891 resultados para pacs: information storage and retrieval


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This article reviews current technological developments, particularly Peer-to-Peer technologies and Distributed Data Systems, and their value to community memory projects, particularly those concerned with the preservation of the cultural, literary and administrative data of cultures which have suffered genocide or are at risk of genocide. It draws attention to the comparatively good representation online of genocide denial groups and changes in the technological strategies of holocaust denial and other far-right groups. It draws on the author's work in providing IT support for a UK-based Non-Governmental Organization providing support for survivors of genocide in Rwanda.

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Emerging evidence suggests that a group of dietary-derived phytochemicals known as flavonoids are able to induce improvements in memory acquisition, consolidation, storage and retrieval. These low molecular weight polyphenols are widespread in the human diet, are absorbed to only a limited degree and localise in the brain at low concentration. However, they have been found to be highly effective in reversing age-related declines in memory via their ability to interact with the cellular and molecular architecture of the brain responsible for memory. These interactions include an ability to activate signalling pathways, critical in controlling synaptic plasticity, and a potential to induce vascular effects capable of causing new nerve cell growth in the hippocampus. Their ability to activate the extracellular signal-regulated kinase (ERK1/2) and the protein kinase B (PKB/Akt) signalling pathways, leading to the activation of the cAMP response element-binding protein (CREB), a transcription factor responsible for increasing the expression of a number of neurotrophins important in de. ning memory, will be discussed. How these effects lead to improvements in memory through induction of synapse growth and connectivity, increases in dendritic spine density and the functional integration of old and new neurons will be illustrated. The overall goal of this critical review is to emphasize future areas of investigation as well as to highlight these dietary agents as promising candidates for the design of memory-enhancing drugs with relevance to normal and pathological brain ageing (161 references).

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BACKGROUND: Since the discovery in 2002 of acrylamide in a wide range of foods, there has been much work done to explore mechanisms of formation and to reduce acrylamide in commercial products. This study aimed to investigate simple measures which could be used to reduce acrylamide formation in home-cooked French fries, using potatoes from three cultivars stored under controlled conditions and sampled at three time points. RESULTS: The reducing sugar content for all three cultivars increased during storage, which led to increased acrylamide levels in the French fries. Washing and soaking (30 min or 2 h) raw French fries before cooking led to reductions in acrylamide of up to 23, 38 and 48% respectively. Pre-treated fries were lighter in colour after cooking than the corresponding controls. CONCLUSION: Pre-treatments such as soaking or washing raw French fries in water reduce acrylamide and colour formation in the final product when cooking is stopped at a texture-determined endpoint. (c) 2008 Society of Chemical Industry.

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There are still major challenges in the area of automatic indexing and retrieval of multimedia content data for very large multimedia content corpora. Current indexing and retrieval applications still use keywords to index multimedia content and those keywords usually do not provide any knowledge about the semantic content of the data. With the increasing amount of multimedia content, it is inefficient to continue with this approach. In this paper, we describe the project DREAM, which addresses such challenges by proposing a new framework for semi-automatic annotation and retrieval of multimedia based on the semantic content. The framework uses the Topic Map Technology, as a tool to model the knowledge automatically extracted from the multimedia content using an Automatic Labelling Engine. We describe how we acquire knowledge from the content and represent this knowledge using the support of NLP to automatically generate Topic Maps. The framework is described in the context of film post-production.

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A novel framework referred to as collaterally confirmed labelling (CCL) is proposed, aiming at localising the visual semantics to regions of interest in images with textual keywords. Both the primary image and collateral textual modalities are exploited in a mutually co-referencing and complementary fashion. The collateral content and context-based knowledge is used to bias the mapping from the low-level region-based visual primitives to the high-level visual concepts defined in a visual vocabulary. We introduce the notion of collateral context, which is represented as a co-occurrence matrix of the visual keywords. A collaborative mapping scheme is devised using statistical methods like Gaussian distribution or Euclidean distance together with collateral content and context-driven inference mechanism. We introduce a novel high-level visual content descriptor that is devised for performing semantic-based image classification and retrieval. The proposed image feature vector model is fundamentally underpinned by the CCL framework. Two different high-level image feature vector models are developed based on the CCL labelling of results for the purposes of image data clustering and retrieval, respectively. A subset of the Corel image collection has been used for evaluating our proposed method. The experimental results to-date already indicate that the proposed semantic-based visual content descriptors outperform both traditional visual and textual image feature models. (C) 2007 Elsevier B.V. All rights reserved.

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Many small businesses lease commercial premises. The terms of a lease can affect the ability of the business to grow and adapt and have an impact on cashflow. Ensuring that they have the information with which to negotiate terms is part of the UK government policy focus on small businesses. Such information is most effectively disseminated through the sources of advice that small businesses use during the leasing process. Therefore these sources of advice need identifying. An interview survey of small business tenants who have recently taken leases provides initial results that suggest small businesses do not seek out advice during the leasing process or see the need to be better informed. The only formal professional input is from solicitors but this is not until after the main commercial terms have been agreed. The landlords’ letting agents play a key, but ambiguous, role in providing information as well as advice. These results suggest that the most effective way of disseminating information by government could be via the letting agents, the very people with whom the tenants are negotiating.

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We consider the finite sample properties of model selection by information criteria in conditionally heteroscedastic models. Recent theoretical results show that certain popular criteria are consistent in that they will select the true model asymptotically with probability 1. To examine the empirical relevance of this property, Monte Carlo simulations are conducted for a set of non–nested data generating processes (DGPs) with the set of candidate models consisting of all types of model used as DGPs. In addition, not only is the best model considered but also those with similar values of the information criterion, called close competitors, thus forming a portfolio of eligible models. To supplement the simulations, the criteria are applied to a set of economic and financial series. In the simulations, the criteria are largely ineffective at identifying the correct model, either as best or a close competitor, the parsimonious GARCH(1, 1) model being preferred for most DGPs. In contrast, asymmetric models are generally selected to represent actual data. This leads to the conjecture that the properties of parameterizations of processes commonly used to model heteroscedastic data are more similar than may be imagined and that more attention needs to be paid to the behaviour of the standardized disturbances of such models, both in simulation exercises and in empirical modelling.