Waves for change : the role of the South Tarawa-based women's interests program in the decolonisation process of the Gilbert Islands

This thesis has created a space for women in the history of the decolonisation of the Gilbert Islands. It traces the historical development of the national women's interests program in the Republic of Kiribati (formerly of the Gilbert and Ellice Islands Colony (GEIC)) as it was implemented through a network of women's clubs during the 1960s and 1970s. This thesis has provided the first history and interpretation of the Indigenous women's interests movement as it impacted the Gilbert Islands. It offers a narrative of the movement in terms of three overlapping waves of women leaders, based on an analysis of fieldwork, archival research and interviews conducted on South Tarawa, Kiribati.

My Kitchen Rules pair are all the rage on social media – for now

The launch of the current series of My Kitchen Rules has undoubtedly been successful, both in terms of television ratings and in capturing a social media audience, clearly winning the battle for the Twitter audience on premiere night, and maintaining a lead over both The Block and The Biggest Loser since then. But it is the controversy surrounding Perth contestants Kelly Ramsay and Chloe James that has dominated media coverage today, detailing the abuse to which they have been subjected on social media.

An efficient proactive route maintenance process for reliable data transmissions in sensor networks

For industrial wireless sensor networks, maintaining the routing path for a high packet delivery ratio is one of the key objectives in network operations. It is important to both provide the high data delivery rate at the sink node and guarantee a timely delivery of the data packet at the sink node. Most proactive routing protocols for sensor networks are based on simple periodic updates to distribute the routing information. A faulty link causes packet loss and retransmission at the source until periodic route update packets are issued and the link has been identified as broken. We propose a new proactive route maintenance process where periodic update is backed-up with a secondary layer of local updates repeating with shorter periods for timely discovery of broken links. Proposed route maintenance scheme improves reliability of the network by decreasing the packet loss due to delayed identification of broken links. We show by simulation that proposed mechanism behaves better than the existing popular routing protocols (AODV, AOMDV and DSDV) in terms of end-to-end delay, routing overhead, packet reception ratio.

Professionalizing Business Process Management : towards a Body of Knowledge for BPM

Business Process Management (BPM) is rapidly evolving as an established discipline. There are a number of efforts underway to formalize the various aspects of BPM practice; creating a formal Body of Knowledge (BoK) is one such effort. Bodies of knowledge are artifacts that have a proven track record for accelerating the professionalization of various disciplines. In order for this to succeed in BPM, it is vital to involve the broader business process community and derive a BoK that has essential characteristics that addresses the discipline’s needs. We argue for the necessity of a comprehensive BoK for the BPM domain, and present a core list of essential features to consider when developing a BoK based on preliminary empirical evidence. The paper identifies and critiques existing Bodies of Knowledge related to BPM, and firmly calls for an effort to develop a more accurate and sustainable BoK for BPM. An approach for this effort is presented with preliminary outcomes.

Prioritizing process improvement : an example from the Australian financial services sector

Process improvement has become a number one business priority, and more and more project requests are raised in organizations, seeking approval and resources for process-related projects. Realistically, the total of the requested funds exceeds the allocated budget, the number of projects is higher than the available bandwidth, and only some of these (very often only few) can be supported and most never see any light. Relevant resources are scarce, and correct decisions must be made to make sure that those projects that are of best value are implemented. How can decision makers make the right decision on the following: Which project(s) are to be approved and when to commence work on them? Which projects are most aligned with corporate strategy? How can the project’s value to the business be calculated and explained? How can these decisions be made in a fair, justifiable manner that brings the best results to the company and its stakeholders? This chapter describes a business value scoring (BVS) model that was built, tested, and implemented by a leading financial institution in Australia to address these very questions. The chapter discusses the background and motivations for such an initiative and describes the tool in detail. All components and underlying concepts are explained, together with details on its application. This tool has been successfully implemented in the case organization. The chapter provides practical guidelines for organizations that wish to adopt this approach.

