Search results for "Data point"
showing 10 items of 29 documents
Quantitative Characteristics of Information Society and ICT Industry in Latvia
2015
Abstract The article is devoted to statistical analysis of information and communication technology (ICT) industry in Latvia and the development of Information Society in the country. On the basis of statistical data comparison of Latvia with other European countries is made. This comparison shows that Latvia belongs to countries with very well developed Internet. On the other hand the statistical data points on the fact that it is necessary to increase the awareness of population regarding possibilities offered by using of ICT and e-Government.
Assessment of data availability influence on integrated urban drainage modelling uncertainty
2009
In urban water quality management, several models are connected and integrated for analysing the fate of pollutants from the sources in the urban catchment to the final recipient; classical problems connected with the selection and calibration of parameters are amplified by the complexity of the modelling approach increasing their uncertainty. The present paper aims at studying the influence of reductions in available data on the modelling response uncertainty with respect to the different integrated modelling outputs (both considering quantity and quality variables). At this scope, a parsimonious integrated home-made model has been used allowing for analysing the combinative effect of data…
Outlier recognition in crystal-structure least-squares modelling by diagnostic techniques based on leverage analysis.
2005
The identification of the actual outliers in a least-squares crystal-structure model refinement and their subsequent elimination from the data set is a non-trivial task that has to be carried out carefully when a high level of accuracy of the estimates is required. One of the most suitable tools for detecting the influence of each data entry on the regression is the identification of ;leverage points'. On the other hand, the recognition of the actual statistical outliers is effectively possible by using some diagnostics as a function of the leverage, such as Cook's distance, DFFITS and FVARATIO. The evaluation of these estimators makes it possible to achieve a reliable identification of the…
Single-trial Connectivity Estimation through the Least Absolute Shrinkage and Selection Operator.
2019
Methods based on the use of multivariate autoregressive models (MVAR) have proved to be an accurate tool for the estimation of functional links between the activity originated in different brain regions. A well-established method for the parameters estimation is the Ordinary Least Square (OLS) approach, followed by an assessment procedure that can be performed by means of Asymptotic Statistic (AS). However, the performances of both procedures are strongly influenced by the number of data samples available, thus limiting the conditions in which brain connectivity can be estimated. The aim of this paper is to introduce and test a regression method based on Least Absolute Shrinkage and Selecti…
Estimating brain connectivity when few data points are available: Perspectives and limitations
2017
Methods based on the use of multivariate autoregressive modeling (MVAR) have proved to be an accurate and flexible tool for the estimation of brain functional connectivity. The multivariate approach, however, implies the use of a model whose complexity (in terms of number of parameters) increases quadratically with the number of signals included in the problem. This can often lead to an underdetermined problem and to the condition of multicollinearity. The aim of this paper is to introduce and test an approach based on Ridge Regression combined with a modified version of the statistics usually adopted for these methods, to broaden the estimation of brain connectivity to those conditions in …
Scalar mesons moving in a finite volume and the role of partial wave mixing
2012
Phase shifts and resonance parameters can be obtained from finite-volume lattice spectra for interacting pairs of particles, moving with nonzero total momentum. We present a simple derivation of the method that is subsequently applied to obtain the pi pi and pi K phase shifts in the sectors with total isospin I=0 and I=1/2, respectively. Considering different total momenta, one obtains extra data points for a given volume that allow for a very efficient extraction of the resonance parameters in the infinite-volume limit. Corrections due to the mixing of partial waves are provided. We expect that our results will help to optimize the strategies in lattice simulations, which aim at an accurat…
On Optimizing Locally Linear Nearest Neighbour Reconstructions Using Prototype Reduction Schemes
2010
This paper concerns the use of Prototype Reduction Schemes (PRS) to optimize the computations involved in typical k-Nearest Neighbor (k-NN) rules. These rules have been successfully used for decades in statistical Pattern Recognition (PR) applications, and have numerous applications because of their known error bounds. For a given data point of unknown identity, the k-NN possesses the phenomenon that it combines the information about the samples from a priori target classes (values) of selected neighbors to, for example, predict the target class of the tested sample. Recently, an implementation of the k-NN, named as the Locally Linear Reconstruction (LLR) [11], has been proposed. The salien…
Quantitative T 1 and proton density mapping with direct calculation of radiofrequency coil transmit and receive profiles from two-point variable flip…
2016
Quantitative T1 mapping of brain tissue is frequently based on the variable flip angle (VFA) method, acquiring spoiled gradient echo (GE) datasets at different excitation angles. However, accurate T1 calculation requires a knowledge of the sensitivity profile B1 of the radiofrequency (RF) transmit coil. For an additional derivation of proton density (PD) maps, the receive coil sensitivity profile (RP) must also be known. Mapping of B1 and RP increases the experiment duration, which may be critical when investigating patients. In this work, a method is presented for the direct calculation of B1 and RP from VFA data. Thus, quantitative maps of T1 , PD, B1 and RP can be obtained from only two …
Highly efficient multichannel spin-polarization detection.
2011
Since the original work by Mott, the low efficiency of electron spin polarimeters, remaining orders of magnitude behind optical polarimeters, has prohibited many fundamental experiments. Here we report a solution to this problem using a novel concept of multichannel spin-polarization analysis that provides a stunning increase in efficiency by 4 orders of magnitude. This improvement was demonstrated in a setup using a hemispherical electron energy analyzer. An imaging setup proved the principal capability of resolving more than ${10}^{5}$ data points in parallel.
Minimal learning machine in hyperspectral imaging classification
2020
A hyperspectral (HS) image is typically a stack of frames, where each frame represents the intensity of a different wavelength of light. Each spatial pixel has a spectrum. In the classification of the HS image, each spectrum is classified pixel-by-pixel. In some of the real-time applications, the amount of the HS image data causes performance challenges. Those issues relate to the platforms (e.g. drones) payload restrictions, the issues of the available energy and to the complexity of the machine learning models. In this study, we introduce the minimal learning machine (MLM) as a computationally cheap training and classification machine learning method for the hyperspectral imaging classificatio…