Results 21 to 30 of about 573,989 (290)
Potential Partnerships: Progressive Criminology, Grassroots Organizations and Social Justice
Criminologists around the globe are writing about the disproportionate criminalization of minority groups and – in the US in particular – about racial disproportionality in all aspects of the criminal justice system.
Tim Goddard +2 more
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A chemometric approach to the headspace sampled volatiles of selected Salvia species from Southeastern Serbia [PDF]
Headspace sampling is a fast, simple and economical way to prepare plant samples for analysis by gas chromatography. For the first time, the composition of the head space volatiles (HSV) of six Salvia species (S. verticillata, S. glutinosa, S.
Emilija Kostić +5 more
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PCA in autocorrelation space [PDF]
The use of higher order autocorrelations as features for pattern classification has been usually restricted to second or third orders due to high computational costs. Since the autocorrelation space is a high dimensional space we are interested in reducing the dimensionality of feature vectors for the benefit of the pattern classification task.
Popovici, V., Thiran, J.
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A system with many degrees of freedom can be characterized by a covariance matrix; principal components analysis (PCA) focuses on the eigenvalues of this matrix, hoping to find a lower dimensional description. But when the spectrum is nearly continuous, any distinction between components that we keep and those that we ignore becomes arbitrary; it then ...
Bradde, Serena, Bialek, William
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Comparison of temporal and spatial patterns of water quality parameters in Anzali Wetland (southwest of the Caspian Sea) using Support vector machine model [PDF]
Urgent is growing to have reliable information from the country's water resources. In recent years, data mining models such as artificial neural network (ANN), gene expression programming, Bayesian network, machine algorithms, such as a support vector ...
Maryam Fallah +3 more
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Validation of Nonlinear PCA [PDF]
Linear principal component analysis (PCA) can be extended to a nonlinear PCA by using artificial neural networks. But the benefit of curved components requires a careful control of the model complexity. Moreover, standard techniques for model selection, including cross-validation and more generally the use of an independent test set, fail when applied ...
openaire +4 more sources
DWT/PCA face recognition using automatic coefficient selection [PDF]
In PCA-based face recognition, there is often a trade-off between selecting the most relevant parts of a face image for recognition and not discarding information which may be useful.
Paul Nicholl +3 more
core +1 more source
$e$PCA: High dimensional exponential family PCA
Many applications, such as photon-limited imaging and genomics, involve large datasets with noisy entries from exponential family distributions. It is of interest to estimate the covariance structure and principal components of the noiseless distribution.
Liu, Lydia T. +2 more
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Principal component analysis and its generalizations for any type of sequence (PCA-Seq)
In the 1940s, Karhunen and Loève proposed a method for processing a one-dimensional numeric time series by converting it into multidimensional by shifts. In fact, a one-dimensional number series was decomposed into several orthogonal time series.
V. M. Efimov +2 more
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Orthosiphon aristatus (called kumis kucing in Indonesia) is a valuable herb for diabetes mellitus treatment. In this study, LC-MS/MS and PCA analyses were used to investigate the metabolite profile, classify O.
Faizal Maulana +5 more
doaj +1 more source

