913 resultados para 004 - Informatik (Data processing Computer science)


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This is the website for the Nano Research group based at the University of Southampton ECS department, and details current research topics and the people connected with these. It shows some of the current research topics undertaken at the center, and gives an outline of what can be done for post graduate courses.

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What is Computer Science about?

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4 examples of student reflections

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Tuesday 22nd April 2014 Speaker(s): Sue Sentance Organiser: Leslie Carr Time: 22/04/2014 15:00-16:00 Location: B32/3077 File size: 698 Mb Abstract Until recently, "computing" education in English schools mainly focused on developing general Digital Literacy and Microsoft Office skills. As of this September, a new curriculum comes into effect that provides a strong emphasis on computation and programming. This change has generated some controversy in the news media (4-year-olds being forced to learn coding! boss of the government’s coding education initiative cannot code shock horror!!!!) and also some concern in the teaching profession (how can we possibly teach programming when none of the teachers know how to program)? Dr Sue Sentance will explain the work of Computing At School, a part of the BCS Academy, in galvanising universities to help teachers learn programming and other computing skills. Come along and find out about the new English Computing Revolution - How will your children and your schools be affected? - How will our University intake change? How will our degrees have to change? - What is happening to the national perception of Computer Science?

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Abstract: As one of the newest art forms available to young people, gaming has become an increasing influence on young people’s education, even if not used in a classroom environment. This talk aims to explore examples of how video games have changed how young people understand and learn about certain subjects, with particular focus on how the indie title Minecraft allows them to learn about the world of Computer Science and how groups are looking to forward the cause of education though games.

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Resumen tomado de la publicación

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Image registration is an important component of image analysis used to align two or more images. In this paper, we present a new framework for image registration based on compression. The basic idea underlying our approach is the conjecture that two images are correctly registered when we can maximally compress one image given the information in the other. The contribution of this paper is twofold. First, we show that the image registration process can be dealt with from the perspective of a compression problem. Second, we demonstrate that the similarity metric, introduced by Li et al., performs well in image registration. Two different versions of the similarity metric have been used: the Kolmogorov version, computed using standard real-world compressors, and the Shannon version, calculated from an estimation of the entropy rate of the images

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This article analyses the results of an empirical study on the 200 most popular UK-based websites in various sectors of e-commerce services. The study provides empirical evidence on unlawful processing of personal data. It comprises a survey on the methods used to seek and obtain consent to process personal data for direct marketing and advertisement, and a test on the frequency of unsolicited commercial emails (UCE) received by customers as a consequence of their registration and submission of personal information to a website. Part One of the article presents a conceptual and normative account of data protection, with a discussion of the ethical values on which EU data protection law is grounded and an outline of the elements that must be in place to seek and obtain valid consent to process personal data. Part Two discusses the outcomes of the empirical study, which unveils a significant departure between EU legal theory and practice in data protection. Although a wide majority of the websites in the sample (69%) has in place a system to ask separate consent for engaging in marketing activities, it is only 16.2% of them that obtain a consent which is valid under the standards set by EU law. The test with UCE shows that only one out of three websites (30.5%) respects the will of the data subject not to receive commercial communications. It also shows that, when submitting personal data in online transactions, there is a high probability (50%) of incurring in a website that will ignore the refusal of consent and will send UCE. The article concludes that there is severe lack of compliance of UK online service providers with essential requirements of data protection law. In this respect, it suggests that there is inappropriate standard of implementation, information and supervision by the UK authorities, especially in light of the clarifications provided at EU level.

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Background: Expression microarrays are increasingly used to obtain large scale transcriptomic information on a wide range of biological samples. Nevertheless, there is still much debate on the best ways to process data, to design experiments and analyse the output. Furthermore, many of the more sophisticated mathematical approaches to data analysis in the literature remain inaccessible to much of the biological research community. In this study we examine ways of extracting and analysing a large data set obtained using the Agilent long oligonucleotide transcriptomics platform, applied to a set of human macrophage and dendritic cell samples. Results: We describe and validate a series of data extraction, transformation and normalisation steps which are implemented via a new R function. Analysis of replicate normalised reference data demonstrate that intrarray variability is small (only around 2 of the mean log signal), while interarray variability from replicate array measurements has a standard deviation (SD) of around 0.5 log(2) units (6 of mean). The common practise of working with ratios of Cy5/Cy3 signal offers little further improvement in terms of reducing error. Comparison to expression data obtained using Arabidopsis samples demonstrates that the large number of genes in each sample showing a low level of transcription reflect the real complexity of the cellular transcriptome. Multidimensional scaling is used to show that the processed data identifies an underlying structure which reflect some of the key biological variables which define the data set. This structure is robust, allowing reliable comparison of samples collected over a number of years and collected by a variety of operators. Conclusions: This study outlines a robust and easily implemented pipeline for extracting, transforming normalising and visualising transcriptomic array data from Agilent expression platform. The analysis is used to obtain quantitative estimates of the SD arising from experimental (non biological) intra- and interarray variability, and for a lower threshold for determining whether an individual gene is expressed. The study provides a reliable basis for further more extensive studies of the systems biology of eukaryotic cells.