Children and information communication technologies in the media : a study using moral panic theory

This thesis is an investigation of the media's representation of children and ICT. The study draws on moral panic theory and Queensland newspaper media, to identify the impact of newspaper reporting on the public's perceptions of young people and ICT.

Slicing big data - Twitter, gambling and time sensitive information

Big Data presents many challenges related to volume, whether one is interested in studying past datasets or, even more problematically, attempting to work with live streams of data. The most obvious challenge, in a ‘noisy’ environment such as contemporary social media, is to collect the pertinent information; be that information for a specific study, tweets which can inform emergency services or other responders to an ongoing crisis, or give an advantage to those involved in prediction markets. Often, such a process is iterative, with keywords and hashtags changing with the passage of time, and both collection and analytic methodologies need to be continually adapted to respond to this changing information. While many of the data sets collected and analyzed are preformed, that is they are built around a particular keyword, hashtag, or set of authors, they still contain a large volume of information, much of which is unnecessary for the current purpose and/or potentially useful for future projects. Accordingly, this panel considers methods for separating and combining data to optimize big data research and report findings to stakeholders. The first paper considers possible coding mechanisms for incoming tweets during a crisis, taking a large stream of incoming tweets and selecting which of those need to be immediately placed in front of responders, for manual filtering and possible action. The paper suggests two solutions for this, content analysis and user profiling. In the former case, aspects of the tweet are assigned a score to assess its likely relationship to the topic at hand, and the urgency of the information, whilst the latter attempts to identify those users who are either serving as amplifiers of information or are known as an authoritative source. Through these techniques, the information contained in a large dataset could be filtered down to match the expected capacity of emergency responders, and knowledge as to the core keywords or hashtags relating to the current event is constantly refined for future data collection. The second paper is also concerned with identifying significant tweets, but in this case tweets relevant to particular prediction market; tennis betting. As increasing numbers of professional sports men and women create Twitter accounts to communicate with their fans, information is being shared regarding injuries, form and emotions which have the potential to impact on future results. As has already been demonstrated with leading US sports, such information is extremely valuable. Tennis, as with American Football (NFL) and Baseball (MLB) has paid subscription services which manually filter incoming news sources, including tweets, for information valuable to gamblers, gambling operators, and fantasy sports players. However, whilst such services are still niche operations, much of the value of information is lost by the time it reaches one of these services. The paper thus considers how information could be filtered from twitter user lists and hash tag or keyword monitoring, assessing the value of the source, information, and the prediction markets to which it may relate. The third paper examines methods for collecting Twitter data and following changes in an ongoing, dynamic social movement, such as the Occupy Wall Street movement. It involves the development of technical infrastructure to collect and make the tweets available for exploration and analysis. A strategy to respond to changes in the social movement is also required or the resulting tweets will only reflect the discussions and strategies the movement used at the time the keyword list is created — in a way, keyword creation is part strategy and part art. In this paper we describe strategies for the creation of a social media archive, specifically tweets related to the Occupy Wall Street movement, and methods for continuing to adapt data collection strategies as the movement’s presence in Twitter changes over time. We also discuss the opportunities and methods to extract data smaller slices of data from an archive of social media data to support a multitude of research projects in multiple fields of study. The common theme amongst these papers is that of constructing a data set, filtering it for a specific purpose, and then using the resulting information to aid in future data collection. The intention is that through the papers presented, and subsequent discussion, the panel will inform the wider research community not only on the objectives and limitations of data collection, live analytics, and filtering, but also on current and in-development methodologies that could be adopted by those working with such datasets, and how such approaches could be customized depending on the project stakeholders.

Identity-based signcryption

The notion of identity-based IB cryptography was proposed by Shamir [177] as a specialization of public key PK cryptography which dispensed with the need for cumbersome directories, certificates, and revocation lists.

