International images and mass media: The effects of media coverage on Canadians' perceptions of ethnic and race relations in Australia

Recently, there has been much speculation about the impact of international media coverage of Australia's position on Indigenous people, migrants and asylum seekers on other nations' images of Australia. In this experiment we examined whether there was any basis for such concerns by considering the short-term impact of negative TV coverage of Australians on Canadian viewers. A questionnaire provided baseline data on Canadian students' perceptions of Australians and Australian race relations. Four months later, the students were assigned to one of three conditions that varied media contact with Australians. Students viewed one of two television programs (about right-wing political independent, Pauline Hanson, and her emotive criticisms of Aborigines and Asian immigrants or about an ethnically-mixed group of young Australians and their positive sense of cultural identity), or they viewed no program (no contact control). Results indicated that both positive and negative media coverage of Australians affected Canadians' views of Australia in the short-term. In particular, negative coverage (of Hanson) promoted less favourable views of Australians and Australian race relations over time and relative to the positive media and no media control conditions. The media's role in shaping international images is discussed.

Civil-Military Relations in Croatia: Politicisation and Politics of Reform.

This article argues that since 2000 successive Croatian governments have shown themselves increasingly dedicated to reforming civil-military relations. However, their efforts have been hampered by four key obstacles. First, the need to implement defence reforms in the context of an unwieldy set of civil-military relationships, political and institutional rivalries, a lack of civil and military defence expertise and a continuing legacy of politicisation. Second, the need to cut defence spending as a proportion of the overall budget whilst taking on new military roles and improving the capability of the armed forces. Third, the need to balance the demands of the NATO accession process while implementing a balanced and fundamental reform of the armed forces as a whole. Finally, the need to implement root and branch personnel reforms and downsizing in the OSRH while simultaneously recruiting and retaining quality personnel and addressing the wider social issue of unemployment.

Summarizing level-two topological relations in large spatial datasets

Summarizing topological relations is fundamental to many spatial applications including spatial query optimization. In this article, we present several novel techniques to effectively construct cell density based spatial histograms for range (window) summarizations restricted to the four most important level-two topological relations: contains, contained, overlap, and disjoint. We first present a novel framework to construct a multiscale Euler histogram in 2D space with the guarantee of the exact summarization results for aligned windows in constant time. To minimize the storage space in such a multiscale Euler histogram, an approximate algorithm with the approximate ratio 19/12 is presented, while the problem is shown NP-hard generally. To conform to a limited storage space where a multiscale histogram may be allowed to have only k Euler histograms, an effective algorithm is presented to construct multiscale histograms to achieve high accuracy in approximately summarizing aligned windows. Then, we present a new approximate algorithm to query an Euler histogram that cannot guarantee the exact answers; it runs in constant time. We also investigate the problem of nonaligned windows and the problem of effectively partitioning the data space to support nonaligned window queries. Finally, we extend our techniques to 3D space. Our extensive experiments against both synthetic and real world datasets demonstrate that the approximate multiscale histogram techniques may improve the accuracy of the existing techniques by several orders of magnitude while retaining the cost efficiency, and the exact multiscale histogram technique requires only a storage space linearly proportional to the number of cells for many popular real datasets.

Multiscale histograms: Summarizing topological relations in large spatial datasets

Summarizing topological relations is fundamental to many spatial applications including spatial query optimization. In this paper, we present several novel techniques to eectively construct cell density based spatial histograms for range (window) summarizations restricted to the four most important topological relations: contains, contained, overlap, and disjoint. We rst present a novel framework to construct a multiscale histogram composed of multiple Euler histograms with the guarantee of the exact summarization results for aligned windows in constant time. Then we present an approximate algorithm, with the approximate ratio 19/12, to minimize the storage spaces of such multiscale Euler histograms, although the problem is generally NP-hard. To conform to a limited storage space where only k Euler histograms are allowed, an effective algorithm is presented to construct multiscale histograms to achieve high accuracy. Finally, we present a new approximate algorithm to query an Euler histogram that cannot guarantee the exact answers; it runs in constant time. Our extensive experiments against both synthetic and real world datasets demonstrated that the approximate mul- tiscale histogram techniques may improve the accuracy of the existing techniques by several orders of magnitude while retaining the cost effciency, and the exact multiscale histogram technique requires only a storage space linearly proportional to the number of cells for the real datasets.