Search results for "Data set"
showing 10 items of 154 documents
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.
Background subtraction and peak search from threefold gamma event data
1990
Abstract A method for subtracting background from triple-coincidence γ events is presented. In our data set it was used to remove 40% of the noise without affecting photopeaks with intensity of >18 counts. An example of performance of Ward's clustering algorithm applied to three-dimensional photopeak searching is also presented. Several standard clustering algorithms were found to be applicable only to background-subtracted data.
High-statistics study of f0(1500) decay into π0π0
1995
Abstract A partial-wave analysis of the reaction p p →π 0 π 0 π 0 has been performed using a high-quality high-statistics data set of 712 000 events. In addition to the f0(975) and f0(1300), the scalar resonance with mass m = (1500 ± 15) MeV and width Γ = (120 ± 25) MeV is necessary to describe the data.
Polar Classification of Nominal Data
2013
Many modern systems record various types of parameter values. Numerical values are relatively convenient for data analysis tools because there are many methods to measure distances and similarities between them. The application of dimensionality reduction techniques for data sets with such values is also a well known practice. Nominal (i.e., categorical) values, on the other hand, encompass some problems for current methods. Most of all, there is no meaningful distance between possible nominal values, which are either equal or unequal to each other. Since many dimensionality reduction methods rely on preserving some form of similarity or distance measure, their application to such data sets…
Streamlining distributed Deep Learning I/O with ad hoc file systems
2021
With evolving techniques to parallelize Deep Learning (DL) and the growing amount of training data and model complexity, High-Performance Computing (HPC) has become increasingly important for machine learning engineers. Although many compute clusters already use learning accelerators or GPUs, HPC storage systems are not suitable for the I/O requirements of DL workflows. Therefore, users typically copy the whole training data to the worker nodes or distribute partitions. Because DL depends on randomized input data, prior work stated that partitioning impacts DL accuracy. Their solutions focused mainly on training I/O performance on a high-speed network but did not cover the data stage-in pro…
Algorithms for Image Reconstruction
2010
Three-dimensional (3D) imaging is becoming one of the most important applications of radioactive materials in medicine. It offers good spatial resolution, a 3D insight into the human body, and a high sensitivity in the picomolar range because markers for biological processes can be detected well when labeled with radioactive materials. In addition, the technical equipment has undergone many technological achievements. This is true for single-photon emission computed tomography (SPECT), positron emission tomography (PET), and X-ray computed tomography (CT), which is often used in connection with the nuclear medical imaging systems, as also described in chapter 5 about sources in nuclear medi…