910 resultados para principal coordinates analysis
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A combinação da agricultura de precisão e do Sistema Integrado de Recomendação Foliar (DRIS) possibilita monitorar espacialmente o balanço nutricional dos cafezais para fornecer recomendações de adubação mais equilibradas e mais ajustadas economicamente. O objetivo deste trabalho foi avaliar a variabilidade espacial do estado nutricional do cafeeiro conilon, utilizando o Índice de Balanço Nutricional (IBN) e sua relação com a produtividade. A produtividade das plantas em cada ponto amostral foi determinada e construiu-se o seu mapa considerando a variabilidade espacial; determinou-se o Índice de Equilíbrio Nutricional (IBN) das plantas em cada ponto amostral e construiu-se o seu mapa; e utilizou-se a análise de componentes principais (ACP) para estimar o IBN do cafeeiro por cokrigagem. Os dados do cafeeiro conilon foram coletados em fazenda experimental, no município de Cachoeiro de Itapemirim-ES. O IBN do cafeeiro e a sua produtividade foram analisados por meio de geoestatística, com base nos modelos e parâmetros dos semivariogramas, utilizando o método de interpolação krigagem ordinária para estimar valores para locais não amostrados. O índice de Balanço Nutricional da lavoura do cafeeiro conilon apresentou dependência espacial, porém não apresentou correlação linear e nem espacial com a produtividade. A lavoura em estudo se encontra em desequilíbrio nutricional, sendo que entre os macronutrientes, o Potássio foi o que apresentou maior desequilíbrio na área, entre os micronutrientes, o Zinco e o Ferro foram os que apresentaram menores concentrações nas folhas. A confecção dos mapas possibilitou a distinção de regiões com maior e menor desequilíbrio nutricional e produtividade, o que possibilita adotar o manejo de forma diferenciada e localizada. A análise multivariada baseada em componentes principais fornece componentes com alta correlação com as variáveis originais P, Ca, Zn , Cu, K e B. A cokrigagem utilizando as componentes principais permite estimar o IBN e a produtividade da área.
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The increasing need for starches with specific characteristics makes it important to study unconventional starches and their modifications in order to meet consumer demands. The aim of this work was to study physicochemical characteristics of native starch and phosphate starch of S. lycocarpum. Native starch was phosphated with sodium tripolyphosphate (5-11%) added with stirring. Chemical composition, morphology, density, binding ability to cold water, swelling power and solubility index, turbidity and syneresis, rheological and calorimetric properties were determined. Phosphorus was not detected in the native sample, but the phosphating process produced modified starches with phosphorus contents of 0.015, 0.092 and 0.397%, with the capacity of absorbing more water, either cold or hot. Rheological data showed the strong influence of phosphorus content on viscosity of phosphate starch, with lower pasting temperature and peak viscosity higher than those of native starch. Enthalpy was negatively correlated with the phosphorus content, requiring 9.7; 8.5; 8.1 and 6.4 kJ g-1 of energy for the transition from the amorphous to the crystalline state for the starch granules with phosphorus contents of 0; 0.015; 0.092 and 0.397%, respectively. Cluster analysis and principal component analysis showed that starches with 0.015 and 0.092% phosphorus have similar characteristics and are different from the others. Our results show that the characteristics of phosphate modified S. lycocarpum starch have optimal conditions to meet the demands of raw materials, which require greater consistency in stickiness, combined with low rates of retrogradation and syneresis.
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One Plus Sequential Air Sampler—Partisol was placed in a small village (Foros de Arrão) in central Portugal to collect PM10 (particles with an aerodynamic diameter below 10 μm), during the winter period for 3 months (December 2009–March 2010). Particles masses were gravimetrically determined and the filters were analyzed by instrumental neutron activation analysis to assess their chemical composition. The water-soluble ion compositions of the collected particles were determined by Ion-exchange Chromatography. Principal component analysis was applied to the data set of chemical elements and soluble ions to assess the main sources of the air pollutants. The use of both analytical techniques provided information about elemental solubility, such as for potassium, which was important to differentiate sources.
