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		<citationkey>VeroneseRosaVijaBolz:2009:GeNuLa</citationkey>
		<title>Generalized Numerical Lattices for Time Series Representation in Complex Data Systems</title>
		<format>On-line.</format>
		<year>2009</year>
		<secondarytype>PRE CN</secondarytype>
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		<author>Veronese, Thalita B.,</author>
		<author>Rosa, Reinaldo R.,</author>
		<author>Vijaykumar, Nandamudi L.,</author>
		<author>Bolzan, Mauricio J. A.,</author>
		<group>SPG-INPE-MCT-BR</group>
		<group>LAC-CTE-INPE-MCT-BR</group>
		<group>LAC-CTE-INPE-MCT-BR</group>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<affiliation>Universidade do Vale do Paraíba (UNIVAP)</affiliation>
		<editor>Velho, Haroldo Fraga de Campos,</editor>
		<editor>Soterroni, Aline Cristina,</editor>
		<editor>Vasconcellos, Eduardo Charles,</editor>
		<editor>Carneiro, Eduílson Lívio Neves da Costa,</editor>
		<editor>Pantaleão, Eliana,</editor>
		<editor>Goltz, Gustavo Augusto Mascarenhas,</editor>
		<editor>Anochi, Juliana Aparecida,</editor>
		<editor>Dantas, Murilo da Silva,</editor>
		<editor>Rosa, Reinaldo Roberto,</editor>
		<editor>Junior, Rodolfo Ranck,</editor>
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		<conferencename>Workshop dos Cursos de Computação Aplicada do INPE, 9 (WORCAP).</conferencename>
		<conferencelocation>São José dos Campos</conferencelocation>
		<date>21 e 22 out. 2009</date>
		<publisher>Instituto Nacional de Pesquisas Espaciais (INPE)</publisher>
		<publisheraddress>São José dos Campos</publisheraddress>
		<booktitle>Anais</booktitle>
		<organization>Instituto Nacional de Pesquisas Espaciais (INPE)</organization>
		<transferableflag>1</transferableflag>
		<keywords>x.</keywords>
		<abstract>Analysis of information from multiple data sources obtained through high resolution instrumental measurements has become a fundamental task in all scientific areas. The development of expert methods able to treat such multisource data systems, with both large variability and measurement extension, is a key for studying complex scientific phenomena, especially those related to systemic analysis in space and environmental sciences. In this paper, we propose a times series generalization introducing the concept of generalized numerical lattice, which represents a discrete sequence of temporal measures for a given variable. As a case study, we show a preliminary application in space science data, highlighting the possibility of a real time analysis expert system to be developed in a future work.</abstract>
		<area>COMP</area>
		<language>pt</language>
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