The adoption of advanced quality practices and its impact on manufacturers

Presently, the manufacturing sector faces unprecedented levels of competition in both the domestic and international markets. This competition is mainly as a result of rapidly expanding international trade, gradual removal of protection, substantial reforms in labour markets and industrial relations, rapid technological changes and discerning customers. Intense global competition requires manufacturers to deliver products with higher quality in a shorter time. Simultaneously, owing to new technological innovations, the complexity of the products is increasing. In Australia, the impact of this intense competition and structural changes appear to be having negative effects on the manufacturing sector. This paper discusses the quality and reliability (Q & R) practices and associated drawbacks of Australian manufacturers and presents the findings of an investigation of the challenges Australian manufacturers are currently facing. The results reported in the paper are based on the data collected from a survey using the standard questionnaire. The study was driven by a conceptual model, which relates advanced quality practices to manufacturing performance and manufacturing difficulties.Evidence indicates that Q & R is the main competitive factor for Australian manufacturers. Design capability and on time delivery (OTD) came second. Results show that Australian manufacturers in general are facing some manufacturing difficulties. The relationship between advanced quality practices and company performance and manufacturing difficulties are explored. It is found that the companies who have more emphasis on advanced quality practices have fewer problems in manufacturing practices. Moreover, companies who have actively implemented the advanced quality practices have managed to improve the quality of the product continuously. The results validate the proposed hypothesis and lend credence to current thinking that improvement in Q & R is a vital tool for competitive advantage.

The Bayesian conditional independence model for measurement error: applications in ecology

The measurement error model is a well established statistical method for regression problems in medical sciences, although rarely used in ecological studies. While the situations in which it is appropriate may be less common in ecology, there are instances in which there may be benefits in its use for prediction and estimation of parameters of interest. We have chosen to explore this topic using a conditional independence model in a Bayesian framework using a Gibbs sampler, as this gives a great deal of flexibility, allowing us to analyse a number of different models without losing generality. Using simulations and two examples, we show how the conditional independence model can be used in ecology, and when it is appropriate.

Towards a CRM and SCM Benefits Measurement Model

Organizations invest heavily in Customer Relationship Management (CRM) and Supply Chain Management (SCM) systems, and their related infrastructure, presumably expecting positive benefits to the organization. Assessing the benefits of such systems is an important aspect of managing such systems. Given the substantial differences between CRM and SCM systems with traditional intra-organizational applications, existing Information Systems benefits measurement models and frameworks are ill-suited to gauge CRM and SCM benefits. This paper reports the preliminary findings of a research that seeks to develop a measurement model to assess benefits of CRM and SCM applications. The a-priori benefits measurement model is developed reviewing the 55 academic studies and 40 practitioner papers. The review of related literature yielded 606 benefits, which were later synthesized into 74 mutually exclusive benefit measures of CRM and SCM applications arranged under five dimensions.

The rademacher complexity of coregularized kernel classes

In the multi-view approach to semisupervised learning, we choose one predictor from each of multiple hypothesis classes, and we co-regularize our choices by penalizing disagreement among the predictors on the unlabeled data. We examine the co-regularization method used in the co-regularized least squares (CoRLS) algorithm, in which the views are reproducing kernel Hilbert spaces (RKHS's), and the disagreement penalty is the average squared difference in predictions. The final predictor is the pointwise average of the predictors from each view. We call the set of predictors that can result from this procedure the co-regularized hypothesis class. Our main result is a tight bound on the Rademacher complexity of the co-regularized hypothesis class in terms of the kernel matrices of each RKHS. We find that the co-regularization reduces the Rademacher complexity by an amount that depends on the distance between the two views, as measured by a data dependent metric. We then use standard techniques to bound the gap between training error and test error for the CoRLS algorithm. Experimentally, we find that the amount of reduction in complexity introduced by co regularization correlates with the amount of improvement that co-regularization gives in the CoRLS algorithm.

Theorising a model for teaching and assessing reflective learning in higher education

The importance of reflection in higher education, and across disciplinary fields is widely recognised; it is generally included in university graduate attributes, professional standards and program objectives. Furthermore, reflection is commonly embedded into assessment requirements in higher education subjects, often without necessary scaffolding or clear expectations for students. Despite the rhetoric around the importance of reflection for ongoing learning, there is scant literature on any systematic, developmental approach to teaching reflective learning across higher education programs/courses. Given that professional or academic reflection is not intuitive, and requires specific pedagogic intervention to do well, a program/course-wide approach is essential. This paper draws on current literature to theorise a new, transferable and customisable model for teaching and assessing reflective learning across higher education, which foregrounds and explains the pedagogic field of higher education as a multi-dimensional space. We argue that explicit and strategic pedagogic intervention, supported by dynamic resources, is necessary for successful, broad-scale approaches to reflection in higher education.

