under the effects of diffusion and stochasticity in time spans that were, until now, simply unfeasible. Our methodologies are supported by theoretical considerations on the different modelling regimes, i.e. spatial vs. delay-temporal, as indicated by the corresponding Master Equations and presented elsewhere.

Making sense of dementia : understanding amongst indigenous Australians

Dementia is a growing health and social concern for all Australians. Whilst the prevalence of dementia amongst Australia's indigenous people is unclear, there is some evidence that dementia rates are five times that of the general Australian population. To date no studies have examined dementia knowledge levels in indigenous communities. Purpose of the study: This paper aims to explore indigenous Australians' understanding, knowledge and misconceptions of dementia. Design and methods: Hundered and seventy-four indigenous adults participated in a cross-sectional survey using a modified version of the Alzheimer's Disease Knowledge Test (ADK). The survey included demographic information, two open-ended questions and 20 multiple choice questions. Each ADK item was examined to identify responses that revealed commonly held correct beliefs, knowledge gaps and misconceptions. Results: The overall level of understanding of dementia was poor. Younger participants were significantly more likely to have no knowledge of Alzheimer's Disease, whereas the other age groups were most likely to have at least some knowledge. It was also revealed that there are common misconceptions about Alzheimer's Disease held by both indigenous and non-indigenous communities. Implications: Culturally appropriate awareness campaigns and targeted educational interventions need to be implemented to improve the general level of understanding of dementia in indigenous communities.

A Bayesian approach to assess interaction between known risk factors: The risk of lung cancer from exposure to asbestos and smoking

We review the literature on the combined effect of asbestos exposure and smoking on lung cancer, and explore a Bayesian approach to assess evidence of interaction. Previous approaches have focussed on separate tests for an additive or multiplicative relation. We extend these approaches by exploring the strength of evidence for either relation using approaches which allow the data to choose between both models. We then compare the different approaches.