The Brazilian Seismographic Integrated Systems (BRASIS): Infrastructure and data management

In geophysics and seismology, raw data need to be processed to generate useful information that can be turned into knowledge by researchers. The number of sensors that are acquiring raw data is increasing rapidly. Without good data management systems, more time can be spent in querying and preparing datasets for analyses than in acquiring raw data. Also, a lot of good quality data acquired at great effort can be lost forever if they are not correctly stored. Local and international cooperation will probably be reduced, and a lot of data will never become scientific knowledge. For this reason, the Seismological Laboratory of the Institute of Astronomy, Geophysics and Atmospheric Sciences at the University of São Paulo (IAG-USP) has concentrated fully on its data management system. This report describes the efforts of the IAG-USP to set up a seismology data management system to facilitate local and international cooperation. © 2011 by the Istituto Nazionale di Geofisica e Vulcanologia. All rights reserved.

A gestão de estoques em sistemas produtivos Engineering-To-Order e Make-To-Stock: estudo de casos em empresas do setor gráfico

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Proposta de zoneamento ambiental das paisagens para o alto curso da bacia hidrográfica do Rio Sucuriú, Mato Grosso do Sul-Brasil

Pós-graduação em Geografia - FCT

Plano Munucipal de saúde: análise do instrumento de gestão

Among planning instruments used by manager instances of Brazilian Health System it pointed the Health Municipal Plan (PMS) that should be built collectively showing political intentions, directresses, priorities, objectives, goals framework, estimative of resources and need costs to get the goals of the health sector. The aim of this work was to analyze the plans in relation to attendance of legal requirements which manage the Brazilian Health System, its constitution and showing of essential items. The study included three municipalities form São Paulo State. It was used the documental analysis as research technique. Near all plans showed an analysis of situation with detailed descriptions of general situation of municipality, and only one of them realized critical analysis of their epidemiological data; the financial income applied on health was decrypted by only one municipality. About programming, all municipalities described the main problems and its solutions. Although they had goals framework, the question about cost estimative to get the goals was not approached. Any municipality showed an annual review, being one of them delayed over than two years. It was observed no participation of Municipal Health Council on elaboration and review of plans. It was concluded that there was a deficiency in the plans analyzed. It’s necessary to execute continuing education with managers in relation to importance of systematic elaboration of plans and to incentive the promotion of active participation of Municipal Health Council promotion of aiming to became true the social control of health actions.

Comparação de metodologias na definição de fluxos acumulados a partir de modelos digitais de elevação do terreno aplicado a suscetibilidade de inundações

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Planejamento e gestão na responsabilidade social: desafios para o Serviço Social

Pós-graduação em Serviço Social - FCHS

Gerenciamento de Big Data em plantas industriais

Nowadays the companies generate great amount of data from different sources, however some of them produce more data than they can analyze. Big Data is a set of data that grows very fast, collected several times during a short period of time. This work focus on the importance of the correct management of Big Data in an industrial plant. Through a case study based on a company that belongs to the pulp and paper area, the problems resolutions are going to be presented with the usage of appropriate data management. In the final chapters, the results achieved by the company are discussed, showing how the correct choice of data to be monitored and analyzed brought benefits to the company, also best practices will be recommended for the Big Data management