128 resultados para Nelson and Siegel model


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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.

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Vehicle emitted particles are of significant concern based on their potential to influence local air quality and human health. Transport microenvironments usually contain higher vehicle emission concentrations compared to other environments, and people spend a substantial amount of time in these microenvironments when commuting. Currently there is limited scientific knowledge on particle concentration, passenger exposure and the distribution of vehicle emissions in transport microenvironments, partially due to the fact that the instrumentation required to conduct such measurements is not available in many research centres. Information on passenger waiting time and location in such microenvironments has also not been investigated, which makes it difficult to evaluate a passenger’s spatial-temporal exposure to vehicle emissions. Furthermore, current emission models are incapable of rapidly predicting emission distribution, given the complexity of variations in emission rates that result from changes in driving conditions, as well as the time spent in driving condition within the transport microenvironment. In order to address these scientific gaps in knowledge, this work conducted, for the first time, a comprehensive statistical analysis of experimental data, along with multi-parameter assessment, exposure evaluation and comparison, and emission model development and application, in relation to traffic interrupted transport microenvironments. The work aimed to quantify and characterise particle emissions and human exposure in the transport microenvironments, with bus stations and a pedestrian crossing identified as suitable research locations representing a typical transport microenvironment. Firstly, two bus stations in Brisbane, Australia, with different designs, were selected to conduct measurements of particle number size distributions, particle number and PM2.5 concentrations during two different seasons. Simultaneous traffic and meteorological parameters were also monitored, aiming to quantify particle characteristics and investigate the impact of bus flow rate, station design and meteorological conditions on particle characteristics at stations. The results showed higher concentrations of PN20-30 at the station situated in an open area (open station), which is likely to be attributed to the lower average daily temperature compared to the station with a canyon structure (canyon station). During precipitation events, it was found that particle number concentration in the size range 25-250 nm decreased greatly, and that the average daily reduction in PM2.5 concentration on rainy days compared to fine days was 44.2 % and 22.6 % at the open and canyon station, respectively. The effect of ambient wind speeds on particle number concentrations was also examined, and no relationship was found between particle number concentration and wind speed for the entire measurement period. In addition, 33 pairs of average half-hourly PN7-3000 concentrations were calculated and identified at the two stations, during the same time of a day, and with the same ambient wind speeds and precipitation conditions. The results of a paired t-test showed that the average half-hourly PN7-3000 concentrations at the two stations were not significantly different at the 5% confidence level (t = 0.06, p = 0.96), which indicates that the different station designs were not a crucial factor for influencing PN7-3000 concentrations. A further assessment of passenger exposure to bus emissions on a platform was evaluated at another bus station in Brisbane, Australia. The sampling was conducted over seven weekdays to investigate spatial-temporal variations in size-fractionated particle number and PM2.5 concentrations, as well as human exposure on the platform. For the whole day, the average PN13-800 concentration was 1.3 x 104 and 1.0 x 104 particle/cm3 at the centre and end of the platform, respectively, of which PN50-100 accounted for the largest proportion to the total