27 resultados para forward selection component analysis


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Conventional methods to solve the problem of blind source separation nonlinear, in general, using series of restrictions to obtain the solution, often leading to an imperfect separation of the original sources and high computational cost. In this paper, we propose an alternative measure of independence based on information theory and uses the tools of artificial intelligence to solve problems of blind source separation linear and nonlinear later. In the linear model applies genetic algorithms and Rényi of negentropy as a measure of independence to find a separation matrix from linear mixtures of signals using linear form of waves, audio and images. A comparison with two types of algorithms for Independent Component Analysis widespread in the literature. Subsequently, we use the same measure of independence, as the cost function in the genetic algorithm to recover source signals were mixed by nonlinear functions from an artificial neural network of radial base type. Genetic algorithms are powerful tools for global search, and therefore well suited for use in problems of blind source separation. Tests and analysis are through computer simulations

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Image compress consists in represent by small amount of data, without loss a visual quality. Data compression is important when large images are used, for example satellite image. Full color digital images typically use 24 bits to specify the color of each pixel of the Images with 8 bits for each of the primary components, red, green and blue (RGB). Compress an image with three or more bands (multispectral) is fundamental to reduce the transmission time, process time and record time. Because many applications need images, that compression image data is important: medical image, satellite image, sensor etc. In this work a new compression color images method is proposed. This method is based in measure of information of each band. This technique is called by Self-Adaptive Compression (S.A.C.) and each band of image is compressed with a different threshold, for preserve information with better result. SAC do a large compression in large redundancy bands, that is, lower information and soft compression to bands with bigger amount of information. Two image transforms are used in this technique: Discrete Cosine Transform (DCT) and Principal Component Analysis (PCA). Primary step is convert data to new bands without relationship, with PCA. Later Apply DCT in each band. Data Loss is doing when a threshold discarding any coefficients. This threshold is calculated with two elements: PCA result and a parameter user. Parameters user define a compression tax. The system produce three different thresholds, one to each band of image, that is proportional of amount information. For image reconstruction is realized DCT and PCA inverse. SAC was compared with JPEG (Joint Photographic Experts Group) standard and YIQ compression and better results are obtain, in MSE (Mean Square Root). Tests shown that SAC has better quality in hard compressions. With two advantages: (a) like is adaptive is sensible to image type, that is, presents good results to divers images kinds (synthetic, landscapes, people etc., and, (b) it need only one parameters user, that is, just letter human intervention is required

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This work considers the development of a filtering system composed of an intelligent algorithm, that separates information and noise coming from sensors interconnected by Foundation Fieldbus (FF) network. The algorithm implementation will be made through FF standard function blocks, with on-line training through OPC (OLE for Process Control), and embedded technology in a DSP (Digital Signal Processor) that interacts with the fieldbus devices. The technique ICA (Independent Component Analysis), that explores the possibility of separating mixed signals based on the fact that they are statistically independent, was chosen to this Blind Source Separation (BSS) process. The algorithm and its implementations will be Presented, as well as the results

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The oil industry has several segments that can impact the environment. Among these, produced water which has been highlight in the environmental problem because of the great volume generated and its toxic composition. Those waters are the major source of waste in the oil industry. The composition of the produced water is strongly dependent on the production field. A good example is the wastewater produced on a Petrobras operating unit of Rio Grande do Norte and Ceará (UO-RNCE). A single effluent treatment station (ETS) of this unit receives effluent from 48 wells (onshore and offshore), which leads a large fluctuations in the water quality that can become a complicating factor for future treatment processes. The present work aims to realize a diagnosis of a sample of produced water from the OU - RNCE in compliance to certain physical and physico-chemical parameters (chloride concentration, conductivity, dissolved oxygen, pH, TOG (oil & grease), nitrate concentration, turbidity, salinity and temperature). The analysis of the effluent is accomplished by means of a MP TROLL 9500 Multiparameter probe, a TOG/TPH Infracal from Wilks Enterprise Corp. - Model HATR - T (TOG) and a MD-31 condutivimeter of Digimed. Results were analyzed by univariated and multivariated analysis (principal component analysis) associated statistical control charts. The multivariate analysis showed a negative correlation between dissolved oxygen and turbidity (-0.55) and positive correlations between salinity and chloride (1), conductivity, chloride and salinity (0.70). Multivariated analysis showed there are seven principal components which can explain the variability of the parameters. The variables, salinity, conductivity and chloride were the most important variables, with, higher sampling variance. Statistical control charts have helped to establish a general trend between the physical and chemical evaluated parameters

