937 resultados para iterative multitier ensembles


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Amphibian is an 10’00’’ musical work which explores new musical interfaces and approaches to hybridising performance practices from the popular music, electronic dance music and computer music traditions. The work is designed to be presented in a range of contexts associated with the electro-acoustic, popular and classical music traditions. The work is for two performers using two synchronised laptops, an electric guitar and a custom designed gestural interface for vocal performers - the e-Mic (Extended Mic-stand Interface Controller). This interface was developed by one of the co-authors, Donna Hewitt. The e-Mic allows a vocal performer to manipulate the voice in real time through the capture of physical gestures via an array of sensors - pressure, distance, tilt - along with ribbon controllers and an X-Y joystick microphone mount. Performance data are then sent to a computer, running audio-processing software, which is used to transform the audio signal from the microphone. In this work, data is also exchanged between performers via a local wireless network, allowing performers to work with shared data streams. The duo employs the gestural conventions of guitarist and singer (i.e. 'a band' in a popular music context), but transform these sounds and gestures into new digital music. The gestural language of popular music is deliberately subverted and taken into a new context. The piece thus explores the nexus between the sonic and performative practices of electro acoustic music and intelligent electronic dance music (‘idm’). This work was situated in the research fields of new musical interfacing, interaction design, experimental music composition and performance. The contexts in which the research was conducted were live musical performance and studio music production. The work investigated new methods for musical interfacing, performance data mapping, hybrid performance and compositional practices in electronic music. The research methodology was practice-led. New insights were gained from the iterative experimental workshopping of gestural inputs, musical data mapping, inter-performer data exchange, software patch design, data and audio processing chains. In respect of interfacing, there were innovations in the design and implementation of a novel sensor-based gestural interface for singers, the e-Mic, one of the only existing gestural controllers for singers. This work explored the compositional potential of sharing real time performance data between performers and deployed novel methods for inter-performer data exchange and mapping. As regards stylistic and performance innovation, the work explored and demonstrated an approach to the hybridisation of the gestural and sonic language of popular music with recent ‘post-digital’ approaches to laptop based experimental music The development of the work was supported by an Australia Council Grant. Research findings have been disseminated via a range of international conference publications, recordings, radio interviews (ABC Classic FM), broadcasts, and performances at international events and festivals. The work was curated into the major Australian international festival, Liquid Architecture, and was selected by an international music jury (through blind peer review) for presentation at the International Computer Music Conference in Belfast, N. Ireland.

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Establishing a framework for measuring the performance of public sector programs is fraught with dangers. Many public sector organisations are satisfied with measuring activity in programs and fail to see the need for establishing a framework that will meet the needs of participants and measure outcomes as well as activities. This paper explores how a government department in Queensland went about establishing a performance management framework to measure the outcomes and activities in a program that was a public private partnership. Findings indicate that using an iterative consultative approach performance measure can be put in place that are meaningful and assist the participants to review the program.

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The implementation of ‘good governance’ in Indonesia’s regional government sector became a central tenet in governance research following the introduction of the national code for governance in 2006. The code was originally drafted in 1999 as a response to the Asian financial crises and many cases of unearthed corruption, collusion, and nepotism. It was reviewed in 2001 and again in 2006 to incorporate relevant political, economical, and social developments. Even though the national code exists along with many regional government decrees on good governance, the extent of implementation of the tenets of good governance in Indonesia’s regional government is still questioned. Previous research on good governance implementation in Indonesian regional government (Mardiasmo, Barnes and Sakurai, 2008) identified differences in the nature and depth of implementation between various Indonesian regional governments. This paper analyses and extends this recent work and explores key factors that may impede the implementation and sustained application of governance practices across regional settings. The bureaucratic culture of Indonesian regional government is one that has been shaped for over approximately 30 years, in particular during that of the Soeharto regime. Previous research on this regime suggests a bureaucratic culture with a mix of positive and negative aspects. On one hand Soeharto’s regime resulted in strong development growth and strong economic fundamentals, resulting in Indonesia being recognised as one of the Asian economic tigers prior to the 1997 Asian financial crises. The financial crises however revealed a bureaucratic culture that was rife with corruption, collusion, and nepotism. Although subsequent Indonesian governments have been committed to eradicating entrenched practices it seems apparent that the culture is ingrained within the bureaucracy and eradication of it will take time. Informants from regional government agree with this observation, as they identify good governance as an innovative mechanism and to implement it will mean a deviation from the “old ways.” Thus there is a need for a “changed” mind set in order to implement sustained governance practices. Such an exercise has proven to be challenging so far, as there is “hidden” resistance from within the bureaucracy to change its ways. The inertia of such bureaucratic cultures forms a tension against the opportunity for the implementation of good governance. From this context an emergent finding is the existence of a ‘bureaucratic generation gap’ as an impeding variable to enhanced and more efficient implementation of governance systems. It was found that after the Asian financial crises the Indonesian government (both at national and regional level) drew upon a wider human resources pool to fill government positions – including entrants from academia, the private sector, international institutions, foreign nationals and new graduates. It suggested that this change in human capital within government is at the core of this ‘inter-generational divide.’ This divergence is exemplified, at one extreme, by [older] bureaucrats who have been in-position for long periods of time serving during the extended Soeharto regime. The “new” bureaucrats have only sat in their positions since the end of Asian financial crisis and did not serve during Soeharto’s regime. It is argued that the existence of this generation gap and associated aspects of organisational culture have significantly impeded modernising governance practices across regional Indonesia. This paper examines the experiences of government employees in five Indonesian regions: Solok, Padang, Gorontalo, Bali, and Jakarta. Each regional government is examined using a mixed methodology comprising of on-site observation, document analysis, and iterative semi-structured interviewing. Drawing from the experiences of five regional governments in implementing good governance this paper seeks to better understand the causal contexts of variable implementation governance practices and to suggest enhancements to the development of policies for sustainable inter-generational change in governance practice across regional government settings.

