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Peer Reviewed
See detailErreurs de catégorie et erreur de catégoriser
Leclercq, Bruno ULg

Conference (2000, May 06)

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See detailErreurs de classification dans les tables de contingence
Magis, David ULg

Scientific conference (2003, December)

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See detailErreurs de désignations d'Etoiles Ap ou Am
Renson, Pierre ULg

in Bulletin d'Information du Centre de Données Stellaires (1988), 34

A table of erroneous designations which appeared in the literature for Ap and Am stars is given. The number of stars erroneously designated at least once is of the order of 2% of the total number of known ... [more ▼]

A table of erroneous designations which appeared in the literature for Ap and Am stars is given. The number of stars erroneously designated at least once is of the order of 2% of the total number of known or probable Ap and Am stars. [less ▲]

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See detailLes erreurs humaines en anesthésie
De Keyser, Véronique ULg; Nyssen, Anne-Sophie ULg

in Travail Humain (Le) (1993), 56(2-3), 243-266

Human errors in anesthesia - with due respect to the French-speaking tradition, human error is studied in field work, here in anesthesia. The authors specify the social context, compare the process of ... [more ▼]

Human errors in anesthesia - with due respect to the French-speaking tradition, human error is studied in field work, here in anesthesia. The authors specify the social context, compare the process of anesthesia to a continuous process, present a cognitive analyse of the task, emphasizing temporal characteristics and cognitive demands regarding the cognitive aspects of human behavior. Referring to the dictinction made by Hollnagel (1991) between reliability, robustness and adaptiveness of the system (man and machine), they present and analyse some human errors which reveal the importance of variation elements and the dynamic dimension of the environment. Influenced by Time Psychology, they postulate the existence of different systems of temporal reference and of external synchronizers connected to these systems, which would allow an individual to adaptively respond to the demands for synchronization in the face of events and actions whose evolutions cannot be calibrated in clock time. Inadequate systems of temporal reference and the absence of synchronizers can make this adaptation to the evolution and the dynamicity of the environment fail. The prevention integrates different measures (technological, ergonomic, social, organizational, of expertise development, etc.) and relies on collection and in-depth analysis of human error. This paper is dedicated to J. Leplat. [less ▲]

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See detailError analysis of a high-resolution physical model of the Mediterranean Sea
Vandenbulcke, Luc ULg; Barth, Alexander ULg; Alvera Azcarate, Aïda ULg et al

Conference (2007)

We analyze the errors that are inevitably associated to hydrodynamic models, in a realistic case. The error of the GHER model in the Mediterranean Sea has already been studied in e.g. Beckers et al. (2000 ... [more ▼]

We analyze the errors that are inevitably associated to hydrodynamic models, in a realistic case. The error of the GHER model in the Mediterranean Sea has already been studied in e.g. Beckers et al. (2000) by comparing it with other primitive equation models, or in Alvera (2004) by comparing the model with observations and with the climatology, using usual statistical methods and also wavelet decompositions. In this study, we rather study the sensitivity of the model to various variables using an ensemble of models. We chose a relatively high resolution, 1/16°, corresponding to the resolution now used in operational OGCMs covering the Mediterranean, such as the MFS system (http://www.bo.ingv.it/mfs). We explain how we generated an ensemble of model simulations, where various more-or-less well known inputs are allowed to vary according to the uncertainty affecting them. Statistics calculated on this ensemble are, in fact, the response of the non-linear hydrodynamic system to errors on the forcing terms. When those statistics are calculated at a certain timestep, they allow us to provide a spatial analysis of the model error; statistics calculated over the time dimension will show whether errors are intensified by the system, or rather disappear. The model error is interesting as such. However, it can also be used for different purposes. For example, it allows using data assimilation techniques without needing the usual assumptions of reduced-rank Kalman Filters. It also allows studying the sensitivity of coupled model (biological, oil spill, search-and-rescue, …) to physical forcings. [less ▲]