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We seek consistency empirical and analytical rigor to the concept of touristification in the course of the contemporary arrangements of subjectivity and urbanity stations through a landscape of social (dis)encounters between residents and foreigners living in the capital of Rio Grande do Norte, Natal. In the last three decades the city has become a major destination country for national and international tourism, making tourism an important monitor of choreography in search of synchrony between cities and subjectivities, orchestrated by the cyclical crises and the relentless battle for systemic capitalistic expansion and survival. We proceed with an ethnographic and cartographic inspiration in Ponta Negra, where the waterfront redevelopment in 2000 conducted by the government, influenced the implementation of various establishments, services and practices related to the construction of Natal s major industry hub of tourism and entertainment. We proposed an arch-genealogy of touristification inspared on Michel Foucault analytical perspective, increased by authors in confluence or in different theoretical and methodological approaches, among which stand out Karl Marx, Gilles Deleuze and Felix Guattari, Michael Hardt and Antonio Negri. The reflections that initially turned to the advancement of the sphere of consumerism as the issue capable of articulating the developmental trajectory of the capitalist system and the practice of tourism, promoting some effects (un)desirable in the conflictual dynamics of the condition of the district of Ponta Negra, territory each again (re) produces the designs to meet the consumption by affluent portion of the population and foreign, encountering social exclusion and inclusion differentiated a growing trend. We go forward with an analysis of the "liberation of desire" phenomenal features of the process of producing subjective, providing a breakdown of the recent world s financial crisis initially, but proved social and political crisis also, through a plot derived from the operation of real estate speculation, which Natal is mainly caught through touristification, showing the outlines of a generalized crisis in establishing a new order buoyed by the emergence of a context "biopolitical" since it is a major route that uses the capital to survive and expand, while guiding the process of "strategic beautification" held in Ponta Negra, problematized by us. We conclude by assessing the appropriateness of proposing on further analysis to explore the establishment of a "new social ontology in terms of interference touristification ongoing and the constitution of a "new order" local/global, away from that characterize a system's capitalist overcoming, try to give emphasis in the current stage of the radicalization of a capitalistic utopia

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In this work we used chemometric tools to classify and quantify the protein content in samples of milk powder. We applied the NIR diffuse reflectance spectroscopy combined with multivariate techniques. First, we carried out an exploratory method of samples by principal component analysis (PCA), then the classification of independent modeling of class analogy (SIMCA). Thus it became possible to classify the samples that were grouped by similarities in their composition. Finally, the techniques of partial least squares regression (PLS) and principal components regression (PCR) allowed the quantification of protein content in samples of milk powder, compared with the Kjeldahl reference method. A total of 53 samples of milk powder sold in the metropolitan areas of Natal, Salvador and Rio de Janeiro were acquired for analysis, in which after pre-treatment data, there were four models, which were employed for classification and quantification of samples. The methods employed after being assessed and validated showed good performance, good accuracy and reliability of the results, showing that the NIR technique can be a non invasive technique, since it produces no waste and saves time in analyzing the samples

