Information extraction from web services : a comparison of Tokenisation algorithms

Most web service discovery systems use keyword-based search algorithms and, although partially successful, sometimes fail to satisfy some users information needs. This has given rise to several semantics-based approaches that look to go beyond simple attribute matching and try to capture the semantics of services. However, the results reported in the literature vary and in many cases are worse than the results obtained by keyword-based systems. We believe the accuracy of the mechanisms used to extract tokens from the non-natural language sections of WSDL files directly affects the performance of these techniques, because some of them can be more sensitive to noise. In this paper three existing tokenization algorithms are evaluated and a new algorithm that outperforms all the algorithms found in the literature is introduced.

Productivity, Technical and Efficiency Change in Singapore’s Services Sector, 2005 to 2008

The current study was motivated by statements made by the Economic Strategies Committee that Singapore’s recent productivity levels in services were well below countries such as the US, Japan and Hong Kong. Massive employment of foreign workers was cited as the reason for poor productivity levels. To shed more light on Singapore’s falling productivity, a nonparametric Malmquist productivity index was employed which provides measures of productivity change, technical change and efficiency change. The findings reveal that growth in total factor productivity was attributed to technical change with no improvement in efficiency change. Such results suggest that gains from TFP were input-driven rather than from a ‘best-practice’ approach such as improvements in operations or better resource allocation.

Ensuring student success : the role of support services in improving the quality of the student learning experience

This paper is based on the premise that universities have an obligation to provide adequate student support services, such as learning assistance (that is, assistance with academic writing and other study skills) and that in order to be effective such services must be responsive to the wider policy and social implications of student attrition and retention. The paper outlines briefly some of the factors that have influenced the development of learning assistance practices in Australia and America. This is followed by an account of experiences at one Australian metropolitan university where learning assistance service provision shifted from a decentralised, faculty-based model to a centralised model of service delivery. This shift was in response to concerns about lack of quality and consistency in a support model dependent upon faculty resources yet a follow up study identified other problems in the centralised delivery of learning assistance services. These problems, clustered under the heading contextualised versus decontextualised learning assistance, include the relevance of generic learning assistance services to students struggling with specific course related demands; the apparent tensions between challenging students and assisting students at risk of failure; and variations in the level of collaboration between learning advisers and academic staff in supporting students in the learning environment. These problems are analysed using the theoretical modelling derived from the tools made available through cultural historical activity theory and expansive visibilisation (Engeström & Miettinen, 1999).

Inequitable Provision of Optimal Services for Patients with Chronic Heart failure: A National Geo-Mapping Study

Objective: To compare the location and accessibility of current Australian chronic heart failure (CHF) management programs and general practice services with the probable distribution of the population with CHF. Design and setting: Data on the prevalence and distribution of the CHF population throughout Australia, and the locations of CHF management programs and general practice services from 1 January 2004 to 31 December 2005 were analysed using geographic information systems (GIS) technology. Outcome measures: Distance of populations with CHF to CHF management programs and general practice services. Results: The highest prevalence of CHF (20.3–79.8 per 1000 population) occurred in areas with high concentrations of people over 65 years of age and in areas with higher proportions of Indigenous people. Five thousand CHF patients (8%) discharged from hospital in 2004–2005 were managed in one of the 62 identified CHF management programs. There were no CHF management programs in the Northern Territory or Tasmania. Only four CHF management programs were located outside major cities, with a total case load of 80 patients (0.7%). The mean distance from any Australian population centre to the nearest CHF management program was 332 km (median, 163 km; range, 0.15–3246 km). In rural areas, where the burden of CHF management falls upon general practitioners, the mean distance to general practice services was 37 km (median, 20 km; range, 0–656 km). Conclusion: There is an inequity in the provision of CHF management programs to rural Australians.

Improving the provision of learning assistance services in higher education

This study is motivated by the need to look continually for ways to improve Griffith University's learning assistance services so that they meet the changed needs of stakeholders and are at the same time cost-effective and efficient. This study uses the conceptual tools of cultural-historical activity theory and expansive visibilisation to investigaate the developmenet and transformation of learning assistance services at Griffith University, one of Australia's largest mult-campus universities.

Resource allocation and scheduling of multiple composite web services in cloud computing using cooperative coevolution genetic algorithm

In cloud computing, resource allocation and scheduling of multiple composite web services is an important and challenging problem. This is especially so in a hybrid cloud where there may be some low-cost resources available from private clouds and some high-cost resources from public clouds. Meeting this challenge involves two classical computational problems: one is assigning resources to each of the tasks in the composite web services; the other is scheduling the allocated resources when each resource may be used by multiple tasks at different points of time. In addition, Quality-of-Service (QoS) issues, such as execution time and running costs, must be considered in the resource allocation and scheduling problem. Here we present a Cooperative Coevolutionary Genetic Algorithm (CCGA) to solve the deadline-constrained resource allocation and scheduling problem for multiple composite web services. Experimental results show that our CCGA is both efficient and scalable.