Media innovations, user innovations, societal innovations

As the Journal of Media Innovations comes into existence, this article reflects on the first and most obvious question: just what do we mean by “media innovations”? Drawing on the examples of a range of recent innovations in media technologies and practices, initiated by a variety of media audiences, users, professionals, and providers, it explores the interplay between the different drivers of innovation and the effects of such innovation on the complex frameworks of contemporary society and the media ecology which supports it. In doing so, this article makes a number of key observations: first, it notes that media innovation is an innovation in media practices at least as much as in media technologies, and that changes to the practices of media both reflect and promote societal changes as well – media innovations are never just media technology innovations. Second, it shows that the continuing mediatisation of society, and the shift towards a more widespread participation of ordinary users as active content creators and media innovators, make it all the more important to investigate in detail these interlinked, incremental, everyday processes of media and societal change – media innovations are almost always also user innovations. Finally, it suggests that a full understanding of these processes as they unfold across diverse interleaved media spaces and complex societal structures necessarily requires a holistic perspective on media innovations, which considers the contemporary media ecology as a crucial constitutive element of societal structures and seeks to trace the repercussions of innovations across both media and society – media innovations are inextricably interlinked with societal innovations (even if, at times, they may not be considered to be improvements to the status quo).

Acceptability-based QoE management for user-centric mobile video delivery : a field study evaluation

Effective Quality of Experience (QoE) management for mobile video delivery – to optimize overall user experience while adapting to heterogeneous use contexts – is still a big challenge to date. This paper proposes a mobile video delivery system to emphasize the use of acceptability as the main indicator of QoE to manage the end-to-end factors in delivering mobile video services. The first contribution is a novel framework for user-centric mobile video system that is based on acceptability-based QoE (A-QoE) prediction models, which were derived from comprehensive subjective studies. The second contribution is results from a field study that evaluates the user experience of the proposed system during realistic usage circumstances, addressing the impacts of perceived video quality, loading speed, interest in content, viewing locations, network bandwidth, display devices, and different video coding approaches, including region-of-interest (ROI) enhancement and center zooming

Interactive content analysis : evaluating interactive variants of non-negative Matrix Factorisation and Latent Dirichlet Allocation as qualitative content analysis aids

This thesis addressed issues that have prevented qualitative researchers from using thematic discovery algorithms. The central hypothesis evaluated whether allowing qualitative researchers to interact with thematic discovery algorithms and incorporate domain knowledge improved their ability to address research questions and trust the derived themes. Non-negative Matrix Factorisation and Latent Dirichlet Allocation find latent themes within document collections but these algorithms are rarely used, because qualitative researchers do not trust and cannot interact with the themes that are automatically generated. The research determined the types of interactivity that qualitative researchers require and then evaluated interactive algorithms that matched these requirements. Theoretical contributions included the articulation of design guidelines for interactive thematic discovery algorithms, the development of an Evaluation Model and a Conceptual Framework for Interactive Content Analysis.

User perceived video quality modelling on mobile devices for Vp9 and H265 encoders

This study constructs performance prediction models to estimate the end-user perceived video quality on mobile devices for the latest video encoding techniques –VP9 and H.265. Both subjective and objective video quality assessments were carried out for collecting data and selecting the most desirable predictors. Using statistical regression, two models were generated to achieve 94.5% and 91.5% of prediction accuracies respectively, depending on whether the predictor derived from the objective assessment is involved. These proposed models can be directly used by media industries for video quality estimation, and will ultimately help them to ensure a positive end-user quality of experience on future mobile devices after the adaptation of the latest video encoding technologies.