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Nowadays, the use of chemicals that satisfactorily meet the needs of different sectors of the chemical industry is linked to the consumption of biodegradable materials. In this context, this work contemplated biotechnological aspects with the objective of developing a more environmentally-friendly corrosion inhibitor. In order to achieve this goal, nanoemulsion-type systems (NE) were obtained by varying the amount of Tween 80 (9 to 85 ppm) a sortitan surfactant named polyoxyethylene (20) monooleate. This NE-system was analyzed using phase diagrams in which the percentage of the oil phase (commercial soybean oil, codenamed as OS) was kept constant. By changing the amount of Tween 80, several polar NE-OS derived systems (O/W-type nanoemulsion) were obtained and characterized through light scattering, conductivity and pH, and further subjected to electrochemical studies. The interfacial behavior of these NE-OS derived systems (codenamed NE-OS1, S2, S3, S4 and S5) as corrosion inhibitors on carbon steel AISI 1020 in saline media (NaCl 3.5%) were evaluated by measurement of Open Circuit Potential (OCP), Polarization Curves (Tafel extrapolation method) and Electrochemical Impedance Spectroscopy (EIS). The analyzed NE-OS1 and NE-OS2 systems were found to be mixed inhibitors with quantitative efficacy (98.6% - 99.7%) for concentrations of Tween 80 ranging between 9 and 85 ppm. According to the EIS technique, maximum corrosion efficiency was observed for some tested NE-OS samples. Additionaly to the electrochemical studies, Analysis of Variance (ANOVA) and Principal Component Analysis (PCA) were used, characterization of the nanoemulsion tested systems and adsorption studies, respectively, which confirmed the results observed in the experimental analyses using diluted NE-OS samples in lower concentrations of Tween 80 (0.5 1.75 ppm)

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Aiming to consumer s safety the presence of pathogenic contaminants in foods must be monitored because they are responsible for foodborne outbreaks that depending on the level of contamination can ultimately cause the death of those who consume them. In industry is necessary that this identification be fast and profitable. This study shows the utility and application of near-infrared (NIR) transflectance spectroscopy as an alternative method for the identification and classification of Escherichia coli and Salmonella Enteritidis in commercial fruit pulp (pineapple). Principal Component Analysis (PCA), Independent Modeling of Class Analogy (SIMCA) and Discriminant Analysis Partial Least Squares (PLS-DA) were used in the analysis. It was not possible to obtain total separation between samples using PCA and SIMCA. The PLS-DA showed good performance in prediction capacity reaching 87.5% for E. coli and 88.3% for S. Enteritides, respectively. The best models were obtained for the PLS-DA with second derivative spectra treated with a sensitivity and specificity of 0.87 and 0.83, respectively. These results suggest that the NIR spectroscopy and PLS-DA can be used to discriminate and detect bacteria in the fruit pulp

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This paper investigates the potential of near infrared spectroscopy (NIR) for forensic analysis of human hair samples in order to differentiate smokers from nonsmokers, using chemometric modeling as an analytical tool. We obtained a total of 19 hair samples, 9 smokers and 10 nonsmokers varying gender, hair color, age and duration of smoking, all collected directly from the head of the same great Natal-RN. From the NIR spectra obtained without any pretreatment of the samples was performed an exploratory multivariate chemical data by applying spectral pretreatments followed by principal component analysis (PCA). After chemometric modeling of the data was achieved without any experimental data beyond the NIR spectra, differentiate smokers from nonsmokers, by demonstrating the significant influence of tabacco on the chemical composition of hair as well as the potential of the methodology in forensic identification

