Conceptual fashion : design, practice and process

While Conceptual fashion design practices have been a pervasive influence in fashion since the early 1980s, there is little academic analysis that might explain how they are distinct from conventional fashion design practices. In addition, fashion practitioners have not historically contributed to fashion research. As a result, contemporary fashion practitioners have difficulty setting critical contexts and expanding their creative work as there is little relevant literature available from practitioner perspectives. This project uses practice-led research to develop a discourse for understanding Conceptual fashion design process and how it relates to more conventional fashion design practices. In this exegesis I use Conceptual art as a lens to expand understandings of Conceptual fashion and my own creative practice. This analysis demonstrates that there are valuable connections to be drawn between Conceptual art and Conceptual fashion practice. In particular, these connections reveal the differences between the way Conceptual and more conventional fashion designers relate to the conceptual and the visual in their design process. This exploration demonstrates that while fashion is a visual field, Conceptual fashion designers produce a more ‘intellectual’ type of fashion that uses the visual to communicate ideas that question the nature of fashion. I explore the relevance of these ideas through application and experimentation in my creative practice projects by drawing from systems and rules identified in the work of early Conceptual artists and contemporary Conceptual fashion designers.

Reimagining learning spaces : A research report for the Queensland Council for Social Science Innovation

The purpose of the Reimagining Learning Spaces project was to conduct an empirical study that would result in findings to inform the design and use of physical school facilities and examine the ways in which these constructions influence pedagogy. The study focused on newly-established school libraries in Queensland, many of which had been established with funding from the Federal Government’s Building the Education Revolution economic stimulus program. To explore the field, the study sought multiple perspectives that included those of school students as well as teacher-librarians and other key school staff, addressing the following focus question: - How does the physical environment of school libraries influence pedagogic practices and learning outcomes? Further research questions that guided the inquiry included: - What are the implications for teacher-librarians when transitioning into a new library learning space? - How do members of the school community (principals, teachers, teacher-librarians and students) experience the creation of a new school library learning space? - How do school students imagine the design and use of engaging library learning spaces? An extensive review explored Australian and international literature based on the research questions, focused on the following major areas: • School library renewal: trends in reimagining the place of libraries in virtual and real space • School libraries as learning spaces: the expanded role of school libraries in whole-school pedagogical support. • The role of teacher-librarians in new times • Built environments and the implications for learning • Learners and learning in newly established spaces • Learning space design: perspectives, research and principles • Pedagogical principles and voices of experience • Transitions to newly created learning spaces Approach Using an innovative qualitative research design, Reimagining Learning Spaces investigated learner and teacher perspectives across three intersecting domains exploring: - Imagined spaces: learners’ imaginative concepts of learning within engaging learning environments; - Emerging spaces: experiences of teacher-librarians in the transition into new spaces for learning, and - Established spaces: learners’ and teachers’ perceptions of ways in which the physical environment influences and shapes pedagogy. Seven schools that had recently benefitted from the BER program became the research sites at which data were collected from teacher-librarians, teachers, school leaders and students. With this range of participants, an appropriately diverse set of data collection tools was developed, including video interviews, drawings, and focus groups. Evocative narrative case studies (Simons 2009) were developed from the data, representing the voices of users of learning spaces. Key findings The study’s findings are presented in this report and complemented by an array of visual materials on the project web site http:// The report includes: • a set of seven cases studies that reveal nuanced experiences of designing and creating school libraries, based on the narrative of key stakeholders (teacher-librarians, teachers, students and principals) • thematic discussion of student imaginings of their ideal school library, based on drawings and narrative of students at the seven case study schools • critical analysis of the case study and student imaginings, focusing on implications for (re)designing school learning spaces and pedagogy, and responding to the study’s overarching research question - .17 recommendations to support: designing, transitioning and reimagining pedagogy; leadership; and policy development