Multiscale features and information extraction of online strain for long-span bridges

The strain data acquired from structural health monitoring (SHM) systems play an important role in the state monitoring and damage identification of bridges. Due to the environmental complexity of civil structures, a better understanding of the actual strain data will help filling the gap between theoretical/laboratorial results and practical application. In the study, the multi-scale features of strain response are first revealed after abundant investigations on the actual data from two typical long-span bridges. Results show that, strain types at the three typical temporal scales of 10^5, 10^2 and 10^0 sec are caused by temperature change, trains and heavy trucks, and have their respective cut-off frequency in the order of 10^-2, 10^-1 and 10^0 Hz. Multi-resolution analysis and wavelet shrinkage are applied for separating and extracting these strain types. During the above process, two methods for determining thresholds are introduced. The excellent ability of wavelet transform on simultaneously time-frequency analysis leads to an effective information extraction. After extraction, the strain data will be compressed at an attractive ratio. This research may contribute to a further understanding of actual strain data of long-span bridges; also, the proposed extracting methodology is applicable on actual SHM systems.

Fluid registration of diffusion tensor images using information theory

We apply an information-theoretic cost metric, the symmetrized Kullback-Leibler (sKL) divergence, or $J$-divergence, to fluid registration of diffusion tensor images. The difference between diffusion tensors is quantified based on the sKL-divergence of their associated probability density functions (PDFs). Three-dimensional DTI data from 34 subjects were fluidly registered to an optimized target image. To allow large image deformations but preserve image topology, we regularized the flow with a large-deformation diffeomorphic mapping based on the kinematics of a Navier-Stokes fluid. A driving force was developed to minimize the $J$-divergence between the deforming source and target diffusion functions, while reorienting the flowing tensors to preserve fiber topography. In initial experiments, we showed that the sKL-divergence based on full diffusion PDFs is adaptable to higher-order diffusion models, such as high angular resolution diffusion imaging (HARDI). The sKL-divergence was sensitive to subtle differences between two diffusivity profiles, showing promise for nonlinear registration applications and multisubject statistical analysis of HARDI data.

Information theory and one-dimensional disordered conductors

A novel method is proposed to treat the problem of the random resistance of a strictly one-dimensional conductor with static disorder. It is suggested, for the probability distribution of the transfer matrix of the conductor, the distribution of maximum information-entropy, constrained by the following physical requirements: 1) flux conservation, 2) time-reversal invariance and 3) scaling, with the length of the conductor, of the two lowest cumulants of ζ, where = sh2ζ. The preliminary results discussed in the text are in qualitative agreement with those obtained by sophisticated microscopic theories.

Harnessing information from injury narrative in the 'big data' era: Understanding and applying machine learning for injury surveillance

Objective Vast amounts of injury narratives are collected daily and are available electronically in real time and have great potential for use in injury surveillance and evaluation. Machine learning algorithms have been developed to assist in identifying cases and classifying mechanisms leading to injury in a much timelier manner than is possible when relying on manual coding of narratives. The aim of this paper is to describe the background, growth, value, challenges and future directions of machine learning as applied to injury surveillance. Methods This paper reviews key aspects of machine learning using injury narratives, providing a case study to demonstrate an application to an established human-machine learning approach. Results The range of applications and utility of narrative text has increased greatly with advancements in computing techniques over time. Practical and feasible methods exist for semi-automatic classification of injury narratives which are accurate, efficient and meaningful. The human-machine learning approach described in the case study achieved high sensitivity and positive predictive value and reduced the need for human coding to less than one-third of cases in one large occupational injury database. Conclusion The last 20 years have seen a dramatic change in the potential for technological advancements in injury surveillance. Machine learning of ‘big injury narrative data’ opens up many possibilities for expanded sources of data which can provide more comprehensive, ongoing and timely surveillance to inform future injury prevention policy and practice.

Information theory and resistance fluctuations in one-dimensional disordered conductors

A novel method is proposed to treat the problem of the random resistance of a strictly one-dimensional conductor with static disorder. For the probability distribution of the transfer matrix R of the conductor we propose a distribution of maximum information entropy, constrained by the following physical requirements: (1) flux conservation, (2) time-reversal invariance, and (3) scaling with the length of the conductor of the two lowest cumulants of ω, where R=exp(iω→⋅Jbhat). The preliminary results discussed in the text are in qualitative agreement with those obtained by sophisticated microscopic theories.

