Emergence in interactive art

This thesis is concerned with creating and evaluating interactive art systems that facilitate emergent participant experiences. For the purposes of this research, interactive art is the computer based arts involving physical participation from the audience, while emergence is when a new form or concept appears that was not directly implied by the context from which it arose. This emergent ‘whole’ is more than a simple sum of its parts. The research aims to develop understanding of the nature of emergent experiences that might arise during participant interaction with interactive art systems. It also aims to understand the design issues surrounding the creation of these systems. The approach used is Practice-based, integrating practice, evaluation and theoretical research. Practice used methods from Reflection-in-action and Iterative design to create two interactive art systems: Glass Pond and +-now. Creation of +-now resulted in a novel method for instantiating emergent shapes. Both art works were also evaluated in exploratory studies. In addition, a main study with 30 participants was conducted on participant interaction with +-now. These sessions were video recorded and participants were interviewed about their experience. Recordings were transcribed and analysed using Grounded theory methods. Emergent participant experiences were identified and classified using a taxonomy of emergence in interactive art. This taxonomy draws on theoretical research. The outcomes of this Practice-based research are summarised as follows. Two interactive art systems, where the second work clearly facilitates emergent interaction, were created. Their creation involved the development of a novel method for instantiating emergent shapes and it informed aesthetic and design issues surrounding interactive art systems for emergence. A taxonomy of emergence in interactive art was also created. Other outcomes are the evaluation findings about participant experiences, including different types of emergence experienced and the coding schemes produced during data analysis.

The Growing Pains of Data Breach Notification Law

Mandatory data breach notification laws are a novel statutory solution in relation to organizational protections of personal information. They require organizations which have suffered a breach of security involving personal information to notif'y those persons whose information may have been affected. These laws originated in the state based legislatures of the United States during the last decade and have subsequently garnered worldwide legislative interest. Despite their perceived utility, mandatory data breach notification laws have several conceptual and practical concems that limit the scope of their applicability, particularly in relation to existing information privacy law regimes. We outline these concerns, and in doing so, we contend that while mandatory data breach notification laws have many useful facets, their utility as an 'add-on' to enhance the failings of current information privacy law frameworks should not necessarily be taken for granted.

Young children’s metarepresentational competence in data modelling

longitudinal study of data modelling across grades 1-3. The activity engaged children in designing, implementing, and analysing a survey about their new playground. Data modelling involves investigations of meaningful phenomena, deciding what is worthy of attention (identifying complex attributes), and then progressing to organising, structuring, visualising, and representing data. The core components of data modelling addressed here are children’s structuring and representing of data, with a focus on their display of metarepresentational competence (diSessa, 2004). Such competence includes students’ abilities to invent or design a variety of new representations, explain their creations, understand the role they play, and critique and compare the adequacy of representations. Reported here are the ways in which the children structured and represented their data, the metarepresentational competence displayed, and links between their metarepresentational competence and conceptual competence.

Contextualizing a university-school STEM education collaboration : distributed and self-activated leadership for project outcomes

Implementing educational reform requires partnerships, and university-school collaborations in the form of investigative and experimental projects can aim to determine the practicalities of reform. However, there are funded projects that do not achieve intended outcomes. In the context of a new reform initiative in education, namely, science, technology, engineering and mathematics (STEM) education, this article explores the management of a government-funded project. In a university school partnership for STEM education, how can leadership be distributed for achieving project outcomes? Participants included university personnel from different STEM areas, school teachers and school executives. Data collected included observations, interviews, resource materials, and video and photographic images. Findings indicated that leadership roles were distributed and selfactivated by project partners according to their areas of expertise and proximal activeness to the project phases, that is: (1) establishing partnerships; (2) planning and collaboration; (3) project implementation; and (4) project evaluation and further initiatives. Leadership can be intentional and unintentional within project phases, and understanding how leadership can be distributed and selfactivated more purposefully may aid in generating more expedient project outcomes.

Between formal and informal : the shakeout in China’s online video industry

While a rich body of literature in television and film studies and media policy studies has tended to focus on the media activities in the formal sector, we know much less about informal media activities, its influence on state policies, as well as the dynamics between the formal and the informal sectors. This article examines these issues with reference to a particularly revealing period following a large-scale government crackdown on peer-to-peer video sharing sites in China in 2008. By analyzing the aim and consequences of the state action, I point to the counter-productive effect in terms of cultural loss and the resurgence of offline piracy; and show the positive impact on forcing the informal into the formal sector, and pressuring the formal to innovate. Meanwhile, an increasing rapprochement between professional and user-created content leads to a new relationship between formal and informal sectors. This case demonstrates the importance of considering the dynamics between the two sectors. It also offers compelling evidence of the role of the informal sector in engendering state action, which in turn impacted on the co-evolution of the formal and the informal sectors.