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Lisbon is the largest urban area in the Western European coast. Due to this geographical position the Atlantic Ocean serves as an important source of particles and plays an important role in many atmospheric processes. The main objectives of this study were to (1) perform a chemical characterization of particulate matter (PM2.5) sampled in Lisbon, (2) identify the main sources of particles, (3) determine PM contribution to this urban area, and (4) assess the impact of maritime air mass trajectories on concentration and composition of respirable PM sampled in Lisbon. During 2007, PM2.5 was collected on a daily basis in the center of Lisbon with a Partisol sampler. The exposed Teflon filters were measured by gravimetry and cut into two parts: one for analysis by instrumental neutron activation analysis (INAA) and the other by ion chromatography (IC). Principal component analysis (PCA) and multilinear regression analysis (MLRA) were used to identify possible sources of PM2.5 and determine mass contribution. Five main groups of sources were identified: secondary aerosols, traffic, calcium, soil, and sea. Four-day backtracking trajectories ending in Lisbon at the starting sampling time were calculated using the HYSPLIT model. Results showed that maritime transport scenarios were frequent. These episodes were characterized by a significant decrease of anthropogenic aerosol concentrations and exerted a significant role on air quality in this urban area.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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This paper presents a proposal for an automatic vehicle detection and classification (AVDC) system. The proposed AVDC should classify vehicles accordingly to the Portuguese legislation (vehicle height over the first axel and number of axels), and should also support profile based classification. The AVDC should also fulfill the needs of the Portuguese motorway operator, Brisa. For the classification based on the profile we propose:he use of Eigenprofiles, a technique based on Principal Components Analysis. The system should also support multi-lane free flow for future integration in this kind of environments.
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Dissertação para obtenção do grau de Mestre em Engenharia Informática
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The present study, covering students from public schools and a private school on the island of São Miguel (Azores, Portugal), aims to meet the difficulties of the students of the 3rd and 4th years of the primary education in solving tasks involving construction, reading and interpreting tables and statistical graphs, in the context of Organization and Data Handling (ODH). We present the main results obtained from statistical methods, among which we highlight some non-parametric hypothesis tests and the Categorical Principal Component Analysis (CatPCA), given the nature of the variables included in the questionnaire (mostly nominal and ordinal variables).
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The first and second authors would like to thank the support of the PhD grants with references SFRH/BD/28817/2006 and SFRH/PROTEC/49517/2009, respectively, from Fundação para a Ciência e Tecnol ogia (FCT). This work was partially done in the scope of the project “Methodologies to Analyze Organs from Complex Medical Images – Applications to Fema le Pelvic Cavity”, wi th reference PTDC/EEA- CRO/103320/2008, financially supported by FCT.
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This study aimed to characterize air pollution and the associated carcinogenic risks of polycyclic aromatic hydrocarbon (PAHs) at an urban site, to identify possible emission sources of PAHs using several statistical methodologies, and to analyze the influence of other air pollutants and meteorological variables on PAH concentrations.The air quality and meteorological data were collected in Oporto, the second largest city of Portugal. Eighteen PAHs (the 16 PAHs considered by United States Environment Protection Agency (USEPA) as priority pollutants, dibenzo[a,l]pyrene, and benzo[j]fluoranthene) were collected daily for 24 h in air (gas phase and in particles) during 40 consecutive days in November and December 2008 by constant low-flow samplers and using polytetrafluoroethylene (PTFE) membrane filters for particulate (PM10 and PM2.5 bound) PAHs and pre-cleaned polyurethane foam plugs for gaseous compounds. The other monitored air pollutants were SO2, PM10, NO2, CO, and O3; the meteorological variables were temperature, relative humidity, wind speed, total precipitation, and solar radiation. Benzo[a]pyrene reached a mean concentration of 2.02 ngm−3, surpassing the EU annual limit value. The target carcinogenic risks were equal than the health-based guideline level set by USEPA (10−6) at the studied site, with the cancer risks of eight PAHs reaching senior levels of 9.98×10−7 in PM10 and 1.06×10−6 in air. The applied statistical methods, correlation matrix, cluster analysis, and principal component analysis, were in agreement in the grouping of the PAHs. The groups were formed according to their chemical structure (number of rings), phase distribution, and emission sources. PAH diagnostic ratios were also calculated to evaluate the main emission sources. Diesel vehicular emissions were the major source of PAHs at the studied site. Besides that source, emissions from residential heating and oil refinery were identified to contribute to PAH levels at the respective area. Additionally, principal component regression indicated that SO2, NO2, PM10, CO, and solar radiation had positive correlation with PAHs concentrations, while O3, temperature, relative humidity, and wind speed were negatively correlated.
