962 resultados para data complexity
Resumo:
A new algorithm for the velocity vector estimation of moving ships using Single Look Complex (SLC) SAR data in strip map acquisition mode is proposed. The algorithm exploits both amplitude and phase information of the Doppler decompressed data spectrum, with the aim to estimate both the azimuth antenna pattern and the backscattering coefficient as function of the look angle. The antenna pattern estimation provides information about the target velocity; the backscattering coefficient can be used for vessel classification. The range velocity is retrieved in the slow time frequency domain by estimating the antenna pattern effects induced by the target motion, while the azimuth velocity is calculated by the estimated range velocity and the ship orientation. Finally, the algorithm is tested on simulated SAR SLC data.
Resumo:
In machine learning and pattern recognition tasks, the use of feature discretization techniques may have several advantages. The discretized features may hold enough information for the learning task at hand, while ignoring minor fluctuations that are irrelevant or harmful for that task. The discretized features have more compact representations that may yield both better accuracy and lower training time, as compared to the use of the original features. However, in many cases, mainly with medium and high-dimensional data, the large number of features usually implies that there is some redundancy among them. Thus, we may further apply feature selection (FS) techniques on the discrete data, keeping the most relevant features, while discarding the irrelevant and redundant ones. In this paper, we propose relevance and redundancy criteria for supervised feature selection techniques on discrete data. These criteria are applied to the bin-class histograms of the discrete features. The experimental results, on public benchmark data, show that the proposed criteria can achieve better accuracy than widely used relevance and redundancy criteria, such as mutual information and the Fisher ratio.
Resumo:
Trabalho de Projeto para obtenção do grau de mestre em Engenharia Civil
Resumo:
This study identifies predictors and normative data for quality of life (QOL) in a sample of Portuguese adults from general population. A cross-sectional correlational study was undertaken with two hundred and fifty-five (N = 255) individuals from Portuguese general population (mean age 43 years, range 25–84 years; 148 females, 107 males). Participants completed the European Portuguese version of the World Health Organization Quality of Life short-form instrument and the European Portuguese version of the Center for Epidemiologic Studies Depression Scale. Demographic information was also collected. Portuguese adults reported their QOL as good. The physical, psychological and environmental domains predicted 44 % of the variance of QOL. The strongest predictor was the physical domain and the weakest was social relationships. Age, educational level, socioeconomic status and emotional status were significantly correlated with QOL and explained 25 % of the variance of QOL. The strongest predictor of QOL was emotional status followed by education and age. QOL was significantly different according to: marital status; living place (mainland or islands); type of cohabitants; occupation; health. The sample of adults from general Portuguese population reported high levels of QOL. The life domain that better explained QOL was the physical domain. Among other variables, emotional status best predicted QOL. Further variables influenced overall QOL. These findings inform our understanding on adults from Portuguese general population QOL and can be helpful for researchers and practitioners using this assessment tool to compare their results with normative data
Resumo:
Trabalho apresentado no âmbito do Mestrado em Engenharia Informática, como requisito parcial para obtenção do grau de Mestre em Engenharia Informática.
Resumo:
Dimensionality reduction plays a crucial role in many hyperspectral data processing and analysis algorithms. This paper proposes a new mean squared error based approach to determine the signal subspace in hyperspectral imagery. The method first estimates the signal and noise correlations matrices, then it selects the subset of eigenvalues that best represents the signal subspace in the least square sense. The effectiveness of the proposed method is illustrated using simulated and real hyperspectral images.
Resumo:
Hyperspectral imaging sensors provide image data containing both spectral and spatial information from the Earth surface. The huge data volumes produced by these sensors put stringent requirements on communications, storage, and processing. This paper presents a method, termed hyperspectral signal subspace identification by minimum error (HySime), that infer the signal subspace and determines its dimensionality without any prior knowledge. The identification of this subspace enables a correct dimensionality reduction yielding gains in algorithm performance and complexity and in data storage. HySime method is unsupervised and fully-automatic, i.e., it does not depend on any tuning parameters. The effectiveness of the proposed method is illustrated using simulated data based on U.S.G.S. laboratory spectra and real hyperspectral data collected by the AVIRIS sensor over Cuprite, Nevada.
Resumo:
Mestrado em Engenharia Informática - Área de Especialização em Tecnologias do Conhecimento e Decisão
Resumo:
Endmember extraction (EE) is a fundamental and crucial task in hyperspectral unmixing. Among other methods vertex component analysis ( VCA) has become a very popular and useful tool to unmix hyperspectral data. VCA is a geometrical based method that extracts endmember signatures from large hyperspectral datasets without the use of any a priori knowledge about the constituent spectra. Many Hyperspectral imagery applications require a response in real time or near-real time. Thus, to met this requirement this paper proposes a parallel implementation of VCA developed for graphics processing units. The impact on the complexity and on the accuracy of the proposed parallel implementation of VCA is examined using both simulated and real hyperspectral datasets.
