891 resultados para sampling error
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In this work we use Interval Mathematics to establish interval counterparts for the main tools used in digital signal processing. More specifically, the approach developed here is oriented to signals, systems, sampling, quantization, coding and Fourier transforms. A detailed study for some interval arithmetics which handle with complex numbers is provided; they are: complex interval arithmetic (or rectangular), circular complex arithmetic, and interval arithmetic for polar sectors. This lead us to investigate some properties that are relevant for the development of a theory of interval digital signal processing. It is shown that the sets IR and R(C) endowed with any correct arithmetic is not an algebraic field, meaning that those sets do not behave like real and complex numbers. An alternative to the notion of interval complex width is also provided and the Kulisch- Miranker order is used in order to write complex numbers in the interval form enabling operations on endpoints. The use of interval signals and systems is possible thanks to the representation of complex values into floating point systems. That is, if a number x 2 R is not representable in a floating point system F then it is mapped to an interval [x;x], such that x is the largest number in F which is smaller than x and x is the smallest one in F which is greater than x. This interval representation is the starting point for definitions like interval signals and systems which take real or complex values. It provides the extension for notions like: causality, stability, time invariance, homogeneity, additivity and linearity to interval systems. The process of quantization is extended to its interval counterpart. Thereafter the interval versions for: quantization levels, quantization error and encoded signal are provided. It is shown that the interval levels of quantization represent complex quantization levels and the classical quantization error ranges over the interval quantization error. An estimation for the interval quantization error and an interval version for Z-transform (and hence Fourier transform) is provided. Finally, the results of an Matlab implementation is given
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O objetivo deste trabalho foi analizar a distribuição espacial da compactação do solo e a influência da umidade do solo na resistência à penetração. Esta última variável foi descrita pelo índice de cone. O solo estudado foi Nitossolo e os dados de índice de cone foram obtidos usando um penetrômetro. A resistência do solo foi avaliada a 5 profundidades diferentes, 0-10 cm, 10-20 cm, 20-30 cm, 30-40 cm e mais de 40 cm, porém o conteúdo de umidade do solo foi medido a 0-20 cm e 20-40 cm. As condições hídricas do solo variaram nas diferentes amostragems. Os coeficientes de variação para o índice de cone foram 16,5% a 45,8% e os do conteúdo de umidade do solo variaram entre 8,96% e 21,38%. Os resultados sugeriram elevada correlação entre a resistência do solo, estimada pelo índice de cone e a profundidade do solo. Sem embargo, a relação esperada com a umidade do solo não foi apreciada. Observou-se dependência espacial em 31 de 35 séries de dados de índice de cone e umidade do solo. Esta dependência foi ajustada por modelos exponenciais com efeito pepita variável de 0 a 90% o valor do patamar. em séries de dados o comportamento foi aleatório. Portanto, a técnica das distâncias inversas foi utilizada para cartografar a distribuição das variáveis que não tiveram estrutura espacial. Na krigagem constatou-se uma suavização dos mapas comparados com esses das distâncias inversas. A krigagem indicadora foi utilizada para cartografar a variabilidade espacial do índice de cone e recomendar melhor manejo do solo.