count. Furthermore, the contribution of exposure at the bus station to the overall daily exposure was assessed using two assumed scenarios of a school student and an office worker. It was found that, although the daily time fraction (the percentage of time spend at a location in a whole day) at the station was only 0.8 %, the daily exposure fractions (the percentage of exposures at a location accounting for the daily exposure) at the station were 2.7% and 2.8 % for exposure to PN13-800 and 2.7% and 3.5% for exposure to PM2.5 for the school student and the office worker, respectively. A new parameter, “exposure intensity” (the ratio of daily exposure fraction and the daily time fraction) was also defined and calculated at the station, with values of 3.3 and 3.4 for exposure to PN13-880, and 3.3 and 4.2 for exposure to PM2.5, for the school student and the office worker, respectively. In order to quantify the enhanced emissions at critical locations and define the emission distribution in further dispersion models for traffic interrupted transport microenvironments, a composite line source emission (CLSE) model was developed to specifically quantify exposure levels and describe the spatial variability of vehicle emissions in traffic interrupted microenvironments. This model took into account the complexity of vehicle movements in the queue, as well as different emission rates relevant to various driving conditions (cruise, decelerate, idle and accelerate), and it utilised multi-representative segments to capture the accurate emission distribution for real vehicle flow. This model does not only helped to quantify the enhanced emissions at critical locations, but it also helped to define the emission source distribution of the disrupted steady flow for further dispersion modelling. The model then was applied to estimate particle number emissions at a bidirectional bus station used by diesel and compressed natural gas fuelled buses. It was found that the acceleration distance was of critical importance when estimating particle number emission, since the highest emissions occurred in sections where most of the buses were accelerating and no significant increases were observed at locations where they idled. It was also shown that emissions at the front end of the platform were 43 times greater than at the rear of the platform. The CLSE model was also applied at a signalled pedestrian crossing, in order to assess increased particle number emissions from motor vehicles when forced to stop and accelerate from rest. The CLSE model was used to calculate the total emissions produced by a specific number and mix of light petrol cars and diesel passenger buses including 1 car travelling in 1 direction (/1 direction), 14 cars / 1 direction, 1 bus / 1 direction, 28 cars / 2 directions, 24 cars and 2 buses / 2 directions, and 20 cars and 4 buses / 2 directions. It was found that the total emissions produced during stopping on a red signal were significantly higher than when the traffic moved at a steady speed. Overall, total emissions due to the interruption of the traffic increased by a factor of 13, 11, 45, 11, 41, and 43 for the above 6 cases, respectively. In summary, this PhD thesis presents the results of a comprehensive study on particle number and mass concentration, together with particle size distribution, in a bus station transport microenvironment, influenced by bus flow rates, meteorological conditions and station design. Passenger spatial-temporal exposure to bus emitted particles was also assessed according to waiting time and location along the platform, as well as the contribution of exposure at the bus station to overall daily exposure. Due to the complexity of the interrupted traffic flow within the transport microenvironments, a unique CLSE model was also developed, which is capable of quantifying emission levels at critical locations within the transport microenvironment, for the purpose of evaluating passenger exposure and conducting simulations of vehicle emission dispersion. The application of the CLSE model at a pedestrian crossing also proved its applicability and simplicity for use in a real-world transport microenvironment.