The responsibility of intermediaries: Emerging IP protection schemes, from Content ID, to three-strikes and follow-the-money

The only effective and scalable way to regulate the actions of people on the internet is through online intermediaries. These are the institutions that facilitate communication: internet service providers, search engines, content hosts, and social networks. Governments, private firms, and civil society organisations are increasingly seeking to influence these intermediaries to take more responsibility to prevent or respond to IP infringements. Around the world, intermediaries are increasingly subject to a variety of obligations to help enforce IP rights, ranging from informal social and governmental pressure, to industry codes and private negotiated agreements, to formal legislative schemes. This paper provides an overview of this emerging shift in regulatory approaches, away from legal liability and towards increased responsibilities for intermediaries. This shift straddles two different potential futures: an optimistic set of more effective, more efficient mechanisms for regulating user behaviour, and a dystopian vision of rule by algorithm and private power, without the legitimising influence of the rule of law.

Comparative kinomics of human and chimpanzee reveal unique kinship and functional diversity generated by new domain combinations

Background: Phosphorylation by protein kinases is a common event in many cellular processes. Further, many kinases perform specialized roles and are regulated by non-kinase domains tethered to kinase domain. Perturbation in the regulation of kinases leads to malignancy. We have identified and analysed putative protein kinases encoded in the genome of chimpanzee which is a close evolutionary relative of human. Result: The shared core biology between chimpanzee and human is characterized by many orthologous protein kinases which are involved in conserved pathways. Domain architectures specific to chimp/human kinases have been observed. Chimp kinases with unique domain architectures are characterized by deletion of one or more non-kinase domains in the human kinases. Interestingly, counterparts of some of the multi-domain human kinases in chimp are characterized by identical domain architectures but with kinase-like non-kinase domain. Remarkably, out of 587 chimpanzee kinases no human orthologue with greater than 95% sequence identity could be identified for 160 kinases. Variations in chimpanzee kinases compared to human kinases are brought about also by differences in functions of domains tethered to the catalytic kinase domain. For example, the heterodimer forming PB1 domain related to the fold of ubiquitin/Ras-binding domain is seen uniquely tethered to PKC-like chimpanzee kinase. Conclusion: Though the chimpanzee and human are evolutionary very close, there are chimpanzee kinases with no close counterpart in the human suggesting differences in their functions. This analysis provides a direction for experimental analysis of human and chimpanzee protein kinases in order to enhance our understanding on their specific biological roles.

Shifting the Focus. Incorporating knowledge about Aboriginal engineering into main stream content

BACKGROUND OR CONTEXT The concept of 'Aboriginal engineering' has had little exposure in conventional engineering education programs, despite more than 40,000 years of active human engagement with the diverse Australian environment. The work reported in this paper began with the premise that Indigenous Student Support Through Indigenous Perspectives Embedded in Engineering Curricula (Goldfinch, et al 2013) would provide a clear and replicable means of encouraging Aboriginal teenagers to consider a career in engineering. Although that remains a key outcome of this OLT project, the direction taken by the research had led to additional insights and perspectives that have wide implications for engineering education more generally. There has only been passing reference to the achievements of Aboriginal engineering in current texts, and the very absence of such references was a prompt to explore further as our work developed. PURPOSE OR GOAL Project goals focused on curriculum-based change, including development of a model for inclusive teaching spaces, and study units employing key features of the model. As work progressed we found we needed to understand more about the principles and practices informing the development of pre-contact Aboriginal engineering strategies for sustaining life and society within the landscape of this often harsh continent. We also found ourselves being asked 'what engineering did Aboriginal cultures have?' Finding that there are no easy-to- access answers, we began researching the question, while continuing to engage with specific curriculum trials. APPROACH Stakeholders in the project had been identified as engineering educators, potential Aboriginal students and Aboriginal communities local to Universities involved in the project. We realised, early on, that at least one more group was involved - all the non-Aboriginal students in engineering classes. This realisation, coupled with recognition of the need to understand Aboriginal engineering as a set of viable, long term practices, altered the focus of our efforts. Rather than focusing primarily on finding ways to attract Aboriginal engineering students, the shift has been towards evolving ways of including knowledge about Aboriginal practices and principles in relevant engineering content. DISCUSSION This paper introduces the model resulting from the work of this project, explores its potential influence on engineering curriculum development and reports on implementation strategies. The model is a static representation of a dynamic and cyclic approach to engaging with Aboriginal engineering through contact with local communities in regard to building knowledge about the social beliefs underlying Aboriginal engineering principles and practices. Ways to engage engineering educators, students and the wider community are evolving through the continuing work of the project team and will be reported in more detail in the paper. RECOMMENDATIONS/IMPLICATIONS/CONCLUSION While engineering may be considered by some to be agnostic in regard to culture and social issues, the work of this project is drawing attention to the importance of including such issues into curriculum materials at a number of levels of complexity. The paper will introduce and explore the central concepts of the research completed to date, as well as suggesting ways in which engineering educators can extend their knowledge and understanding of Aboriginal engineering principles in the context of their own specialisations.

