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.

Intergroup relations in action: questions asked about lesbian, gay and bisexual issues in diversity training

This paper focuses on the questions which heterosexual trainees ask about lesbian, gay and bisexual (LGB) experience within diversity training about LGB issues. Drawing on a data corpus of 162 questions asked by trainees in 13 tape-recorded training sessions, questions were coded into six categories: (1) general understanding questions; (2) questions about the trainer's life, experience and practices; (3) professional practice questions; (4) questions about lesbian and gay related legislation, policies and procedures; (5) questions about specific people and projects and (6) questions about the meanings, derivations and correct use of terms and symbols. Real questions are compared with the decontexualized questions (and answers to them) that are provided in training manuals and it is demonstrated that these questions differ markedly from how questions actually get asked and how they actually get answered. Recommendations are provided for improving training and the argument made for turning towards analyses of the real world in action, especially when considering intergroup relations. Copyright © 2008 John Wiley & Sons, Ltd.

Employment relations in India

This paper examines the employment relations (ERs) scenario in Indian organisations. The investigation is based on a questionnaire survey of 137 Indian firms in the manufacturing sector. The analysis of existing literature highlights the role of three key actors (management, unions, and the state) in the management of ERs in Indian organisations. It also shows the significant impact of the competitive pressures created by the liberalisation of the Indian economy in the changing nature of ERs in Indian firms. The study has key implications both for academicians and for practitioners.

Mirror-image relations in category learning

The discrimination of patterns that are mirror-symmetric counterparts of each other is difficult and requires substantial training. We explored whether mirror-image discrimination during expertise acquisition is based on associative learning strategies or involves a representational shift towards configural pattern descriptions that permit resolution of symmetry relations. Subjects were trained to discriminate between sets of unfamiliar grey-level patterns in two conditions, which either required the separation of mirror images or not. Both groups were subsequently tested in a 4-class category-learning task employing the same set of stimuli. The results show that subjects who had successfully learned to discriminate between mirror-symmetric counterparts were distinctly faster in the categorization task, indicating a transfer of conceptual knowledge between the two tasks. Additional computer simulations suggest that the development of such symmetry concepts involves the construction of configural, protoholistic descriptions, in which positions of pattern parts are encoded relative to a spatial frame of reference.