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Organizations from every industry sector seek to enhance their business performance and competitiveness through the deployment of contemporary information systems (IS), such as Enterprise Systems (ERP). Investments in ERP are complex and costly, attracting scrutiny and pressure to justify their cost. Thus, IS researchers highlight the need for systematic evaluation of information system success, or impact, which has resulted in the introduction of varied models for evaluating information systems. One of these systematic measurement approaches is the IS-Impact Model introduced by a team of researchers at Queensland University of technology (QUT) (Gable, Sedera, & Chan, 2008). The IS-Impact Model is conceptualized as a formative, multidimensional index that consists of four dimensions. Gable et al. (2008) define IS-Impact as "a measure at a point in time, of the stream of net benefits from the IS, to date and anticipated, as perceived by all key-user-groups" (p.381). The IT Evaluation Research Program (ITE-Program) at QUT has grown the IS-Impact Research Track with the central goal of conducting further studies to enhance and extend the IS-Impact Model. The overall goal of the IS-Impact research track at QUT is "to develop the most widely employed model for benchmarking information systems in organizations for the joint benefit of both research and practice" (Gable, 2009). In order to achieve that, the IS-Impact research track advocates programmatic research having the principles of tenacity, holism, and generalizability through extension research strategies. This study was conducted within the IS-Impact Research Track, to further generalize the IS-Impact Model by extending it to the Saudi Arabian context. According to Hofsted (2012), the national culture of Saudi Arabia is significantly different from the Australian national culture making the Saudi Arabian culture an interesting context for testing the external validity of the IS-Impact Model. The study re-visits the IS-Impact Model from the ground up. Rather than assume the existing instrument is valid in the new context, or simply assess its validity through quantitative data collection, the study takes a qualitative, inductive approach to re-assessing the necessity and completeness of existing dimensions and measures. This is done in two phases: Exploratory Phase and Confirmatory Phase. The exploratory phase addresses the first research question of the study "Is the IS-Impact Model complete and able to capture the impact of information systems in Saudi Arabian Organization?". The content analysis, used to analyze the Identification Survey data, indicated that 2 of the 37 measures of the IS-Impact Model are not applicable for the Saudi Arabian Context. Moreover, no new measures or dimensions were identified, evidencing the completeness and content validity of the IS-Impact Model. In addition, the Identification Survey data suggested several concepts related to IS-Impact, the most prominent of which was "Computer Network Quality" (CNQ). The literature supported the existence of a theoretical link between IS-Impact and CNQ (CNQ is viewed as an antecedent of IS-Impact). With the primary goal of validating the IS-Impact model within its extended nomological network, CNQ was introduced to the research model. The Confirmatory Phase addresses the second research question of the study "Is the Extended IS-Impact Model Valid as a Hierarchical Multidimensional Formative Measurement Model?". The objective of the Confirmatory Phase was to test the validity of IS-Impact Model and CNQ Model. To achieve that, IS-Impact, CNQ, and IS-Satisfaction were operationalized in a survey instrument, and then the research model was assessed by employing the Partial Least Squares (PLS) approach. The CNQ model was validated as a formative model. Similarly, the IS-Impact Model was validated as a hierarchical multidimensional formative construct. However, the analysis indicated that one of the IS-Impact Model indicators was insignificant and can be removed from the model. Thus, the resulting Extended IS-Impact Model consists of 4 dimensions and 34 measures. Finally, the structural model was also assessed against two aspects: explanatory and predictive power. The analysis revealed that the path coefficient between CNQ and IS-Impact is significant with t-value= (4.826) and relatively strong with â = (0.426) with CNQ explaining 18% of the variance in IS-Impact. These results supported the hypothesis that CNQ is antecedent of IS-Impact. The study demonstrates that the quality of Computer Network affects the quality of the Enterprise System (ERP) and consequently the impacts of the system. Therefore, practitioners should pay attention to the Computer Network quality. Similarly, the path coefficient between IS-Impact and IS-Satisfaction was significant t-value = (17.79) and strong â = (0.744), with IS-Impact alone explaining 55% of the variance in Satisfaction, consistent with results of the original IS-Impact study (Gable et al., 2008). The research contributions include: (a) supporting the completeness and validity of IS-Impact Model as a Hierarchical Multi-dimensional Formative Measurement Model in the Saudi Arabian context, (b) operationalizing Computer Network Quality as conceptualized in the ITU-T Recommendation E.800 (ITU-T, 1993), (c) validating CNQ as a formative measurement model and as an antecedent of IS Impact, and (d) conceptualizing and validating IS-Satisfaction as a reflective measurement model and as an immediate consequence of IS Impact. The CNQ model provides a framework to perceptually measure Computer Network Quality from multiple perspectives. The CNQ model features an easy-to-understand, easy-to-use, and economical survey instrument.