From Habits to Social Structures : Pragmatism and Contemporary Social Theory

Pragmatism has sometimes been taken as a catchphrase for epistemological stances in which anything goes. However, other authors argue that the real novelty and contribution of this tradition has to do with its view of action as the context in which all things human take place. Thus, it is action rather than, for example, discourses that should be our starting point in social theory. The introductory section of the book situates pragmatism (especially the ideas of G. H. Mead and John Dewey) within the field and tradition of social theory. This introductory also contextualizes the main core of the book which consists of four chapters. Two of these chapters have been published as articles in scientific journals and one in an edited book. All of them discuss the core problem of social theory: how is action related to social structures (and vice versa)? The argument is that habitual action is the explanation for the emergence of social structures from our action. Action produces structures and social reproduction takes place when action is habitualized; that is, when we develop social dispositions to act in a certain manner in familiar environments. This also means that even though the physical environment is the same for all of us, our habits structure it into different kinds of action possibilities. Each chapter highlights these general insights from different angles. Practice theory has gained momentum in recent years and it has many commonalities with pragmatism because both highlight the situated and corporeal character of human activity. One famous proponent of practice theory is Margaret Archer who has argued that the pragmatism of G. H. Mead leads to an oversocialized conception of selfhood. Mead does indeed present a socialized view of selfhood but this is a meta-sociological argument rather than a substantial sociological claim. Accordingly, one can argue that in this general sense intersubjectivity precedes subjectivity and not the other way around. Such a view does not indicate that our social relation would necessarily "colonize" individual action because there is a place for internal conversations (in Archer s terminology); it is especially in those phases of action where it meets obstacles due to the changes of the environment. The second issue discussed has the background assumption that social structures can fruitfully be conceptualized as institutions. A general classification of different institution theories is presented and it is argued that there is a need for a habitual theory of institutions due to the problems associated with these other theories. So-called habitual institutionalism accounts for institutions in terms of established and prevalent social dispositions that structure our social interactions. The germs of this institution theory can be found in the work of Thorstein Veblen. Since Veblen s times, these ideas have been discussed for example, by the economist Geoffrey M. Hodgson. His ideas on the evolution of institutions are presented but a critical stance is taken towards his tendency of defining institutions with the help of rules because rules are not always present in institutions. Accordingly, habitual action is the most basic but by no means the only aspect of institutional reproduction. The third chapter deals with theme of action and structures in the context of Pierre Bourdieu s thought. Bourdieu s term habitus refers to a system of dispositions which structure social fields. It is argued that habits come close to the concept of habitus in the sense that the latter consists of particular kinds of habits; those that are related to the reproduction of socioeconomic positions. Habits are thus constituents of a general theory of societal reproduction whereas habitus is a systematic combination of socioeconomic habits. The fourth theme relates to issues of social change and development. The capabilities approach has been associated with the name of Amartya Sen, for example, and it underscores problems inhering in economistic ways of evaluating social development. However, Sen s argument has some theoretical problems. For example, his theory cannot adequately confront the problem of relativism. In addition, Sen s discussion lacks also a theory of the role of the public. With the help of arguments derived from pragmatism, one gets an action-based, socially constituted view of freedom in which the role of the public is essential. In general, it is argued that a socially constituted view of agency does not necessarily to lead to pessimistic conclusions about the freedom of action.

Data structures and software tools for the computer aided design of control systems: a survey.

CAD software can be structured as a set of modular 'software tools' only if there is some agreement on the data structures which are to be passed between tools. Beyond this basic requirement, it is desirable to give the agreed structures the status of 'data types' in the language used for interactive design. The ultimate refinement is to have a data management capability which 'understands' how to manipulate such data types. In this paper the requirements of CACSD are formulated from the point of view of Database Management Systems. Progress towards meeting these requirements in both the DBMS and the CACSD community is reviewed. The conclusion reached is that there has been considerable movement towards the realisation of software tools for CACSD, but that this owes more to modern ideas about programming languages, than to DBMS developments. The DBMS field has identified some useful concepts, but further significant progress is expected to come from the exploitation of concepts such as object-oriented programming, logic programming, or functional programming.