1,720,990 research outputs found

    Dataset Popularity Prediction for Caching of CMS Big Data

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    The Compact Muon Solenoid (CMS) expe- riment at the European Organization for Nuclear Research (CERN) deploys its data collections, simula- tion and analysis activities on a distributed computing infrastructure involving more than 70 sites worldwide. The historical usage data recorded by this large infras- tructure is a rich source of information for system tun- ing and capacity planning. In this paper we investigate how to leverage machine learning on this huge amount of data in order to discover patterns and correlations useful to enhance the overall efficiency of the dis- tributed infrastructure in terms of CPU utilization and task completion time. In particular we propose a scal- able pipeline of components built on top of the Spark engine for large-scale data processing, whose goal is collecting from different sites the dataset access logs, organizing them into weekly snapshots, and training, on these snapshots, predictive models able to fore- cast which datasets will become popular over time. The high accuracy achieved indicates the ability of the learned model to correctly separate popular datasets from unpopular ones. Dataset popularity predictions are then exploited within a novel data caching policy, called PPC (Popularity Prediction Caching). We eval- uate the performance of PPC against popular caching policy baselines like LRU (Least Recently Used). The experiments conducted on large traces of real dataset accesses show that PPC outperforms LRU reducing the number of cache misses up to 20% in some sites

    AN APPARATUS FOR SCINTIGRAPHIC ANALYSIS, PARTICULARLY A MAMMOGRAPH,WITH SUB-MILLIMETRIC SPATIAL RESOLUTION

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    A scintigraphic mammograph with sub-millimetric spatial resolution adapted to detect gamma radiations with 30 KeV to 2 MeV energy, comprising a sensitive head section (10) with a box shaped shielding container (16) co-operating with a standard pressure member and receiving the following essential components combined together in the following succession: an apertured collimator (11), of a high atomic number material, adapted to collimate the gamma radiation emissions from the body organ being investigated; a scintillating crystal and fluorescent fiber structure adapted to convert the gamma radiations emitted from the concerned body organ into light radiations; a multi-anode or crossed wire photo-multiplier or position sensitive solid state detector, which receives the light radiations emitted from said scintillating crystals and fluorescent fibers and generates signals proportional to the received light radiations; a hardware assembly adapted to perform conversion and integration of all signals generated by said photo-multiplier assembly from an analog to a digital format as well as their amplification in order to subsequently couple them to an electronic processor which processes and displays then on a suitable monitor in the form of an image of the concerned body organ

    Popularity-Based Caching of CMS Datasets

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    The distributed monitoring infrastructure of the Compact Muon Solenoid (CMS) experiment at the European Organization for Nuclear Research (CERN) records on a Hadoop infrastructures a broad variety of computing and storage logs. They represent a valuable source of information for system tuning and capacity planning. In this paper we analyze machine learning (ML) techniques on large amount of traces to discover patterns and correlations useful to classify the popularity of experiment-related datasets. We implement a scalable pipeline of Spark components which collect the dataset access logs from heterogeneous monitoring sources and group them into weekly snapshots organized by CMS sites. Predictive models are trained on these snapshots and forecast which dataset will become popular over time. Dataset popularity predictions are then used to experiment a novel strategy of data caching, called Popularity Prediction Caching (PPC). We compare the hit rates of PPC with those produced by well known caching policies. We demonstrate how the performance improvement is as high as 20% in some sites

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed

    Variations on the Author

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    “Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship

    Appropriate Similarity Measures for Author Cocitation Analysis

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    We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis

    Dispelling the Myths Behind First-author Citation Counts

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    We conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more sophisticated methods

    Author Index

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    koamabayili/VECTRON-author-checklist: VECTRON author checklist

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    We have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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