Estratégia multi-temporal para produção automática de cartografia de ocupação do solo com imagens AWiFS

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Ciência e Sistemas de Informação Geográfica

Air pollution and its impacts on health in Vitoria, Espirito Santo, Brazil

ABSTRACT OBJECTIVE To analyze the impact of air pollution on respiratory and cardiovascular morbidity of children and adults in the city of Vitoria, state of Espirito Santo. METHODS A study was carried out using time-series models via Poisson regression from hospitalization and pollutant data in Vitoria, ES, Southeastern Brazil, from 2001 to 2006. Fine particulate matter (PM10), sulfur dioxide (SO2), and ozone (O3) were tested as independent variables in simple and cumulative lags of up to five days. Temperature, humidity and variables indicating weekdays and city holidays were added as control variables in the models. RESULTS For each increment of 10 µg/m3 of the pollutants PM10, SO2, and O3, the percentage of relative risk (%RR) for hospitalizations due to total respiratory diseases increased 9.67 (95%CI 11.84-7.54), 6.98 (95%CI 9.98-4.17) and 1.93 (95%CI 2.95-0.93), respectively. We found %RR = 6.60 (95%CI 9.53-3.75), %RR = 5.19 (95%CI 9.01-1.5), and %RR = 3.68 (95%CI 5.07-2.31) for respiratory diseases in children under the age of five years for PM10, SO2, and O3, respectively. Cardiovascular diseases showed a significant relationship with O3, with %RR = 2.11 (95%CI 3.18-1.06). CONCLUSIONS Respiratory diseases presented a stronger and more consistent relationship with the pollutants researched in Vitoria. A better dose-response relationship was observed when using cumulative lags in polynomial distributed lag models.

Densities and refractive indices for the ternary mixture methanol/propan-1-Ol/acetonitrile

Refractive indices, n(D), and densities, rho, at 298.15 K were measured for the ternary mixture methanol (MeOH)/propan-1-ol (1-PrOH)/acetonitrile (MeCN) for a total of 22 mole fractions, along with 18 mole fractions of each of the corresponding binary mixtures, methanol/propan-1-ol, propan-1-ol/acetonitrile and methanol/acetonitrile. The variation of excess refractive indices and excess molar volumes with composition was modeled by the Redlich-Kister polynomial function in the case of binary mixtures and by the Cibulka equation for the ternary mixture. A thermodynamic approach to excess refractive indices, recently proposed by other authors, was applied for the first time to ternary liquid mixtures. Structural effects were identified and interpreted both in the binary and ternary systems. A complex relationship between excess refractive indices and excess molar volumes was identified, revealing all four possible sign combinations between these two properties. Structuring of the mixtures was also discussed on the basis of partial molar volumes of the binary and ternary mixtures.

Wetland Habitat Studies using various Classification Techniques on Multi-Spectral Landsat Imagery: Case study: Tram chim National Park, Dong Thap Vietnam

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies

Avaliação do potencial eólico para geração de energia eléctrica

Trabalho Final de Mestrado para a obtenção do grau de Mestre em Engenharia Mecânica /Energia

Task assignment algorithms for two-type heterogeneous multiprocessors

Consider the problem of assigning implicit-deadline sporadic tasks on a heterogeneous multiprocessor platform comprising two different types of processors—such a platform is referred to as two-type platform. We present two low degree polynomial time-complexity algorithms, SA and SA-P, each providing the following guarantee. For a given two-type platform and a task set, if there exists a task assignment such that tasks can be scheduled to meet deadlines by allowing them to migrate only between processors of the same type (intra-migrative), then (i) using SA, it is guaranteed to find such an assignment where the same restriction on task migration applies but given a platform in which processors are 1+α/2 times faster and (ii) SA-P succeeds in finding a task assignment where tasks are not allowed to migrate between processors (non-migrative) but given a platform in which processors are 1+α times faster. The parameter 0<α≤1 is a property of the task set; it is the maximum of all the task utilizations that are no greater than 1. We evaluate average-case performance of both the algorithms by generating task sets randomly and measuring how much faster processors the algorithms need (which is upper bounded by 1+α/2 for SA and 1+α for SA-P) in order to output a feasible task assignment (intra-migrative for SA and non-migrative for SA-P). In our evaluations, for the vast majority of task sets, these algorithms require significantly smaller processor speedup than indicated by their theoretical bounds. Finally, we consider a special case where no task utilization in the given task set can exceed one and for this case, we (re-)prove the performance guarantees of SA and SA-P. We show, for both of the algorithms, that changing the adversary from intra-migrative to a more powerful one, namely fully-migrative, in which tasks can migrate between processors of any type, does not deteriorate the performance guarantees. For this special case, we compare the average-case performance of SA-P and a state-of-the-art algorithm by generating task sets randomly. In our evaluations, SA-P outperforms the state-of-the-art by requiring much smaller processor speedup and by running orders of magnitude faster.