mCOPA: analysis of heterogeneous features in cancer expression data

Background Cancer outlier profile analysis (COPA) has proven to be an effective approach to analyzing cancer expression data, leading to the discovery of the TMPRSS2 and ETS family gene fusion events in prostate cancer. However, the original COPA algorithm did not identify down-regulated outliers, and the currently available R package implementing the method is similarly restricted to the analysis of over-expressed outliers. Here we present a modified outlier detection method, mCOPA, which contains refinements to the outlier-detection algorithm, identifies both over- and under-expressed outliers, is freely available, and can be applied to any expression dataset. Results We compare our method to other feature-selection approaches, and demonstrate that mCOPA frequently selects more-informative features than do differential expression or variance-based feature selection approaches, and is able to recover observed clinical subtypes more consistently. We demonstrate the application of mCOPA to prostate cancer expression data, and explore the use of outliers in clustering, pathway analysis, and the identification of tumour suppressors. We analyse the under-expressed outliers to identify known and novel prostate cancer tumour suppressor genes, validating these against data in Oncomine and the Cancer Gene Index. We also demonstrate how a combination of outlier analysis and pathway analysis can identify molecular mechanisms disrupted in individual tumours. Conclusions We demonstrate that mCOPA offers advantages, compared to differential expression or variance, in selecting outlier features, and that the features so selected are better able to assign samples to clinically annotated subtypes. Further, we show that the biology explored by outlier analysis differs from that uncovered in differential expression or variance analysis. mCOPA is an important new tool for the exploration of cancer datasets and the discovery of new cancer subtypes, and can be combined with pathway and functional analysis approaches to discover mechanisms underpinning heterogeneity in cancers

Intercultural competence in engineering education : who are we teaching?

BACKGROUND There is little doubt that our engineering graduates’ ability to identify cultural differences and their potential to impact on engineering projects, and to work effectively with these differences is of key importance in the modern engineering practice. Within engineering degree programs themselves there is also a significant need to recognise the impact of changing student and staff profiles on what happens in the classroom. The research described in this paper forms part of a larger project exploring issues of intercultural competence in engineering. PURPOSE This paper presents an observational and survey study of undergraduate and postgraduate engineering students from four institutions working in groups on tasks with a purely technical focus, or with a cultural and humanitarian element. The study sought to explore how students rate their own intercultural competence and team process and whether any differences exist depending on the nature of the task they are working on. We also investigated whether any differences were evident between groups of first year, second year and postgraduate students. DESIGN/METHOD The study used the miniCQS instrument (Ang & Van Dyne, 2008) and a Bales Interaction Process Analysis based scale (Bales, 1950; Carney, 1976) to collect students self ratings of group process, task management, and cultural experience and behaviour. The Bales IPA was also used for coding video observations of students working in groups. Survey data were used to form descriptive variables to compare outcomes across the different tasks and contexts. Observations analysed in Nvivo were used to provide commentary and additional detail on the quantitative data. RESULTS The results of the survey indicated consistent mean scores on each survey item for each group of students, despite vastly different tasks, student backgrounds and educational contexts. Some small, statistically significant mean differences existed, offering some basic insights into how task and student group composition could affect self ratings. Overall though, the results suggest minimal shift in how students view group function and their intercultural experience, irrespective of differing educational experience. CONCLUSIONS The survey results, contrasted with group observations, indicate that either students are not translating their experience (in the group tasks) into critical self assessment of their cultural competence and teamwork, or that they become more critical of team performance and cultural competence as their competence in these areas grows, so their ratings remain consistent. Both outcomes indicate that students need more intensive guidance to build their critical self and peer assessment skills in these areas irrespective of their year level of study.

WebPut : Efficient web-based data imputation

In this paper, we present WebPut, a prototype system that adopts a novel web-based approach to the data imputation problem. Towards this, Webput utilizes the available information in an incomplete database in conjunction with the data consistency principle. Moreover, WebPut extends effective Information Extraction (IE) methods for the purpose of formulating web search queries that are capable of effectively retrieving missing values with high accuracy. WebPut employs a confidence-based scheme that efficiently leverages our suite of data imputation queries to automatically select the most effective imputation query for each missing value. A greedy iterative algorithm is also proposed to schedule the imputation order of the different missing values in a database, and in turn the issuing of their corresponding imputation queries, for improving the accuracy and efficiency of WebPut. Experiments based on several real-world data collections demonstrate that WebPut outperforms existing approaches.