Burn healing is dependent on burn site : a quantitative analysis from a porcine burn model

This retrospective review examines healing in different sites on a porcine burn model; 24 pairs of burns on 18 pigs from other animal trials were selected for analysis. Each pair of burns was located on the either the cranial or the caudal part of the thoracic ribs region, on the same side of the animal. The burns were 40-50 cm(2) in size and of uniform deep-dermal partial thickness. Caudal burns healed significantly better than cranial burns, demonstrated by earlier closure of wounds, less scar formation and better cosmesis. To our knowledge, this is the first detailed study reporting that burn healing is affected by location on a porcine burn model. We recommend that similar symmetrical burns should be used for future comparative assessments of burn healing.

Major issues in business process management : an expert perspective

Study Approach The results presented in this report are part of a larger global study on the major issues in BPM. Only one part of the larger study is reported here, viz. interviews with BPM experts. Interviews of BPM tool vendors together with focus group studies involving user organizations were conducted in parallel and set the groundwork for the identification of BPM issues on a global scale. Through this multi-method approach, we identify four distinct sets of outcomes. First, as is the focus of this report, we identify the BPM issues as perceived by BPM experts. Second, the research design allows us to gain insight into the opinions of organizations deploying BPM solutions. Third, an understanding of organizations’ misconceptions of BPM technologies, as confronted by BPM tool vendors, is obtained. Last, we seek to gain an understanding of BPM issues on a global scale, together with knowledge of matters of concern. This final outcome is aimed to produce an industry-driven research agenda that will inform practitioners and, in particular, the research community worldwide on issues and challenges that are prevalent or emerging in BPM and related areas...

What are the secrets of successful process modelling? Insights from an Australian case study

L'intérêt suscité par la ré-ingénierie des processus et les technologies de l'information révèle l'émergence du paradigme du management par les processus. Bien que beaucoup d'études aient été publiées sur des outils et techniques alternatives de modélisation de processus, peu d'attention a été portée à l'évaluation post-hoc des activités de modélisation de processus ou à l'établissement de directives sur la façon de conduire efficacement une modélisation de processus. La présente étude a pour objectif de combler ce manque. Nous présentons les résultats d'une étude de cas détaillée, conduite dans une organisation leader australienne dans le but de construire un modèle de réussite de la modélisation des processus.

Expertise in Business Process Management

As organizations attempt to become more business process-oriented, existing role descriptions are revised and entire new business process-related roles emerge. A lot of attention is often being paid to the technological aspect of Business Process Management (BPM), but relatively little work has been done concerning the people factor of BPM and the specification of BPM expertise in particular. This study tries to close this gap by proposing a comprehensive BPM expertise model, which consolidates existing theories and related work. This model describes the key attributes characterizing “BPM expertise” and outlines their structure, dynamics, and interrelationships. Understanding BPM expertise is a predecessor to being able to develop and apply it effectively. This is the cornerstone of human capital and talent management in BPM.

Business process mining success

Process mining has developed into a popular research discipline and nowadays its associated techniques are widely applied in practice. What is currently ill-understood is how the success of a process mining project can be measured and what the antecedent factors of process mining success are. We consider an improved, grounded understanding of these aspects of value to better manage the effectiveness and efficiency of process mining projects in practice. As such, we advance a model, tailored to the characteristics of process mining projects, which identifies and relates success factors and measures. We draw inspiration from the literature from related fields for the construction of a theoretical, a priori model. That model has been validated and re-specified on the basis of a multiple case study, which involved four industrial process mining projects. The unique contribution of this paper is that it presents the first set of success factors and measures on the basis of an analysis of real process mining projects. The presented model can also serve as a basis for further extension and refinement using insights from additional analyses.

