Search results for "ALGORITHM"
showing 10 items of 4887 documents
Accurate estimation of retinal vessel width using bagged decision trees and an extended multiresolution Hermite model.
2012
We present an algorithm estimating the width of retinal vessels in fundus camera images. The algorithm uses a novel parametric surface model of the cross-sectional intensities of vessels, and ensembles of bagged decision trees to estimate the local width from the parameters of the best-fit surface. We report comparative tests with REVIEW, currently the public database of reference for retinal width estimation, containing 16 images with 193 annotated vessel segments and 5066 profile points annotated manually by three independent experts. Comparative tests are reported also with our own set of 378 vessel widths selected sparsely in 38 images from the Tayside Scotland diabetic retinopathy scre…
Accélération de la convergence et algorithme proximal
1995
Nous faisons une première étude de la question de savoir s'il est possible d'accélérer des suites issues de l'algorithme proximal ou de la méthode de l'inverse partiel par des méthodes d'extrapolation.
Submicellar and micellar reversed-phase liquid chromatographic modes applied to the separation of beta-blockers.
2009
The behaviour of a reversed-phase liquid chromatographic (RPLC) system (i.e. elution order, resolution and analysis time), used in the analysis of β-blockers with acetonitrile-water mobile phases, changes drastically upon addition of an anionic surfactant (sodium dodecyl sulphate, SDS). Surfactant monomers cover the alkyl-bonded phase in different extent depending on the concentration of both modifiers, in the ranges 1 × 10-3-0.15 M SDS and 5-50% acetonitrile. Meanwhile, the surfactant is dissolved in the mobile phase as free monomers, associated in small clusters or forming micelles. Four characteristic RPLC modes are yielded, with transition regions between them: hydro-organic, micellar, …
Prediction of peak shape in hydro-organic and micellar-organic liquid chromatography as a function of mobile phase composition
2007
A simple model is proposed that relates the parameters describing the peak width with the retention time, which can be easily predicted as a function of mobile phase composition. This allows the further prediction of peak shape with global errors below 5%, using a modified Gaussian model with a parabolic variance. The model is useful in the optimisation of chromatographic resolution to assess an eventual overlapping of close peaks. The dependence of peak shape with mobile phase composition was studied for mobile phases containing acetonitrile in the presence and absence of micellised surfactant (micellar-organic and hydro-organic reversed-phase liquid chromatography, RPLC). In micellar RPLC…
Assisted baseline subtraction in complex chromatograms using the BEADS algorithm.
2017
The data processing step of complex signals in high-performance liquid chromatography may constitute a bottleneck to obtain significant information from chromatograms. Data pre-processing should be preferably done with little (or no) user supervision, for a maximal benefit and highest speed. In this work, a tool for the configuration of a state-of-the-art baseline subtraction algorithm, called BEADS (Baseline Estimation And Denoising using Sparsity) is developed and verified. A quality criterion based on the measurement of the autocorrelation level was designed to select the most suitable working parameters to obtain the best baseline. The use of a log transformation of the signal attenuate…
Wooden panel paintings investigation: An air-coupled ultrasonic imaging approach
2007
In this paper, a method for the study of wooden panel paintings using air-coupled acoustical imaging is presented. In order to evaluate the advantages of the technique, several samples were made to mimic panel paintings along with their typical defects. These specimens were tested by means of both single-sided and through-transmission techniques using planar transducers. Image data were processed by means of a two-dimensional (2-D)-fast Fourier transform-based algorithm to increase the S/N ratio and 2-D representations (C-scans) were generated. The simulated defects were imaged using both configurations. Investigations were undertaken on four antique paintings from a private collection. The…
Active learning strategies for the deduplication of electronic patient data using classification trees.
2012
Graphical abstractDisplay Omitted Highlights? Active learning for medical record linkage is used on a large data set. ? We compare a simple active learning strategy with a more sophisticated variant. ? The active learning method of Sarawagi and Bhamidipaty (2002) 6] is extended. ? We deliver insights into the variations of the results due to random sampling in the active learning strategies. IntroductionSupervised record linkage methods often require a clerical review to gain informative training data. Active learning means to actively prompt the user to label data with special characteristics in order to minimise the review costs. We conducted an empirical evaluation to investigate whether…
Active Learning for Monitoring Network Optimization
2012
Kernel-based active learning strategies were studied for the optimization of environmental monitoring networks. This chapter introduces the basic machine learning algorithms originated in the statistical learning theory of Vapnik (1998). Active learning is closer to an optimization done using sequential Gaussian simulations. The chapter presents the general ideas of statistical learning from data. It derives the basics of kernel-based support vector algorithms. The active learning framework is presented and machine learning extensions for active learning are described in the chapter. Kernel-based active learning strategies are tested on real case studies. The chapter explores the use of a c…
Remote sensing image segmentation by active queries
2012
Active learning deals with developing methods that select examples that may express data characteristics in a compact way. For remote sensing image segmentation, the selected samples are the most informative pixels in the image so that classifiers trained with reduced active datasets become faster and more robust. Strategies for intelligent sampling have been proposed with model-based heuristics aiming at the search of the most informative pixels to optimize model's performance. Unlike standard methods that concentrate on model optimization, here we propose a method inspired in the cluster assumption that holds in most of the remote sensing data. Starting from a complete hierarchical descri…
Is the nonREM–REM sleep cycle reset by forced awakenings from REM sleep?
2002
In selective REM sleep deprivation (SRSD), the occurrence of stage REM is repeatedly interrupted by short awakenings. Typically, the interventions aggregate in clusters resembling the REM episodes in undisturbed sleep. This salient phenomenon can easily be explained if the nonREM–REM sleep process is continued during the periods of forced wakefulness. However, earlier studies have alternatively suggested that awakenings from sleep might rather discontinue and reset the ultradian process. Theoretically, the two explanations predict a different distribution of REM episode duration. We evaluated 117 SRSD treatment nights recorded from 14 depressive inpatients receiving low dosages of Trimipram…