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See detail‘… dat dit alles waar is’. Over De nacht der Girondijnen
Spinoy, Erik ULg

in Nieuwzuid (2007), 7(27), 4-15

This article rereads the novella De nacht van de Girondijnen by the Jewish-Dutch writer and historian Jacques Presser. This text is often considered to be a failed work of literature. This article avers ... [more ▼]

This article rereads the novella De nacht van de Girondijnen by the Jewish-Dutch writer and historian Jacques Presser. This text is often considered to be a failed work of literature. This article avers that this so-called failure in fact bears witness to Presser's traumatizing experience of the Shoah. [less ▲]

Detailed reference viewed: 23 (0 ULg)
See detailData adjudication
Adams, R.; Rust, K.; Monseur, Christian ULg

in Adams, R.; Wu, M. (Eds.) PISA 2000 : technical report (2002)

Detailed reference viewed: 10 (1 ULg)
See detailData analysis for linkage studies
Lathrop, M.; Cartwright, P.; Wright, S. et al

in Schook, L. B.; Lewin; McLaren (Eds.) Gene Mapping: strategies, techniques and applications (1991)

Detailed reference viewed: 6 (1 ULg)
See detailData Analysis Manual : sas second edition
Monseur, Christian ULg; OECD

Book published by OECD (2009)

Detailed reference viewed: 4 (1 ULg)
See detailData assimilation as a tool for upscaling
Vandenbulcke, Luc ULg; Barth, Alexander ULg; Ben Bouallegue, Z. et al

Conference (2006, April)

In ocean and atmospheric sciences, grid nesting is a common procedure in order to achieve (very) high resolution model outputs in regions of particular interest, at an acceptable computational cost ... [more ▼]

In ocean and atmospheric sciences, grid nesting is a common procedure in order to achieve (very) high resolution model outputs in regions of particular interest, at an acceptable computational cost. Nesting of grids can be passive (one-way nesting) or active (two-way nesting, with feedback from the high resolution to the low resolution grid). The benefits of active nesting have been shown multiple times in the litterature (see e.g. [1]). The positive effect of the feedback is visible inside the nested grid, but also outside of it, as corrections are advected with the flow. It must be noted however that in many operationnal implementations, only passive nesting is used, usually because active nesting requires too much data exchange between models, which should then wait for each other during their run. Data assimilation techniques are also widespread in oceanic and atmospheric models. They are usually applied in order to merge observations in models, but also e.g. to merge different outputs from ensemble runs of a model, to merge outputs from different models, or to replace downscaling between nested grids (see [3]). In our work, we present an alternative to active nesting (for implementations currently using passive nesting). First, the low-resolution model is run, followed by the local model. Afterwards, the low-resolution model is run once more, assimilating outputs from the local model as pseudo-data. The benefits of this approach over simple passive nesting are shown using a twin experiment. The GHER model (see [2]) is configured with a 0.25 resolution of the Mediterranean Sea, and with a 0.05 resoluion of the North-Western part; a twin experiment is then set. The reference run uses full two-way nesting, another run uses one-way nesting, and in a third run the assimilation procedure described above is implemented.Conclusions from this experiment are that our "upscaling" has positive impacts on the forecasts, provided a fair amount of EOFs is used during (reduced-rank) assimilation cycles. Finally, the set-up of ongoing work to implement our upscaling procedure in a realistic, operationnal system (the MFS system) is presented. [less ▲]

Detailed reference viewed: 28 (0 ULg)
See detailData Assimilation in a Nested Model of the Gulf of Lions
Vandenbulcke, Luc ULg; Barth, Alexander ULg; Ben Bouallegue, Z. et al

Conference (2004)

Detailed reference viewed: 13 (2 ULg)
See detailData assimilation in nested-grid models
Vandenbulcke, Luc ULg; Barth, Alexander ULg; Ben Bouallegue, Z. et al

Conference (2004, May)

Detailed reference viewed: 16 (2 ULg)
See detailData cleaning
Monseur, Christian ULg

in Adams, R.; Wu, M. (Eds.) PISA 2000 : technical report (2002)

