Cyberbullying : the new face of workplace bullying?

While the subject of cyberbullying of children and adolescents has begun to be addressed, there has been less attention or research on cyberbullying in the workplace. Whilst male-dominated workplaces such as manufacturing settings have been found to have an increased risk of workplace bullying, the prevalence of cyberbullying in this sector is not known. This exploratory study investigated the prevalence and methods of face-to-face bullying and cyberbullying of males at work. One hundred and three surveys (a modified version of the NAQ-R1), were returned from randomly selected members of the Australian Manufacturing Worker’s Union (AMWU). The results showed that 34% of the respondents were bullied face-to-face, and 10.7% were cyberbullied. All victims of cyberbullying also experienced face-to-face bullying. The implications for organisations of their “duty of care” in regards to this new form of bullying are indicated.

Neurolinguistic contributions to understanding the bilingual mental lexicon

Introduction Many bilinguals will have had the experience of unintentionally reading something in a language other than the intended one (e.g. MUG to mean mosquito in Dutch rather than a receptacle for a hot drink, as one of the possible intended English meanings), of finding themselves blocked on a word for which many alternatives suggest themselves (but, somewhat annoyingly, not in the right language), of their accent changing when stressed or tired and, occasionally, of starting to speak in a language that is not understood by those around them. These instances where lexical access appears compromised and control over language behavior is reduced hint at the intricate structure of the bilingual lexical architecture and the complexity of the processes by which knowledge is accessed and retrieved. While bilinguals might tend to blame word finding and other language problems on their bilinguality, these difficulties per se are not unique to the bilingual population. However, what is unique, and yet far more common than is appreciated by monolinguals, is the cognitive architecture that subserves bilingual language processing. With bilingualism (and multilingualism) the rule rather than the exception (Grosjean, 1982), this architecture may well be the default structure of the language processing system. As such, it is critical that we understand more fully not only how the processing of more than one language is subserved by the brain, but also how this understanding furthers our knowledge of the cognitive architecture that encapsulates the bilingual mental lexicon. The neurolinguistic approach to bilingualism focuses on determining the manner in which the two (or more) languages are stored in the brain and how they are differentially (or similarly) processed. The underlying assumption is that the acquisition of more than one language requires at the very least a change to or expansion of the existing lexicon, if not the formation of language-specific components, and this is likely to manifest in some way at the physiological level. There are many sources of information, ranging from data on bilingual aphasic patients (Paradis, 1977, 1985, 1997) to lateralization (Vaid, 1983; see Hull & Vaid, 2006, for a review), recordings of event-related potentials (ERPs) (e.g. Ardal et al., 1990; Phillips et al., 2006), and positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) studies of neurologically intact bilinguals (see Indefrey, 2006; Vaid & Hull, 2002, for reviews). Following the consideration of methodological issues and interpretative limitations that characterize these approaches, the chapter focuses on how the application of these approaches has furthered our understanding of (1) selectivity of bilingual lexical access, (2) distinctions between word types in the bilingual lexicon and (3) control processes that enable language selection.

How is a fruit tree like you? Using artistic metaphors to explore and develop emotional competence in children

Counselling children often requires the use of supplementary strategies in order to interest and engage the child in the therapeutic process. One such strategy is the Metaphorical Fruit Tree (MFT); an art metaphor suited to exploring and developing self-concept. Quantitative and qualitative data was used to explore the relationships between children’s ability to use metaphor, age, gender, and level of emotional competence (N = 58). Quantitative and qualitative analyses revealed a significant negative relationship between self-reported emotional competence and ability to use the MFT. It is proposed that children rely on different processes to understand self and as children’s ability to cognitively report on their emotional capabilities via the Emotional Competence Questionnaire (ECQ) increases, their ability to report creatively on those capabilities via the MFT is undermined. It is suggested that the MFT may be used, via creative processes and as an alternative to cognitive processes, to increase understanding and awareness of intrapersonal and interpersonal concepts of self in the child during counselling.

Abstracting and correlating heterogeneous events to detect complex scenarios

The research presented in this thesis addresses inherent problems in signaturebased intrusion detection systems (IDSs) operating in heterogeneous environments. The research proposes a solution to address the difficulties associated with multistep attack scenario specification and detection for such environments. The research has focused on two distinct problems: the representation of events derived from heterogeneous sources and multi-step attack specification and detection. The first part of the research investigates the application of an event abstraction model to event logs collected from a heterogeneous environment. The event abstraction model comprises a hierarchy of events derived from different log sources such as system audit data, application logs, captured network traffic, and intrusion detection system alerts. Unlike existing event abstraction models where low-level information may be discarded during the abstraction process, the event abstraction model presented in this work preserves all low-level information as well as providing high-level information in the form of abstract events. The event abstraction model presented in this work was designed independently of any particular IDS and thus may be used by any IDS, intrusion forensic tools, or monitoring tools. The second part of the research investigates the use of unification for multi-step attack scenario specification and detection. Multi-step attack scenarios are hard to specify and detect as they often involve the correlation of events from multiple sources which may be affected by time uncertainty. The unification algorithm provides a simple and straightforward scenario matching mechanism by using variable instantiation where variables represent events as defined in the event abstraction model. The third part of the research looks into the solution to address time uncertainty. Clock synchronisation is crucial for detecting multi-step attack scenarios which involve logs from multiple hosts. Issues involving time uncertainty have been largely neglected by intrusion detection research. The system presented in this research introduces two techniques for addressing time uncertainty issues: clock skew compensation and clock drift modelling using linear regression. An off-line IDS prototype for detecting multi-step attacks has been implemented. The prototype comprises two modules: implementation of the abstract event system architecture (AESA) and of the scenario detection module. The scenario detection module implements our signature language developed based on the Python programming language syntax and the unification-based scenario detection engine. The prototype has been evaluated using a publicly available dataset of real attack traffic and event logs and a synthetic dataset. The distinct features of the public dataset are the fact that it contains multi-step attacks which involve multiple hosts with clock skew and clock drift. These features allow us to demonstrate the application and the advantages of the contributions of this research. All instances of multi-step attacks in the dataset have been correctly identified even though there exists a significant clock skew and drift in the dataset. Future work identified by this research would be to develop a refined unification algorithm suitable for processing streams of events to enable an on-line detection. In terms of time uncertainty, identified future work would be to develop mechanisms which allows automatic clock skew and clock drift identification and correction. The immediate application of the research presented in this thesis is the framework of an off-line IDS which processes events from heterogeneous sources using abstraction and which can detect multi-step attack scenarios which may involve time uncertainty.

