993 resultados para Artistic techniques


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This practice-led research project examines some of the factors and issues facing artists working in the public domain who wish to engage with the community as audience. Using the methodology of action research, the three major creative projects in this study use art as a socio-political tool with the aim of providing an effective vehicle for broadening awareness, understanding forms of social protest and increasing tolerance for diversity. The three projects: Floodline November 7, 2004, Look in, Look out, and The Urban Terrorist Project, dealt with issues of marginalisation of communities, audiences and graffiti artists respectively. The artist/researcher is outlined as both creator and collaborator in the work. Processes included ephemeral elements, such as temporary installation and performance, as well as interactive elements that encouraged direct audience involvement as part of the work. In addition to the roles of creator and collaborator, both of which included audience as well as artist, the presence of an outside entity was evident. Whether local, legal authorities or prevailing attitudes, outside entities had an unavoidable impact on the processes and outcomes of the work. Each project elicited a range of responses from their respective audiences; however, the overarching concept of reciprocity was seen to be the crucial factor in conception, artistic methods and outcomes.

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3D Motion capture is a medium that plots motion, typically human motion, converting it into a form that can be represented digitally. It is a fast evolving field and recent inertial technology may provide new artistic possibilities for its use in live performance. Although not often used in this context, motion capture has a combination of attributes that can provide unique forms of collaboration with performance arts. The inertial motion capture suit used for this study has orientation sensors placed at strategic points on the body to map body motion. Its portability, real-time performance, ease of use, and its immunity from line-of-sight problems inherent in optical systems suggest it would work well as a live performance technology. Many animation techniques can be used in real-time. This research examines a broad cross-section of these techniques using four practice-led cases to assess the suitability of inertial motion capture to live performance. Although each case explores different visual possibilities, all make use of the performativity of the medium, using either an improvisational format or interactivity among stage, audience and screen that would be difficult to emulate any other way. A real-time environment is not capable of reproducing the depth and sophistication of animation people have come to expect through media. These environments take many hours to render. In time the combination of what can be produced in real-time and the tools available in a 3D environment will no doubt create their own tree of aesthetic directions in live performance. The case study looks at the potential of interactivity that this technology offers.

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Texture based techniques for visualisation of unsteady vector fields have been applied for the visualisation of a Finite volume model for variably saturated groundwater flow through porous media. This model has been developed by staff in the School of Mathematical Sciences QUT for the study of salt water intrusion into coastal aquifers. This presentation discusses the implementation and effectiveness of the IBFV algorithm in the context of visualisation of the groundwater simulation outputs.

