Front-line workers as intermediaries : the changing landscape of disability and employment services in Australia

Recent welfare reform in Australia has been constructed around the now-familiar principle of paid work and willingness to work as the fundamental marker of social citizenship. Beginning with the long-term unemployed in Australia in the mid 1990s, the scope of welfare reform has now extended to include people with a disability – which is a category of income support that has been growing in Australia. From the national government’s point of view this growth is a financial concern as it seeks to move as many people as possible into paid work to support the costs of an ageing population (DEWR, 2005). In doing so, the government has changed the meaning of disability in terms of eligibility for financial support from the state, and at the same time redefined the role of people with a disability with regard to work, and the role of the state with regard to the disabled. This has been a matter of some political contention in Australia.

Optimal camera planning under versatile user constraints in multi-camera image processing systems

The selection of optimal camera configurations (camera locations, orientations, etc.) for multi-camera networks remains an unsolved problem. Previous approaches largely focus on proposing various objective functions to achieve different tasks. Most of them, however, do not generalize well to large scale networks. To tackle this, we propose a statistical framework of the problem as well as propose a trans-dimensional simulated annealing algorithm to effectively deal with it. We compare our approach with a state-of-the-art method based on binary integer programming (BIP) and show that our approach offers similar performance on small scale problems. However, we also demonstrate the capability of our approach in dealing with large scale problems and show that our approach produces better results than two alternative heuristics designed to deal with the scalability issue of BIP. Last, we show the versatility of our approach using a number of specific scenarios.

A systematic review of telemedicine services for residents in long term care facilities

We conducted a systematic review of the literature on telemedicine use in long-term care facilities (LTCFs) and assessed the quality of the published evidence. A database search identified 22 papers which met the inclusion criteria. The quality of the studies was assessed and if they contained economic data, they were rated according to standard criteria. The clinical services provided by telemedicine included allied health (n = 5), dermatology (3), general practice (4), neurology (2), geriatrics (1), psychiatry (4) and multiple specialities (3). Most studies (17) employed real-time telemedicine using videoconferencing. The remaining five used store and forward telemedicine. The papers focused on economics (3), feasibility (9), stakeholder satisfaction (12), reliability (5) and service implementation (2). Overall, the quality of evidence for telemedicine in LTCFs was low. There was only one small randomised controlled trial (RCT). Most studies were observational and qualitative, and focused on utilisation. They were mainly based on surveys and interviews of stakeholders. A few studies evaluated the cost associated with implementing telemedicine services in LTCFs. The present review shows that there is evidence for feasibility and stakeholder satisfaction in using telemedicine in LTCFs in a number of clinical specialities.

Transit passenger segmentation using travel regularity mined from Smart Card transactions data

Transit passenger market segmentation enables transit operators to target different classes of transit users to provide customized information and services. The Smart Card (SC) data, from Automated Fare Collection system, facilitates the understanding of multiday travel regularity of transit passengers, and can be used to segment them into identifiable classes of similar behaviors and needs. However, the use of SC data for market segmentation has attracted very limited attention in the literature. This paper proposes a novel methodology for mining spatial and temporal travel regularity from each individual passenger’s historical SC transactions and segments them into four segments of transit users. After reconstructing the travel itineraries from historical SC transactions, the paper adopts the Density-Based Spatial Clustering of Application with Noise (DBSCAN) algorithm to mine travel regularity of each SC user. The travel regularity is then used to segment SC users by an a priori market segmentation approach. The methodology proposed in this paper assists transit operators to understand their passengers and provide them oriented information and services.