Abstract concepts made real: A pilot study examining pedagogical approaches in thermodynamics tutorials

BACKGROUND OR CONTEXT Thermodynamics is a core concept for mechanical engineers yet notoriously difficult. Evidence suggests students struggle to understand and apply the core fundamental concepts of thermodynamics with analysis indicating a problem with student learning/engagement. A contributing factor is that thermodynamics is a ‘science involving concepts based on experiments’ (Mayhew 1990) with subject matter that cannot be completely defined a priori. To succeed, students must engage in a deep-holistic approach while taking ownership of their learning. The difficulty in achieving this often manifests itself in students ‘not getting’ the principles and declaring thermodynamics ‘hard’. PURPOSE OR GOAL Traditionally, students practice and “learn” the application of thermodynamics in their tutorials, however these do not consider prior conceptions (Holman & Pilling 2004). As ‘hands on’ learning is the desired outcome of tutorials it is pertinent to study methods of improving their efficacy. Within the Australian context, the format of thermodynamics tutorials has remained relatively unchanged over the decades, relying anecdotally on a primarily didactic pedagogical approach. Such approaches are not conducive to deep learning (Ramsden 2003) with students often disengaged from the learning process. Evidence suggests (Haglund & Jeppsson 2012), however, that a deeper level and ownership of learning can be achieved using a more constructivist approach for example through self generated analogies. This pilot study aimed to collect data to support the hypothesis that the ‘difficulty’ of thermodynamics is associated with the pedagogical approach of tutorials rather than actual difficulty in subject content or deficiency in students. APPROACH Successful application of thermodynamic principles requires solid knowledge of the core concepts. Typically, tutorial sessions guide students in this application. However, a lack of deep and comprehensive understanding can lead to student confusion in the applications resulting in the learning of the ‘process’ of application without understanding ‘why’. The aim of this study was to gain empirical data on student learning of both concepts and application, within thermodynamic tutorials. The approach taken for data collection and analysis was: - 1 Four concurrent tutorial streams were timetabled to examine student engagement/learning in traditional ‘didactic’ (3 weeks) and non-traditional (3 weeks). In each week, two of the selected four sessions were traditional and two non-traditional. This provided a control group for each week. - 2 The non-traditional tutorials involved activities designed to promote student-centered deep learning. Specific pedagogies employed were: self-generated analogies, constructivist, peer-to-peer learning, inquiry based learning, ownership of learning and active learning. - 3 After a three-week period, teaching styles of the selected groups was switched, to allow each group to experience both approaches with the same tutor. This also acted to mimimise any influence of tutor personality / style on the data. - 4 At the conclusion of the trial participants completed a ‘5 minute essay’ on how they liked the sessions, a small questionnaire, modelled on the modified (Christo & Hoang, 2013)SPQ designed by Biggs (1987) and a small formative quiz to gauge the level of learning achieved. DISCUSSION Preliminary results indicate that overall students respond positively to in class demonstrations (inquiry based learning), and active learning activities. Within the active learning exercises, the current data suggests students preferred individual rather than group or peer-to-peer activities. Preliminary results from the open-ended questions such as “What did you like most/least about this tutorial” and “do you have other comments on how this tutorial could better facilitate your learning”, however, indicated polarising views on the nontraditional tutorial. Some student’s responded that they really like the format and emphasis on understanding the concepts, while others were very vocal that that ‘hated’ the style and just wanted the solutions to be presented by the tutor. RECOMMENDATIONS/IMPLICATIONS/CONCLUSION Preliminary results indicated a mixed, but overall positive response by students with more collaborative tutorials employing tasks promoting inquiry based, peer-to-peer, active, and ownership of learning activities. Preliminary results from student feedback supports evidence that students learn differently, and running tutorials focusing on only one pedagogical approached (typically didactic) may not be beneficial to all students. Further, preliminary data suggests that the learning / teaching style of both students and tutor are important to promoting deep learning in students. Data collection is still ongoing and scheduled for completion at the end of First Semester (Australian academic calendar). The final paper will examine in more detail the results and analysis of this project.