Comparing methods for modelling spreading cell fronts

Spreading cell fronts play an essential role in many physiological processes. Classically, models of this process are based on the Fisher-Kolmogorov equation; however, such continuum representations are not always suitable as they do not explicitly represent behaviour at the level of individual cells. Additionally, many models examine only the large time asymptotic behaviour, where a travelling wave front with a constant speed has been established. Many experiments, such as a scratch assay, never display this asymptotic behaviour, and in these cases the transient behaviour must be taken into account. We examine the transient and asymptotic behaviour of moving cell fronts using techniques that go beyond the continuum approximation via a volume-excluding birth-migration process on a regular one-dimensional lattice. We approximate the averaged discrete results using three methods: (i) mean-field, (ii) pair-wise, and (iii) one-hole approximations. We discuss the performace of these methods, in comparison to the averaged discrete results, for a range of parameter space, examining both the transient and asymptotic behaviours. The one-hole approximation, based on techniques from statistical physics, is not capable of predicting transient behaviour but provides excellent agreement with the asymptotic behaviour of the averaged discrete results, provided that cells are proliferating fast enough relative to their rate of migration. The mean-field and pair-wise approximations give indistinguishable asymptotic results, which agree with the averaged discrete results when cells are migrating much more rapidly than they are proliferating. The pair-wise approximation performs better in the transient region than does the mean-field, despite having the same asymptotic behaviour. Our results show that each approximation only works in specific situations, thus we must be careful to use a suitable approximation for a given system, otherwise inaccurate predictions could be made.

Laser-radar data fusion with Gaussian Process Implicit Surfaces

This work considers the problem of building high-fidelity 3D representations of the environment from sensor data acquired by mobile robots. Multi-sensor data fusion allows for more complete and accurate representations, and for more reliable perception, especially when different sensing modalities are used. In this paper, we propose a thorough experimental analysis of the performance of 3D surface reconstruction from laser and mm-wave radar data using Gaussian Process Implicit Surfaces (GPIS), in a realistic field robotics scenario. We first analyse the performance of GPIS using raw laser data alone and raw radar data alone, respectively, with different choices of covariance matrices and different resolutions of the input data. We then evaluate and compare the performance of two different GPIS fusion approaches. The first, state-of-the-art approach directly fuses raw data from laser and radar. The alternative approach proposed in this paper first computes an initial estimate of the surface from each single source of data, and then fuses these two estimates. We show that this method outperforms the state of the art, especially in situations where the sensors react differently to the targets they perceive.

Traversability estimation for a planetary rover via experimental kernel learning in a Gaussian process framework

A critical requirement for safe autonomous navigation of a planetary rover is the ability to accurately estimate the traversability of the terrain. This work considers the problem of predicting the attitude and configuration angles of the platform from terrain representations that are often incomplete due to occlusions and sensor limitations. Using Gaussian Processes (GP) and exteroceptive data as training input, we can provide a continuous and complete representation of terrain traversability, with uncertainty in the output estimates. In this paper, we propose a novel method that focuses on exploiting the explicit correlation in vehicle attitude and configuration during operation by learning a kernel function from vehicle experience to perform GP regression. We provide an extensive experimental validation of the proposed method on a planetary rover. We show significant improvement in the accuracy of our estimation compared with results obtained using standard kernels (Squared Exponential and Neural Network), and compared to traversability estimation made over terrain models built using state-of-the-art GP techniques.

Laser-camera data discrepancies and reliable perception in outdoor robotics

This work aims to promote integrity in autonomous perceptual systems, with a focus on outdoor unmanned ground vehicles equipped with a camera and a 2D laser range finder. A method to check for inconsistencies between the data provided by these two heterogeneous sensors is proposed and discussed. First, uncertainties in the estimated transformation between the laser and camera frames are evaluated and propagated up to the projection of the laser points onto the image. Then, for each pair of laser scan-camera image acquired, the information at corners of the laser scan is compared with the content of the image, resulting in a likelihood of correspondence. The result of this process is then used to validate segments of the laser scan that are found to be consistent with the image, while inconsistent segments are rejected. Experimental results illustrate how this technique can improve the reliability of perception in challenging environmental conditions, such as in the presence of airborne dust.

Process modelling and simulation of tissue damage during mechanical peeling of pumpkin as a tough skinned vegetable

Food waste is a current challenge that both developing and developed countries face. This project applied a novel combination of available methods in Mechanical, agricultural and food engineering to address these challenges. A systematic approach was devised to investigate possibilities of reducing food waste and increasing the efficiency of industry by applying engineering concepts and theories including experimental, mathematical and computational modelling methods. This study highlights the impact of comprehensive understanding of agricultural and food material response to the mechanical operations and its direct relation to the volume of food wasted globally.