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The value of soil evidence in the forensic discipline is well known. However, it would be advantageous if an in-situ method was available that could record responses from tyre or shoe impressions in ground soil at the crime scene. The development of optical fibres and emerging portable NIR instruments has unveiled a potential methodology which could permit such a proposal. The NIR spectral region contains rich chemical information in the form of overtone and combination bands of the fundamental infrared absorptions and low-energy electronic transitions. This region has in the past, been perceived as being too complex for interpretation and consequently was scarcely utilized. The application of NIR in the forensic discipline is virtually non-existent creating a vacancy for research in this area. NIR spectroscopy has great potential in the forensic discipline as it is simple, nondestructive and capable of rapidly providing information relating to chemical composition. The objective of this study is to investigate the ability of NIR spectroscopy combined with Chemometrics to discriminate between individual soils. A further objective is to apply the NIR process to a simulated forensic scenario where soil transfer occurs. NIR spectra were recorded from twenty-seven soils sampled from the Logan region in South-East Queensland, Australia. A series of three high quartz soils were mixed with three different kaolinites in varying ratios and NIR spectra collected. Spectra were also collected from six soils as the temperature of the soils was ramped from room temperature up to 6000C. Finally, a forensic scenario was simulated where the transferral of ground soil to shoe soles was investigated. Chemometrics methods such as the commonly known Principal Component Analysis (PCA), the less well known fuzzy clustering (FC) and ranking by means of multicriteria decision making (MCDM) methodology were employed to interpret the spectral results. All soils were characterised using Inductively Coupled Plasma Optical Emission Spectroscopy and X-Ray Diffractometry. Results were promising revealing NIR combined with Chemometrics is capable of discriminating between the various soils. Peak assignments were established by comparing the spectra of known minerals with the spectra collected from the soil samples. The temperature dependent NIR analysis confirmed the assignments of the absorptions due to adsorbed and molecular bound water. The relative intensities of the identified NIR absorptions reflected the quantitative XRD and ICP characterisation results. PCA and FC analysis of the raw soils in the initial NIR investigation revealed that the soils were primarily distinguished on the basis of their relative quartz and kaolinte contents, and to a lesser extent on the horizon from which they originated. Furthermore, PCA could distinguish between the three kaolinites used in the study, suggesting that the NIR spectral region was sensitive enough to contain information describing variation within kaolinite itself. The forensic scenario simulation PCA successfully discriminated between the ‘Backyard Soil’ and ‘Melcann® Sand’, as well as the two sampling methods employed. Further PCA exploration revealed that it was possible to distinguish between the various shoes used in the simulation. In addition, it was possible to establish association between specific sampling sites on the shoe with the corresponding site remaining in the impression. The forensic application revealed some limitations of the process relating to moisture content and homogeneity of the soil. These limitations can both be overcome by simple sampling practices and maintaining the original integrity of the soil. The results from the forensic scenario simulation proved that the concept shows great promise in the forensic discipline.

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Survey-based health research is in a boom phase following an increased amount of health spending in OECD countries and the interest in ageing. A general characteristic of survey-based health research is its diversity. Different studies are based on different health questions in different datasets; they use different statistical techniques; they differ in whether they approach health from an ordinal or cardinal perspective; and they differ in whether they measure short-term or long-term effects. The question in this paper is simple: do these differences matter for the findings? We investigate the effects of life-style choices (drinking, smoking, exercise) and income on six measures of health in the US Health and Retirement Study (HRS) between 1992 and 2002: (1) self-assessed general health status, (2) problems with undertaking daily tasks and chores, (3) mental health indicators, (4) BMI, (5) the presence of serious long-term health conditions, and (6) mortality. We compare ordinal models with cardinal models; we compare models with fixed effects to models without fixed-effects; and we compare short-term effects to long-term effects. We find considerable variation in the impact of different determinants on our chosen health outcome measures; we find that it matters whether ordinality or cardinality is assumed; we find substantial differences between estimates that account for fixed effects versus those that do not; and we find that short-run and long-run effects differ greatly. All this implies that health is an even more complicated notion than hitherto thought, defying generalizations from one measure to the others or one methodology to another.

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Applied Theatre is an umbrella term for a range of drama-based techniques, all of which align with a lineage of pedagogical theory and practice: (e.g.) Freire, Moreno, Heathcote. It encompasses methods and forms including Drama Education (O’Neill); Forum Theatre (Boal); and Process Drama (Haseman, O’Toole). Applied theatre often occurs in non-theatrical settings (schools, hospitals, prisons) with the aim of helping participants address issues of local concern. Increasingly, Applied Theatre practices are utilised in the corporate environment. Appied Theatre adopts artistic principles in production, but posits a practical utility beyond simple entertainment.