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Many studies on environmental ecosystems quality related to polycyclic aromatic hydrocarbons (PAH) have been carried out routinely due to their ubiquotus presence worldwide and to their potential toxicity after its biotransformation. PAH may be introduced into the environmet by natural and anthropogenic processes from direct runoff and discharges and indirect atmospheric deposition. Sources of naturally occurring PAHs include natural fires, natural oil seepage and recent biological or diagenetic processes. Anthropogenic sources of PAHs, acute or chronic, are combustion of organic matter (petroleum, coal, wood), waste and releases/spills of petroleum and derivatives (river runoff, sewage outfalls, maritime transport, pipelines). Besides the co-existence of multiples sources of PAH in the environmental samples, these compounds are subject to many processes that lead to geochemical fates (physical-chemical transformation, biodegradation and photo-oxidation), which leads to an alteration of their composition. All these facts make the identification of the hydrocarbons sources, if petrogenic, pyrolytic or natural, a challenge. One of the objectives of this study is to establish tools to identify the origin of hydrocarbons in environmental samples. PAH diagnostic ratios and PAH principal component analysis were tested on a critical area: Guanabara Bay sediments. Guanabara Bay is located in a complex urban area of Rio de Janeiro with a high anthropogenic influence, being an endpoint of chronic pollution from the Greater Rio and it was the scenario of an acute event of oil release in January 2000. It were quantified 38 compounds, parental and alkylated PAH, in 21 sediment samples collected in two surveys: 2000 and 2003. The PAH levels varied from 400 to 58439 ng g-1. Both tested techniques for origin identification of hydrocarbons have shown their applicability, being able to discriminate the PAH sources for the majority of the samples analysed. The bay sediments were separated into two big clusters: sediments with a clear pattern of petrogenic introduction of hydrocarbons (from intertidal area) and sediments with combustion characteristics (from subtidal region). Only a minority of the samples could not display a clear contribution of petrogenic or pyrolytic input. The diagnostic ratios that have exhibited high ability to distinguish combustion- and petroleum-derived PAH inputs for Guanabara Bay sediments were Phenanthrene+Anthracene/(Phenanthrene+Anthracene+C1Phenanthrene); Fluorantene/(Fluorantene+Pyrene); Σ (other 3-6 ring PAHs)/ Σ (5 alkylated PAH series). The PCA results prooved to be a useful tool for PAH source identification in the environment, corroborating the diagnostic indexes. In relation to the temporal evaluation carried out in this study, it was not verified significant changes on the class of predominant source of the samples. This result indicates that the hydrocarbons present in the Guanabara Bay sediments are mainly related to the long-term anthropogenic input and not directly related to acute events such as the oil spill of January 2000. This findings were similar to various international estuarine sites. Finally, this work had a complementary objective of evaluating the level of hydrocarbons exposure of the aquatic organisms of Guanabara Bay. It was a preliminary study in which a quantification of 12 individual biliar metabolites of PAH was performed in four demersal fish representing three different families. The analysed metabolites were 1-hydroxynaphtalene, 2-hidroxinaphtalene, 1hydroxyphenanthrene, 9-hydroxyphenanthrene, 2-hydroxyphenanthrene, 1hydroxypyrene, 3-hidroxibiphenil, 3- hydroxyphenanthrene, 1-hydroxychrysene, 9hydroxyfluorene, 4-hydroxyphenanthrene, 3-hydroxybenz(a)pyrene. The metabolites concentrations were found to be high, ranging from 13 to 177 µg g-1, however they were similar to worldwide regions under high anthropogenic input. Besides the metabolites established by the used protocol, it was possible to verified high concentrations of three other compounds not yet reported in the literature. They were related to pyrolytic PAH contribution to Guanabara Bay aquatic biota: 1-hydroxypyrine and 3-hydroxybenz(a)pyrine isomers

