3 resultados para information bottleneck method

em DRUM (Digital Repository at the University of Maryland)


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Problem This dissertation presents a literature-based framework for communication in science (with the elements partners, purposes, message, and channel), which it then applies in and amends through an empirical study of how geoscientists use two social computing technologies (SCTs), blogging and Twitter (both general use and tweeting from conferences). How are these technologies used and what value do scientists derive from them? Method The empirical part used a two-pronged qualitative study, using (1) purposive samples of ~400 blog posts and ~1000 tweets and (2) a purposive sample of 8 geoscientist interviews. Blog posts, tweets, and interviews were coded using the framework, adding new codes as needed. The results were aggregated into 8 geoscientist case studies, and general patterns were derived through cross-case analysis. Results A detailed picture of how geoscientists use blogs and twitter emerged, including a number of new functions not served by traditional channels. Some highlights: Geoscientists use SCTs for communication among themselves as well as with the public. Blogs serve persuasion and personal knowledge management; Twitter often amplifies the signal of traditional communications such as journal articles. Blogs include tutorials for peers, reviews of basic science concepts, and book reviews. Twitter includes links to readings, requests for assistance, and discussions of politics and religion. Twitter at conferences provides live coverage of sessions. Conclusions Both blogs and Twitter are routine parts of scientists' communication toolbox, blogs for in-depth, well-prepared essays, Twitter for faster and broader interactions. Both have important roles in supporting community building, mentoring, and learning and teaching. The Framework of Communication in Science was a useful tool in studying these two SCTs in this domain. The results should encourage science administrators to facilitate SCT use of scientists in their organization and information providers to search SCT documents as an important source of information.

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We present a detailed analysis of the application of a multi-scale Hierarchical Reconstruction method for solving a family of ill-posed linear inverse problems. When the observations on the unknown quantity of interest and the observation operators are known, these inverse problems are concerned with the recovery of the unknown from its observations. Although the observation operators we consider are linear, they are inevitably ill-posed in various ways. We recall in this context the classical Tikhonov regularization method with a stabilizing function which targets the specific ill-posedness from the observation operators and preserves desired features of the unknown. Having studied the mechanism of the Tikhonov regularization, we propose a multi-scale generalization to the Tikhonov regularization method, so-called the Hierarchical Reconstruction (HR) method. First introduction of the HR method can be traced back to the Hierarchical Decomposition method in Image Processing. The HR method successively extracts information from the previous hierarchical residual to the current hierarchical term at a finer hierarchical scale. As the sum of all the hierarchical terms, the hierarchical sum from the HR method provides an reasonable approximate solution to the unknown, when the observation matrix satisfies certain conditions with specific stabilizing functions. When compared to the Tikhonov regularization method on solving the same inverse problems, the HR method is shown to be able to decrease the total number of iterations, reduce the approximation error, and offer self control of the approximation distance between the hierarchical sum and the unknown, thanks to using a ladder of finitely many hierarchical scales. We report numerical experiments supporting our claims on these advantages the HR method has over the Tikhonov regularization method.

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In 2013, a series of posters began appearing in Washington, DC’s Metro system. Each declared “The internet: Your future depends on it” next to a photo of a middle-aged black Washingtonian, and an advertisement for the municipal government’s digital training resources. This hopeful discourse is familiar but where exactly does it come from? And how are our public institutions reorganized to approach the problem of poverty as a problem of technology? The Clinton administration’s ‘digital divide’ policy program popularized this hopeful discourse about personal computing powering social mobility, positioned internet startups as the ‘right’ side of the divide, and charged institutions of social reproduction such as schools and libraries with closing the gap and upgrading themselves in the image of internet startups. After introducing the development regime that builds this idea into the urban landscape through what I call the ‘political economy of hope’, and tracing the origin of the digital divide frame, this dissertation draws on three years of comparative ethnographic fieldwork in startups, schools, and libraries to explore how this hope is reproduced in daily life, becoming the common sense that drives our understanding of and interaction with economic inequality and reproduces that inequality in turn. I show that the hope in personal computing to power social mobility becomes a method of securing legitimacy and resources for both white émigré technologists and institutions of social reproduction struggling to understand and manage the persistent poverty of the information economy. I track the movement of this common sense between institutions, showing how the political economy of hope transforms them as part of a larger development project. This dissertation models a new, relational direction for digital divide research that grounds the politics of economic inequality with an empirical focus on technologies of poverty management. It demands a conceptual shift that sees the digital divide not as a bug within the information economy, but a feature of it.