An interpretive field study of packaged software selection processes

Packaged software is pre-built with the intention of licensing it to users in domestic settings and work organisations. This thesis focuses upon the work organisation where packaged software has been characterised as one of the latest ‘solutions’ to the problems of information systems. The study investigates the packaged software selection process that has, to date, been largely viewed as objective and rational. In contrast, this interpretive study is based on a 21⁄2 year long field study of organisational experiences with packaged software selection at T.Co, a consultancy organisation based in the United Kingdom. Emerging from the iterative process of case study and action research is an alternative theory of packaged software selection. The research argues that packaged software selection is far from the rationalistic and linear process that previous studies suggest. Instead, the study finds that aspects of the traditional process of selection incorporating the activities of gathering requirements, evaluation and selection based on ‘best fit’ may or may not take place. Furthermore, even where these aspects occur they may not have equal weight or impact upon implementation and usage as may be expected. This is due to the influence of those multiple realities which originate from the organisational and market environments within which packages are created, selected and used, the lack of homogeneity in organisational contexts and the variously interpreted characteristics of the package in question.

Education higher degree research students writing for publication

Higher Degree Research (HDR) student publications are increasingly valued by students, by professional communities and by research institutions. Peer-reviewed publications form the HDR student writer's publication track record and increase competitiveness in employment and research funding opportunities. These publications also make the results of HDR student research available to the community in accessible formats. HDR student publications are also valued by universities because they provide evidence of institutional research activity within a field and attract a return on research performance. However, although publications are important to multiple stakeholders, many Education HDR students do not publish the results of their research. Hence, an investigation of Education HDR graduates who submitted work for publication during their candidacy was undertaken. This multiple, explanatory case study investigated six recent Education HDR graduates who had submitted work to peer-reviewed outlets during their candidacy. The conceptual framework supported an analysis of the development of Education HDR student writing using Alexander's (2003, 2004) Model of Domain Learning which focuses on expertise, and Lave and Wenger's (1991) situated learning within a community of practice. Within this framework, the study investigated how these graduates were able to submit or publish their research despite their relative lack of writing expertise. Case data were gathered through interviews and from graduate publication records. Contextual data were collected through graduate interviews, from Faculty and university documents, and through interviews with two Education HDR supervisors. Directed content analysis was applied to all data to ascertain the support available in the research training environment. Thematic analysis of graduate and supervisor interviews was then undertaken to reveal further information on training opportunities accessed by the HDR graduates. Pattern matching of all interview transcripts provided information on how the HDR graduates developed writing expertise. Finally, explanation building was used to determine causal links between the training accessed by the graduates and their writing expertise. The results demonstrated that Education HDR graduates developed publications and some level of expertise simultaneously within communities of practice. Students were largely supported by supervisors who played a critical role. They facilitated communities of practice and largely mediated HDR engagement in other training opportunities. However, supervisor support alone did not ensure that the HDR graduates developed writing expertise. Graduates who appeared to develop the most expertise, and produce a number of publications reported experiencing both a sustained period of engagement within one community of practice, and participation in multiple communities of practice. The implications for the MDL theory, as applied to academic writing, suggests that communities of practice can assist learners to progress from initial contact with a new domain of interest through to competence. The implications for research training include the suggestion that supervisors as potentially crucial supporters of HDR student writing for publication should themselves be active publishers. Also, Faculty or university sponsorship of communities of practice focussed on HDR student writing for publication could provide effective support for the development of HDR student writing expertise and potentially increase the number of their peer-reviewed publications.

Towards a model of spray-canopy interactions : interception, shatter, bounce and retention of droplets on horizontal leaves