Efficient schedulability tests for real-time embedded systems with urgent routines

Task scheduling is one of the key mechanisms to ensure timeliness in embedded real-time systems. Such systems have often the need to execute not only application tasks but also some urgent routines (e.g. error-detection actions, consistency checkers, interrupt handlers) with minimum latency. Although fixed-priority schedulers such as Rate-Monotonic (RM) are in line with this need, they usually make a low processor utilization available to the system. Moreover, this availability usually decreases with the number of considered tasks. If dynamic-priority schedulers such as Earliest Deadline First (EDF) are applied instead, high system utilization can be guaranteed but the minimum latency for executing urgent routines may not be ensured. In this paper we describe a scheduling model according to which urgent routines are executed at the highest priority level and all other system tasks are scheduled by EDF. We show that the guaranteed processor utilization for the assumed scheduling model is at least as high as the one provided by RM for two tasks, namely 2(2√−1). Seven polynomial time tests for checking the system timeliness are derived and proved correct. The proposed tests are compared against each other and to an exact but exponential running time test.

ECG biometrics using a dissimilarity space representation

Electrocardiogram (ECG) biometrics are a relatively recent trend in biometric recognition, with at least 13 years of development in peer-reviewed literature. Most of the proposed biometric techniques perform classifi-cation on features extracted from either heartbeats or from ECG based transformed signals. The best representation is yet to be decided. This paper studies an alternative representation, a dissimilarity space, based on the pairwise dissimilarity between templates and subjects' signals. Additionally, this representation can make use of ECG signals sourced from multiple leads. Configurations of three leads will be tested and contrasted with single-lead experiments. Using the same k-NN classifier the results proved superior to those obtained through a similar algorithm which does not employ a dissimilarity representation. The best Authentication EER went as low as 1:53% for a database employing 503 subjects. However, the employment of extra leads did not prove itself advantageous.

The development of the N1 and N2 components in auditory oddball paradigms: a systematic review with narrative analysis and suggested normative values

Auditory event-related potentials (AERPs) are widely used in diverse fields of today’s neuroscience, concerning auditory processing, speech perception, language acquisition, neurodevelopment, attention and cognition in normal aging, gender, developmental, neurologic and psychiatric disorders. However, its transposition to clinical practice has remained minimal. Mainly due to scarce literature on normative data across age, wide spectrumof results, variety of auditory stimuli used and to different neuropsychological meanings of AERPs components between authors. One of the most prominent AERP components studied in last decades was N1, which reflects auditory detection and discrimination. Subsequently, N2 indicates attention allocation and phonological analysis. The simultaneous analysis of N1 and N2 elicited by feasible novelty experimental paradigms, such as auditory oddball, seems an objective method to assess central auditory processing. The aim of this systematic review was to bring forward normative values for auditory oddball N1 and N2 components across age. EBSCO, PubMed, Web of Knowledge and Google Scholarwere systematically searched for studies that elicited N1 and/or N2 by auditory oddball paradigm. A total of 2,764 papers were initially identified in the database, of which 19 resulted from hand search and additional references, between 1988 and 2013, last 25 years. A final total of 68 studiesmet the eligibility criteria with a total of 2,406 participants from control groups for N1 (age range 6.6–85 years; mean 34.42) and 1,507 for N2 (age range 9–85 years; mean 36.13). Polynomial regression analysis revealed thatN1latency decreases with aging at Fz and Cz,N1 amplitude at Cz decreases from childhood to adolescence and stabilizes after 30–40 years and at Fz the decrement finishes by 60 years and highly increases after this age. Regarding N2, latency did not covary with age but amplitude showed a significant decrement for both Cz and Fz. Results suggested reliable normative values for Cz and Fz electrode locations; however, changes in brain development and components topography over age should be considered in clinical practice.

