Mapping the Pasture Steppe in Bayankhongor, Mongolia: comparison of classification methods, using Landsat-8 and geophysical data

Grasslands in semi-arid regions, like Mongolian steppes, are facing desertification and degradation processes, due to climate change. Mongolia’s main economic activity consists on an extensive livestock production and, therefore, it is a concerning matter for the decision makers. Remote sensing and Geographic Information Systems provide the tools for advanced ecosystem management and have been widely used for monitoring and management of pasture resources. This study investigates which is the higher thematic detail that is possible to achieve through remote sensing, to map the steppe vegetation, using medium resolution earth observation imagery in three districts (soums) of Mongolia: Dzag, Buutsagaan and Khureemaral. After considering different thematic levels of detail for classifying the steppe vegetation, the existent pasture types within the steppe were chosen to be mapped. In order to investigate which combination of data sets yields the best results and which classification algorithm is more suitable for incorporating these data sets, a comparison between different classification methods were tested for the study area. Sixteen classifications were performed using different combinations of estimators, Landsat-8 (spectral bands and Landsat-8 NDVI-derived) and geophysical data (elevation, mean annual precipitation and mean annual temperature) using two classification algorithms, maximum likelihood and decision tree. Results showed that the best performing model was the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), using the decision tree. For maximum likelihood, the model that incorporated Landsat-8 bands with mean annual precipitation (Model 5) and the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), achieved the higher accuracies for this algorithm. The decision tree models consistently outperformed the maximum likelihood ones.

Safety classification using GIS in decision-making process to define priority road interventions

Given the current economic situation of the Portuguese municipalities, it is necessary to identify the priority investments in order to achieve a more efficient financial management. The classification of the road network of the municipality according to the occurrence of traffic accidents is fundamental to set priorities for road interventions. This paper presents a model for road network classification based on traffic accidents integrated in a geographic information system. Its practical application was developed through a case study in the municipality of Barcelos. An equation was defined to obtain a road safety index through the combination of the following indicators: severity, property damage only and accident costs. In addition to the road network classification, the application of the model allows to analyze the spatial coverage of accidents in order to determine the centrality and dispersion of the locations with the highest incidence of road accidents. This analysis can be further refined according to the nature of the accidents namely in collision, runoff and pedestrian crashes.

Mapeamento do uso e cobertura da terra a partir da segmentação e classificação de imagens-fração solo, sombra e vegetação derivadas do modelo linear de mistura aplicado a dados do sensor TM/Landsat5, na região do reservatório de Tucuruí - PA

Técnicas de sensoriamento remoto são fundamentais para o monitoramento das mudanças de uso da terra, principalmente em áreas extensas como a Amazônia. O mapeamento de uso da terra, geralmente é realizado por métodos de classificação manual ou digital pixel a pixel, os quais consomem muito tempo. Este estudo aborda a aplicação do modelo linear de mistura em uma imagem Landsat-TM segmentada para o mapeamento das classes de uso da terra na região do reservatório de Tucuruí-PA para os anos de 1996 e 2001.

Detecção de cicatrizes de áreas queimadas baseada no modelo linear de mistura espectral e imagens índice de vegetação utilizando dados multitemporais do sensor MODIS/TERRA no estado do Mato Grosso, Amazônia brasileira

O objetivo desta pesquisa foi avaliar os dados do sensor MODIS para detectar e monitorar cicatrizes de áreas recém queimadas. Utilizamos imagens da reflectância de superfície do sensor MODIS: produto MOD09 (dia 5 de outubro) e produto MOD13A1 (meses de outubro e novembro). Foi avaliada também uma série temporal de um ano dos índices de vegetação (IV) EVI e NDVI (produto MOD13A1). Uma imagem do sensor ETM+ (dia 5 de outubro) foi utilizada como base para a delimitação dos polígonos amostrais e avaliação dos dados MODIS devido a sua melhor resolução espacial. A metodologia focou na aplicação do modelo linear de mistura espectral nas imagens reflectância para a geração das imagens fração sombra. Análises de regressão foram efetuadas para comparação entre o percentual de sombra derivado da imagem ETM+ e das imagens MODIS. As alterações multitemporais nas imagens IV foram avaliadas com base no teste de Tukey. Os resultados mostraram que a imagem fração sombra gerada a partir do produto MOD09 apresentou um R² = 0,66 (p < 0,01) em relação aos dados ETM+. Para as imagens do produto MOD13A1 não foram identificadas relações significativas. Os IV dentro dos mesmos polígonos apresentaram uma variação sazonal durante o ano. No entanto, não houve uma diminuição significativa dos valores destes índices nos meses onde foram observadas as cicatrizes de áreas recém queimadas. Portanto, o produto MOD09 mostrou-se mais eficiente que o produto MOD13A1 para a detecção de cicatrizes de áreas recém queimadas. A análise multitemporal dos IV sugeriu que não foi possível detectar este mesmo padrão na área de estudo.