Pesticides used in agricultural systems must be applied in economically viable and environmentally sensitive ways, and this often requires expensive field trials on spray deposition and retention by plant foliage. Computational models to describe whether a spray droplet sticks (adheres), bounces or shatters on impact, and if any rebounding parent or shatter daughter droplets are recaptured, would provide an estimate of spray retention and thereby act as a useful guide prior to any field trials. Parameter-driven interactive software has been implemented to enable the end-user to study and visualise droplet interception and impaction on a single, horizontal leaf. Living chenopodium, wheat and cotton leaves have been scanned to capture the surface topography and realistic virtual leaf surface models have been generated. Individual leaf models have then been subjected to virtual spray droplets and predictions made of droplet interception with the virtual plant leaf. Thereafter, the impaction behaviour of the droplets and the subsequent behaviour of any daughter droplets, up until re-capture, are simulated to give the predicted total spray retention by the leaf. A series of critical thresholds for the stick, bounce, and shatter elements in the impaction process have been developed for different combinations of formulation, droplet size and velocity, and leaf surface characteristics to provide this output. The results show that droplet properties, spray formulations and leaf surface characteristics all influence the predicted amount of spray retained on a horizontal leaf surface. Overall the predicted spray retention increases as formulation surface tension, static contact angle, droplet size and velocity decreases. Predicted retention on cotton is much higher than on chenopodium. The average predicted retention on a single horizontal leaf across all droplet size, velocity and formulations scenarios tested, is 18, 30 and 85% for chenopodium, wheat and cotton, respectively.

Composite SaaS resource management in cloud computing using evolutionary computation

Cloud computing is an emerging computing paradigm in which IT resources are provided over the Internet as a service to users. One such service offered through the Cloud is Software as a Service or SaaS. SaaS can be delivered in a composite form, consisting of a set of application and data components that work together to deliver higher-level functional software. SaaS is receiving substantial attention today from both software providers and users. It is also predicted to has positive future markets by analyst firms. This raises new challenges for SaaS providers managing SaaS, especially in large-scale data centres like Cloud. One of the challenges is providing management of Cloud resources for SaaS which guarantees maintaining SaaS performance while optimising resources use. Extensive research on the resource optimisation of Cloud service has not yet addressed the challenges of managing resources for composite SaaS. This research addresses this gap by focusing on three new problems of composite SaaS: placement, clustering and scalability. The overall aim is to develop efficient and scalable mechanisms that facilitate the delivery of high performance composite SaaS for users while optimising the resources used. All three problems are characterised as highly constrained, large-scaled and complex combinatorial optimisation problems. Therefore, evolutionary algorithms are adopted as the main technique in solving these problems. The first research problem refers to how a composite SaaS is placed onto Cloud servers to optimise its performance while satisfying the SaaS resource and response time constraints. Existing research on this problem often ignores the dependencies between components and considers placement of a homogenous type of component only. A precise problem formulation of composite SaaS placement problem is presented. A classical genetic algorithm and two versions of cooperative co-evolutionary algorithms are designed to now manage the placement of heterogeneous types of SaaS components together with their dependencies, requirements and constraints. Experimental results demonstrate the efficiency and scalability of these new algorithms. In the second problem, SaaS components are assumed to be already running on Cloud virtual machines (VMs). However, due to the environment of a Cloud, the current placement may need to be modified. Existing techniques focused mostly at the infrastructure level instead of the application level. This research addressed the problem at the application level by clustering suitable components to VMs to optimise the resource used and to maintain the SaaS performance. Two versions of grouping genetic algorithms (GGAs) are designed to cater for the structural group of a composite SaaS. The first GGA used a repair-based method while the second used a penalty-based method to handle the problem constraints. The experimental results confirmed that the GGAs always produced a better reconfiguration placement plan compared with a common heuristic for clustering problems. The third research problem deals with the replication or deletion of SaaS instances in coping with the SaaS workload. To determine a scaling plan that can minimise the resource used and maintain the SaaS performance is a critical task. Additionally, the problem consists of constraints and interdependency between components, making solutions even more difficult to find. A hybrid genetic algorithm (HGA) was developed to solve this problem by exploring the problem search space through its genetic operators and fitness function to determine the SaaS scaling plan. The HGA also uses the problem's domain knowledge to ensure that the solutions meet the problem's constraints and achieve its objectives. The experimental results demonstrated that the HGA constantly outperform a heuristic algorithm by achieving a low-cost scaling and placement plan. This research has identified three significant new problems for composite SaaS in Cloud. Various types of evolutionary algorithms have also been developed in addressing the problems where these contribute to the evolutionary computation field. The algorithms provide solutions for efficient resource management of composite SaaS in Cloud that resulted to a low total cost of ownership for users while guaranteeing the SaaS performance.

