71 resultados para Guangdong Sheng

em Queensland University of Technology - ePrints Archive


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Many studies have focused on why deliberative institutions should be established in order to develop Chinese people’s citizenry skills; however few focus on the social conditions and public sentiments that shape the development of deliberative mechanisms. Skills and awareness of citizenry is not only brought into being by deliberative institutions that are set up by the government, but evolve through interplays between technologies and social changes. As a test-bed for economic reform Guangdong is increasingly identified by translocality and hybrid culture. This is framed by identity conflict and unrests, much of which is due to soaring wealth polarisation, high volumes of population movement, cultural collisions and ongoing linguistic contestations. These unrests show the region’s transformation goes beyond the economic front. Profound changes are occurring at what anthropologists and philosophers call the changing social conciseness or moral landscape (Ci, 1994; Yan, 2010). The changing social moralities are a reflection of the awareness of individuals’ rights and responsibilities, and their interdependencies from dominant ideologies. This paper discusses Guangdong’s social and cultural characteristics, and questions how existing social conditions allow the staging of political deliberation by facilitating political engagement and the formation of public opinion. The paper will investigate the tragedy of Xiao Yueyue in Foshan, Guangdong, where ‘right’ and ‘responsibility’, ‘self’ and ‘other’ define the public sentiments of deliberation and participation.

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Background Dengue fever has been a major public health concern in China since it re-emerged in Guangdong province in 1978. This study aimed to explore spatiotemporal characteristics of dengue fever cases for both indigenous and imported cases during recent years in Guangdong province, so as to identify high-risk areas of the province and thereby help plan resource allocation for dengue interventions. Methods Notifiable cases of dengue fever were collected from all 123 counties of Guangdong province from 2005 to 2010. Descriptive temporal and spatial analysis were conducted, including plotting of seasonal distribution of cases, and creating choropleth maps of cumulative incidence by county. The space-time scan statistic was used to determine space-time clusters of dengue fever cases at the county level, and a geographical information system was used to visualize the location of the clusters. Analysis were stratified by imported and indigenous origin. Results 1658 dengue fever cases were recorded in Guangdong province during the study period, including 94 imported cases and 1564 indigenous cases. Both imported and indigenous cases occurred more frequently in autumn. The areas affected by the indigenous and imported cases presented a geographically expanding trend over the study period. The results showed that the most likely cluster of imported cases (relative risk = 7.52, p < 0.001) and indigenous cases (relative risk = 153.56, p < 0.001) occurred in the Pearl River Delta Area; while a secondary cluster of indigenous cases occurred in one district of the Chao Shan Area (relative risk = 471.25, p < 0.001). Conclusions This study demonstrated that the geographic range of imported and indigenous dengue fever cases has expanded over recent years, and cases were significantly clustered in two heavily urbanised areas of Guangdong province. This provides the foundation for further investigation of risk factors and interventions in these high-risk areas.

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The time for conducting Preventive Maintenance (PM) on an asset is often determined using a predefined alarm limit based on trends of a hazard function. In this paper, the authors propose using both hazard and reliability functions to improve the accuracy of the prediction particularly when the failure characteristic of the asset whole life is modelled using different failure distributions for the different stages of the life of the asset. The proposed method is validated using simulations and case studies.

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It is a big challenge to clearly identify the boundary between positive and negative streams. Several attempts have used negative feedback to solve this challenge; however, there are two issues for using negative relevance feedback to improve the effectiveness of information filtering. The first one is how to select constructive negative samples in order to reduce the space of negative documents. The second issue is how to decide noisy extracted features that should be updated based on the selected negative samples. This paper proposes a pattern mining based approach to select some offenders from the negative documents, where an offender can be used to reduce the side effects of noisy features. It also classifies extracted features (i.e., terms) into three categories: positive specific terms, general terms, and negative specific terms. In this way, multiple revising strategies can be used to update extracted features. An iterative learning algorithm is also proposed to implement this approach on RCV1, and substantial experiments show that the proposed approach achieves encouraging performance.

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A deconvolution method that combines nanoindentation and finite element analysis was developed to determine elastic modulus of thin coating layer in a coating-substrate bilayer system. In this method, the nanoindentation experiments were conducted to obtain the modulus of both the bilayer system and the substrate. The finite element analysis was then applied to deconvolve the elastic modulus of the coating. The results demonstrated that the elastic modulus obtained using the developed method was in good agreement with that reported in literature.

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We estimate the impact of retirement on three subjective and objective measures of health using a regression discontinuity design. The results indicate that retirement increases an individual's sense of well-being and their mental health but not necessarily their physical health. Specifications tests suggest that the results are robust.

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Many data mining techniques have been proposed for mining useful patterns in databases. However, how to effectively utilize discovered patterns is still an open research issue, especially in the domain of text mining. Most existing methods adopt term-based approaches. However, they all suffer from the problems of polysemy and synonymy. This paper presents an innovative technique, pattern taxonomy mining, to improve the effectiveness of using discovered patterns for finding useful information. Substantial experiments on RCV1 demonstrate that the proposed solution achieves encouraging performance.