4 resultados para hierarchical knowledge representation

em WestminsterResearch - UK


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Colombia’s Internet connectivity has increased immensely. Colombia has also ‘opened for business’, leading to an influx of extractive projects to which social movements object heavily. Studies on the role of digital media in political mobilisation in developing countries are still scarce. Using surveys, interviews, and reviews of literature, policy papers, website and social media content, this study examines the role of digital and social media in social movement organisations and asks how increased digital connectivity can help spread knowledge and mobilise mining protests. Results show that the use of new media in Colombia is hindered by socioeconomic constraints, fear of oppression, the constraints of keyboard activism and strong hierarchical power structures within social movements. Hence, effects on political mobilisation are still limited. Social media do not spontaneously produce non-hierarchical knowledge structures. Attention to both internal and external knowledge sharing is therefore conditional to optimising digital and social media use.

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This study examines managers‟ perceptions of Knowledge Management (KM) prior to implementation of KM-systems in a global insurance company and investigates whether Hierarchical structures are conducive to KM. Mixed methods are used, combining large scale surveying and case study using content analysis to organize the data into themes that provide the basis for arguments. Evidence suggests that managers strongly align their perception of KM with communication. Despite a multi-layered, hierarchical structure and strong middle management presence, organizational structure was not viewed as an issue. These factors are usually barriers to communication and organizational flexibility, yet managers believe that they may not inhibit KM becoming fully embedded. This evidence is contradicted by the results of a global KM study where silos, stovepipe and hierarchical structures were commonly cited as barriers. This contributes to the understanding of managerial mis-conceptions of knowledge as opposed to communication, and how organizations effectively share knowledge.

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This article seeks to revise Jo Doezema’s suggestion that ‘the white slave’ was the only dominant representation of ‘the trafficked woman’ used by early anti-trafficking advocates in Europe and the United States, and that discourses based on this figure of injured innocence are the only historical discourses that are able to shine light on contemporary anti-trafficking rhetoric. ‘The trafficked woman’ was a figure painted using many shades of grey in the past, with a number of injurious consequences, not only for trafficked persons but also for female labour migrants and migrant populations at large. In England, dominant organizational portrayals of ‘the trafficked woman’ had first acquired these shades by the 1890s, when trafficking started to proliferate amid mass migration from Continental Europe, and when controversy began to mount over the migration to the country of various groups of working-class foreigner. The article demonstrates these points by exploring the way in which the Jewish Association for the Protection of Girls and Women (JAPGW), one of the pillars of England’s early anti-trafficking movement, represented the female Jewish migrants it deemed at risk from being trafficked into sex work between 1890 and 1910. It argues that the JAPGW stigmatised these women, placing most of the onus for trafficking upon them and positioning them to a greater or a lesser extent as ‘undesirable and undeserving working-class foreigners’ who could never become respectable English women. It also contends that the JAPGW, in outlining what was wrong with certain female migrants, drew a line between ‘the migrant’ and respectable English society at large, and paradoxically endorsed the extension of the very ‘anti-alienist’ and Antisemitic prejudices that it strove to dispel.

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This work presents the design of a real-time system to model visual objects with the use of self-organising networks. The architecture of the system addresses multiple computer vision tasks such as image segmentation, optimal parameter estimation and object representation. We first develop a framework for building non-rigid shapes using the growth mechanism of the self-organising maps, and then we define an optimal number of nodes without overfitting or underfitting the network based on the knowledge obtained from information-theoretic considerations. We present experimental results for hands and faces, and we quantitatively evaluate the matching capabilities of the proposed method with the topographic product. The proposed method is easily extensible to 3D objects, as it offers similar features for efficient mesh reconstruction.