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            <name>Title</name>
            <description>A name given to the resource</description>
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                <text>Coronavirus</text>
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            <description>An account of the resource</description>
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                <text>Dominio científico: Coronavirus</text>
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          <name>Title</name>
          <description>A name given to the resource</description>
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              <text>Table Organization Optimization in Schools for Preserving the Social Distance during the COVID-19 Pandemic</text>
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          <name>Creator</name>
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              <text>Hilde Pérez, Javier Díez-González, Paula Verde, Rubén Ferrero-Guillén, Rubén Álvarez</text>
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              <text>The COVID-19 pandemic has supposed a challenge for education. The school closures during the initial coronavirus outbreak for reducing the infections have promoted negative effects on children, such as the interruption of their normal social relationships or their necessary physical activity. Thus, most of the countries worldwide have considered as a priority the reopening of schools but imposing some rules for keeping safe places for the school lessons such as social distancing, wearing facemasks, hydroalcoholic gels or reducing the capacity in the indoor rooms. In Spain, the government has fixed a minimum distance of 1.5 m among the students’ desks for preserving the social distancing and schools have followed orthogonal and triangular mesh patterns for achieving valid table dispositions that meet the requirements. However, these patterns may not attain the best results for maximizing the distances among the tables. Therefore, in this paper, we introduce for the first time in the authors’ best knowledge a Genetic Algorithm (GA) for optimizing the disposition of the tables at schools during the coronavirus pandemic. We apply this GA in two real-application scenarios in which we find table dispositions that increase the distances among the tables by 19.33% and 10%, respectively, with regards to regular government patterns in these classrooms, thus fulfilling the main objectives of the paper.</text>
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              <text>2020</text>
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          <name>Subject</name>
          <description>The topic of the resource</description>
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              <text>covid-19, genetic algorithms, Genetic Operators, table distribution optimization, table location problem</text>
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          <name>Identifier</name>
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              <text>10.3390/app10238392</text>
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              <text>Epidemiology and Health</text>
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          <name>Publisher</name>
          <description>An entity responsible for making the resource available</description>
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              <text>Korean Society of Epidemiology</text>
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          <name>Coverage</name>
          <description>The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant</description>
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              <text>Biology (General), Chemistry, Engineering (General). Civil engineering (General), Technology, Physics</text>
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