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See detailError analysis of generalized-alpha Lie group time integration methods for constrained mechanical systems
Arnold, Martin; Bruls, Olivier ULg; Cardona, Alberto

in Numerische Mathematik (in press)

Generalized-alpha methods are very popular in structural dynamics. They are methods of Newmark type and combine favourable stability properties with second order convergence for unconstrained second order ... [more ▼]

Generalized-alpha methods are very popular in structural dynamics. They are methods of Newmark type and combine favourable stability properties with second order convergence for unconstrained second order systems in linear spaces. Recently, they were extended to constrained systems in flexible multibody dynamics that have a configuration space with Lie group structure. In the present paper, the convergence of these Lie group methods is analysed by a coupled one-step error recursion for differential and algebraic solution components. It is shown that spurious oscillations in the transient phase result from order reduction that may be avoided by a perturbation of starting values or by index reduction. Numerical tests for a benchmark problem from the literature illustrate the results of the theoretical investigations. [less ▲]

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See detailError assessment of sea surface temperature satellite data relative to in situ data: effect of spatial and temporal coverage
Alvera Azcarate, Aïda ULg; Barth, Alexander ULg; Troupin, Charles ULg et al

Conference (2010, April 30)

A comparison between satellite and in situ sea surface temperature (SST) data in the Western Mediterranean Sea in 1999 is shown. The aim of this study is to better understand the differences between these ... [more ▼]

A comparison between satellite and in situ sea surface temperature (SST) data in the Western Mediterranean Sea in 1999 is shown. The aim of this study is to better understand the differences between these two data sets, in order to compute merged maps of SST using satellite and in situ data. When merging temperature from different platforms, it is crucial to take the expected RMS error of the observations into account and to correct for possible biases. Different in situ data sensors and platforms (CTD, XBT, drifter, etc) are available for the comparison, each with specificities in the nature of the measurement (accuracy and precision of the measures), and with different spatial and temporal distributions. A comparison with satellite data needs to take these factors into account. Statistics about the differences due to the hour of the day, the month of the year, the type of sensor/ platform used and the spatial distribution is therefore realised through a combination of error measures, diagrams and statistical hypothesis testing. The data used are Advanced Very High Resolution Radiometer (AVHRR) SST day-time and night-time satellite data, and in situ temperature data from various databases (World Ocean Database’05, Coriolis, Medar/Medatlas and ICES). [less ▲]

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Peer Reviewed
See detailError convergence of some classical high order curl-conforming finite elements
Geuzaine, Christophe ULg; Dular, Patrick ULg; Meys, B. et al

in Proceedings of the 4th International Workshop on Electric and Magnetic Fields, EMF 1998 (1998)

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See detailAn error decomposition method: Application to mediterranean sst simulations assessment
Ben Bouallegue, Z.; Alvera Azcarate, Aïda ULg; Beckers, Jean-Marie ULg

Conference (2004, September)

Fields composed of daily simulations provided by an OGCM of the Mediterranean Sea are compared to weekly satellite observations. The method used is inspired of the object-oriented verification procedure ... [more ▼]

Fields composed of daily simulations provided by an OGCM of the Mediterranean Sea are compared to weekly satellite observations. The method used is inspired of the object-oriented verification procedure introduced in meteorological forecast assessment by Ebert and al. 2000. The Error Decomposition Method presented here aims to identify error sources. The method is carried out within the framework of the MFSTEP hindcasts. The MFSTEP project is an international scientific collaboration program which aims to create an operational forecasting system for the Mediterranean Sea. The simulations provided at the basin scale are 10 days forecasting fields in a 3-D ocean. The hydrodynamic model primitive equations are combined with the data assimilation scheme SOFA applied every week. The set of data used for the comparison are weekly SST satellite observations and means of seven daily MFSTEP simulations (analyzed fields) for the equivalent weeks. The original simulation is transformed until the total squared difference between the observed and hindcast fields is minimized. Successively, a new combination of seven consecutive daily simulations is produced, the new SST field is displaced horizontally and the bias suppressed. This allows a decomposition of the total error in 4 parts: a temporal shift error, a position error, an intensity error and a pattern error. This last element is the remaining error after simulation field transformation and corresponds to the unexplained error. The method is applied at different restricted areas of the Mediterranean basin. The predominant displacements in time and in space minimizing error are discussed through the physical processes taking places at each location. More over, ratio between the different error components is analysed in term of scale effect: the role of the application domain size is pointed out. Finally, the seasonal impact on the different results is commented. [less ▲]

