Gendered dichotomies and segregation patterns in computing jobs in Australia

The uneven distribution of women and men in IT employment is often depicted as reflecting adistinction between 'hard' and 'soft' tasks, skills and attributes. This article uses detailed occupational data on professional computing jobs in Australia to examine the extent to which patterns of gender segregation are consistent with such dichotomies. Additionally, we draw on qualitative interview data from aset oforganisational case studies for insights into the ways in which segregation patterns are reproduced and/or reshaped at"the workplace level. While perceptions ofgendered dichotomies were evident among many of our interviewees, overall our analysis shows considerably more complexity, with segregation patterns not necessarily aligned with clear-cut dichotomies and career directions often directly influenced by the organisation ofworking time in particular occupational streams.

A scalarization technique for computing the power and exponential moments of gaussian random matrices

We consider the problems of computing the power and exponential moments EXs and EetX of square Gaussian random matrices X=A+BWC for positive integer s and real t, where W is a standard normal random vector and A, B, C are appropriately dimensioned constant matrices. We solve the problems by a matrix product scalarization technique and interpret the solutions in system-theoretic terms. The results of the paper are applicable to Bayesian prediction in multivariate autoregressive time series and mean-reverting diffusion processes.

Developing context-aware pervasive computing applications: Models and approach

There is growing interest in the use of context-awareness as a technique for developing pervasive computing applications that are flexible, adaptable, and capable of acting autonomously on behalf of users. However, context-awareness introduces a variety of software engineering challenges. In this paper, we address these challenges by proposing a set of conceptual models designed to support the software engineering process, including context modelling techniques, a preference model for representing context-dependent requirements, and two programming models. We also present a software infrastructure and software engineering process that can be used in conjunction with our models. Finally, we discuss a case study that demonstrates the strengths of our models and software engineering approach with respect to a set of software quality metrics.

Advanced computing for systems biology

Systems biology is based on computational modelling and simulation of large networks of interacting components. Models may be intended to capture processes, mechanisms, components and interactions at different levels of fidelity. Input data are often large and geographically disperse, and may require the computation to be moved to the data, not vice versa. In addition, complex system-level problems require collaboration across institutions and disciplines. Grid computing can offer robust, scaleable solutions for distributed data, compute and expertise. We illustrate some of the range of computational and data requirements in systems biology with three case studies: one requiring large computation but small data (orthologue mapping in comparative genomics), a second involving complex terabyte data (the Visible Cell project) and a third that is both computationally and data-intensive (simulations at multiple temporal and spatial scales). Authentication, authorisation and audit systems are currently not well scalable and may present bottlenecks for distributed collaboration particularly where outcomes may be commercialised. Challenges remain in providing lightweight standards to facilitate the penetration of robust, scalable grid-type computing into diverse user communities to meet the evolving demands of systems biology.

Affective priming - is it only affect that primes?

A target word is classified faster as pleasant or unpleasant if preceded by a prime that matches the target word’s valence. This affective priming phenomenon is currently popular as an implicit measure of stimulus valence. The present set of experiments investigated whether rated stimulus arousal will affect target classification as well. In three experiments, word targets were preceded by prime stimuli that differed in rated arousal and valence. The basic priming effect was replicated in all experiments, however, priming was largest after high arousal unpleasant and low arousal pleasant primes, and reduced after low arousal unpleasant and high arousal pleasant primes. This finding emerged for picture and word primes and does not reflect the effect of differences in stimulus complexity. The difference in the effectiveness of the primes was not affected by SOA and seemed to hold across a wide range (50-200 ms for words and 200-500 ms for pictures). The present results suggest that some failures to find affective priming may not reflect on prime valence, but on prime arousal. Moreover, it suggests that increases in stimulus arousal have differential effects for the processing of pleasant and unpleasant stimuli.

Attention vs. emotion: Affective learning and the startle reflex

The eye-blink startle reflex can be modulated by attentional and emotional processes. The reflex is facilitated during stimuli that engage attention. A linear pattern of emotional modulation has also been consistently demonstrated: the reflex is facilitated during unpleasant stimuli and attenuated during pleasant stimuli. However, during anticipation of pleasant or unpleasant stimuli it is unclear whether emotion or attention drives startle reflex modulation. This study used a differential learning procedure to investigate whether startle modulation during anticipation of a salient stimulus reflected emotional or attentional processes. In acquisition, a CS+ was paired with a pleasant or unpleasant US and a CS- was presented alone. In extinction, blink startle magnitude was measured during CS+ and CS-. Post-acquisition valence ratings and affective priming showed that CS+ had acquired the same affective value as the pleasant or unpleasant US with which it was paired. No differences in modulation of blink startle reflexes during pleasant CS+ and unpleasant CS+ were found throughout extinction. Blink startle facilitation occurred during CS+ but not CS- across the first third of extinction. Thus, attentional rather than emotional processes appeared to facilitate blink startle during anticipation of salient stimuli.

Bridging technical and HCI research: Creating usable ubiquitous computing

This paper describes methods used to support collaboration and communication between practitioners, designers and engineers when designing ubiquitous computing systems. We tested methods such as “Wizard of Oz” and design games in a real domain, the dental surgery, in an attempt to create a system that is: affordable; minimally disruptive of the natural flow of work; and improves human-computer interaction. In doing so we found that such activities allowed the practitioners to be on a ‘level playing ground’ with designers and engineers. The findings we present suggest that dentists are willing to engage in detailed exploration and constructive critique of technical design possibilities if the design ideas and prototypes are presented in the context of their work practice and are of a resolution and relevance that allow them to jointly explore and question with the design time. This paper is an extension of a short paper submitted to the Participatory Design Conference, 2004.

A software engineering framework for context-aware pervasive computing

There is growing interest in the use of context-awareness as a technique for developing pervasive computing applications that are flexible, adaptable, and capable of acting autonomously on behalf of users. However, context-awareness introduces various software engineering challenges, as well as privacy and usability concerns. In this paper, we present a conceptual framework and software infrastructure that together address known software engineering challenges, and enable further practical exploration of social and usability issues by facilitating the prototyping and fine-tuning of context-aware applications.