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Business process modelling as a practice and research field has received great attention over recent years. Organizations invest significantly into process modelling in terms of training, tools, capabilities and resources. The return on this investment is a function of process model re-use, which we define as the recurring use of process models to support organizational work tasks. While prior research has examined re-use as a design principle, we explore re-use as a behaviour, because evidence suggest that analysts’ re-use of process models is indeed limited. In this paper we develop a two-stage conceptualization of the key object-, behaviour- and socioorganization-centric factors explaining process model re-use behaviour. We propose a theoretical model and detail implications for its operationalization and measurement. Our study can provide significant benefits to our understanding of process modelling and process model use as key practices in analysis and design.

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Process models are used to convey semantics about business operations that are to be supported by an information system. A wide variety of professionals is targeted to use such models, including people who have little modeling or domain expertise. We identify important user characteristics that influence the comprehension of process models. Through a free simulation experiment, we provide evidence that selected cognitive abilities, learning style, and learning strategy influence the development of process model comprehension. These insights draw attention to the importance of research that views process model comprehension as an emergent learning process rather than as an attribute of the models as objects. Based on our findings, we identify a set of organizational intervention strategies that can lead to more successful process modeling workshops.

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Responding to the global and unprecedented challenge of capacity building for twenty-first century life, this book is a practical guide for tertiary education institutions to quickly and effectively renew the curriculum towards education for sustainable development. The book begins by exploring why curriculum change has been so slow. It then describes a model for rapid curriculum renewal, highlighting the important roles of setting timeframes, formal and informal leadership, and key components and action strategies. The second part of the book provides detailed coverage of six core elements that have been trialled and peer reviewed by institutions around the world: - raising awareness among staff and students - mapping graduate attributes - auditing the curriculum - developing niche degrees, flagship courses and fully integrated programs - engaging and catalysing community and student markets - integrating curriculum with green campus operations. With input from more than seventy academics and grounded in engineering education experiences, this book will provide academic staff with tools and insights to rapidly align program offerings with the needs of present and future generations of students.

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This paper presents an unmanned aircraft system (UAS) that uses a probabilistic model for autonomous front-on environmental sensing or photography of a target. The system is based on low-cost and readily-available sensor systems in dynamic environments and with the general intent of improving the capabilities of dynamic waypoint-based navigation systems for a low-cost UAS. The behavioural dynamics of target movement for the design of a Kalman filter and Markov model-based prediction algorithm are included. Geometrical concepts and the Haversine formula are applied to the maximum likelihood case in order to make a prediction regarding a future state of a target, thus delivering a new waypoint for autonomous navigation. The results of the application to aerial filming with low-cost UAS are presented, achieving the desired goal of maintained front-on perspective without significant constraint to the route or pace of target movement.

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Robotics is taught in many Australian ICT classrooms, in both primary and secondary schools. Robotics activities, including those developed using the LEGO Mindstorms NXT technology, are mathematics-rich and provide a fertile round for learners to develop and extend their mathematical thinking. However, this context for learning mathematics is often under-exploited. In this paper a variant of the model construction sequence (Lesh, Cramer, Doerr, Post, & Zawojewski, 2003) is proposed, with the purpose of explicitly integrating robotics and mathematics teaching and learning. Lesh et al.’s model construction sequence and the model eliciting activities it embeds were initially researched in primary mathematics classrooms and more recently in university engineering courses. The model construction sequence involves learners working collaboratively upon product-focussed tasks, through which they develop and expose their conceptual understanding. The integrating model proposed in this paper has been used to design and analyse a sequence of activities in an Australian Year 4 classroom. In that sequence more traditional classroom learning was complemented by the programming of LEGO-based robots to ‘act out’ the addition and subtraction of simple fractions (tenths) on a number-line. The framework was found to be useful for planning the sequence of learning and, more importantly, provided the participating teacher with the ability to critically reflect upon robotics technology as a tool to scaffold the learning of mathematics.

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Traditionally, service encounters have included an interpersonal interaction between the service provider and the customer. The introduction ofself-service technologies to the service encounter, however, is reducing and in some cases, eliminating this interpersonal interaction. Self-se rvice technology is where the customer delivers the service themselves using a technological interface. This CIM funded research programme investigates the effect of self-service technology on the service encounter, and in turn on consumer satisfaction and consumer commitment. This paper reviews the literature relevant to the current study and outlines the constructs of interest in this study. The resear ch hypotheses and conceptual model are also introduced.Finally, the agenda for future research is presented.

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This paper presents research findings about the use of remote desktop applications to teach music sequencing software. It highlights the successes, shortcomings and interactive issues encountered during a pilot project with a theoretical focus on a specific interactive bottleneck. The paper proposes a new delivery and partnership model to widen this bottleneck, which currently hinders interactions between the technical support, education and professional development communities in music technology.