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See detailError detection: A study in anaesthesia
Nyssen, Anne-Sophie ULg; Blavier, Adelaïde ULg

in Ergonomics (2006), 49(5-6), 517-525

Although error has been shown as the main cause of accidents in complex systems, little attention has been paid to error detection. However, reducing the consequences of error depends largely on error ... [more ▼]

Although error has been shown as the main cause of accidents in complex systems, little attention has been paid to error detection. However, reducing the consequences of error depends largely on error detection. The goal of this paper is to synthesize the existing scientific knowledge on error detection, mostly based on studies conducted in laboratory or self reporting and to further knowledge through the analysis of a corpus of cases collected in a complex system, anaesthesia. By doing this, this paper is better able to describe how this knowledge can be used to improve understanding of error detection modes. An anaesthesia accident reporting system developed and organized at two Belgian University Hospitals was used in order to collect information about the error detection patterns. Results show that detection of errors principally occurred through the standard check (routine monitoring of the environment). Significant relationships were found between the type of error and the error detection mode, and between the type of error and the training level of the anaesthetist who committed the error. [less ▲]

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See detailError distribution estimation in nonparametric regression with right censored selection biased data
Laurent, Géraldine ULg; Heuchenne, Cédric ULg

Conference (2012, October 25)

In this presentation, we study the nonparametric regression model Y = m(X) +sigma(X) * epsilon where the error epsilon, with unknown distribution, is independent of the covariate X, and m(X) = E[Y|X] and ... [more ▼]

In this presentation, we study the nonparametric regression model Y = m(X) +sigma(X) * epsilon where the error epsilon, with unknown distribution, is independent of the covariate X, and m(X) = E[Y|X] and sigma²(X) =Var[Y|X] are unknown smooth functions. The problem is to estimate the cumulative distribution function of the error in a nonparametric way when the couple (X;Y) is subject to generalized bias selection while the positive response Y can be right-censored. We propose a new estimator for the error distribution function. Asymptotic properties of the proposed estimator are established, namely the rate of convergence and the limiting distribution. A bootstrap procedure is developed to solve the critical problem of the smoothing parameter choice. The performance of the proposed estimator is investigated through simulations. Finally, a data set based on the mortality of diabetics is analyzed. [less ▲]

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See detailError distribution estimation in right censored and selection biased location-scale models
Laurent, Géraldine ULg; Heuchenne, Cédric ULg

Poster (2011, June 23)

Suppose the random vector (X;Y) satis es the regression model Y = m(X)+sigma(X)*epsilon where m(X) = E[Y|X] and sigma²(X) = Var[Y|X] are unknown smooth functions and the error epsilon, with unknown ... [more ▼]

Suppose the random vector (X;Y) satis es the regression model Y = m(X)+sigma(X)*epsilon where m(X) = E[Y|X] and sigma²(X) = Var[Y|X] are unknown smooth functions and the error epsilon, with unknown distribution, is independent of the covariate X. The pair (X;Y) is subject to generalized selection biased and the response to right censoring. We construct a new estimator for the cumulative distribution function of the error epsilon, where the estimators of m(.) and sigma²(.) are obtained by extending the conditional estimation methods introduced in de Uña-Alvarez and Iglesias-Perez (2010). The asymptotic properties of the proposed estimator are established. A bootstrap technique is proposed to select the smoothing parameter involved in the procedure. This method is studied via extended simulations and applied to real unemployment data. Reference de UNA-ALVAREZ, J., IGLESIAS-PEREZ, M.C. (2010): Nonparametric estimation of a conditional distribution from length-biased data. Annals of the Institute of Statistical Mathematics, Vol. 62, 323-341. [less ▲]