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This chapter describes the use of collaborative learning as an approach to enhance English language learning by students from non-English speaking backgrounds. Communicative Language Teaching (CLT) principles were applied to two case studies, one comprising of undergraduate English as Foreign Language Learners in Turkey and the other involved English as Second Language learners in Australia. Social constructivism inspired communicative language teaching using collaborative learning activities such as team work, interactive peer-based learning, and iterative stages of learning matrix were incorporated to enhance students' learning outcomes. Data collected after the CLT intervention was made up of field notes, reflective logs and focus group interviews which revealed complementarities, as well as subtle differences between the two cases. The findings were summarized as learning dispositions; speaking fluency and confidence; learning diagnostics and completion deficiencies; task engagement, flow theory and higher order thinking skills; in addition to self efficacy and development of student identity. CLT has the potential to provide a more inclusive and dynamic education for diverse learners through vital outcomes and benefits which resonate with the real world.

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The fracture healing process is modulated by the mechanical environment created by imposed loads and motion between the bone fragments. Contact between the fragments obviously results in a significantly different stress and strain environment to a uniform fracture gap containing only soft tissue (e.g. haematoma). The assumption of the latter in existing computational models of the healing process will hence exaggerate the inter-fragmentary strain in many clinically-relevant cases. To address this issue, we introduce the concept of a contact zone that represents a variable degree of contact between cortices by the relative proportions of bone and soft tissue present. This is introduced as an initial condition in a two-dimensional iterative finite element model of a healing tibial fracture, in which material properties are defined by the volume fractions of each tissue present. The algorithm governing the formation of cartilage and bone in the fracture callus uses fuzzy logic rules based on strain energy density resulting from axial compression. The model predicts that increasing the degree of initial bone contact reduces the amount of callus formed (periosteal callus thickness 3.1mm without contact, down to 0.5mm with 10% bone in contact zone). This is consistent with the greater effective stiffness in the contact zone and hence, a smaller inter-fragmentary strain. These results demonstrate that the contact zone strategy reasonably simulates the differences in the healing sequence resulting from the closeness of reduction.

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It is a big challenge to clearly identify the boundary between positive and negative streams. Several attempts have used negative feedback to solve this challenge; however, there are two issues for using negative relevance feedback to improve the effectiveness of information filtering. The first one is how to select constructive negative samples in order to reduce the space of negative documents. The second issue is how to decide noisy extracted features that should be updated based on the selected negative samples. This paper proposes a pattern mining based approach to select some offenders from the negative documents, where an offender can be used to reduce the side effects of noisy features. It also classifies extracted features (i.e., terms) into three categories: positive specific terms, general terms, and negative specific terms. In this way, multiple revising strategies can be used to update extracted features. An iterative learning algorithm is also proposed to implement this approach on RCV1, and substantial experiments show that the proposed approach achieves encouraging performance.