Robot visual localization through local feature fusion: an evaluation of multiple classifiers combination approaches

In the last decade, local image features have been widely used in robot visual localization. In order to assess image similarity, a strategy exploiting these features compares raw descriptors extracted from the current image with those in the models of places. This paper addresses the ensuing step in this process, where a combining function must be used to aggregate results and assign each place a score. Casting the problem in the multiple classifier systems framework, in this paper we compare several candidate combiners with respect to their performance in the visual localization task. For this evaluation, we selected the most popular methods in the class of non-trained combiners, namely the sum rule and product rule. A deeper insight into the potential of these combiners is provided through a discriminativity analysis involving the algebraic rules and two extensions of these methods: the threshold, as well as the weighted modifications. In addition, a voting method, previously used in robot visual localization, is assessed. Furthermore, we address the process of constructing a model of the environment by describing how the model granularity impacts upon performance. All combiners are tested on a visual localization task, carried out on a public dataset. It is experimentally demonstrated that the sum rule extensions globally achieve the best performance, confirming the general agreement on the robustness of this rule in other classification problems. The voting method, whilst competitive with the product rule in its standard form, is shown to be outperformed by its modified versions.

Predicting Xerostomia induced by IMRT treatments: A logistic regression approach

Radiotherapy is one of the main treatments used against cancer. Radiotherapy uses radiation to destroy cancerous cells trying, at the same time, to minimize the damages in healthy tissues. The planning of a radiotherapy treatment is patient dependent, resulting in a lengthy trial and error procedure until a treatment complying as most as possible with the medical prescription is found. Intensity Modulated Radiation Therapy (IMRT) is one technique of radiation treatment that allows the achievement of a high degree of conformity between the area to be treated and the dose absorbed by healthy tissues. Nevertheless, it is still not possible to eliminate completely the potential treatments’ side-effects. In this retrospective study we use the clinical data from patients with head-and-neck cancer treated at the Portuguese Institute of Oncology of Coimbra and explore the possibility of classifying new and untreated patients according to the probability of xerostomia 12 months after the beginning of IMRT treatments by using a logistic regression approach. The results obtained show that the classifier presents a high discriminative ability in predicting the binary response “at risk for xerostomia at 12 months”

On the requirements of interpolating polynomials for path motion constraints

In the framework of multibody dynamics, the path motion constraint enforces that a body follows a predefined curve being its rotations with respect to the curve moving frame also prescribed. The kinematic constraint formulation requires the evaluation of the fourth derivative of the curve with respect to its arc length. Regardless of the fact that higher order polynomials lead to unwanted curve oscillations, at least a fifth order polynomials is required to formulate this constraint. From the point of view of geometric control lower order polynomials are preferred. This work shows that for multibody dynamic formulations with dependent coordinates the use of cubic polynomials is possible, being the dynamic response similar to that obtained with higher order polynomials. The stabilization of the equations of motion, always required to control the constraint violations during long analysis periods due to the inherent numerical errors of the integration process, is enough to correct the error introduced by using a lower order polynomial interpolation and thus forfeiting the analytical requirement for higher order polynomials.

Using data mining techniques to support breast cancer diagnosis

More than ever, there is an increase of the number of decision support methods and computer aided diagnostic systems applied to various areas of medicine. In breast cancer research, many works have been done in order to reduce false-positives when used as a double reading method. In this study, we aimed to present a set of data mining techniques that were applied to approach a decision support system in the area of breast cancer diagnosis. This method is geared to assist clinical practice in identifying mammographic findings such as microcalcifications, masses and even normal tissues, in order to avoid misdiagnosis. In this work a reliable database was used, with 410 images from about 115 patients, containing previous reviews performed by radiologists as microcalcifications, masses and also normal tissue findings. Throughout this work, two feature extraction techniques were used: the gray level co-occurrence matrix and the gray level run length matrix. For classification purposes, we considered various scenarios according to different distinct patterns of injuries and several classifiers in order to distinguish the best performance in each case described. The many classifiers used were Naïve Bayes, Support Vector Machines, k-nearest Neighbors and Decision Trees (J48 and Random Forests). The results in distinguishing mammographic findings revealed great percentages of PPV and very good accuracy values. Furthermore, it also presented other related results of classification of breast density and BI-RADS® scale. The best predictive method found for all tested groups was the Random Forest classifier, and the best performance has been achieved through the distinction of microcalcifications. The conclusions based on the several tested scenarios represent a new perspective in breast cancer diagnosis using data mining techniques.

