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Étiquette : networks-systems-distributed-computing

Networks, Systems and Services, Distributed Computing: Part I

Networks, Systems and Services, Distributed Computing: Part I

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Calendar

2:00 pm: PhD Seminars VII

2:00 pm: PhD Seminars VIII

Sujets d’intérêt

Archives

Calendar

2:00 pm: PhD Seminars VII

2:00 pm: PhD Seminars VIII

Talk 1

Talk 2

Talk 1

Talk 1

Talk 2

Talk 1

Nathalie GAYRAUD Mon 09 October 2017 Fri 13 October 2017Séminaires

Talk 1 Title: How to use Hop and HipHop technologies for the scene: The Massively Interactive Music track. Speaker: Bertrand PETIT and Manuel SERANO – INDES Abstract: In a concert the common way of performing music is largely asymmetric. Most of the time, we have the musicians on one side…

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applied mathematics asteroid exploration biological systems brain combinatorial optimization communication conductivity estimation dynamic dynamics EEG fixed point loops fluid dynamics functional emmbeddings fusion plasmas Galerkin time domain methods git health-biology infection spread invariant manifolds mapping marketing mesh modeling nanophotonics networks networks-systems-distributed-computing neuronal cells numerical simulations optimal transport optimisation optimization pattern recognition PDE protein function radar applications regularization retina routing applications scientific dissemination sed shape matching source localization stochastic gradient algorithm variability workshop
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12 2:00 pm: PhD Seminars VIII avril 12, 2021 2:00 – 4:00 Talk 1 Speaker Maroua Tikat (WIMMICS) Title Interactive multimedia visualization for exploring and fixing a multi-dimensional metadata base of popular music Abstract This PHD thesis is concerned by the use of information visualization techniques as a mean to allow the exploration of a large dataset of music metadata. In this paper we review some of the major music datasets available, the data they contain, and how information visualization techniques have been used to explore such data. As we shall see, music is a complex entity that can be described as a multitude of multimedia attributes (ex. lyrics, chords, audio, graphics describing sound analysis, etc.). Thus, music datasets are often created by collecting data from specialized datasets. The integration of data from diverse sources might create problems of data quality (ex. ambiguities, imprecision, incomplete sources, conflicts, etc.). Traditionally, information visualization techniques are used to understand the corpus of data and identify causal relationships, trends, patterns of data concentrations. Nonetheless, we suggest that information visualization techniques be used to inspect the data quality of multivariate data sets and highlight the parts of the data sets that need to be fixed/improved. Moreover, using interactive techniques, we suggest that information visualization techniques could be used as entry point for repairing the data set. In the context of this PhD thesis, the research questions are: how to communicate problems related to data quality to the users, and how to visually represent the outcomes of methods used for data completion and correction (such as crowdsourcing, matrix vectorization, graph reasoning, among other). More