High-throughput prediction of eucalypt lignin syringyl/guaiacyl content using multivariate analysis: a comparison between mid-infrared, near-infrared, and Raman spectroscopies for model development

BACKGROUND: In order to rapidly and efficiently screen potential biofuel feedstock candidates for quintessential traits, robust high-throughput analytical techniques must be developed and honed. The traditional methods of measuring lignin syringyl/guaiacyl (S/G) ratio can be laborious, involve hazardous reagents, and/or be destructive. Vibrational spectroscopy can furnish high-throughput instrumentation without the limitations of the traditional techniques. Spectral data from mid-infrared, near-infrared, and Raman spectroscopies was combined with S/G ratios, obtained using pyrolysis molecular beam mass spectrometry, from 245 different eucalypt and Acacia trees across 17 species. Iterations of spectral processing allowed the assembly of robust predictive models using partial least squares (PLS). RESULTS: The PLS models were rigorously evaluated using three different randomly generated calibration and validation sets for each spectral processing approach. Root mean standard errors of prediction for validation sets were lowest for models comprised of Raman (0.13 to 0.16) and mid-infrared (0.13 to 0.15) spectral data, while near-infrared spectroscopy led to more erroneous predictions (0.18 to 0.21). Correlation coefficients (r) for the validation sets followed a similar pattern: Raman (0.89 to 0.91), mid-infrared (0.87 to 0.91), and near-infrared (0.79 to 0.82). These statistics signify that Raman and mid-infrared spectroscopy led to the most accurate predictions of S/G ratio in a diverse consortium of feedstocks. CONCLUSION: Eucalypts present an attractive option for biofuel and biochemical production. Given the assortment of over 900 different species of Eucalyptus and Corymbia, in addition to various species of Acacia, it is necessary to isolate those possessing ideal biofuel traits. This research has demonstrated the validity of vibrational spectroscopy to efficiently partition different potential biofuel feedstocks according to lignin S/G ratio, significantly reducing experiment and analysis time and expense while providing non-destructive, accurate, global, predictive models encompassing a diverse array of feedstocks.

Clustering Users of Online Content Service

Online content services can greatly benefit from personalisation features that enable delivery of content that is suited to each user's specific interests. This thesis presents a system that applies text analysis and user modeling techniques in an online news service for the purpose of personalisation and user interest analysis. The system creates a detailed thematic profile for each content item and observes user's actions towards content items to learn user's preferences. A handcrafted taxonomy of concepts, or ontology, is used in profile formation to extract relevant concepts from the text. User preference learning is automatic and there is no need for explicit preference settings or ratings from the user. Learned user profiles are segmented into interest groups using clustering techniques with the objective of providing a source of information for the service provider. Some theoretical background for chosen techniques is presented while the main focus is in finding practical solutions to some of the current information needs, which are not optimally served with traditional techniques.

Selective dissemination of XML documents based on genetically learned user model and Support Vector Machines

Extensible Markup Language ( XML) has emerged as a medium for interoperability over the Internet. As the number of documents published in the form of XML is increasing, there is a need for selective dissemination of XML documents based on user interests. In the proposed technique, a combination of Adaptive Genetic Algorithms and multi class Support Vector Machine ( SVM) is used to learn a user model. Based on the feedback from the users, the system automatically adapts to the user's preference and interests. The user model and a similarity metric are used for selective dissemination of a continuous stream of XML documents. Experimental evaluations performed over a wide range of XML documents, indicate that the proposed approach significantly improves the performance of the selective dissemination task, with respect to accuracy and efficiency.

