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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)
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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 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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See detailErrors in 2-D modelling using a 0th order turbulence closure for compound channel flows
Linde, F.; Paquier, A.; Proust, S. et al

in International Conference on Fluvial Hydraulics, River Flow 2012 (2012)

When dealing with flood issues, compound channels flows are often encountered in the field. This paper investigates the errors that can be expected when using 2-D modelling for compound channel flows ... [more ▼]

When dealing with flood issues, compound channels flows are often encountered in the field. This paper investigates the errors that can be expected when using 2-D modelling for compound channel flows, comparing the simulations with experiments. Three flow configurations are analyzed: uniform, gradually varied and rapidly varied flows. The last configuration is obtained by setting a transverse embankment on the flood plain. Errors are estimated on the sub-section mean velocity, discharge andwater depth, on the mixing layer width and on the depth-averaged stream-wise velocity and lateral shear stress. Depending on the flow configuration and on the studied parameter, relative errors significantly vary from nearly zero to 50%. The influence of the 0th order turbulence closure on the mean flow and the dimensions of the recirculation zone behind the embankment is also investigated, using either constant eddy viscosity or Elder's model. © 2012 Taylor & Francis Group, London. [less ▲]

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See detailErrors in architectural design process : towards a cognitive model.
Safin, Stéphane ULg; Leclercq, Pierre ULg; Blavier, Adelaïde ULg

in Marjanovic, Dorian; Storga, Mario; Pavkovic, Neven (Eds.) et al Proceedings of the Design 2008 : 10th International Design Conference (2008)

In architectural design process, the human error has a particular status. The later it is detected, the more expensive it is. Moreover, some errors can not be detected given the current state of the ... [more ▼]

In architectural design process, the human error has a particular status. The later it is detected, the more expensive it is. Moreover, some errors can not be detected given the current state of the design process and object definition. In this paper, we propose a model based on cognitive theories about human errors, applied to architectural preliminary design. In this model we classify the consequences of a design decision (direct, indirect, detected and undetected), we describe the steps of decision in architecture in relation to the process of errors detection and we introduce the concept of evolutive context. [less ▲]

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See detailErrors induced by indexing glomerular filtration rate for body surface area: reductio ad absurdum.
Delanaye, Pierre ULg; Mariat, Christophe; Cavalier, Etienne ULg et al

in Nephrology Dialysis Transplantation (2009), 24(12), 3593-6

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See detailERRUISSOL
Degre, Aurore ULg

Learning material (2009)

Detailed reference viewed: 52 (20 ULg)
See detailERRUISSOL and GISER projects : runoff and erosion risks management in Wallonia
Degre, Aurore ULg

Conference (2011, May 19)

Detailed reference viewed: 45 (14 ULg)
See detailERT/Table ronde des industriels européens
Geuens, Geoffrey ULg

in Durand, Pascal (Ed.) Les Nouveaux Mots du Pouvoir. Abécédaire critique (2007)

Detailed reference viewed: 53 (7 ULg)