28,119 research outputs found

    Disentangling agglomeration and network externalities : a conceptual typology

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    Agglomeration and network externalities are fuzzy concepts. When different meanings are (un)intentionally juxtaposed in analyses of the agglomeration/network externalities-menagerie, researchers may reach inaccurate conclusions about how they interlock. Both externality types can be analytically combined, but only when one adopts a coherent approach to their conceptualization and operationalization, to which end we provide a combinatorial typology. We illustrate the typology by applying a state-of-the-art bipartite network projection detailing the presence of globalized producer services firms in cities in 2012. This leads to two one-mode graphs that can be validly interpreted as topological renderings of agglomeration and network externalities

    Review of analytical instruments for EEG analysis

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    Since it was first used in 1926, EEG has been one of the most useful instruments of neuroscience. In order to start using EEG data we need not only EEG apparatus, but also some analytical tools and skills to understand what our data mean. This article describes several classical analytical tools and also new one which appeared only several years ago. We hope it will be useful for those researchers who have only started working in the field of cognitive EEG

    The State of the Art in Cartograms

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    Cartograms combine statistical and geographical information in thematic maps, where areas of geographical regions (e.g., countries, states) are scaled in proportion to some statistic (e.g., population, income). Cartograms make it possible to gain insight into patterns and trends in the world around us and have been very popular visualizations for geo-referenced data for over a century. This work surveys cartogram research in visualization, cartography and geometry, covering a broad spectrum of different cartogram types: from the traditional rectangular and table cartograms, to Dorling and diffusion cartograms. A particular focus is the study of the major cartogram dimensions: statistical accuracy, geographical accuracy, and topological accuracy. We review the history of cartograms, describe the algorithms for generating them, and consider task taxonomies. We also review quantitative and qualitative evaluations, and we use these to arrive at design guidelines and research challenges

    Anomalous transport effects and possible environmental symmetry "violation" in heavy ion collisions

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    The heavy ion collision provides a unique many-body environment where local domains of strongly interacting chiral medium may occur and in a sense allow environmental symmetry "violation" phenomena. For example certain anomalous transport processes, forbidden in usual medium, become possible in such domains. We briefly review recent progress in both the theoretical understanding and experimental search of various anomalous transport effects (such as the Chiral Magnetic Effect, Chiral Separation Effect, Chiral Electric Separation Effect, Chiral Electric/Magnetic Waves, etc) in the hot QCD fluid created by such collisions.Comment: final version with minor updates; 24 pages, 5 figures; invited review for Pramana - Journal of Physic

    On the use of empirical or artifical project data

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    This paper gives a brief overview of the artificial and empirical project data generated and collected by the researchers from the Operations Research and Scheduling (OR&S) group from Ghent University in Belgium. Artificial data are generated by project network generators under a strict design to control both the network structure and the resource constraints, while the empirical project data are collected over a time horizon of multiple years, using a standardized collection and classification method. All data are publicly available on the OR&S website www.projectmanagement.ugent. be/research/data) and can be used anywhere for academic purposes. More detailed information on the network and resource parameters used to generate the artificial data and the classification process for the collection of empirical data is available in a paper published in the Journal of Modern Project Management (Vanhoucke et al., 2016)
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