Distinguishing between mean-field, moment dynamics and stochastic descriptions of birth-death-movement processes

Mathematical descriptions of birth–death–movement processes are often calibrated to measurements from cell biology experiments to quantify tissue growth rates. Here we describe and analyze a discrete model of a birth–death-movement process applied to a typical two–dimensional cell biology experiment. We present three different descriptions of the system: (i) a standard mean–field description which neglects correlation effects and clustering; (ii) a moment dynamics description which approximately incorporates correlation and clustering effects, and; (iii) averaged data from repeated discrete simulations which directly incorporates correlation and clustering effects. Comparing these three descriptions indicates that the mean–field and moment dynamics approaches are valid only for certain parameter regimes, and that both these descriptions fail to make accurate predictions of the system for sufficiently fast birth and death rates where the effects of spatial correlations and clustering are sufficiently strong. Without any method to distinguish between the parameter regimes where these three descriptions are valid, it is possible that either the mean–field or moment dynamics model could be calibrated to experimental data under inappropriate conditions, leading to errors in parameter estimation. In this work we demonstrate that a simple measurement of agent clustering and correlation, based on coordination number data, provides an indirect measure of agent correlation and clustering effects, and can therefore be used to make a distinction between the validity of the different descriptions of the birth–death–movement process.

Failure analysis of laminated glass panels subjected to blast loads

This paper presents a rigorous and a reliable analytical procedure using finite element (FE) techniques to study the blast response of laminated glass (LG) panel and predict the failure of its components. The 1st principal stress (σ11) is used as the failure criterion for glass and the von mises stress (σv) is used for the interlayer and sealant joints. The results from the FE analysis for mid-span deflection, energy absorption and the stresses at critical locations of glass, interlayer and structural sealant are presented in the paper. These results compared well with those obtained from a free field blast test reported in the literature. The tensile strength (T) of the glass has a significant influence on the behaviour of the LG panel and should be treated carefully in the analysis. The glass panes absorb about 80% of the blast energy for the treated blast load and this should be minimised in the design.

On effective accounting information systems in a dynamic business environment : the role of complementing capabilities

The global business environment is witnessing tough times, and this situation has significant implications on how organizations manage their processes and resources. Accounting information system (AIS) plays a critical role in this situation to ensure appropriate processing of financial transactions and availability to relevant information for decision-making. We suggest the need for a dynamic AIS environment for today’s turbulent business environment. This environment is possible with a dynamic AIS, complementary business intelligence systems, and technical human capability. Data collected through a field survey suggests that the dynamic AIS environment contributes to an organization’s accounting functions of processing transactions, providing information for decision making, and ensuring an appropriate control environment. These accounting processes contribute to the firm-level performance of the organization. From these outcomes, one can infer that a dynamic AIS environment contributes to organizational performance in today’s challenging business environment.

Segmentation of cone-beam CT using a hidden Markov random field with informative priors

Cone-beam computed tomography (CBCT) has enormous potential to improve the accuracy of treatment delivery in image-guided radiotherapy (IGRT). To assist radiotherapists in interpreting these images, we use a Bayesian statistical model to label each voxel according to its tissue type. The rich sources of prior information in IGRT are incorporated into a hidden Markov random field model of the 3D image lattice. Tissue densities in the reference CT scan are estimated using inverse regression and then rescaled to approximate the corresponding CBCT intensity values. The treatment planning contours are combined with published studies of physiological variability to produce a spatial prior distribution for changes in the size, shape and position of the tumour volume and organs at risk. The voxel labels are estimated using iterated conditional modes. The accuracy of the method has been evaluated using 27 CBCT scans of an electron density phantom. The mean voxel-wise misclassification rate was 6.2\%, with Dice similarity coefficient of 0.73 for liver, muscle, breast and adipose tissue. By incorporating prior information, we are able to successfully segment CBCT images. This could be a viable approach for automated, online image analysis in radiotherapy.