Ag-TiNx electrodes deposited on piezoelectric poly(vinylidene fluoride) for biomedical sensor applications

Electroactive polymers are one of the most interesting class of polymers used as smart materials in various applications, such as the development of sensors and actuators for biomedical applications in areas such as smart prosthesis, implantable biosensors and biomechanical signal monitoring, among others. For acquiring or applying the electrical signal from/to the piezoelectric material, suitable electrodes can be produced from Ti based coatings with tailored multifunctional properties, conductivity and antibacterial characteristics, through Ag inclusions. This work reports on Ag-TiNx electrodes, deposited by d. c. and pulsed magnetron sputtering at room temperature on poly(vinylidene fluoride), PVDF, the all-round best piezoelectric polymer.. Composition of the electrodes was assessed by microanalysis X-ray system (EDS - energy dispersive spectrometer). The XRD results revealed that the deposition conditions preserve the polymer structure and suggested the presence of crystalline fcc-TiN phase and fcc-Ag phase in samples with N2 flow above 3 sccm. According to the results obtained from SEM analysis, the coatings are homogeneous and Ag clusters were found for samples with nitrogen flow above 3 sccm. With increasing nitrogen flow, the sheet resistivity tend to be lower than the samples without nitrogen, leading also to a decrease of the piezoelectric response. It is concluded that the deposition conditions do significantly affect the piezoelectric polymer, which maintain its characteristics for sensor/actuator applications.

A hybrid MAC Scheme to improve the transmission performance in body sensor networks

Wireless body sensor networks (WBSNs) constitute a key technology for closing the loop between patients and healthcare providers, as WBSNs provide sensing ability, as well as mobility and portability, essential characteristics for wide acceptance of wireless healthcare technology. However, one important and difficult aspect of WBSNs is to provide data transmissions with quality of service, among other factors due to the antennas being small size and placed close to the body. Such transmissions cannot be fully provided without the assumption of a MAC protocol that solves the problems of the medium sharing. A vast number of MAC protocols conceived for wireless networks are based on random or scheduled schemes. This paper studies firstly the suitability of two MAC protocols, one using CSMA and the other TDMA, to transmit directly to the base station the signals collected continuously from multiple sensor nodes placed on the human body. Tests in a real scenario show that the beaconed TDMA MAC protocol presents an average packet loss ratio lower than CSMA. However, the average packet loss ratio is above 1.0 %. To improve this performance, which is of vital importance in areas such as e-health and ambient assisted living, a hybrid TDMA/CSMA scheme is proposed and tested in a real scenario with two WBSNs and four sensor nodes per WBSN. An average packet loss ratio lower than 0.2 % was obtained with the hybrid scheme. To achieve this significant improvement, the hybrid scheme uses a lightweight algorithm to control dynamically the start of the superframes. Scalability and traffic rate variation tests show that this strategy allows approximately ten WBSNs operating simultaneously without significant performance degradation.

Sensory intensity assessment of olive oils using an electronic tongue

Olive oils may be commercialized as intense, medium or light, according to the intensity perception of fruitiness, bitterness and pungency attributes, assessed by a sensory panel. In this work, the capability of an electronic tongue to correctly classify olive oils according to the sensory intensity perception levels was evaluated. Cross-sensitivity and non-specific lipid polymeric membranes were used as sensors. The sensor device was firstly tested using quinine monohydrochloride standard solutions. Mean sensitivities of 14±2 to 25±6 mV/decade, depending on the type of plasticizer used in the lipid membranes, were obtained showing the device capability for evaluating bitterness. Then, linear discriminant models based on sub-sets of sensors, selected by a meta-heuristic simulated annealing algorithm, were established enabling to correctly classify 91% of olive oils according to their intensity sensory grade (leave-one-out cross-validation procedure). This capability was further evaluated using a repeated K-fold cross-validation procedure, showing that the electronic tongue allowed an average correct classification of 80% of the olive oils used for internal-validation. So, the electronic tongue can be seen as a taste sensor, allowing differentiating olive oils with different sensory intensities, and could be used as a preliminary, complementary and practical tool for panelists during olive oil sensory analysis.

Mapeamento da antiga cobertura vegetal de várzea do Baixo Amazonas a partir de imagens históricas (1975-1981) do Sensor MSS-Landsat