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Nowadays, classifying proteins in structural classes, which concerns the inference of patterns in their 3D conformation, is one of the most important open problems in Molecular Biology. The main reason for this is that the function of a protein is intrinsically related to its spatial conformation. However, such conformations are very difficult to be obtained experimentally in laboratory. Thus, this problem has drawn the attention of many researchers in Bioinformatics. Considering the great difference between the number of protein sequences already known and the number of three-dimensional structures determined experimentally, the demand of automated techniques for structural classification of proteins is very high. In this context, computational tools, especially Machine Learning (ML) techniques, have become essential to deal with this problem. In this work, ML techniques are used in the recognition of protein structural classes: Decision Trees, k-Nearest Neighbor, Naive Bayes, Support Vector Machine and Neural Networks. These methods have been chosen because they represent different paradigms of learning and have been widely used in the Bioinfornmatics literature. Aiming to obtain an improvment in the performance of these techniques (individual classifiers), homogeneous (Bagging and Boosting) and heterogeneous (Voting, Stacking and StackingC) multiclassification systems are used. Moreover, since the protein database used in this work presents the problem of imbalanced classes, artificial techniques for class balance (Undersampling Random, Tomek Links, CNN, NCL and OSS) are used to minimize such a problem. In order to evaluate the ML methods, a cross-validation procedure is applied, where the accuracy of the classifiers is measured using the mean of classification error rate, on independent test sets. These means are compared, two by two, by the hypothesis test aiming to evaluate if there is, statistically, a significant difference between them. With respect to the results obtained with the individual classifiers, Support Vector Machine presented the best accuracy. In terms of the multi-classification systems (homogeneous and heterogeneous), they showed, in general, a superior or similar performance when compared to the one achieved by the individual classifiers used - especially Boosting with Decision Tree and the StackingC with Linear Regression as meta classifier. The Voting method, despite of its simplicity, has shown to be adequate for solving the problem presented in this work. The techniques for class balance, on the other hand, have not produced a significant improvement in the global classification error. Nevertheless, the use of such techniques did improve the classification error for the minority class. In this context, the NCL technique has shown to be more appropriated
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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The general assumption under which the (X) over bar chart is designed is that the process mean has a constant in-control value. However, there are situations in which the process mean wanders. When it wanders according to a first-order autoregressive (AR (1)) model, a complex approach involving Markov chains and integral equation methods is used to evaluate the properties of the (X) over bar chart. In this paper, we propose the use of a pure Markov chain approach to study the performance of the (X) over bar chart. The performance of the chat (X) over bar with variable parameters and the (X) over bar with double sampling are compared. (C) 2011 Elsevier B.V. All rights reserved.
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In this article, we consider the T(2) chart with double sampling to control bivariate processes (BDS chart). During the first stage of the sampling, n(1) items of the sample are inspected and two quality characteristics (x; y) are measured. If the Hotelling statistic T(1)(2) for the mean vector of (x; y) is less than w, the sampling is interrupted. If the Hotelling statistic T(1)(2) is greater than CL(1), where CL(1) > w, the control chart signals an out-of-control condition. If w < T(1)(2) <= CL(1), the sampling goes on to the second stage, where the remaining n(2) items of the sample are inspected and T(2)(2) for the mean vector of the whole sample is computed. During the second stage of the sampling, the control chart signals an out-of-control condition when the statistic T(2)(2) is larger than CL(2). A comparative study shows that the BDS chart detects process disturbances faster than the standard bivariate T(2) chart and the adaptive bivariate T(2) charts with variable sample size and/or variable sampling interval.
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We propose a new statistic to control the covariance matrix of bivariate processes. This new statistic is based on the sample variances of the two quality characteristics, in short VMAX statistic. The points plotted on the chart correspond to the maximum of the values of these two variances. The reasons to consider the VMAX statistic instead of the generalized variance vertical bar S vertical bar is its faster detection of process changes and its better diagnostic feature; that is, with the VMAX statistic it is easier to identify the out-of-control variable. We study the double sampling (DS) and the exponentially weighted moving average (EWMA) charts based on the VMAX statistic. (C) 2008 Elsevier B.V. All rights reserved.
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In distance learning degree in Chemistry in full of the Secretária de Educação a distância da Universidade Federal do Rio Grande do Norte (SEDIS / UFRN). The teacher-tutor to establish the experimental subjects closer relationships with students, mediating the pedagogical actions that develop in the distance learning course, with a view to achieving the principles of autonomy and learning, contributing to the creation of learning environments collaborative, guided by affection.The article presents the results of an empirical research on affectivity in practice this tutorial experimental classes in higher distance education in the full degree course in Chemistry Polo Currais Novos/ RN, held between 2009 and 2010. The study is based on qualitative methodology, whose data were collected through questionnaires and semi-structured interviews with 48 (forty eight) students involved in distance learning courses and selected in order to compose a group of subjects who showed variability, as guidelines that guide the sampling procedures in qualitative research. The results, based on category theory and empirical analysis of data from the interviews were supplemented by information obtained from participant observation which also served to guide the data collection of the corpus of this work. With the results we understand that there is clarity about what characterizes a loving relationship between those involved in the process of teaching and learning in experimental classes in high school chemistry Distance Education. Furthermore, it was also clear that the communication process in dialogic teaching and learning in higher distance education in chemistry at the trial need to mark out in balanced affective attitudes, the experimental error that value and respect the many possible construction of knowledge by movements social interaction of individual and collective