A novel representation of bioacoustic events for content-based search in field audio data

Bioacoustic data can provide an important base for environmental monitoring. To explore a large amount of field recordings collected, an automated similarity search algorithm is presented in this paper. A region of an audio defined by frequency and time bounds is provided by a user; the content of the region is used to construct a query. In the retrieving process, our algorithm will automatically scan through recordings to search for similar regions. In detail, we present a feature extraction approach based on the visual content of vocalisations – in this case ridges, and develop a generic regional representation of vocalisations for indexing. Our feature extraction method works best for bird vocalisations showing ridge characteristics. The regional representation method allows the content of an arbitrary region of a continuous recording to be described in a compressed format.

Food in an Australian primary school curriculum : a critical sociological study

Food is a multidimensional construct. It has social, cultural, economic, psychological, emotional, biological, and political dimensions. It is both a material object and a catalyst for a range of social and cultural action. Richly implicated in the social and cultural milieu, food is a central marker of culture and society. Yet little is known about the messages and knowledges in the school curriculum about food. Popular debates around food in schools are largely connected with biomedical issues of obesity, exercise and nutrition. This is a study of the sociological dimensions of food-related messages, practices and knowledge formations in the primary school curriculum. It uses an exploratory, qualitative case study methodology to identify and examine the food activities of a Year 5 class in a Queensland school. Data was gathered over a twoyear period using observation, documentation and interviews methods. Food was found to be an integral part of the primary school's activity. It had economic, symbolic, pedagogic, and instrumental value. Messages about food were found in the official, enacted and hidden curricular which were framed by a food governance framework of legislation, procedures and norms. In the school studied, food knowledge was commodified as a part of a political economy that centred on an 'eat more' message. Certain foods were privileged over others while myths about energy, fruit, fruit juice and sugar shaped student dispositions, values, norms and action. There was little engagement with the cognitive and behavioural dimensions of food and nutrition. The thesis concludes with recommendations for a whole scale reconsideration of food in schools as curricular content and knowledge.

Building an augmented map for road risk assessment

Recent road safety statistics show that the decades-long fatalities decreasing trend is stopping and stagnating. Statistics further show that crashes are mostly driven by human error, compared to other factors such as environmental conditions and mechanical defects. Within human error, the dominant error source is perceptive errors, which represent about 50% of the total. The next two sources are interpretation and evaluation, which accounts together with perception for more than 75% of human error related crashes. Those statistics show that allowing drivers to perceive and understand their environment better, or supplement them when they are clearly at fault, is a solution to a good assessment of road risk, and, as a consequence, further decreasing fatalities. To answer this problem, currently deployed driving assistance systems combine more and more information from diverse sources (sensors) to enhance the driver's perception of their environment. However, because of inherent limitations in range and field of view, these systems' perception of their environment remains largely limited to a small interest zone around a single vehicle. Such limitations can be overcomed by increasing the interest zone through a cooperative process. Cooperative Systems (CS), a specific subset of Intelligent Transportation Systems (ITS), aim at compensating for local systems' limitations by associating embedded information technology and intervehicular communication technology (IVC). With CS, information sources are not limited to a single vehicle anymore. From this distribution arises the concept of extended or augmented perception. Augmented perception allows extending an actor's perceptive horizon beyond its "natural" limits not only by fusing information from multiple in-vehicle sensors but also information obtained from remote sensors. The end result of an augmented perception and data fusion chain is known as an augmented map. It is a repository where any relevant information about objects in the environment, and the environment itself, can be stored in a layered architecture. This thesis aims at demonstrating that augmented perception has better performance than noncooperative approaches, and that it can be used to successfully identify road risk. We found it was necessary to evaluate the performance of augmented perception, in order to obtain a better knowledge on their limitations. Indeed, while many promising results have already been obtained, the feasibility of building an augmented map from exchanged local perception information and, then, using this information beneficially for road users, has not been thoroughly assessed yet. The limitations of augmented perception, and underlying technologies, have not be thoroughly assessed yet. Most notably, many questions remain unanswered as to the IVC performance and their ability to deliver appropriate quality of service to support life-saving critical systems. This is especially true as the road environment is a complex, highly variable setting where many sources of imperfections and errors exist, not only limited to IVC. We provide at first a discussion on these limitations and a performance model built to incorporate them, created from empirical data collected on test tracks. Our results are more pessimistic than existing literature, suggesting IVC limitations have been underestimated. Then, we develop a new CS-applications simulation architecture. This architecture is used to obtain new results on the safety benefits of a cooperative safety application (EEBL), and then to support further study on augmented perception. At first, we confirm earlier results in terms of crashes numbers decrease, but raise doubts on benefits in terms of crashes' severity. In the next step, we implement an augmented perception architecture tasked with creating an augmented map. Our approach is aimed at providing a generalist architecture that can use many different types of sensors to create the map, and which is not limited to any specific application. The data association problem is tackled with an MHT approach based on the Belief Theory. Then, augmented and single-vehicle perceptions are compared in a reference driving scenario for risk assessment,taking into account the IVC limitations obtained earlier; we show their impact on the augmented map's performance. Our results show that augmented perception performs better than non-cooperative approaches, allowing to almost tripling the advance warning time before a crash. IVC limitations appear to have no significant effect on the previous performance, although this might be valid only for our specific scenario. Eventually, we propose a new approach using augmented perception to identify road risk through a surrogate: near-miss events. A CS-based approach is designed and validated to detect near-miss events, and then compared to a non-cooperative approach based on vehicles equiped with local sensors only. The cooperative approach shows a significant improvement in the number of events that can be detected, especially at the higher rates of system's deployment.

