593 research outputs found

    Studies of final states in small x deep inelastic scattering

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    We investigate the possibility of identifying In(l/x) dynamics from studies of the final state in electron - proton deep inelastic scattering (DIS) in the small x region of the HERA collider at DESY. Motivated by recent observations at HERA we consider again the measurement of DIS events containing an identified forward jet as proposed by Mueller. We find that the shape of the x distribution of the data is described well by a prediction based on In(l/x) dynamics. Since forward jets are difficult to identify and measure accurately in the experiments we suggest the study of deep inelastic events containing an energetic isolated photon. We quantify the enhancement arising from the leading In(l/x) gluon emissions with a view to using such events to identify the underlying dynamics in the small x regime at HERA. To overcome the small event rate of jet + γ we propose that the forward jet may alternatively be identified through a single energetic decay product, the π . We investigate the feasibility of utilizing these deep inelastic + forward π events as an indicator of the small x dynamics. Motivated by this study the HI collaboration recently performed a DIS + π measurement. Therefore we update our BFKL prediction imposing the HI cuts in the calculation. We fix the normalisation by comparing with HERA data for DIS + jet. Finally we study the transverse momentum (pr) spectrum of charged particles produced in DIS at small Bjorken x in the central region between the current jet and the proton remnants. Again we normalize the BFKL prediction by comparing with the H1 DIS + jet data. We calculate the spectrum at large pr with the BFKL ln(l/x) resummation included and then repeat the calculation with it omitted. We find that data favour the former

    Transforming Information Into Knowledge

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    Welche Themen hat die Femina Politica bislang vernachlässigt?

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    Montage braucht Erfahrung: Erfahrungsbasierte Wissensarbeit in der Montage

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    Hat Montage in Deutschland noch Perspektive, wenn betriebliche Layouts und Abläufe weltweit exportiert werden? Gibt es besondere Bedingungen für flexible Montagen, die Deutschland als Montagestandort attraktiv machen? Was sind es für Kernkompetenzen, die sich Standardisierung und Tätigkeitsbeschreibungen entziehen und - trotz globaler Ausrichtung - eine Montage im Inland erfolgreich machen? Die Beiträge dieses Bandes geben einen Einblick in die konkrete Bedeutung des Erfahrungswissens der Beschäftigten für moderne Montagearbeitsplätze. Sie zeigen, warum Montagearbeit auch Wissensarbeit ist, warum diese sich einer einfachen Messung und (entgeltpolitischen) Bewertung entzieht, warum die Nutzung und Entwicklung eng mit einer erfahrungsförderlichen Arbeitsgestaltung verbunden ist und warum für eine betriebliche Qualifizierung vor dem Hintergrund Ganzheitlicher Produktionskonzepte die Vermittlung von Erfahrungswissen wichtig ist. Darüber hinaus leistet der Band einen Beitrag zu den laufenden Debatten um neue Produktionskonzepte, um die Zukunft von Produktionstätigkeiten am Standort Deutschland, um die Verkürzung von Taktzeiten und um die Auswirkungen auf Berufsbildung und Arbeitspolitik

    Large-scale interactive retrieval in art collections using multi-style feature aggregation

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    Finding objects and motifs across artworks is of great importance for art history as it helps to understand individual works and analyze relations between them. The advent of digitization has produced extensive digital art collections with many research opportunities. However, manual approaches are inadequate to handle this amount of data, and it requires appropriate computer-based methods to analyze them. This article presents a visual search algorithm and user interface to support art historians to find objects and motifs in extensive datasets. Artistic image collections are subject to significant domain shifts induced by large variations in styles, artistic media, and materials. This poses new challenges to most computer vision models which are trained on photographs. To alleviate this problem, we introduce a multi-style feature aggregation that projects images into the same distribution, leading to more accurate and style-invariant search results. Our retrieval system is based on a voting procedure combined with fast nearest-neighbor search and enables finding and localizing motifs within an extensive image collection in seconds. The presented approach significantly improves the state-of-the-art in terms of accuracy and search time on various datasets and applies to large and inhomogeneous collections. In addition to the search algorithm, we introduce a user interface that allows art historians to apply our algorithm in practice. The interface enables users to search for single regions, multiple regions regarding different connection types and holds an interactive feedback system to improve retrieval results further. With our methodological contribution and easy-to-use user interface, this work manifests further progress towards a computer-based analysis of visual art
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