Towards a typology of hashtag publics: A large-scale comparative study of user engagement across trending topics

Twitter’s hashtag functionality is now used for a very wide variety of purposes, from covering crises and other breaking news events through gathering an instant community around shared media texts (such as sporting events and TV broadcasts) to signalling emotive states from amusement to despair. These divergent uses of the hashtag are increasingly recognised in the literature, with attention paid especially to the ability for hashtags to facilitate the creation of ad hoc or hashtag publics. A more comprehensive understanding of these different uses of hashtags has yet to be developed, however. Previous research has explored the potential for a systematic analysis of the quantitative metrics that could be generated from processing a series of hashtag datasets. Such research found, for example, that crisis-related hashtags exhibited a significantly larger incidence of retweets and tweets containing URLs than hashtags relating to televised events, and on this basis hypothesised that the information-seeking and -sharing behaviours of Twitter users in such different contexts were substantially divergent. This article updates such study and their methodology by examining the communicative metrics of a considerably larger and more diverse number of hashtag datasets, compiled over the past five years. This provides an opportunity both to confirm earlier findings, as well as to explore whether hashtag use practices may have shifted subsequently as Twitter’s userbase has developed further; it also enables the identification of further hashtag types beyond the “crisis” and “mainstream media event” types outlined to date. The article also explores the presence of such patterns beyond recognised hashtags, by incorporating an analysis of a number of keyword-based datasets. This large-scale, comparative approach contributes towards the establishment of a more comprehensive typology of hashtags and their publics, and the metrics it describes will also be able to be used to classify new hashtags emerging in the future. In turn, this may enable researchers to develop systems for automatically distinguishing newly trending topics into a number of event types, which may be useful for example for the automatic detection of acute crises and other breaking news events.

Selective dissemination of XML documents based on genetically learned user model and Support Vector Machines

Extensible Markup Language ( XML) has emerged as a medium for interoperability over the Internet. As the number of documents published in the form of XML is increasing, there is a need for selective dissemination of XML documents based on user interests. In the proposed technique, a combination of Adaptive Genetic Algorithms and multi class Support Vector Machine ( SVM) is used to learn a user model. Based on the feedback from the users, the system automatically adapts to the user's preference and interests. The user model and a similarity metric are used for selective dissemination of a continuous stream of XML documents. Experimental evaluations performed over a wide range of XML documents, indicate that the proposed approach significantly improves the performance of the selective dissemination task, with respect to accuracy and efficiency.

Discovering user preferences by using time entries in click-through data to improve search engine results

The search engine log files have been used to gather direct user feedback on the relevancy of the documents presented in the results page. Typically the relative position of the clicks gathered from the log files is used a proxy for the direct user feedback. In this paper we identify reasons for the incompleteness of the relative position of clicks for deciphering the user preferences. Hence, we propose the use of time spent by the user in reading through the document as indicative of user preference for a document with respect to a query. Also, we identify the issues involved in using the time measure and propose means to address them.

Flow Generated By Pitched Blade Turbines Ii: Simulation Using Κ-Ε Model

Experimental data on average velocity and turbulence intensity generated by pitched blade downflow turbines (PTD) were presented in Part I of this paper. Part II presents the results of the simulation of flow generated by PTD The standard κ-ε model along with the boundary conditions developed in the Part 1 have been employed to predict the flow generated by PTD in cylindrical baffled vessel. This part describes the new software FIAT (Flow In Agitated Tanks) for the prediction of three dimensional flow in stirred tanks. The basis of this software has been described adequately. The influence of grid size, impeller boundary conditions and values of model parameters on the predicted flow have been analysed. The model predictions successfully reproduce the three dimensionality and the other essential characteristics of the flow. The model can be used to improve the overall understanding about the relative distribution of turbulence by PTD in the agitated tank