Search results for " Methods"
showing 10 items of 4102 documents
A Bayesian unified framework for risk estimation and cluster identification in small area health data analysis.
2020
Many statistical models have been proposed to analyse small area disease data with the aim of describing spatial variation in disease risk. In this paper, we propose a Bayesian hierarchical model that simultaneously allows for risk estimation and cluster identification. Our model formulation assumes that there is an unknown number of risk classes and small areas are assigned to a risk class by means of independent allocation variables. Therefore, areas within each cluster are assumed to share a common risk but they may be geographically separated. The posterior distribution of the parameter representing the number of risk classes is estimated using a novel procedure that combines its prior …
Kernel-Based Framework for Multitemporal and Multisource Remote Sensing Data Classification and Change Detection
2008
The multitemporal classification of remote sensing images is a challenging problem, in which the efficient combination of different sources of information (e.g., temporal, contextual, or multisensor) can improve the results. In this paper, we present a general framework based on kernel methods for the integration of heterogeneous sources of information. Using the theoretical principles in this framework, three main contributions are presented. First, a novel family of kernel-based methods for multitemporal classification of remote sensing images is presented. The second contribution is the development of nonlinear kernel classifiers for the well-known difference and ratioing change detectio…
Selective Harmonic Elimination in a 5-Level Single Phase Converter with FPGA Based Controller
2018
Multilevel converters are becoming popular in high-power applications such as motor drives, renewable energy systems and distribution systems. Among all modulation techniques, selective harmonic elimination methods offer high quality voltage waveforms with operations at low switching frequency, hence, they are especially suitable for high-power applications. In this paper, a new analytical expression for the SHE problem formulated for a five-level converter is introduced, which is able to calculate the exact value of the switching angles. After a mathematical description of the proposed approach, this manuscript reports simulation and experimental results and analysis showing achievable res…
Multiscale Granger causality analysis by à trous wavelet transform
2017
Since interactions in neural systems occur across multiple temporal scales, it is likely that information flow will exhibit a multiscale structure, thus requiring a multiscale generalization of classical temporal precedence causality analysis like Granger's approach. However, the computation of multiscale measures of information dynamics is complicated by theoretical and practical issues such as filtering and undersampling: to overcome these problems, we propose a wavelet-based approach for multiscale Granger causality (GC) analysis, which is characterized by the following properties: (i) only the candidate driver variable is wavelet transformed (ii) the decomposition is performed using the…
Passenger Car Equivalents for Heavy Vehicles at Roundabouts. a Synthesis Review
2019
Passenger Car Equivalents (PCEs in the following) are used to transform a mixed fleet of vehicles into a fleet of equivalent passenger cars and to analyze capacity and level-of-service of roads and intersections. Most roundabouts guidelines propose constant values for PCEs but a single PCE value can result improper under heterogeneous traffic conditions. PCEs should be vary with traffic and road conditions and consequently PCEs applied to undersaturated traffic conditions can overestimate the heavy vehicle effect or be not sensitive to the traffic level or characteristics of heavy vehicles. Compared to other at-grade intersections, the interaction between the operational performances of the…
Genotoxicity investigations on nanomaterials: methods, preparation and characterization of test material, potential artifacts and limitations--many q…
2008
Nanomaterials display novel properties to which most toxicologists have not consciously been exposed before the advent of their practical use. The same properties, small size and particular shape, large surface area and surface activity, which make nanomaterials attractive in many applications, may contribute to their toxicological profile. This review describes what is known about genotoxicity investigations on nanomaterials published in the openly available scientific literature to-date. The most frequently used test was the Comet assay: 19 studies, 14 with positive outcome. The second most frequently used test was the micronucleus test: 14 studies, 12 of them with positive outcome. The A…
Improved Statistically Based Retrievals via Spatial-Spectral Data Compression for IASI Data
2019
In this paper, we analyze the effect of spatial and spectral compression on the performance of statistically based retrieval. Although the quality of the information is not com- pletely preserved during the coding process, experiments reveal that a certain amount of compression may yield a positive impact on the accuracy of retrievals. We unveil two strategies, both with interesting benefits: either to apply a very high compression, which still maintains the same retrieval performance as that obtained for uncompressed data; or to apply a moderate to high compression, which improves the performance. As a second contribution of this paper, we focus on the origins of these benefits. On the one…
Structured Output SVM for Remote Sensing Image Classification
2011
Traditional kernel classifiers assume independence among the classification outputs. As a consequence, each misclassification receives the same weight in the loss function. Moreover, the kernel function only takes into account the similarity between input values and ignores possible relationships between the classes to be predicted. These assumptions are not consistent for most of real-life problems. In the particular case of remote sensing data, this is not a good assumption either. Segmentation of images acquired by airborne or satellite sensors is a very active field of research in which one tries to classify a pixel into a predefined set of classes of interest (e.g. water, grass, trees,…
Quantitative evaluation of muscle synergy models: a single-trial task decoding approach.
2012
Delis, Ioannis | Berret, Bastien | Pozzo, Thierry | Panzeri, Stefano; International audience; ''Muscle synergies, i.e., invariant coordinated activations of groups of muscles, have been proposed as building blocks that the central nervous system (CNS) uses to construct the patterns of muscle activity utilized for executing movements . Several efficient dimensionality reduction algorithms that extract putative synergies from electromyographic (EMG) signals have been developed. Typically, the quality of synergy decompositions is assessed by computing the Variance Accounted For (VAF). Yet, little is known about the extent to which the combination of those synergies en codes task discriminating…
Design of composite measure schemes for comparative severity assessment in animal-based neuroscience research: A case study focussed on rat epilepsy …
2020
PLOS ONE 15(5), e0230141 (2020). doi:10.1371/journal.pone.0230141