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Over the years, people have often held the hypothesis that negative feedback should be very useful for largely improving the performance of information filtering systems; however, we have not obtained very effective models to support this hypothesis. This paper, proposes an effective model that use negative relevance feedback based on a pattern mining approach to improve extracted features. This study focuses on two main issues of using negative relevance feedback: the selection of constructive negative examples to reduce the space of negative examples; and the revision of existing features based on the selected negative examples. The former selects some offender documents, where offender documents are negative documents that are most likely to be classified in the positive group. The later groups the extracted features into three groups: the positive specific category, general category and negative specific category to easily update the weight. An iterative algorithm is also proposed to implement this approach on RCV1 data collections, and substantial experiments show that the proposed approach achieves encouraging performance.

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Matrix function approximation is a current focus of worldwide interest and finds application in a variety of areas of applied mathematics and statistics. In this thesis we focus on the approximation of A^(-α/2)b, where A ∈ ℝ^(n×n) is a large, sparse symmetric positive definite matrix and b ∈ ℝ^n is a vector. In particular, we will focus on matrix function techniques for sampling from Gaussian Markov random fields in applied statistics and the solution of fractional-in-space partial differential equations. Gaussian Markov random fields (GMRFs) are multivariate normal random variables characterised by a sparse precision (inverse covariance) matrix. GMRFs are popular models in computational spatial statistics as the sparse structure can be exploited, typically through the use of the sparse Cholesky decomposition, to construct fast sampling methods. It is well known, however, that for sufficiently large problems, iterative methods for solving linear systems outperform direct methods. Fractional-in-space partial differential equations arise in models of processes undergoing anomalous diffusion. Unfortunately, as the fractional Laplacian is a non-local operator, numerical methods based on the direct discretisation of these equations typically requires the solution of dense linear systems, which is impractical for fine discretisations. In this thesis, novel applications of Krylov subspace approximations to matrix functions for both of these problems are investigated. Matrix functions arise when sampling from a GMRF by noting that the Cholesky decomposition A = LL^T is, essentially, a `square root' of the precision matrix A. Therefore, we can replace the usual sampling method, which forms x = L^(-T)z, with x = A^(-1/2)z, where z is a vector of independent and identically distributed standard normal random variables. Similarly, the matrix transfer technique can be used to build solutions to the fractional Poisson equation of the form ϕn = A^(-α/2)b, where A is the finite difference approximation to the Laplacian. Hence both applications require the approximation of f(A)b, where f(t) = t^(-α/2) and A is sparse. In this thesis we will compare the Lanczos approximation, the shift-and-invert Lanczos approximation, the extended Krylov subspace method, rational approximations and the restarted Lanczos approximation for approximating matrix functions of this form. A number of new and novel results are presented in this thesis. Firstly, we prove the convergence of the matrix transfer technique for the solution of the fractional Poisson equation and we give conditions by which the finite difference discretisation can be replaced by other methods for discretising the Laplacian. We then investigate a number of methods for approximating matrix functions of the form A^(-α/2)b and investigate stopping criteria for these methods. In particular, we derive a new method for restarting the Lanczos approximation to f(A)b. We then apply these techniques to the problem of sampling from a GMRF and construct a full suite of methods for sampling conditioned on linear constraints and approximating the likelihood. Finally, we consider the problem of sampling from a generalised Matern random field, which combines our techniques for solving fractional-in-space partial differential equations with our method for sampling from GMRFs.

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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.

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A method of improving the security of biometric templates which satisfies desirable properties such as (a) irreversibility of the template, (b) revocability and assignment of a new template to the same biometric input, (c) matching in the secure transformed domain is presented. It makes use of an iterative procedure based on the bispectrum that serves as an irreversible transformation for biometric features because signal phase is discarded each iteration. Unlike the usual hash function, this transformation preserves closeness in the transformed domain for similar biometric inputs. A number of such templates can be generated from the same input. These properties are illustrated using synthetic data and applied to images from the FRGC 3D database with Gabor features. Verification can be successfully performed using these secure templates with an EER of 5.85%

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This paper explores a method of comparative analysis and classification of data through perceived design affordances. Included is discussion about the musical potential of data forms that are derived through eco-structural analysis of musical features inherent in audio recordings of natural sounds. A system of classification of these forms is proposed based on their structural contours. The classifications include four primitive types; steady, iterative, unstable and impulse. The classification extends previous taxonomies used to describe the gestural morphology of sound. The methods presented are used to provide compositional support for eco-structuralism.