Melanoma mouse model implicates metabotropic glutamate signaling in melanocytic neoplasia

To gain insight into melanoma pathogenesis, we characterized an insertional mouse mutant, TG3, that is predisposed to develop multiple melanomas. Physical mapping identified multiple tandem insertions of the transgene into intron 3 of Grm1 (encoding metabotropic glutamate receptor 1) with concomitant deletion of 70 kb of intronic sequence. To assess whether this insertional mutagenesis event results in alteration of transcriptional regulation, we analyzed Grm1 and two flanking genes for aberrant expression in melanomas from TG3 mice. We observed aberrant expression of only Grm1. Although we did not detect its expression in normal mouse melanocytes, Grm1 was ectopically expressed in the melanomas from TG3 mice. To confirm the involvement of Grm1 in melanocytic neoplasia, we created an additional transgenic line with Grm1 expression driven by the dopachrome tautomerase promoter. Similar to the original TG3, the Tg(Grm1)EPv line was susceptible to melanoma. In contrast to human melanoma, these transgenic mice had a generalized hyperproliferation of melanocytes with limited transformation to fully malignant metastasis. We detected expression of GRM1 in a number of human melanoma biopsies and cell lines but not in benign nevi and melanocytes. This study provides compelling evidence for the importance of metabotropic glutamate signaling in melanocytic neoplasia.

Stochastic models and simulation of ion channel dynamics

The behaviour of ion channels within cardiac and neuronal cells is intrinsically stochastic in nature. When the number of channels is small this stochastic noise is large and can have an impact on the dynamics of the system which is potentially an issue when modelling small neurons and drug block in cardiac cells. While exact methods correctly capture the stochastic dynamics of a system they are computationally expensive, restricting their inclusion into tissue level models and so approximations to exact methods are often used instead. The other issue in modelling ion channel dynamics is that the transition rates are voltage dependent, adding a level of complexity as the channel dynamics are coupled to the membrane potential. By assuming that such transition rates are constant over each time step, it is possible to derive a stochastic differential equation (SDE), in the same manner as for biochemical reaction networks, that describes the stochastic dynamics of ion channels. While such a model is more computationally efficient than exact methods we show that there are analytical problems with the resulting SDE as well as issues in using current numerical schemes to solve such an equation. We therefore make two contributions: develop a different model to describe the stochastic ion channel dynamics that analytically behaves in the correct manner and also discuss numerical methods that preserve the analytical properties of the model.

Exploring the parameter space of a rabbit ventricular action potential model to investigate the effect of variation on action potential and calcium transients

Computational models for cardiomyocyte action potentials (AP) often make use of a large parameter set. This parameter set can contain some elements that are fitted to experimental data independently of any other element, some elements that are derived concurrently with other elements to match experimental data, and some elements that are derived purely from phenomenological fitting to produce the desired AP output. Furthermore, models can make use of several different data sets, not always derived for the same conditions or even the same species. It is consequently uncertain whether the parameter set for a given model is physiologically accurate. Furthermore, it is only recently that the possibility of degeneracy in parameter values in producing a given simulation output has started to be addressed. In this study, we examine the effects of varying two parameters (the L-type calcium current (I(CaL)) and the delayed rectifier potassium current (I(Ks))) in a computational model of a rabbit ventricular cardiomyocyte AP on both the membrane potential (V(m)) and calcium (Ca(2+)) transient. It will subsequently be determined if there is degeneracy in this model to these parameter values, which will have important implications on the stability of these models to cell-to-cell parameter variation, and also whether the current methodology for generating parameter values is flawed. The accuracy of AP duration (APD) as an indicator of AP shape will also be assessed.

