Estimativa da evapotranspiração espacial em uma região semiárida utilizando sensoriamento remoto

With the need to deploy management and monitoring systems of natural resources in areas susceptible to environmental degradation, as is the case of semiarid regions, several works have been developed in order to find effective models and technically and economically viable. Therefore, this study aimed to estimate the daily actual evapotranspiration (ETr) through the application of the Surface Energy Balance Algorithm for Land (SEBAL), from remote sensing products, in a semiarid region, Seridó of the Rio Grande do Norte, and do the validation of these estimates using ETr values obtained by the Penman-Monteith (standard method of the Food and Agriculture Organization-FAO). The SEBAL is based on energy balance method, which allows obtaining the vertical latent heat flux (LE) with orbital images and, consequently, of the evapotranspiration through the difference of flows, also vertical, of heat in the soil (G), sensitive heat (H) and radiation balance (Rn). The study area includes the surrounding areas of the Dourado reservoir, located in the Currais Novos/RN city. For the implementation of the algorithm were used five images TM/Landsat-5. The work was divided in three chapters in order to facilitate a better discussion of each part of the SEBAL processing, distributed as follows: first chapter addressing the spatio-temporal variability of the biophysical variables; second chapter dealing with spatio-temporal distribution of instant and daily radiation balance; and the third chapter discussing the heart of the work, the daily actual evapotranspiration estimation and the validation than to the study area

Sistema de aquisição de dados para estudos de transiente de pressão e detecção de vazamentos em oleodutos

In February 2011, the National Agency of Petroleum, Natural Gas and Biofuels (ANP) has published a new Technical Rules for Handling Land Pipeline Petroleum and Natural Gas Derivatives (RTDT). Among other things, the RTDT made compulsory the use of monitoring systems and leak detection in all onshore pipelines in the country. This document provides a study on the method for detection of transient pressure. The study was conducted on a industrial duct 16" diameter and 9.8 km long. The pipeline is fully pressurized and carries a multiphase mixture of crude oil, water and natural gas. For the study, was built an infrastructure for data acquisition and validation of detection algorithms. The system was designed with SCADA architecture. Piezoresistive sensors were installed at the ends of the duct and Digital Signal Processors (DSPs) were used for sampling, storage and processing of data. The study was based on simulations of leaks through valves and search for patterns that characterize the occurrence of such phenomena

Arquitetura inteligente fuzzy para monitoramento de sinais vitais de pacientes: um estudo de caso em UTI

The area of the hospital automation has been the subject a lot of research, addressing relevant issues which can be automated, such as: management and control (electronic medical records, scheduling appointments, hospitalization, among others); communication (tracking patients, staff and materials), development of medical, hospital and laboratory equipment; monitoring (patients, staff and materials); and aid to medical diagnosis (according to each speciality). This thesis presents an architecture for a patient monitoring and alert systems. This architecture is based on intelligent systems techniques and is applied in hospital automation, specifically in the Intensive Care Unit (ICU) for the patient monitoring in hospital environment. The main goal of this architecture is to transform the multiparameter monitor data into useful information, through the knowledge of specialists and normal parameters of vital signs based on fuzzy logic that allows to extract information about the clinical condition of ICU patients and give a pre-diagnosis. Finally, alerts are dispatched to medical professionals in case any abnormality is found during monitoring. After the validation of the architecture, the fuzzy logic inferences were applied to the trainning and validation of an Artificial Neural Network for classification of the cases that were validated a priori with the fuzzy system