Search results for "data set"
showing 10 items of 154 documents
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.
Quantification and Characterization of Pulmonary Emphysema in Multislice-CT
2003
The new technology of the Multislice-CT provides volume data sets with approximately isotropic resolution, which permits a non invasive measurement of diffuse lung diseases like emphysema in the 3D space. The aim of our project is the development of a full automatic 3D CAD (Computer Aided Diagnosis) software tool for detection, quantification and characterization of emphysema in a thoracic CT data set. It should supply independently an analysis of an image data set to support the physician in clinical daily routine. In this paper we describe the developed 3D algorithms for the segmentation of the tracheo-bronchial tree, the lungs and the emphysema regions. We present different emphysema des…
An efficient cluster-based outdoor user positioning using LTE and WLAN signal strengths
2015
In this paper we propose a novel cluster-based RF fingerprinting method for outdoor user-equipment (UE) positioning using both LTE and WLAN signals. It uses a simple cost effective agglomerative hierarchical clustering with Davies-Bouldin criterion to select the optimal cluster number. The positioning method does not require training signature formation prior to UE position estimation phase. It is capable of reducing the search space for clustering operation by using LTE cell-ID searching criteria. This enables the method to estimate UE positioning in short time with less computational expense. To validate the cluster-based positioning real-time field measurements were collected using readi…
SELECTING HERB-RICH FOREST NETWORKS TO PROTECT DIFFERENT MEASURES OF BIODIVERSITY
2001
Data on vascular plants of herb-rich forests in Finland were used to compare the efficiency of reserve selection methods in representing three measures of biodiversity: species richness, phylogenetic diversity, and restricted-range diversity. Comparisons of reserve selection methods were carried out both with and without consideration of the existing reserve system. Our results showed that the success of a reserve network of forests in representing different measures of biodiversity depends on the selection procedure, selection criteria, and data set used. Ad hoc selection was the worst option. A scoring procedure was generally more efficient than maximum random selection. Heuristic methods…
Applications of Bond-Based 3D-Chiral Quadratic Indices in QSAR Studies Related to Central Chirality Codification
2009
The concept of bond-based quadratic indices is generalized to codify chemical structure information for chiral drugs, making use of a trigonometric 3D-chirality correction factor. In order to evaluate the effectiveness of this novel approach in drug design, we have modeled several well-known data sets. In particularly, Cramer's steroid data set has become a benchmark for the assessment of novel QSAR methods. This data set has been used by several researchers using 3D-QSAR approaches. Therefore, it is selected by us for the shake of comparability. In addition, to evaluate the effectiveness of this novel approach in drug design, we model the angiotensin-converting enzyme inhibitory activity o…
Treating missing data in a clinical neuropsychological dataset--data imputation.
2001
Missing data frequently reduce the applicability of clinically collected data in research requiring multivariate statistics. In data imputation, missing values are replaced by predicted values obtained from models based on auxiliary information. Our aim was to complete a clinical child neuropsychological data set containing 5.2% of missing observations. This was to be used in research requiring multivariate statistics. We compared four data imputation methods by artificially deleting some data. A real-donor imputation method which preserved the parameter estimates and which predicted the observed values with acceptable accuracy was used to complete the data set. In addressing the lack of st…
ATLANTIC BIRDS: a data set of bird species from the Brazilian Atlantic Forest
2017
South America holds 30% of the world's avifauna, with the Atlantic Forest representing one of the richest regions of the Neotropics. Here we have compiled a data set on Brazilian Atlantic Forest bird occurrence (150,423) and abundance samples (N = 832 bird species; 33,119 bird individuals) using multiple methods, including qualitative surveys, mist nets, point counts, and line transects). We used four main sources of data: museum collections, on‐line databases, literature sources, and unpublished reports. The data set comprises 4,122 localities and data from 1815 to 2017. Most studies were conducted in the Florestas de Interior (1,510 localities) and Serra do Mar (1,280 localities) biogeogr…
Weighted Least-Squares Likelihood Ratio Test for Branch Testing in Phylogenies Reconstructed from Distance Measures
2005
A variety of analytical methods is available for branch testing in distance-based phylogenies. However, these methods are rarely used, possibly because the estimation of some of their statistics, especially the covariances, is not always feasible. We show that these difficulties can be overcome if some simplifying assumptions are made, namely distance independence. The weighted least-squares likelihood ratio test (WLS-LRT) we propose is easy to perform, using only the distances and some of their associated variances. If no variances are known, the use of the Felsenstein F-test, also based on weighted least squares, is discussed. Using simulated data and a data set of 43 mammalian mitochondr…
Clustering categorical data: A stability analysis framework
2011
Clustering to identify inherent structure is an important first step in data exploration. The k-means algorithm is a popular choice, but K-means is not generally appropriate for categorical data. A specific extension of k-means for categorical data is the k-modes algorithm. Both of these partition clustering methods are sensitive to the initialization of prototypes, which creates the difficulty of selecting the best solution for a given problem. In addition, selecting the number of clusters can be an issue. Further, the k-modes method is especially prone to instability when presented with ‘noisy’ data, since the calculation of the mode lacks the smoothing effect inherent in the calculation …
Urban monitoring using multi-temporal SAR and multi-spectral data
2006
In some key operational domains, the joint use of synthetic aperture radar (SAR) and multi-spectral sensors has shown to be a powerful tool for Earth observation. In this paper, we analyze the potentialities of combining interferometric SAR and multi-spectral data for urban area characterization and monitoring. This study is carried out following a standard multi-source processing chain. First, a pre-processing stage is performed taking into account the underlying physics, geometry, and statistical models for the data from each sensor. Second, two different methodologies, one for supervised and another for unsupervised approaches, are followed to obtain features that optimize the urban rela…