Parameter estimation for a phenomenological model of the cardiac action potential

The action potential (ap) of a cardiac cell is made up of a complex balance of ionic currents which flow across the cell membrane in response to electrical excitation of the cell. Biophysically detailed mathematical models of the ap have grown larger in terms of the variables and parameters required to model new findings in subcellular ionic mechanisms. The fitting of parameters to such models has seen a large degree of parameter and module re-use from earlier models. An alternative method for modelling electrically exciteable cardiac tissue is a phenomenological model, which reconstructs tissue level ap wave behaviour without subcellular details. A new parameter estimation technique to fit the morphology of the ap in a four variable phenomenological model is presented. An approximation of a nonlinear ordinary differential equation model is established that corresponds to the given phenomenological model of the cardiac ap. The parameter estimation problem is converted into a minimisation problem for the unknown parameters. A modified hybrid Nelder–Mead simplex search and particle swarm optimization is then used to solve the minimisation problem for the unknown parameters. The successful fitting of data generated from a well known biophysically detailed model is demonstrated. A successful fit to an experimental ap recording that contains both noise and experimental artefacts is also produced. The parameter estimation method’s ability to fit a complex morphology to a model with substantially more parameters than previously used is established.

Narratives of complexity : an ethnographic exploration of resilience and wellbeing among single refugee women in Brisbane

This study aimed to explore resilience and wellbeing among a group of eight refugee women originating from several countries (mainly African) and living in Brisbane, most of whom were single mothers. To challenge mostly quantitative and gender-blind explorations of mental health concepts among refugee groups, the project sought an emic and contextual understanding of resilience and wellbeing. Established perspectives, while useful, tend to overlook the complexities of refugee mental health experiences and can neglect the dense nature of individual stories. The purpose of my study was to contest relatively simplistic narratives of mental health constructs that tend to dominate migrant and refugee studies and influence practice paradigms in the human services field. In this ethnographic exploration of mental health constructs conducted in 2008 and 2009, the use of in-depth interviews, participant observations, and visual ethnographic elements provided an opportunity for refugee women to tell their own stories. The participants’ unique narratives of pre- and post-migration experiences, shaped by specific gender, age, social, cultural and political aspects prevailing in their lives, yielded ‘thick’ ethnographic description (Geertz, 1973) of their social worlds. The findings explored in this study, namely language issues, the impact of community dynamics, and the single status of refugee women, clearly demonstrate that mental health constructs are fluid, multifaceted and complex in reality. In fact, language, community dynamics, and being a single mother, represented both opportunities and barriers in the lives of participants. In some contexts, these factors were conducive to resilience and wellbeing, while in other circumstances, these three elements acted as a hindrance to positive mental health outcomes. There are multiple dimensions to the findings, signifying that the social worlds of refugee women cannot be simplified using set definitions and neat notions of resilience and wellbeing. Instead, the intricacies and complexities embedded in the mundane of the everyday highlight novel conceptualisations of resilience and wellbeing. Based on the particular circumstances of single refugee mothers, whose experiences differ from that of married women, this thesis presents novel articulations of mental health constructs, as an alternative view to existing trends in the literature on refugee issues. Rich and multi-dimensional meanings associated with the socio-cultural determinants of mental health emerged in the process. This thesis’ findings highlight a significant gap in diasporic studies as well as simplistic assumptions about refugee women’s resettlement experiences. Single refugee women’s distinct issues are so complex and dense, that a contextual approach is critical to yield accurate depictions of their circumstances. It is therefore essential to understand refugee lived experiences within broader socio-political contexts to truly appreciate the depth of these narratives. In this manner, critical aspects salient to refugee journeys can inform different understandings of resilience, wellbeing and mental health, and shape contemporary policy and human service practice paradigms.

Hypothetical model of hydrophilic lubrication in synovial joints

This paper presents a new insight into the mechanism of biolubrication of articulating mammalian joints that includes the function of surface-active phospholipids (SAPLs). SAPLs can be adsorbed on surface of cartilage membranes as a hydrophobic monolayer (H-phobic-M Madel or Hills' Model) or as a newly proposed hydrophilic bilayer (H-philic-B Model). With respect to the synovial joint's frictionless work, three processes are identified namely: monolayer/bilayer phospholipids binding to cartilage with lubricin interaction; influence of induced-pressure on interaction of hyaluronan with phospholipids; and biolubrication arising from two gliding articular hydrophilic surfaces acting as reverse micelle. Lubricin is considered to play critical role as a supplier of phospholipids, which overlay the articular surface of articular cartilage. Hyaluronic acid is considered to play a critical mediating role in the interaction between the hydrophilic part of phospholipids, the articular surface and water (hydration) in facilitating the lubrication process. Tivo models of frictionless lubrication processes, namely hydrophobic (H-phobic-M Model) and our conceptual hydrophilic (H-philic-B Model), are compared. © Institution of Engineers Australia, 2008.