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Providing support for reversible transformations as a basis for round-trip engineering is a significant challenge in model transformation research. While there are a number of current approaches, they require the underlying transformation to exhibit an injective behaviour when reversing changes. This however, does not serve all practical transformations well. In this paper, we present a novel approach to round-trip engineering that does not place restrictions on the nature of the underlying transformation. Based on abductive logic programming, it allows us to compute a set of legitimate source changes that equate to a given change to the target model. Encouraging results are derived from an initial prototype that supports most concepts of the Tefkat transformation language

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Harmful Algal Blooms (HABs) are a worldwide problem that have been increasing in frequency and extent over the past several decades. HABs severely damage aquatic ecosystems by destroying benthic habitat, reducing invertebrate and fish populations and affecting larger species such as dugong that rely on seagrasses for food. Few statistical models for predicting HAB occurrences have been developed, and in common with most predictive models in ecology, those that have been developed do not fully account for uncertainties in parameters and model structure. This makes management decisions based on these predictions more risky than might be supposed. We used a probit time series model and Bayesian Model Averaging (BMA) to predict occurrences of blooms of Lyngbya majuscula, a toxic cyanophyte, in Deception Bay, Queensland, Australia. We found a suite of useful predictors for HAB occurrence, with Temperature figuring prominently in models with the majority of posterior support, and a model consisting of the single covariate average monthly minimum temperature showed by far the greatest posterior support. A comparison of alternative model averaging strategies was made with one strategy using the full posterior distribution and a simpler approach that utilised the majority of the posterior distribution for predictions but with vastly fewer models. Both BMA approaches showed excellent predictive performance with little difference in their predictive capacity. Applications of BMA are still rare in ecology, particularly in management settings. This study demonstrates the power of BMA as an important management tool that is capable of high predictive performance while fully accounting for both parameter and model uncertainty.

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This paper will describe a research project that examines the implications of multidisciplinary student cohorts on teaching and learning within undergraduate and postgraduate units in higher education. Whist students generally specialise in one discipline, it is also common that, at some point during their degree, they will choose to undertake subjects that are outside their specialist area. Students may choose a multidisciplinary learning experience either out of interest or because the subject is seen as complementary to their core discipline. When the lens of identity is applied to the multi-disciplinary cohorts in undergraduate and postgraduate units, it assists in identifying learning needs. The nature of disciplinarity, and the impact it has on students’ academic identity, presents challenges to both students and teachers when they engage in teaching and learning, impacting on curriculum design, assessment practices and teaching delivery strategies (Winberg, 2008). This project aims to identify the barriers that exist to effective teaching and learning in units that have multidisciplinary student cohorts. It will identify the particular needs of students in multidisciplinary student cohorts and determine a teaching and learning model that meets the needs of such cohorts. References Becher, T. & Trowler, P.R. (2001). Academic tribes and territories: Intellectual enquiry and the culture of the discipline. Buckingham, UK: Open University Press. Light, G. & Cox, R. (2001). Learning and teaching in higher education: A reflective professional. Thousand Oaks, CA: Sage. Neumann, R. (2001). Disciplinary differences and university teaching. Studies in Higher Education, 26 (2), 135-46. Neumann, R., Parry, S. & Becher, T. (2002). Teaching and Learning in their disciplinary contexts: A conceptual analysis. Studies in Higher Education, 27(4), 405-417. Taylor, P.G. (1999) Making Sense of Academic Life: Academics, Universities and Change. Buckingham, UK: Open University Press. Winberg, C. (2008). Teaching engineering/engineering teaching: interdisciplinary collaboration and the construction of academic identities. Teaching in Higher Education, 13(3), 353 - 367.