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The following paper presents an evaluation of airborne sensors for use in vegetation management in powerline corridors. Three integral stages in the management process are addressed including, the detection of trees, relative positioning with respect to the nearest powerline and vegetation height estimation. Image data, including multi-spectral and high resolution, are analyzed along with LiDAR data captured from fixed wing aircraft. Ground truth data is then used to establish the accuracy and reliability of each sensor thus providing a quantitative comparison of sensor options. Tree detection was achieved through crown delineation using a Pulse-Coupled Neural Network (PCNN) and morphologic reconstruction applied to multi-spectral imagery. Through testing it was shown to achieve a detection rate of 96%, while the accuracy in segmenting groups of trees and single trees correctly was shown to be 75%. Relative positioning using LiDAR achieved a RMSE of 1.4m and 2.1m for cross track distance and along track position respectively, while Direct Georeferencing achieved RMSE of 3.1m in both instances. The estimation of pole and tree heights measured with LiDAR had a RMSE of 0.4m and 0.9m respectively, while Stereo Matching achieved 1.5m and 2.9m. Overall a small number of poles were missed with detection rates of 98% and 95% for LiDAR and Stereo Matching.

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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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The investigation into the encapsulation of gold nanoparticles (AuNPs) by poly(methyl methacrylate) (PMMA) was undertaken. This was performed by three polymerisation techniques including: grafting PMMA synthesised by reversible addition-fragmentation chain transfer (RAFT) polymerisation to AuNPs, grafting PMMA synthesised by atom transfer radical polymerisation (ATRP) from the surface of functionalised AuNPs and by encapsulation of AuNPs within PMMA latexes produced through photo-initiated oil-in-water (o/w) miniemulsion polymerisation. The grafting of RAFT PMMA to AuNPs was performed by the addition of the RAFT functionalised PMMA to citrate stabilised AuNPs. This was conducted with a range of PMMA of varying molecular weight distribution (MWD) as either the dithioester or thiol end-group functionalities. The RAFT PMMA polymers were characterised by gel permeation chromatography (GPC), ultraviolet-visible (UV-vis), Fourier transform infrared-attenuated total reflectance (FTIR-ATR), Fourier transform Raman (FT-Raman) and proton nuclear magnetic resonance (1H NMR) spectroscopies. The attachment of PMMA to AuNPs showed a tendency for AuNPs to associate with the PMMA structures formed, though significant aggregation occurred. Interestingly, thiol functionalised end-group PMMA showed very little aggregation of AuNPs. The spherical polymer-AuNP structures did not vary in size with variations in PMMA MWD. The PMMA-AuNP structures were characterised using scanning electron microscopy (SEM), transition electron microscopy (TEM), energy dispersive X-ray analysis (EDAX) and UV-vis spectroscopy. The surface confined ATRP grafting of PMMA from initiator functionalised AuNPs was polymerised in both homogeneous and heterogeneous media. 11,11’- dithiobis[1-(2-bromo-2-methylpropionyloxy)undecane] (DSBr) was used as the surface-confined initiator and was synthesised in a three step procedure from mercaptoundecanol (MUD). All compounds were characterised by 1H NMR, FTIR-ATR and Raman spectroscopies. The grafting in homogeneous media resulted in amorphous PMMA with significant AuNP aggregation. Individually grafted AuNPs were difficult to separate and characterise, though SEM, TEM, EDAX and UV-vis spectroscopy was used. The heterogeneous polymerisation did not produce grafted AuNPs as characterised by SEM and EDAX. The encapsulation of AuNPs within PMMA latexes through the process of photoinitiated miniemulsion polymerisation was successfully achieved. Initially, photoinitiated miniemulsion polymerisation was conducted as a viable low temperature method of miniemulsion initiation. This proved successful producing a stable PMMA with good conversion efficiency and narrow particle size distribution (PSD). This is the first report of such a system. The photo-initiated technique was further optimised and AuNPs were included into the miniemulsion. AuNP encapsulation was very effective, producing reproducible AuNP encapsulated PMMA latexes. Again, this is the first reported case of this. The latexes were characterised by TEM, SEM, GPC, gravimetric analysis and dynamic light scattering (DLS).

