Este artigo apresenta os resultados obtidos da exploração dos vetores de características gerados de técnicas de word embedding (especificamente word2vec e wang2vec) a partir de um banco de textos na ordem do bilhão de tokens em comparação com os gerados a partir de bancos pequenos na ordem de dezenas de milhar, na aplicação de detecção de discurso de ódio na língua portuguesa. Dando continuidade às pesquisas desenvolvidas por outros autores no Brasil e em Portugal, e aproveitando os recursos e sugestões por eles disponibilizados, conseguiu-se uma melhora de até 2,5% na taxa de acerto na classificação, em relação ao estado da arte em língua portuguesa.
<p>The thermo-energetic performance of the building is closely related to its climate and, therefore, the effects of climate change can influence the environmental comfort of dwellings over the years. This research aimed to investigate the thermal performance of single-family houses built in different building systems under the influence of the climate change effects on the climate in São Paulo. For this purpose, simulations with EnergyPlus were performed considering four climatic periods: TRY (1954), 2020, 2050 and 2080. The future climate files were generated with the assistance of the CCWorldWeatherGen tool, and the progression generated for the 2020 period was compared with meteorological data measured from 2011 to 2018. The results showed that outdoor air temperature of São Paulo will increase on average of 4.23 °C up to 2100, which will cause the degree-hours for heating (GHA) indicator to decrease to 1.165,24 °Ch and the degree-hours for cooling (GHR) indicator to increase to 144,26 °Ch, according to the constructive system. Furthermore, it was observed that building façades with higher thermal capacity will be important to satisfy the user’s thermal comfort requirements. Therefore, it is necessary to consider climate change in energy efficiency solutions in buildings.</p>
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