I'm the slice of pie that's ostracised.... : Foucault's technologies, and personal agency, in the voice of women who are homeless, Adelaide, South Australia

In contrast to the international research (particularly in the United Kingdom and North America), much of the Australian literature regarding homelessness to date omits the perspective of people who are homeless. In contributing to the fledgling Australian literature in the field, the following article adopts a secondary approach to the data analysis of original research. When analysed, the voices of homeless women from an agency in Adelaide, South Australia exhibit elements of both Foucault’s technologies of domination and the self. While the results show that the women do have a powerful sense of the broader external issues exerted on them (reflecting both technologies of domination and the self), the analysis also reveals ambiguities in their responses. Apparent in the voice of homeless women is a sense of personal agency which appears to be absent in Foucault’s technologies. By considering the viewpoints of homeless women, various policy implications can also be drawn. Indeed, this is one of the motivations of the article, namely to inject into policy debate and development the voices of the people most adversely affected by it. The policy implications of the women’s voices centre around the desire to be included rather than remain on the margins, the need for supportive relationships, the necessity to take small steps to independent living, and the need for more affordable, independent housing.

A unified formalism for landmark based representation of maps and navigation plans

We present a unified formalism for representing maps and using them for constructing plans of navigation for an autonomous agent. The foundation of this work lies in addressing key questions that an agent is confronted with when navigating. That is, besides the main task of how to reach the intended destination from the current position, the agent faces other questions like: where am I? what landmarks can I see? where is my destination relative to me and the landmarks I am seeing? Fundamental to this representation is the use of visual landmarks, which are used as pivotal points in the landscape being described. Further, in the representation of spatial information and navigation there are three different viewpoints: first, the localized representation from the viewpoint of a sighted, mobile agent; second, the static representation seen by the map-maker; and third, the view of an external agent giving directions on the basis of his own experience/knowledge. The major contribution of this map model and the associated navigation method lies in the framework which unifies these three different points of view. This unification enables the agent to make no distinction in terms of following implicit instructions contained in a map and the directions given by external agents.

Conclusion : gender and politics and the changing status of women today

This book concerns a new body of knowledge and an emerging set of questions that has accompanied national, cross national and international global political movements aimed at trying to understand and to improve the situation of women by eliminating gender inequities and injustices.

Effect of type and severity of intimate partner violence on women's health and service use : findings from a primary care trial of women afraid of their partners

Intimate partner violence (IPV) has major affects on women’s wellbeing. There has been limited investigation of the association between type and severity of IPV and health outcomes. This article describes socio-demographic characteristics, experiences of abuse, health, safety, and use of services in women enrolled in the Women’s Evaluation of Abuse and Violence Care (WEAVE) project. We explored associations between type and severity of abuse and women’s health, quality of life, and help seeking. Women (aged 16–50 years) attending 52 Australian general practices, reporting fear of partners in last 12 months were mailed a survey between June 2008 and May 2010. Response rate was 70.5% (272/386). In the last 12 months, one third (33.0%) experienced Severe Combined Abuse, 26.2% Physical and Emotional Abuse, 26.6% Emotional Abuse and/or Harassment only, 2.7% Physical Abuse only and 12.4% scored negative on the Composite Abuse Scale. A total of 31.6% of participants reported poor or fair health and 67.9% poor social support. In the last year, one third had seen a psychologist (36.6%) or had 5 or more general practitioner visits (34.3%); 14.7% contacted IPV services; and 24.4% had made a safety plan. Compared to other abuse groups, women with Severe Combined Abuse had poor quality of life and mental health, despite using more medications, counseling, and IPV services and were more likely to have days out of role because of emotional issues. In summary, women who were fearful of partners in the last year, have poor mental health and quality of life, attend health care services frequently, and domestic violence services infrequently. Those women experiencing severe combined physical, emotional, and sexual abuse have poorer quality of life and mental health than women experiencing other abuse types. Health practitioners should take a history of type and severity of abuse for women with mental health issues to assist access to appropriate specialist support.

The role of women academics in Australian universities

Women academics have been employed in Australian universities for a century. Why, then, are women so poorly represented at senior levels? DEEWR statistics show very different environments and employment trends in Go8 and non-Go8 universities.

Object categorization via sparse representation of local features

Sparse representation has been introduced to address many recognition problems in computer vision. In this paper, we propose a new framework for object categorization based on sparse representation of local features. Unlike most of previous sparse coding based methods in object classification that only use sparse coding to extract high-level features, the proposed method incorporates sparse representation and classification into a unified framework. Therefore, it does not need a further classifier. Experimental results show that the proposed method achieved better or comparable accuracy than the well known bag-of-features representation with various classifiers.

Human identification from ECG signals via sparse representation of local segments

This work proposes a novel framework to extract compact and discriminative features from Electrocardiogram (ECG) signals for human identification based on sparse representation of local segments. Specifically, local segments extracted from an ECG signal are projected to a small number of basic elements in a dictionary, which is learned from training data. A final representation is extracted by performing a max pooling procedure over all the sparse coefficient vectors in the ECG signal. Unlike most of existing methods for human identification from ECG signals which require segmentation of individual heartbeats or extraction of fiducial points, the proposed method does not need to segment individual heartbeats or detect any fiducial points. The method achieves an 99.48% accuracy on a 100 subjects dataset constructed from a publicly available database, which demonstrates that both local and global structural information are well captured to characterize the ECG signals.