Resumo:
In this paper, a new parallel method for sparse spectral unmixing of remotely sensed hyperspectral data on commodity graphics processing units (GPUs) is presented. A semi-supervised approach is adopted, which relies on the increasing availability of spectral libraries of materials measured on the ground instead of resorting to endmember extraction methods. This method is based on the spectral unmixing by splitting and augmented Lagrangian (SUNSAL) that estimates the material's abundance fractions. The parallel method is performed in a pixel-by-pixel fashion and its implementation properly exploits the GPU architecture at low level, thus taking full advantage of the computational power of GPUs. Experimental results obtained for simulated and real hyperspectral datasets reveal significant speedup factors, up to 1 64 times, with regards to optimized serial implementation.
Resumo:
RESUMO - A presente investigação procura descrever e compreender como a estratégia influencia a liderança e como esta por sua vez interage nos processos de inovação e mudança, em organizações de saúde. Desconhecem-se estudos anteriores, em Portugal, sobre este problema de investigação e da respectiva problemática teórica. Trata-se de um estudo exploratório e descritivo que envolveu 5 organizações de saúde, 4 portuguesas e 1 espanhola, 4 hospitais (dois privados e uma unidade local de saúde). Utilizou-se uma abordagem mista de investigação (qualitativa e quantitativa), que permitiu compreender, através do estudo de caso, como se articulam a estratégia, a liderança e a inovação nessas cinco organizações de saúde. Os resultados do estudo empírico foram provenientes da recolha de dados efectuada através de observação directa e estruturada, entrevistas com actores-chave, documentos em suporte de papel e digital, e ainda inquérito por questionário de auto-resposta a uma amostra (n=165) de actores do line e do staff (Administradores, Directores de Serviço/Departamento, Enfermeiros Chefe e Técnicos Coordenadores) das cinco organizações de saúde. Tanto o modelo de Miles & Snow (estratégia organizacional), como o modelo dos valores contrastantes de Quinn (cultura organizacional e liderança), devidamente adaptados, mostram-se heurísticos e provam poder aplicar-se às organizações de saúde, apesar a sua complexidade e especificidade. Tanto as organizações do sector público como do sector privado e organizações públicas concessionadas (parcerias público privadas) podem ser acompanhadas e monitorizadas nos seus processos de inovação e mudança, associados aos tipos de cultura, liderança ou estratégia organizacionais adoptadas. As organizações de saúde coabitam num continuum, onde o ambiente (quer interno quer externo) e o tempo são factores decisivos que condicionam a estratégia a adoptar. Também aqui, em função da realidade dinâmica e complexa onde a organização se move, não há tipologias puras. Há, sim, uma grande plasticidade e flexibilidade organizacionais. Quanto aos líderes, exercem habitualmente a autoridade formal, pela via da circular normativa. Não são pares (nem primi inter pares), colocam-se por vezes numa posição de superioridade, quando o mais adequado seria a relação de parceria, cooperação e procura de consensos, com todos os colaboradores, afim de serem eles os verdadeiros protagonistas e facilitadores da mudança e das inovações. Como factores facilitadores da inovação e da mudança, encontrámos nas organizações de saúde estudadas o seguinte: facilidade de aprender; visão/missão adequadas; ausência de medo de falhar; e como factores inibidores: falta de articulação entre serviços/departamentos; estrutura organizacional (no sector público muito verticalizada e no sector privado mais horizontalizada); resistência à mudança; falta de tempo; falha no tempo de reacção (o tempo útil para a tomada de decisão é, por vezes, ultrapassado). --------ABSTRACT - The present research seeks to describe and understand how strategy influences leadership and how this in turn interacts in the process of innovation and change in health organizations. Previous studies on these topics are unknown in Portugal, about this research problem and its theoretical problem. This is an exploratory and descriptive study that involved 5 health organizations, 4 Portuguese and 1 Spanish. We used a mixed approach of research (qualitative and quantitative), which enabled us to understand, through case study, how strategy and leadership were articulated with innovation in these five health organizations. The results of the empirical study came from data collection through direct observation, interviews with key actors, documents and survey questionnaire answered by 165 participants of line and staff (Administrators, Medical Directors of Service /Department, Head Nurses and Technical Coordinators) of the five health organizations. Despite their complexity and specificity, both the model of Miles & Snow (organizational strategy) and the model of the Competing Values Framework of Quinn (organizational culture and leadership), suitably adapted, have proven heuristic power and able to be apply to healthcare organizations. Both public sector organizations, private and public organizations licensed (public-private partnerships) can be tracked and monitored in their processes of innovation and change in order to understand its kind of culture, leadership or organizational strategy adopted. Health organizations coexist in a continuum, where the environment (internal and external) and time are key factors which determine the strategy to adopt. Here too depending on the dynamic and complex reality where the organization moves, there are no pure types. There is indeed a great organizational plasticity and flexibility. Leaders usually carry the formal authority by circular normative. They are not pairs (or primi inter pares). Instead they are, sometimes, in a position of superiority, when the best thing is partnership, collaboration, cooperation, building consensus and cooperation with all stakeholders, in order that they are the real protagonists and facilitators of change and innovation. As factors that facilitate innovation and change, we found in health organizations studied, the following: ease of learning; vision / mission appropriate; absence of fear of failure, and as inhibiting factors: lack of coordination between agencies / departments; organizational structure (in the public sector it is too vertical and in the private sector it is more horizontal); resistance to change; lack of time and failure in the reaction time (the time for decision making is sometimes exceeded).