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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Informática e Computadores
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OBJECTIVE To analyze evidence of the validity and reliability of a Brazilian Portuguese version of the Quality of Care Scale from the perspective of people with physical and intellectual disabilities.METHODS There were 162 people with physical disabilities and 156 with intellectual disabilities from Porto Alegre and metropolitan region, who participated in the study in 2008. Classical psychometrics was used to independently analyze the two samples. Hypotheses for evidence of criterion validity (concurrent type) were tested with the Mann-Whitney test for non-normal distributions. Principal components analysis was used to explore factorial models. Evidence of reliability was calculated with Cronbach alpha for the scales and subscales. Test-retest reliability was analyzed for individuals with intellectual disabilities through intra-class correlation coefficient and the Willcoxon test.RESULTS The principal components in the group with physical disabilities replicated the original model presented as a solution to the international project data. Evidence of discriminant validity and test-retest reliability was found.CONCLUSIONS The transcultural factor model found within the international sample project seems appropriate for the samples investigated in this study, especially the physical disabilities group. Depression, pain, satisfaction with life and disability may play a mediating role in the evaluation of quality of care. Additional research is needed to add to evidence of the validity of the instruments.
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Pine forests constitute some of the most important renewable resources supplying timber, paper and chemical industries, among other functions. Characterization of the volatiles emitted by different Pinus species has proven to be an important tool to decode the process of host tree selection by herbivore insects, some of which cause serious economic damage to pines. Variations in the relative composition of the bouquet of semiochemicals are responsible for the outcome of different biological processes, such as mate finding, egg-laying site recognition and host selection. The volatiles present in phloem samples of four pine species, P. halepensis, P. sylvestris, P. pinaster and P. pinea, were identified and characterized with the aim of finding possible host-plant attractants for native pests, such as the bark beetle Tomicus piniperda. The volatile compounds emitted by phloem samples of pines were extracted by headspace solid-phase micro extraction, using a 2 cm 50/30 mm divinylbenzene/carboxen/polydimethylsiloxane table flex solid-phase microextraction fiber and its contents analyzed by high-resolution gas chromatography, using flame ionization and a non polar and chiral column phases. The components of the volatile fraction emitted by the phloem samples were identified by mass spectrometry using time-of-flight and quadrupole mass analyzers. The estimated relative composition was used to perform a discriminant analysis among pine species, by means of cluster and principal component analysis. It can be concluded that it is possible to discriminate pine species based on the monoterpenes emissions of phloem samples.
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ABSTRACT OBJECTIVE To validate an instrument designed to assess health promotion in the school environment. METHODS A questionnaire, based on guidelines from the World Health Organization and in line with the Brazilian school health context, was developed to validate the research instrument. There were 60 items in the instrument that included 40 questions for the school manager and 20 items with direct observations made by the interviewer. The items’ content validation was performed using the Delphi technique, with the instrument being applied in 53 schools from two medium-sized cities in the South region of Brazil. Reliability (Cronbach’s alpha and split-half) and validity (principal component analysis) analyses were performed. RESULTS The final instrument remained composed of 28 items, distributed into three dimensions: pedagogical, structural and relational. The resulting components showed good factorial loads (> 0.4) and acceptable reliability (> 0.6) for most items. The pedagogical dimension identifies educational activities regarding drugs and sexuality, violence and prejudice, auto care and peace and quality of life. The structural dimension is comprised of access, sanitary structure, and conservation and equipment. The relational dimension includes relationships within the school and with the community. CONCLUSIONS The proposed instrument presents satisfactory validity and reliability values, which include aspects relevant to promote health in schools. Its use allows the description of the health promotion conditions to which students from each educational institution are exposed. Because this instrument includes items directly observed by the investigator, it should only be used during periods when there are full and regular activities at the school in question.
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In this paper a new PCA-based positioning sensor and localization system for mobile robots to operate in unstructured environments (e. g. industry, services, domestic ...) is proposed and experimentally validated. The inexpensive positioning system resorts to principal component analysis (PCA) of images acquired by a video camera installed onboard, looking upwards to the ceiling. This solution has the advantage of avoiding the need of selecting and extracting features. The principal components of the acquired images are compared with previously registered images, stored in a reduced onboard image database, and the position measured is fused with odometry data. The optimal estimates of position and slippage are provided by Kalman filters, with global stable error dynamics. The experimental validation reported in this work focuses on the results of a set of experiments carried out in a real environment, where the robot travels along a lawn-mower trajectory. A small position error estimate with bounded co-variance was always observed, for arbitrarily long experiments, and slippage was estimated accurately in real time.