Input-orientated data envelopment analysis framework for measuring and decomposing economic, environmental and ecological efficiency : an application to OECD agriculture

This paper presents an input-orientated data envelopment analysis (DEA) framework which allows the measurement and decomposition of economic, environmental and ecological efficiency levels in agricultural production across different countries. Economic, environmental and ecological optimisations search for optimal input combinations that minimise total costs, total amount of nutrients, and total amount of cumulative exergy contained in inputs respectively. The application of the framework to an agricultural dataset of 30 OECD countries revealed that (i) there was significant scope to make their agricultural production systemsmore environmentally and ecologically sustainable; (ii) the improvement in the environmental and ecological sustainability could be achieved by being more technically efficient and, even more significantly, by changing the input combinations; (iii) the rankings of sustainability varied significantly across OECD countries within frontier-based environmental and ecological efficiency measures and between frontier-based measures and indicators.

Participatory content creation and collective intelligence in Rio de Janeiro's favelas [Virtual presentation]

This proposal combines ethnographic techniques and discourse studies to investigating a collective of people engaged with audiovisual productions who collaborate in Curta Favela’s workshops in Rio de Janeiro’s favelas. ‘Favela’ is often translated simply as ‘slum’ or ‘shantytown’, but these terms connote negative characteristics such as shortage, poverty, and deprivation referring to favelas which end up stigmatizing these low income suburbs. Curta Favela (Favela Shorts) is an independent project which all participants join to use photography and participatory audiovisual production as a tool for social change and raising consciousness. As cameras are not affordable for favelas dwellers, Curta Favela’s volunteers teach favela residents how they can use their mobile phones and compact cameras to take pictures and make movies, and afterwards, how they can edit the data using free editing video software programs and publish it on the Internet. To record audio, they use their mp3 or mobile phones. The main aim of this study is to shed light not only on how this project operates, but also to highlight how collective intelligence can be used as a way of fighting against the lack of basic resources.

Participatory content creation and collective intelligence in Rio de Janeiro's favelas

This proposal combines ethnographic techniques and discourse studies to investigate a collective of people engaged with audiovisual productions who collaborate in Curta Favela’s workshops in Rio de Janeiro’s favelas. ‘Favela’ is often translated simply as ‘slum’ or ‘shantytown’, but these terms connote negative characteristics such as shortage, poverty, and deprivation which end up stigmatizing these low income suburbs. Curta Favela (Favela Shorts) is an independent project in which all participants join to use photography and participatory audiovisual production as tools for social change and to raise consciousness. As cameras are not affordable for favela dwellers, Curta Favela’s volunteers teach favela residents how they can use their mobile phones and compact cameras to take pictures and make movies, and afterwards, how they can edit the data using free editing video software programs and publish it on the Internet. To record audio, they use their mp3 or mobile phones. The main aim of this study is to shed light not only on how this project operates, but also to highlight how collective intelligence can be used as a way of fighting against a lack of basic resources.

Anomalous event detection using a semi-two dimensional hidden Markov model

The rapid increase in the deployment of CCTV systems has led to a greater demand for algorithms that are able to process incoming video feeds. These algorithms are designed to extract information of interest for human operators. During the past several years, there has been a large effort to detect abnormal activities through computer vision techniques. Typically, the problem is formulated as a novelty detection task where the system is trained on normal data and is required to detect events which do not fit the learned `normal' model. Many researchers have tried various sets of features to train different learning models to detect abnormal behaviour in video footage. In this work we propose using a Semi-2D Hidden Markov Model (HMM) to model the normal activities of people. The outliers of the model with insufficient likelihood are identified as abnormal activities. Our Semi-2D HMM is designed to model both the temporal and spatial causalities of the crowd behaviour by assuming the current state of the Hidden Markov Model depends not only on the previous state in the temporal direction, but also on the previous states of the adjacent spatial locations. Two different HMMs are trained to model both the vertical and horizontal spatial causal information. Location features, flow features and optical flow textures are used as the features for the model. The proposed approach is evaluated using the publicly available UCSD datasets and we demonstrate improved performance compared to other state of the art methods.

What if you're really different? Case studies of children with high functioning autism participating in the Get REAL programme who had atypical learning trajectories.

Evaluation of the Get REAL programme in an inclusive primary school setting has indicated its effectiveness in promoting pro-social behaviour for children with high functioning Autism. However, two children with co-morbid diagnoses and complex personal circumstances showed less consistent improvements. In order to explain their unique trajectories, not readily derived from quantitative studies, an exploratory case study approach was used to examine contextual influences on patterns of progress. Multiple data sources included coded video footage from the Get REAL programme, school reports on conduct, and parents and classroom teacher reports using the Strengths and Difficulties Questionnaire. While results provide support for the efficacy of the Get REAL programme for the two children, they also highlight the value of co-ordinated strategies and collaborative individualised approaches in more complex cases. This paper outlines the Get REAL intervention and a range of other school and support agency strategies impacting progress.