Resumo:
The importance of wind power energy for energy and environmental policies has been growing in past recent years. However, because of its random nature over time, the wind generation cannot be reliable dispatched and perfectly forecasted, becoming a challenge when integrating this production in power systems. In addition the wind energy has to cope with the diversity of production resulting from alternative wind power profiles located in different regions. In 2012, Portugal presented a cumulative installed capacity distributed over 223 wind farms [1]. In this work the circular data statistical methods are used to analyze and compare alternative spatial wind generation profiles. Variables indicating extreme situations are analyzed. The hour (s) of the day where the farm production attains its maximum daily production is considered. This variable was converted into circular variable, and the use of circular statistics enables to identify the daily hour distribution for different wind production profiles. This methodology was applied to a real case, considering data from the Portuguese power system regarding the year 2012 with a 15-minutes interval. Six geographical locations were considered, representing different wind generation profiles in the Portuguese system.In this work the circular data statistical methods are used to analyze and compare alternative spatial wind generation profiles. Variables indicating extreme situations are analyzed. The hour (s) of the day where the farm production attains its maximum daily production is considered. This variable was converted into circular variable, and the use of circular statistics enables to identify the daily hour distribution for different wind production profiles. This methodology was applied to a real case, considering data from the Portuguese power system regarding the year 2012 with a 15-minutes interval. Six geographical locations were considered, representing different wind generation profiles in the Portuguese system.
Resumo:
Mestrado em Engenharia Química - Ramo Optimização Energética na Indústria Química
Resumo:
Dissertation presented at Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia in fulfilment of the requirements for the Masters degree in Mathematics and Applications, specialization in Actuarial Sciences, Statistics and Operations Research
Resumo:
Nos últimos anos, o processo de ensino e aprendizagem tem sofrido significativas alterações graças ao aparecimento da Internet. Novas ferramentas para apoio ao ensino têm surgido, nas quais se destacam os laboratórios remotos. Atualmente, muitas instituições de ensino disponibilizam laboratórios remotos nos seus cursos, que permitem, a professores e alunos, a realização de experiências reais através da Internet. Estes são implementados por diferentes arquiteturas e infraestruturas, suportados por vários módulos de laboratório acessíveis remotamente (e.g. instrumentos de medição). No entanto, a sua inclusão no ensino é ainda deficitária, devido: i) à falta de meios e competências técnicas das instituições de ensino para os desenvolverem, ii) à dificuldade na partilha dos módulos de laboratório por diferentes infraestruturas e, iii) à reduzida capacidade de os reconfigurar com esses módulos. Para ultrapassar estas limitações, foi idealizado e desenvolvido no âmbito de um trabalho de doutoramento [1] um protótipo, cuja arquitetura é baseada na norma IEEE 1451.0 e na tecnologia de FPGAs. Para além de garantir o desenvolvimento e o acesso de forma normalizada a um laboratório remoto, este protótipo promove ainda a partilha de módulos de laboratório por diferentes infraestruturas. Nesse trabalho explorou-se a capacidade de reconfiguração de FPGAs para embutir na infraestrutura do laboratório vários módulos, todos descritos em ficheiros, utilizando linguagens de descrição de hardware estruturados de acordo com a norma IEEE 1451.0. A definição desses módulos obriga à criação de estruturas de dados binárias (Transducer Electronic Data Sheets, TEDSs), bem como de outros ficheiros que possibilitam a sua interligação com a infraestrutura do laboratório. No entanto, a criação destes ficheiros é bastante complexa, uma vez que exige a realização de vários cálculos e conversões. Tendo em consideração essa mesma complexidade, esta dissertação descreve o desenvolvimento de uma aplicação Web para leitura e escrita dos TEDSs. Para além de um estudo sobre os laboratórios remotos, é efetuada uma descrição da norma IEEE 1451.0, com particular atenção para a sua arquitetura e para a estrutura dos diferentes TEDSs. Com o objetivo de enquadrar a aplicação desenvolvida, efetua-se ainda uma breve apresentação de um protótipo de um laboratório remoto reconfigurável, cuja reconfiguração é apoiada por esta aplicação. Por fim, é descrita a verificação da aplicação Web, de forma a tirar conclusões sobre o seu contributo para a simplificação dessa reconfiguração.