Search results for " set"
showing 10 items of 2095 documents
Determination of quality parameters of beers by the use of attenuated total reflectance-Fourier transform infrared spectroscopy
2005
Abstract The estimation of important quality parameters of beers, such as original and real extracts and alcohol content, has been evaluated by attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR) using a partial least square (PLS) calibration approach. Two sample populations, one consisting of 24 samples and other of 21 samples, obtained from the Spanish market and covering different types of beer were used. The first set was used for building and validating the model, whereas the second, measured 6 months after, was used for evaluating its robustness. The spectral range and the size of the calibration set and its suitability for building the PLS model have been …
Towards a new generation of high-resolution meteorological input data for small-scale hydrologic modeling
2011
Summary Current and future challenges of hydrologic sciences are to accurately predict and assess climate-driven impacts on water resources for the relevant scales of planning. However, process-based small-scale hydrologic modeling is data demanding and large uncertainties exist in data-sparse areas. The aim of our study was to test the applicability of the COSMO-DE analysis data (COSMO-DE-A) for hydrologic modeling. COSMO-DE-A data are a new meteorological data set with high temporal and spatial resolution that originates from the German Weather Service data assimilation system using the COSMO-DE weather prediction model. We collected field parameters in a small (10 km 2 ) mountainous catc…
<title>Methodology for quantitative analysis of scaling effects in multiresolution datasets acquired with airborne sensors flying at different …
2001
Scaling issues are always playing a critical role in most studies based on remote sensing data. The process of getting quantitative scaling information from raw multi-resolution images is not trivial, and many aspects must be taken very carefully into consideration. To get a better picture about the role of spatial resolution, we conducted a series of flights in summer 1997, in several test sites over Spain and Portugal. In order to minimize the time of acquisition (to get minimal changes in atmospheric status and solar illumination) we used three flight altitude levels, that produced images with 1.25 m, 3 m and 12 m resolutions. The main steps in our methodology are: a) Geometrical registr…
'Dual' Gravity: Using Spatial Econometrics to Control for Multilateral Resistance
2010
We propose a quantity-based `dual' version of the gravity equation that yields an estimating equation with both cross-sectional interdependence and spatially lagged error terms. Such an equation can be concisely estimated using spatial econometric techniques. We illustrate this methodology by applying it to the Canada-U.S. data set used previously, among others, by Anderson and van Wincoop (2003) and Feenstra (2002, 2004). Our key result is to show that controlling directly for spatial interdependence across trade flows, as suggested by theory, significantly reduces border effects because it captures `multilateral resistance'. Using a spatial autoregressive moving average specification, we …
Measurement error in schooling data: the OECD case
2003
The effect of human capital is difficult to estimate in cross-country analysis due to measurement errors in schooling data. Using data for OECD countries over the period 1960–1990, the reliability of the widely used Barro and Lee's data set and also the new De la Fuente and Domenech's data set is analysed. Results show that both suffer from measurement errors, but the latter seems to reflect the rate of growth of schooling more accurately, especially when taking long differences.
Computing Sum of Products about the Mean with Pairwise Algorithms
1997
We discuss pairwise algorithms, a kind of computational algorithm which can be useful in dynamically updating statistics as new samples of data are collected. Since test data are usually collected through time as individual data sets, these algorithms would be profitably used in computer programs to treat this situation. Pair-wise algorithms are presented for calculating the sum of products of deviations about the mean for adding a sample of data (or removing one) to the whole data set.
The Model of Possible Web Data Retrieval
2015
In the Dempster-Shafer's theory of evidence, for incorporating uncertainty, the valuation assigns to the data tables the degrees of belief for these data. Firstly, we are looking for the answers to the following questions. Is there a valuation-based system in which combination and marginalization operate on valuations? Has this system prosperities analogical to the t-norm system? In the t-norm system of the valuation for the specific database attributes configuration can be described the algebra of possible data set in which can be interpreted the Information Retrieval Logic.
Integration of high and low resolution NDVI data for monitoring vegetation in Mediterranean environments
1998
Abstract The integration of the useful features of high and low spatial and temporal resolution satellite data is a major issue in remote sensing studies. The current work presents the development and testing of a procedure based on classification and regression analysis techniques for generating an NDVI data set with the spatial resolution of Landsat TM images and the temporal resolution of NOAA AVHRR maximum-value composites. The procedure begins with a classification of the high resolution TM data which yields land use references. These are degraded to low spatial resolution in order to produce abundance images comparable with the AVHRR data. Linear regressions are then applied between t…
A Novel Self-organizing Neural Technique for Wind Speed Mapping
2009
Systems with high nonlinearities are, in general, very difficult to model. This is particularly true in geostatistics, where the problem of the estimation of a regionalized variable (RV) given only a small amount of measurement stations and a complex terrain surface is very challenging. This paper introduces a novel strategy, which couples the Curvilinear Component Analysis (CCA) and the Generalized Mapping Regressor (GMR). CCA, which is a nonlinear projector of a data manifold, is here used in order to find the intrinsic dimension of the data manifold, just giving an insight on the nonlinearities of the problem. This analysis drives the pre-processing of the data set used for the training …
The Analysis of Auxological Data by Means of Nonlinear Multivariate Growth Curves
1999
In this paper we treat the problem to analyse a data set constituted by multivariate growth curves for different subjects; thus in this context we deal with 3-way data tables. Nevertheless, it is not possible using factorial techniques proposed to deal with 3-way data matrices, because the observations are generally not equally spaced; moreover a multilevel approach founded on polynomial models is not suitable to deal with intrinsic nonlinear models. We propose a non-factorial technique to analyse auxological data sets using an intrinsic nonlinear multivariate growth model with autocorrelated errors. The application to a real data set of growing children gave easily interpretable results.