Geek goddesses go to school : A study of female pre-service teachers in information technology courses

Various reasons have been proffered for female under-representation in tertiary information technology (IT) courses and the IT industry with most relating to cultural moirés. The 2006 Geek Goddess calendar was designed to alter IT’s “geeky image” and the term is used here to represent young women enrolled in pre-service IT teaching courses. Their special mix of IT and teaching draws on conflicting stereotypes and represents a micro-climate which is typically lost in studies of IT occupations because of the aggregation of all IT roles. This paper will report on a small-scale investigation of female students (N=25) at a university in Queensland (Australia) studying to become teachers of secondary IT subjects. They are entering the IT industry, gendered as a “male” occupation, through the safe space of teaching a discipline allied to feminine qualities of nurturing. They are “geek goddesses” who – perhaps to balance the masculine and feminine of these occupations - have decided to go to school rather than into corporations or government.

Using data mining to improve building life cycle

The building life cycle process is complex and prone to fragmentation as it moves through its various stages. The number of participants, and the diversity, specialisation and isolation both in space and time of their activities, have dramatically increased over time. The data generated within the construction industry has become increasingly overwhelming. Most currently available computer tools for the building industry have offered productivity improvement in the transmission of graphical drawings and textual specifications, without addressing more fundamental changes in building life cycle management. Facility managers and building owners are primarily concerned with highlighting areas of existing or potential maintenance problems in order to be able to improve the building performance, satisfying occupants and minimising turnover especially the operational cost of maintenance. In doing so, they collect large amounts of data that is stored in the building’s maintenance database. The work described in this paper is targeted at adding value to the design and maintenance of buildings by turning maintenance data into information and knowledge. Data mining technology presents an opportunity to increase significantly the rate at which the volumes of data generated through the maintenance process can be turned into useful information. This can be done using classification algorithms to discover patterns and correlations within a large volume of data. This paper presents how and what data mining techniques can be applied on maintenance data of buildings to identify the impediments to better performance of building assets. It demonstrates what sorts of knowledge can be found in maintenance records. The benefits to the construction industry lie in turning passive data in databases into knowledge that can improve the efficiency of the maintenance process and of future designs that incorporate that maintenance knowledge.

Using videotelephony to support paediatric oncology-related palliative care in the home : from abandoned RCT to acceptability study

Videotelephony (real-time audio-visual communication) has been used successfully in adult palliative home care. This paper describes two attempts to complete an RCT (both of which were abandoned following difficulties with family recruitment), designed to investigate the use of videotelephony with families receiving palliative care from a tertiary paediatric oncology service in Brisbane, Australia. To investigate whether providing videotelephone-based support was acceptable to these families, a 12-month non-randomised acceptability trial was completed. Seventeen palliative care families were offered access to a videotelephone support service in addition to the 24 hours ‘on-call’ service already offered. A 92% participation rate in this study provided some reassurance that the use of videotelephones themselves was not a factor in poor RCT participation rates. The next phase of research is to investigate the integration of videotelephone-based support from the time of diagnosis, through outpatient care and support, and for palliative care rather than for palliative care in isolation

Bayesian versus frequentist statistical inference for investi gating a one-off cancer cluster reported to a health department

Background The problem of silent multiple comparisons is one of the most difficult statistical problems faced by scientists. It is a particular problem for investigating a one-off cancer cluster reported to a health department because any one of hundreds, or possibly thousands, of neighbourhoods, schools, or workplaces could have reported a cluster, which could have been for any one of several types of cancer or any one of several time periods. Methods This paper contrasts the frequentist approach with a Bayesian approach for dealing with silent multiple comparisons in the context of a one-off cluster reported to a health department. Two published cluster investigations were re-analysed using the Dunn-Sidak method to adjust frequentist p-values and confidence intervals for silent multiple comparisons. Bayesian methods were based on the Gamma distribution. Results Bayesian analysis with non-informative priors produced results similar to the frequentist analysis, and suggested that both clusters represented a statistical excess. In the frequentist framework, the statistical significance of both clusters was extremely sensitive to the number of silent multiple comparisons, which can only ever be a subjective "guesstimate". The Bayesian approach is also subjective: whether there is an apparent statistical excess depends on the specified prior. Conclusion In cluster investigations, the frequentist approach is just as subjective as the Bayesian approach, but the Bayesian approach is less ambitious in that it treats the analysis as a synthesis of data and personal judgements (possibly poor ones), rather than objective reality. Bayesian analysis is (arguably) a useful tool to support complicated decision-making, because it makes the uncertainty associated with silent multiple comparisons explicit.