Dependence of residual amplitude noise in electro-optic phase modulators on the intensity distribution of the incident field

Our results demonstrate that photorefractive residual amplitude modulation (RAM) noise in electro-optic modulators (EOMs) can be reduced by modifying the incident beam intensity distribution. Here we report an order of magnitude reduction in RAM when beams with uniform intensity (flat-top) profiles, generated with an LCOS-SLM, are used instead of the usual fundamental Gaussian mode (TEM00). RAM arises from the photorefractive amplified scatter noise off the defects and impurities within the crystal. A reduction in RAM is observed with increasing intensity uniformity (flatness), which is attributed to a reduction in space charge field on the beam axis. The level of RAM reduction that can be achieved is physically limited by clipping at EOM apertures, with the observed results agreeing well with a simple model. These results are particularly important in applications where the reduction of residual amplitude modulation to 10^-6 is essential.

Incorporating spatial correlations into multispecies mean-field models

In biology, we frequently observe different species existing within the same environment. For example, there are many cell types in a tumour, or different animal species may occupy a given habitat. In modelling interactions between such species, we often make use of the mean field approximation, whereby spatial correlations between the locations of individuals are neglected. Whilst this approximation holds in certain situations, this is not always the case, and care must be taken to ensure the mean field approximation is only used in appropriate settings. In circumstances where the mean field approximation is unsuitable we need to include information on the spatial distributions of individuals, which is not a simple task. In this paper we provide a method that overcomes many of the failures of the mean field approximation for an on-lattice volume-excluding birth-death-movement process with multiple species. We explicitly take into account spatial information on the distribution of individuals by including partial differential equation descriptions of lattice site occupancy correlations. We demonstrate how to derive these equations for the multi-species case, and show results specific to a two-species problem. We compare averaged discrete results to both the mean field approximation and our improved method which incorporates spatial correlations. We note that the mean field approximation fails dramatically in some cases, predicting very different behaviour from that seen upon averaging multiple realisations of the discrete system. In contrast, our improved method provides excellent agreement with the averaged discrete behaviour in all cases, thus providing a more reliable modelling framework. Furthermore, our method is tractable as the resulting partial differential equations can be solved efficiently using standard numerical techniques.