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Many studies in the area of project management and social networks have identified the significance of project knowledge transfer within and between projects. However, only few studies have examined the intra- and inter-projects knowledge transfer activities. Knowledge in projects can be transferred via face-to-face interactions on the one hand, and via IT-based tools on the other. Although companies have allocated many resources to the IT tools, it has been found that they are not always effectively utilised, and people prefer to look for knowledge using social face-to-face interactions. This paper explores how to effectively leverage two alternative knowledge transfer techniques, face-to-face and IT-based tools to facilitate knowledge transfer and enhance knowledge creation for intra- and inter-project knowledge transfer. The paper extends the previous research on the relationships between and within teams by examining the project’s external and internal knowledge networks concurrently. Social network qualitative analysis, using a case study within a small-medium enterprise, was used to examine the knowledge transfer activities within and between projects, and to investigate knowledge transfer techniques. This paper demonstrates the significance of overlapping employees working simultaneously on two or more projects and their impact on facilitating knowledge transfer between projects within a small/medium organisation. This research is also crucial to gaining better understanding of different knowledge transfer techniques used for intra- and inter-project knowledge exchange. The research provides recommendations on how to achieve better knowledge transfer within and between projects in order to fully utilise a project’s knowledge and achieve better project performance.

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Automatic recognition of people is an active field of research with important forensic and security applications. In these applications, it is not always possible for the subject to be in close proximity to the system. Voice represents a human behavioural trait which can be used to recognise people in such situations. Automatic Speaker Verification (ASV) is the process of verifying a persons identity through the analysis of their speech and enables recognition of a subject at a distance over a telephone channel { wired or wireless. A significant amount of research has focussed on the application of Gaussian mixture model (GMM) techniques to speaker verification systems providing state-of-the-art performance. GMM's are a type of generative classifier trained to model the probability distribution of the features used to represent a speaker. Recently introduced to the field of ASV research is the support vector machine (SVM). An SVM is a discriminative classifier requiring examples from both positive and negative classes to train a speaker model. The SVM is based on margin maximisation whereby a hyperplane attempts to separate classes in a high dimensional space. SVMs applied to the task of speaker verification have shown high potential, particularly when used to complement current GMM-based techniques in hybrid systems. This work aims to improve the performance of ASV systems using novel and innovative SVM-based techniques. Research was divided into three main themes: session variability compensation for SVMs; unsupervised model adaptation; and impostor dataset selection. The first theme investigated the differences between the GMM and SVM domains for the modelling of session variability | an aspect crucial for robust speaker verification. Techniques developed to improve the robustness of GMMbased classification were shown to bring about similar benefits to discriminative SVM classification through their integration in the hybrid GMM mean supervector SVM classifier. Further, the domains for the modelling of session variation were contrasted to find a number of common factors, however, the SVM-domain consistently provided marginally better session variation compensation. Minimal complementary information was found between the techniques due to the similarities in how they achieved their objectives. The second theme saw the proposal of a novel model for the purpose of session variation compensation in ASV systems. Continuous progressive model adaptation attempts to improve speaker models by retraining them after exploiting all encountered test utterances during normal use of the system. The introduction of the weight-based factor analysis model provided significant performance improvements of over 60% in an unsupervised scenario. SVM-based classification was then integrated into the progressive system providing further benefits in performance over the GMM counterpart. Analysis demonstrated that SVMs also hold several beneficial characteristics to the task of unsupervised model adaptation prompting further research in the area. In pursuing the final theme, an innovative background dataset selection technique was developed. This technique selects the most appropriate subset of examples from a large and diverse set of candidate impostor observations for use as the SVM background by exploiting the SVM training process. This selection was performed on a per-observation basis so as to overcome the shortcoming of the traditional heuristic-based approach to dataset selection. Results demonstrate the approach to provide performance improvements over both the use of the complete candidate dataset and the best heuristically-selected dataset whilst being only a fraction of the size. The refined dataset was also shown to generalise well to unseen corpora and be highly applicable to the selection of impostor cohorts required in alternate techniques for speaker verification.