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The population Monte Carlo algorithm is an iterative importance sampling scheme for solving static problems. We examine the population Monte Carlo algorithm in a simplified setting, a single step of the general algorithm, and study a fundamental problem that occurs in applying importance sampling to high-dimensional problem. The precision of the computed estimate from the simplified setting is measured by the asymptotic variance of estimate under conditions on the importance function. We demonstrate the exponential growth of the asymptotic variance with the dimension and show that the optimal covariance matrix for the importance function can be estimated in special cases.

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The current study examined the conceptions of learning held by upper primary children in government schools in Brunei. Previous studies have shown that the conceptions of learning held by students influence the ways in which they approach learning tasks and, in turn, impact on their learning outcomes. However, the majority of these studies were carried out with university and secondary school students, with little research involving primary school children. A phenomenographic research approach was used to describe the qualitatively different ways in which a group of sixteen upper primary children experienced learning in two government schools in Brunei. Data were gathered using scenariobased semi]structured interviews. Iterative cycles of analysis revealed three categories of description depicting three qualitatively different ways in which the children experienced the phenomenon. The three categories of description were: learning as acquiring information (Category 1), learning as remembering information (Category 2) and learning as doing hands]on activities (Category 3). These categories indicate a variation in the ways in which upper primary children experience learning in government schools in Brunei. The conceptions of learning held by the children provide a platform from which educators and policy]makers can consider possibilities for meaningful learning in government schools in Brunei.

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Network Jamming systems provide real-time collaborative media performance experiences for novice or inexperienced users. In this paper we will outline the theoretical and developmental drivers for our Network Jamming software, called jam2jam. jam2jam employs generative algorithmic techniques with particular implications for accessibility and learning. We will describe how theories of engagement have directed the design and development of jam2jam and show how iterative testing cycles in numerous international sites have informed the evolution of the system and its educational potential. Generative media systems present an opportunity for users to leverage computational systems to make sense of complex media forms through interactive and collaborative experiences. Generative music and art are a relatively new phenomenon that use procedural invention as a creative technique to produce music and visual media. These kinds of systems present a range of affordances that can facilitate new kinds of relationships with music and media performance and production. Early systems have demonstrated the potential to provide access to collaborative ensemble experiences to users with little formal musical or artistic expertise.This presentation examines the educational affordances of these systems evidenced by field data drawn from the Network Jamming Project. These generative performance systems enable access to a unique kind of music/media’ ensemble performance with very little musical/ media knowledge or skill and they further offer the possibility of unique interactive relationships with artists and creative knowledge through collaborative performance. Through the process of observing, documenting and analysing young people interacting with the generative media software jam2jam a theory of meaningful engagement has emerged from the need to describe and codify how users experience creative engagement with music/media performance and the locations of meaning. In this research we observed that the musical metaphors and practices of ‘ensemble’ or collaborative performance and improvisation as a creative process for experienced musicians can be made available to novice users. The relational meanings of these musical practices afford access to high level personal, social and cultural experiences. Within the creative process of collaborative improvisation lie a series of modes of creative engagement that move from appreciation through exploration, selection, direction toward embodiment. The expressive sounds and visions made in real-time by improvisers collaborating are immediate and compelling. Generative media systems let novices access these experiences with simple interfaces that allow them to make highly professional and expressive sonic and visual content simply by using gestures and being attentive and perceptive to their collaborators. These kinds of experiences present the potential for highly complex expressive interactions with sound and media as a performance. Evidence that has emerged from this research suggest that collaborative performance with generative media is transformative and meaningful. In this presentation we draw out these ideas around an emerging theory of meaningful engagement that has evolved from the development of network jamming software. Primarily we focus on demonstrating how these experiences might lead to understandings that may be of educational and social benefit.

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This paper explores how mobile games can transform everyday places into dynamic learning spaces filled with information and inspiration. It discusses the motivation inherent in playing games and creating games for others, and how this stimulates an iterative process of creation and reflection and evokes a natural desire to engage in learning. The use of MiLK at the Adelaide Botanic Gardens is offered as a case in point. MiLK is an authoring tool that allows students and teachers to create and share SMS games for mobile phones. A group of South Australian high school students used MiLK to play a game, create their own games and play each other’s games during a day at the gardens. This paper details the learning processes involved in these activities and how the students reflected on their learning, conducted peer assessment, and engaged in a two-way discussion with their teacher about new technologies and their implications for learning. The paper concludes with a discussion of the needs and requirements of 21st Century learners and how MiLK can support constructivist and connectivist teaching methods that engage learners and may produce an appropriately skilled future workforce.