Pré-processamento e Tag automático de imagens em ambiente móvel e web, aplicado a um sistema de informação geográfica

No panorama socioeconómico atual, a contenção de despesas e o corte no financiamento de serviços secundários consumidores de recursos conduzem à reformulação de processos e métodos das instituições públicas, que procuram manter a qualidade de vida dos seus cidadãos através de programas que se mostrem mais eficientes e económicos. O crescimento sustentado das tecnologias móveis, em conjunção com o aparecimento de novos paradigmas de interação pessoa-máquina com recurso a sensores e sistemas conscientes do contexto, criaram oportunidades de negócio na área do desenvolvimento de aplicações com vertente cívica para indivíduos e empresas, sensibilizando-os para a disponibilização de serviços orientados ao cidadão. Estas oportunidades de negócio incitaram a equipa do projeto a desenvolver uma plataforma de notificação de problemas urbanos baseada no seu sistema de informação geográfico para entidades municipais. O objetivo principal desta investigação foca a idealização, conceção e implementação de uma solução completa de notificação de problemas urbanos de caráter não urgente, distinta da concorrência pela facilidade com que os cidadãos são capazes de reportar situações que condicionam o seu dia-a-dia. Para alcançar esta distinção da restante oferta, foram realizados diversos estudos para determinar características inovadoras a implementar, assim como todas as funcionalidades base expectáveis neste tipo de sistemas. Esses estudos determinaram a implementação de técnicas de demarcação manual das zonas problemáticas e reconhecimento automático do tipo de problema reportado nas imagens, ambas desenvolvidas no âmbito deste projeto. Para a correta implementação dos módulos de demarcação e reconhecimento de imagem, foram feitos levantamentos do estado da arte destas áreas, fundamentando a escolha de métodos e tecnologias a integrar no projeto. Neste contexto, serão apresentadas em detalhe as várias fases que constituíram o processo de desenvolvimento da plataforma, desde a fase de estudo e comparação de ferramentas, metodologias, e técnicas para cada um dos conceitos abordados, passando pela proposta de um modelo de resolução, até à descrição pormenorizada dos algoritmos implementados. Por último, é realizada uma avaliação de desempenho ao par algoritmo/classificador desenvolvido, através da definição de métricas que estimam o sucesso ou insucesso do classificador de objetos. A avaliação é feita com base num conjunto de imagens de teste, recolhidas manualmente em plataformas públicas de notificação de problemas, confrontando os resultados obtidos pelo algoritmo com os resultados esperados.

Desenvolvimento de apoio à decisão operacional – previsão de curto prazo de geração distribuída de tecnologia eólica ligada à RND

No contexto da penetração de energias renováveis no sistema elétrico, Portugal ocupa uma posição de destaque a nível mundial, muito devido à produção de eólica. Com um sistema elétrico com forte presença de fontes de energia renováveis, novos desafios surgem, nomeadamente no caso da energia eólica pela sua imprevisibilidade e volatilidade. O recurso eólico embora seja ilimitado não é armazenável, surgindo assim a necessidade da procura de modelos de previsão de produção de energia elétrica dos parques eólicos de modo a permitir uma boa gestão do sistema. Nesta dissertação apresentam-se as contribuições resultantes de um trabalho de pesquisa e investigação sobre modelos de previsão da potência elétrica com base em valores de previsões meteorológicas, nomeadamente, valores previstos da intensidade e direção do vento. Consideraram-se dois tipos de modelos: paramétricos e não paramétricos. Os primeiros são funções polinomiais de vários graus e a função sigmoide, os segundos são redes neuronais artificiais. Para a estimação dos modelos e respetiva validação, são usados dados recolhidos ao longo de dois anos e três meses no parque eólico do Pico Alto de potência instalada de 6 MW. De forma a otimizar os resultados da previsão, consideram-se diferentes classes de perfis de produção, definidas com base em quatro e oito direções do vento, e ajustam-se os modelos propostos em cada uma das classes. São apresentados e discutidos resultados de uma análise comparativa do desempenho dos diferentes modelos propostos para a previsão da potência.