948 resultados para Information display systems.


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This paper will report on the production, dimensional control, and characterization of arrays of cold-cathode field emitters based on multiwall carbon nanotubes, suitable for use in large-area field-emission-based displays.

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The article discusses the progress and issues related to transparent oxide semiconductor (TOS) TFTs for advanced display and imaging applications. Amorphous oxide semiconductors continue to spark new technological developments in transparent electronics on a multitude of non-conventional substrates. Applications range from high-frame-rate interactive displays with embedded imaging to flexible electronics, where speed and transparency are essential requirements. TOS TFTs exhibit high transparency as well as high electron mobility even when fabricated at room temperature. Compared to conventional a-Si TFT technology, TOS TFTs have higher mobility and sufficiently good uniformity over large areas, similar in many ways to LTPS TFTs. Moreover, because the amorphous oxide semiconductor has higher mobility compared to that of conventional a-Si TFT technology, this allows higher-frame-rate display operation. This would greatly benefit OLED displays in particular because of the need for lower-cost higher-mobility analog circuits at every subpixel.

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Selection power is taken as the fundamental value for information retrieval systems. Selection power is regarded as produced by selection labor, which itself separates historically into description and search labor. As forms of mental labor, description and search labor participate in the conditions for labor and for mental labor. Concepts and distinctions applicable to physical and mental labor are indicated, introducing the necessity of labor for survival, the idea of technology as a human construction, and the possibility of the transfer of human labor to technology. Distinctions specific to mental labor, particular between semantic and syntactic labor, are introduced. Description labor is exemplified by cataloging, classification, and database description, can be more formally understood as the labor involved in the transformation of objects for description into searchable descriptions, and is also understood to include interpretation. The costs of description labor are discussed. Search labor is conceived as the labor expended in searching systems. For both description and search labor, there has been a progressive reduction in direct human labor, with its syntactic aspects transferred to technology, effectively compelled by the high relative costs of direct human labor compared to machine processes.

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We present a new algorithm for exactly solving decision-making problems represented as an influence diagram. We do not require the usual assumptions of no forgetting and regularity, which allows us to solve problems with limited information. The algorithm, which implements a sophisticated variable elimination procedure, is empirically shown to outperform a state-of-the-art algorithm in randomly generated problems of up to 150 variables and 10^64 strategies.