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In distance learning degree in Chemistry in full of the Secretária de Educação a distância da Universidade Federal do Rio Grande do Norte (SEDIS / UFRN). The teacher-tutor to establish the experimental subjects closer relationships with students, mediating the pedagogical actions that develop in the distance learning course, with a view to achieving the principles of autonomy and learning, contributing to the creation of learning environments collaborative, guided by affection.The article presents the results of an empirical research on affectivity in practice this tutorial experimental classes in higher distance education in the full degree course in Chemistry Polo Currais Novos/ RN, held between 2009 and 2010. The study is based on qualitative methodology, whose data were collected through questionnaires and semi-structured interviews with 48 (forty eight) students involved in distance learning courses and selected in order to compose a group of subjects who showed variability, as guidelines that guide the sampling procedures in qualitative research. The results, based on category theory and empirical analysis of data from the interviews were supplemented by information obtained from participant observation which also served to guide the data collection of the corpus of this work. With the results we understand that there is clarity about what characterizes a loving relationship between those involved in the process of teaching and learning in experimental classes in high school chemistry Distance Education. Furthermore, it was also clear that the communication process in dialogic teaching and learning in higher distance education in chemistry at the trial need to mark out in balanced affective attitudes, the experimental error that value and respect the many possible construction of knowledge by movements social interaction of individual and collective
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Spatial sampling designs used to characterize the spatial variability of soil attributes are crucial for science studies. Sample planning for the interpolation of a regionalized variable may use several criteria, which could be best selected from an estimated semivariogram from a previously established grid. The objective of this study was to optimize the procedure for scaled semivariogram use to plan soil sampling in sugarcane fields in the Alfisol and Oxisol regions of Jaboticabal Town in So Paulo State, Brazil. A scaled semivariogram for several soil chemical attributes was estimated from the data obtained from two grids positioned on a sugarcane field area, sampled at a depth of 0.0-0.5 m. The research showed that regular grids with uniform intervals did not express the real spatial variability of the soil attributes of Oxisols and Alfisols in the study area. The calculated final sampling density based on the scaled parameters of the semivariogram was one sample for each 2 ha in Area 1 (convex landscape) and one sample for each 1 ha in Area 2 (linear landscape), as indicated by SANOS 0.1 software. The combined use of the simulation programs and scaled semivariograms can be used to define sampling points. These results may help in soil fertility mapping and thereby improve nutrient management in sugarcane crops.
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Dung beetles (Coleoptera: Scarabaeidae: Scarabaeinae) are very useful insects, as they improve the chemo-physical properties of soil, clean pastures from dung pads, and help control symbovine flies associated with bovine cattle. Their importance makes it fundamental to sample and survey them adequately. The objectives of the present study were to determine the influence of decaying insects trapped in pitfalls on the attractiveness of Moura pig Sus scrofa L. (Suidae) and collared peccary Tayassu tajacu (L.) (Tayassuidae) dung used as baits to lure dung beetles, and to establish how long these baits remain attractive to dung beetles when used in these traps. Some dung beetle species seemed to be able to discriminate against foul smell from decaying insects within the first 24 h, hence decreasing trap efficiency. This was more evident in peccary dung-baited traps, which proved to be the least attractive bait. Attractiveness lasted only 24 h for peccary dung, after which it became unattractive, whereas the pig dung bait was highly attractive for 48 h, after which its attractiveness diminished but was not completely lost.
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This thesis aims to identify how civil servants perceive changes made inthe carrying out of their work after their taking part in the Course forTechnicians in Public Management of the Government of Rio Grande do NorteState. As for the methodological procedures, an exploratory-descriptivequantitative research has been carried out through structured questionnaires appliedto 118 civil servants from the first groups of the Course for Technicians, thusshowing a margin of error of 4.18% to 95% of confidence, according to theprocedures of finite sampling. The table processing and analysis rested uponthe Statistical Package for the Social Sciences SPSS and was carried outthrough univariate, bivariate and multivariate techniques with emphasis on thetechnique called Factor Analysis. It was possible to identify that the level ofsatisfaction of the students was high and there was a clear perception by themthat the course assisted to changes in their work. Through Factor Analysis itwas verified that the factors that may be related to changes in the work of thecivil servants are "Contribution to Society", "Efficiency andEfficacy in the Work Environment", "Applicability of Contents"and "Capacitating for Leadership". The conclusion of the studyindicates that the factors obtained are directly related to the basis of thenew public management by means of guidance toward efficiency and efficacy in aperspective of leadership, the contents of the course being thus made into newattitudes toward work which end up yielding better results for society