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A diagnosis of cancer represents a significant crisis for the child and their family. As the treatment for childhood cancer has improved dramatically over the past three decades, most children diagnosed with cancer today survive this illness. However, it is still an illness which severely disrupts the lifestyle and typical functioning of the family unit. Most treatments for cancer involve lengthy hospital stays, the endurance of painful procedures and harsh side effects. Research has confirmed that to manage and adapt to such a crisis, families must undertake measures which assist their adjustment. Variables such as level of family support, quality of parents’ marital relationship, coping of other family members, lack of other concurrent stresses and open communication within the family have been identified as influences on how well families adjust to a diagnosis of childhood cancer. Theoretical frameworks such as the Resiliency Model of Family Adjustment and Adaptation (McCubbin and McCubbin, 1993, 1996) and the Stress and Coping Model by Lazarus and Folkman (1984) have been used to explain how families and individuals adapt to crises or adverse circumstances. Developmental theories have also been posed to account for how children come to understand and learn about the concept of illness. However more descriptive information about how families and children in particular, experience and manage a diagnosis of cancer is still needed. There are still many unanswered questions surrounding how a child adapts to, understands and makes meaning from having a life-threatening illness. As a result, developing an understanding of the impact that such a serious illness has on the child and their family is crucial. A new approach to examining childhood illness such as cancer is currently underway which allows for a greater understanding of the experience of childhood cancer to be achieved. This new approach invites a phenomenological method to investigate the perspectives of those affected by childhood cancer. In the current study 9 families in which there was a diagnosis of childhood cancer were interviewed twice over a 12 month period. Using the qualitative methodology of Interpretative Phenomenological Analysis (IPA) a semi-structured interview was used to explicate the experience of childhood cancer from both the parent and child’s perspectives. A number of quantitative measures were also administered to gather specific information on the demographics of the sample population. The results of this study revealed a number of pertinent areas which need to be considered when treating such families. More importantly experiences were explicated which revealed vital phenomena that needs to be added to extend current theoretical frameworks. Parents identified the time of the diagnosis as the hardest part of their entire experience. Parents experienced an internal struggle when they were forced to come to the realization that they were not able to help their child get well. Families demonstrated an enormous ability to develop a new lifestyle which accommodated the needs of the sick child, as the sick child became the focus of their lives. Regarding the children, many of them accepted their diagnosis without complaint or question, and they were able to recognise and appreciate the support they received. Physical pain was definitely a component of the children’s experience however the emotional strain of loss of peer contact seemed just as severe. Changes over time were also noted as both parental and child experiences were often pertinent to the stage of treatment the child had reached. The approach used in this study allowed for rich and intimate detail about a sensitive issue to be revealed. Such an approach also allowed for the experience of childhood cancer on parents and the children to be more fully realised. Only now can a comprehensive and sensitive medical and psychosocial approach to the child and family be developed. For example, families may benefit from extra support at the time of diagnosis as this was identified as one of the most difficult periods. Parents may also require counselling support in coming to terms with their lack of ability to help their child heal. Given the ease at which children accepted their diagnosis, we need to question whether children are more receptive to adversity. Yet the emotional struggle children battled as a result of their illness also needs to be addressed.

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The Restrung New Chamber Festival was a practice-led research project which explored the intricacies of musical relationships. Specifically, it investigated the relationships between new music ensembles and pop-oriented bands inspired by the new music genre. The festival, held at the Brisbane Powerhouse (28 February-2 March 2009) comprised 17 diverse groups including the Brodsky Quartet, Topology, Wood, Fourplay and CODA. Restrung used a new and distinctive model which presented new music and syncretic musical genres within an immersive environment. Restrung brought together approaches used in both contemporary classical and popular music festivals, using musical, visual and spatial aspects to engage audiences. Interactivity was encouraged through video and sound installations, workshops and forums. This paper will investigate some of the issues surrounding the conception and design of the Restrung model, within the context of an overview of European new music trends. It includes a discussion of curating such an event in a musically sensitive and effective way, and approaches to identifying new and receptive audiences. As a guide to programming Restrung, I formulated a working definition of new music, further developed by interviews with specialists in Australia and Europe, and this will be outlined below.