Este estudo apresenta um mapa da cobertura vegetal da planície de inundação do Rio Amazonas entre as cidades de Parintins (AM) e Almeirim (PA), com base em imagens Landsat-MSS adquiridas entre 1975 e 1981. O processamento digital dessas imagens envolveu a transformação para imagens-fração de vegetação, solo e água escura (sombra), seguido da aplicação de técnicas de segmentação e classificação por região. O mapa resultante da classificação foi organizado em quatro classes de cobertura do solo: floresta de várzea, vegetação não-florestal de várzea, solo exposto e água aberta. A precisão do mapa foi estimada a partir de dois tipos de informações coletadas em campo: 1) pontos de descrição: para validação das classes de cobertura não sujeitas a grandes alterações, como é o caso dos corpos d'água permanentes, e identificação de indicadores dos tipos de cobertura original presentes na paisagem na ocasião da obtenção das imagens (72 pontos); 2) entrevistas com moradores antigos para a recuperação da memória sobre a cobertura vegetal existente há 30 anos (44 questionários). Ao todo foram coletadas informações em 116 pontos distribuídos ao longo da área de estudo. Esses pontos foram utilizados para calcular o Índice Kappa de concordância entre os dados de campo e o mapa resultante da classificação automática, cujo valor (0,78) indica a boa qualidade do mapa de cobertura vegetal da várzea. Os resultados mostram que a região possuía uma cobertura florestal de várzea de aproximadamente 8.650 km2 no período de aquisição das imagens.

Sistema de visão robótico baseado no sensor kinect para orientação no espaço e contorno de obstáculos

Dissertação de mestrado em Engenharia Eletrónica Industrial e Computadores (área de especialização em Robótica)

Metabolic profiling and classification of propolis samples from Southern Brazil: an NMR-based platform coupled with machine learning

The chemical composition of propolis is affected by environmental factors and harvest season, making it difficult to standardize its extracts for medicinal usage. By detecting a typical chemical profile associated with propolis from a specific production region or season, certain types of propolis may be used to obtain a specific pharmacological activity. In this study, propolis from three agroecological regions (plain, plateau, and highlands) from southern Brazil, collected over the four seasons of 2010, were investigated through a novel NMR-based metabolomics data analysis workflow. Chemometrics and machine learning algorithms (PLS-DA and RF), including methods to estimate variable importance in classification, were used in this study. The machine learning and feature selection methods permitted construction of models for propolis sample classification with high accuracy (>75%, reaching 90% in the best case), better discriminating samples regarding their collection seasons comparatively to the harvest regions. PLS-DA and RF allowed the identification of biomarkers for sample discrimination, expanding the set of discriminating features and adding relevant information for the identification of the class-determining metabolites. The NMR-based metabolomics analytical platform, coupled to bioinformatic tools, allowed characterization and classification of Brazilian propolis samples regarding the metabolite signature of important compounds, i.e., chemical fingerprint, harvest seasons, and production regions.

Optimization of magnetoelectric composites based on electroactive polymers for energy harvesting and sensor application

Tese de Doutoramento em Engenharia de Materiais.

Supercritical fluid and pharmaceutical applications. Part I: Process classification

The supercritical fluid technology has been target of many pharmaceuticals investigations in particles production for almost 35 years. This is due to the great advantages it offers over others technologies currently used for the same purpose. A brief history is presented, as well the classification of supercritical technology based on the role that the supercritical fluid (carbon dioxide) performs in the process.

Development of a novel aptamer-based multi-sensor device for the detection of osteopontin

Doctoral Dissertation for PhD degree in Chemical and Biological Engineering

Ontological representation of tumor-node-metastasis classification and an ontology-driven classifier: a study on colorectal cancer

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Informática Médica)

Marcapasso com sensor de contratilidade regulado pelas variações do sistema nervoso autônomo na miocardiopatia chagásica crônica

OBJETIVO: Analisar o desempenho da estimulação cardíaca artificial com marcapasso do tipo VVIR cujo sensor é regulado pelas variações do sistema nervoso autônomo em pacientes chagásicos com distúrbio no sistema de condução. MÉTODOS: Estudados 47 chagásicos, 28 do sexo masculino, com idades entre 24 e 68 anos, 36 tinham bloqueio atrioventricular (AV) total; 8, bloqueio AV de 2º grau 2; e 3 doença do nódulo sinusal, e encontravam-se, de acordo com a NYHA, em classe I (4), II (15), III (16) e IV (12). Após o implante de marcapasso do tipo VVIR os pacientes foram acompanhados durante 12 meses. A resposta de freqüência foi registrada em gravações de Holter de 24h e divididos em dois grupos de acordo com a FC em repouso - grupo 1: >65bpm e grupo 2: <=65bpm, para estudo comparativo, considerando: 1) FC em exercício no período de pós-implante; 2) PA em repouso após o implante e 3) avaliação dos grupos de eletrodos identificados como TIR-60-UP e outros eletrodos. RESULTADOS: O grupo 1 teve em exercício menor variação entre seus valores, do que o grupo 2, indicando que esse tipo de sistema de estimulação permite controlar individualmente cada paciente. Os valores de PA em repouso e em exercício não foram diferentes entre os grupos. O eletrodo do tipo TIR-60-UP, comportou-se como os demais eletrodos. CONCLUSÃO: O marcapasso do tipo VVIR cujo sensor é regulado pelas variações do SNA propicia o restabelecimento dos mecanismos fisiológicos em chagásicos, sendo que 74% deles tiveram melhora de uma ou duas classes funcionais da NYHA.