Is it the economy, stupid? The role of social versus economic factors in people’s support for hosting the Olympic Games: Evidence from 12 democratic countries

Public referenda have gained momentum as a democratic tool to legitimize public mega projects such as hosting the Olympic Games. Interest groups in favour of hosting the Olympics therefore try to influence voters through public campaigns that primarily focus on economic benefits. However, recent studies find no or hardly any economic impact of hosting the Olympics, instead providing evidence for a positive social impact. This raises the question whether citizens consider economic or social factors when deciding on hosting the Olympics. Based on representative survey data from 12 countries, our results suggest that economic factors can influence voting behaviour, although the influence of social factors is stronger.

Mixed pixel analysis for flood mapping using extended support vector machine

This paper addresses the challenges of flood mapping using multispectral images. Quantitative flood mapping is critical for flood damage assessment and management. Remote sensing images obtained from various satellite or airborne sensors provide valuable data for this application, from which the information on the extent of flood can be extracted. However the great challenge involved in the data interpretation is to achieve more reliable flood extent mapping including both the fully inundated areas and the 'wet' areas where trees and houses are partly covered by water. This is a typical combined pure pixel and mixed pixel problem. In this paper, an extended Support Vector Machines method for spectral unmixing developed recently has been applied to generate an integrated map showing both pure pixels (fully inundated areas) and mixed pixels (trees and houses partly covered by water). The outputs were compared with the conventional mean based linear spectral mixture model, and better performance was demonstrated with a subset of Landsat ETM+ data recorded at the Daly River Basin, NT, Australia, on 3rd March, 2008, after a flood event.

Teacher peer support in social network sites

This paper describes the types of support that teachers are accessing through the Social Network Site (SNS) 'Facebook'. It describes six ways in which teachers support one another within online groups. It presents evidence from a study of a large, open group of teachers online over a twelve week period, repeated with multiple groups a year later over a one week period. The findings suggest that large open groups in SNSs can be a useful source of pragmatic advice for teachers but that these groups are rarely a place for reflection on or feedback about teaching practice.

Non-resident workers: A comparison of family support services for resource, health, and defence communities

Non-resident workforces experience high labour turnover, which has an impact on organisational operations and affects worker satisfaction and, in turn, partners’ ability to cope with work-related absences. Research suggests that partner satisfaction may be increased by providing a range of support services, which include professional, practical, and social support. A search was conducted to identify support available for resources and health-industry non-resident workers. These were compared to the supports available to families of deployed defence personnel. They were used to compare and contrast the spread available for each industry. The resources industry primarily provided social support, and lacked an inclusion of professional and practical supports. Health-professional support services were largely directed towards extended locum support, rather than to Fly-In Fly-Out workers. Improving sources of support which parallel support provided to the Australian Defence Force is suggested as a way to increase partner satisfaction. The implications are to understand the level of uptake, perceived importance, and utilisation of such support services.

Spectral unmixing with estimated adaptive endmember index using Extended Support Vector Machine

The most difficult operation in the flood inundation mapping using optical flood images is to separate fully inundated areas from the ‘wet’ areas where trees and houses are partly covered by water. This can be referred as a typical problem the presence of mixed pixels in the images. A number of automatic information extraction image classification algorithms have been developed over the years for flood mapping using optical remote sensing images. Most classification algorithms generally, help in selecting a pixel in a particular class label with the greatest likelihood. However, these hard classification methods often fail to generate a reliable flood inundation mapping because the presence of mixed pixels in the images. To solve the mixed pixel problem advanced image processing techniques are adopted and Linear Spectral unmixing method is one of the most popular soft classification technique used for mixed pixel analysis. The good performance of linear spectral unmixing depends on two important issues, those are, the method of selecting endmembers and the method to model the endmembers for unmixing. This paper presents an improvement in the adaptive selection of endmember subset for each pixel in spectral unmixing method for reliable flood mapping. Using a fixed set of endmembers for spectral unmixing all pixels in an entire image might cause over estimation of the endmember spectra residing in a mixed pixel and hence cause reducing the performance level of spectral unmixing. Compared to this, application of estimated adaptive subset of endmembers for each pixel can decrease the residual error in unmixing results and provide a reliable output. In this current paper, it has also been proved that this proposed method can improve the accuracy of conventional linear unmixing methods and also easy to apply. Three different linear spectral unmixing methods were applied to test the improvement in unmixing results. Experiments were conducted in three different sets of Landsat-5 TM images of three different flood events in Australia to examine the method on different flooding conditions and achieved satisfactory outcomes in flood mapping.