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See detailError estimates and indicators for adaptive analysis of bulk forming
Dyduch, M.; Cescotto, Serge ULg; Habraken, Anne ULg

in Owen, D. R. J.; Onate, E. (Eds.) Computational plasticity. Fundamentals and Applications (1995)

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See detailError estimation based on a new principle of projection and reconstruction
Remacle, J.-F.; Geuzaine, Christophe ULg; Dular, Patrick ULg et al

in IEEE Transactions on Magnetics (1998), 34(5), 3264--3267

Detailed reference viewed: 30 (1 ULg)
Peer Reviewed
See detailError estimation based on a new principle of projection and reconstruction
Remacle, J.-F.; Geuzaine, Christophe ULg; Dular, Patrick ULg et al

in Proceedings of the 11th COMPUMAG Conference on the Computation of Electromagnetic Fields (1997)

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See detailError rate for imputation from the Illumina BovineSNP50 chip to the Illumina BovineHD chip.
Schrooten, Chris; Dassonneville, Romain; Ducrocq, Vincent et al

in Genetics, Selection, Evolution (2014), 46(1), 10

BACKGROUND: Imputation of genotypes from low-density to higher density chips is a cost-effective method to obtain high-density genotypes for many animals, based on genotypes of only a relatively small ... [more ▼]

BACKGROUND: Imputation of genotypes from low-density to higher density chips is a cost-effective method to obtain high-density genotypes for many animals, based on genotypes of only a relatively small subset of animals (reference population) on the high-density chip. Several factors influence the accuracy of imputation and our objective was to investigate the effects of the size of the reference population used for imputation and of the imputation method used and its parameters. Imputation of genotypes was carried out from 50 000 (moderate-density) to 777 000 (high-density) SNPs (single nucleotide polymorphisms). METHODS: The effect of reference population size was studied in two datasets: one with 548 and one with 1289 Holstein animals, genotyped with the Illumina BovineHD chip (777 k SNPs). A third dataset included the 548 animals genotyped with the 777 k SNP chip and 2200 animals genotyped with the Illumina BovineSNP50 chip. In each dataset, 60 animals were chosen as validation animals, for which all high-density genotypes were masked, except for the Illumina BovineSNP50 markers. Imputation was studied in a subset of six chromosomes, using the imputation software programs Beagle and DAGPHASE. RESULTS: Imputation with DAGPHASE and Beagle resulted in 1.91% and 0.87% allelic imputation error rates in the dataset with 548 high-density genotypes, when scale and shift parameters were 2.0 and 0.1, and 1.0 and 0.0, respectively. When Beagle was used alone, the imputation error rate was 0.67%. If the information obtained by Beagle was subsequently used in DAGPHASE, imputation error rates were slightly higher (0.71%). When 2200 moderate-density genotypes were added and Beagle was used alone, imputation error rates were slightly lower (0.64%). The least imputation errors were obtained with Beagle in the reference set with 1289 high-density genotypes (0.41%). CONCLUSIONS: For imputation of genotypes from the 50 k to the 777 k SNP chip, Beagle gave the lowest allelic imputation error rates. Imputation error rates decreased with increasing size of the reference population. For applications for which computing time is limiting, DAGPHASE using information from Beagle can be considered as an alternative, since it reduces computation time and increases imputation error rates only slightly. [less ▲]

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See detailErrorless learning: A method to help amnesic patients learn new information
Bier, Nathalie; Vanier, Marie; Meulemans, Thierry ULg

in Journal of Cognitive Rehabilitation (2002), 20

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See detailErrorless training as a method in the study of cognitive development
Richelle, Marc ULg

in Activitas Nervosa Superior (1977), 19(4),

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