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The aim of this study is to investigate the eco-environmental vulnerability, its changes, and its causes to develop a management system for application of eco-environmental vulnerability and risk assessment in the Apodi-Mossory estuary, Northeast Brazil. This analysis is focused on the interference of the landscape conditions, and its changes, due to the following factors: the oil and natural gas industry, tropical fruits industry, shrimp farms, marine salt industry, occupation of the sensitive areas; demand for land, vegetation degradation, siltation in rivers, severe flooding, sea level rise (SLR), coastal dynamics, low and flat topography, high ecological value and tourism in the region and the rapid growth of urbanization. Conventional and remote sensing data were analyzed using modeling techniques based on ArcGIS, ER-Mapper, ERDAS Imagine and ENVI software. Digital images were initially processed by Principal Component Analysis and transformation of the maximum fraction of noise, and then all bands were normalized to reduce errors caused by bands of different sizes. They were integrated in a Geographic Information System analysis to detect changes, to generate digital elevation models, geomorphic indices and other variables of the study area. A three band color combination of multispectral bands was used to monitor changes of land and vegetation cover from 1986 to 2009. This task also included the analysis of various secondary data, such as field data, socioeconomic data, environmental data and prospects growth. The main objective of this study was to improve our understanding of eco-environmental vulnerability and risk assessment; it´s causes basically show the intensity, its distribution and human-environment effect on the ecosystem, and identify the high and low sensitive areas and area of inundation due to future SLR, and the loss of land due to coastal erosion in the Apodi-Mossoró estuary in order to establish a strategy for sustainable land use. The developed model includes some basic factors such as geology, geomorphology, soils, land use / land cover, vegetation cover, slope, topography and hydrology. The numerical results indicate that 9.86% of total study area was under very high vulnerability, 29.12% high vulnerability, 52.90% moderate vulnerability and 2.23% were in the category of very low vulnerability. The analysis indicates that 216.1 km² and 362.8 km² area flooded on 1m and 10m in sea levels respectively. The sectors most affected were residential, industrial and recreational areas, agricultural land, and ecosystems of high environmental sensitivity. The results showed that changes in eco-environmental vulnerability have a significant impact on the sustainable development of the RN state, since the indicator is a function of sensitivity, exposure and status in relation to a level of damage. The model were presented as a tool to assist in indexing vulnerability in order to optimize actions and assess the implications of decisions makers and policies regarding the management of coastal and estuarine areas. In this context aspects such as population growth, degradation of vegetation, land use / land cover, amount and type of industrialization, SLR and government policies for environmental protection were considered the main factors that affect the eco-environmental changes over the last three decades in the Apodi-Mossoró estuary.

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This work embraces the application of Landsat 5-TM digital images, comprising August 2 1989 and September 22 1998, for temporal mapping and geoenvironmental analysis of the dynamic of Piranhas-Açu river mouth, situated in the Macau (RN) region. After treatment using several digital processing techniques (e.g. colour composition in RGB, ratio of bands, principal component analysis, index methods, among others), it was possible to generate several image products and multitemporal maps of the coastal morphodynamics of the studied area. Using the image products it was possible the identification and characterization of the principal elements of interest (vegetation, soil, geology and water) in the surface of the studied area, associating the spectral characteristics of these elements to that presented by the image products resulting of the digital processing. Thus, it was possible to define different types of soils: Amd, AQd6, SK1 and LVe4; vegetation grouping: open arboreal-shrubby caatinga, closed arborealshrubby caatinga, closed arboreal caatinga, mangrove vegetation, dune vegetation and areas predominately constituted by juremas; geological units: quaternary units beach sediments, sand banks, dune flats, barrier island, mobile dunes, fixed dunes, alluvium, tidal and inundation flats, and sandy facies of the Potengi Formation; tertiary-quaternary units Barreiras Formation grouped to the clayey facies of the Potengi Formation, Macau Formation grouped to the sediments of the Tibau Formation; Cretaceous units Jandaíra Formation; moreover it was to identify the sea/land limit, shallow submersed areas and suspended sediments. The multitemporal maps of the coastal morphodynamics allowed the identification and a semi-quantitative evoluation of regions which were submitted to erosive and constructive processes in the last decade. This semi-quantitative evoluation in association with an geoenvironmental characterization of the studied area are important data to the elaboration of actions that may minimize the possible/probable impacts caused by the implantation of the Polo Gas/Sal and to the monitoring of areas explorated by the petroleum and salt industries