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This article measures the effects from the adoption of information technology (IT) tools on the productivity of workers in the Brazilian manufacturing sector. IT adoption is related to the use of information management systems by firms. The augmented Cobb-Douglas production function supports the estimation of the econometric model. We use the most complete database related to IT adoption in Brazil. Our sample includes 26,776 companies and refers to the year 2003. The data also cover key information about technological innovation, company balance sheets, labor characteristics, external performance, origin of controlling capital, sector of activity, and region of the country where the firm is installed. The results suggest that IT adoption has a positive effect on labor productivity in Brazil. C 2008 Wiley Periodicals, Inc.

O artigo tem por objetivo mensurar os impactos decorrentes da adoção de tecnologia da informação na produtividade dos trabalhadores da indústria de transformação brasileira. O trabalho utilizou amostra de 26.776 firmas, cujos dados são provenientes da Pesquisa Industrial Anual (PIA) e da Pesquisa Industrial de Inovação Tecnológica (PINTEC), ambas do Instituto Brasileiro de Geografia e Estatística (IBGE), da Relação Anual de Informações Sociais (RAIS) do Ministério do Trabalho e Emprego (MTE), da Secretaria de Comércio Exterior (SECEX) do Ministério de Desenvolvimento, Indústria e Comércio Exterior (MDIC); e do Censo de capitais estrangeiros, do Banco Central do Brasil. O banco de dados foi organizado pelo Instituto de Pesquisa Econômica Aplicada (IPEA). O modelo econométrico de corte transversal estimado refere-se ao ano de 2003. Os resultados indicam que a adoção de TI afeta positivamente a produtividade da mão-de-obra.

The facial expression recognition has attracted most of the researchers attention over the last years, because of that it can be very useful in many applications. The sign language is a spatio-visual language and it does not have the speech intonation support, so facial expression gain relative importance to convey grammatical information in a signed sentence and they contributed to morphological and/or syntactic level to a sign language. Those expressions are called grammatical facial expression and they cooperate to solve the ambiguity between signs and give meaning to sentences. Thus, this master thesis aims to develop models that make possible to recognize automatically grammatical facial expressions from Brazilian Sign Language (Libras).

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