Detailed reference viewed: 7 (1 ULg)
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See detailData Clustering for the Identification of the Bifurcation Behaviour in Non-Linear Aeroelastic Systems using a Coupled Harmonic Balance/Genetic Algorithm Approach
Vio, Gareth Arthur; Dimitriadis, Grigorios ULg; Cooper, Jonathan Edward

in Proceedings of the 2008 International Conference on Noise and Vibration Engineering (2008, September)

This paper describes an efficient method for calculating the bifurcation behaviour of an aeroelastic system using a Harmonic Balance expansion coupled with a Genetic Algorithm, combined with a clustering ... [more ▼]

This paper describes an efficient method for calculating the bifurcation behaviour of an aeroelastic system using a Harmonic Balance expansion coupled with a Genetic Algorithm, combined with a clustering algorithm in order to determine all the solutions at every single flight condition. It will be shown how it is possible to obtain all the bifurcation branches in one step. Two clustering algorithms, K-Means and PAM, together with a number of cluster index techniques, such as Davies-Boulding, Calinski-Harabasz are investigated. The method is applied to an aeroelastic galloping problem as this phenomenon presents a number of co-existing limit cycles at a range of airspeeds. [less ▲]

Detailed reference viewed: 34 (1 ULg)
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Peer Reviewed
See detailData driven choice of the classification rule in discriminant analysis applied to isoberlinia stands
Glele Kakaï, R. L.; Palm, Rodolphe ULg

in West African Journal of Biophysics and Biomathematics (2007), 1

A simulation study is performed to evaluate, in discriminant analysis, the relative performance of the linear, quadratic and logistic rules, on 52,800 sample couples, characterized by the distribution and ... [more ▼]

A simulation study is performed to evaluate, in discriminant analysis, the relative performance of the linear, quadratic and logistic rules, on 52,800 sample couples, characterized by the distribution and the overlap of the populations, the number of variables, the samples size and the theoretical heteroscedasticity degree of the populations, defined in the study. For each sample couple, the relative error of the actual error rate of each classification rule is computed as well as the estimated heteroscedasticity degree and the multinormality test's statistic. The results obtained helps to notice that the linear rule can be advised when the multinormality hypothesis is accepted and the logistic rule in the other cases. The quadratic rule gives the lowest performance in most of the considered cases. Anoter method is based on the estimated heteroscedasticity and normality degrees of the considered sample couple. [less ▲]

Detailed reference viewed: 11 (0 ULg)
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Peer Reviewed
See detailData Entry Errors and Design for Model-Based Tight Glycemic Control in Critical Care
Ward, Logan; Steel, James; Le Compte, Aaron et al

in Journal of Diabetes Science and Technology (2012)

Detailed reference viewed: 11 (8 ULg)
See detailData Fauna-Flora 1.0. Guide d’utilisation.
Barbier, Yvan; Rasmont, Pierre; Dufrêne, Marc ULg et al

Software (2000)

Detailed reference viewed: 5 (1 ULg)
Peer Reviewed
See detailData Fusion by Belief Propagation for Multi-Camera Tracking
Du, Wei ULg; Piater, Justus ULg

in The 9th International Conference on Information Fusion (2006)

Detailed reference viewed: 14 (0 ULg)
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Peer Reviewed
See detailA Data Imputation Method with Support Vector Machines for Activity-Based Transportation Models
Yang, Banghua; Janssens, Davy; Ruan, Da et al

in Wang, Y.; Li, T. (Eds.) Foundations of Intelligent Systems: Proceedings of the Sixth International Conference on Intelligent Systems and Knowledge Engineering, Shanghai, China, Dec 2011 (ISKE 2011) (2011)

In this paper, a data imputation method with a Support Vector Machine (SVM) is proposed to solve the issue of missing data in activity-based diaries. Here two SVM models are established to predict the ... [more ▼]

In this paper, a data imputation method with a Support Vector Machine (SVM) is proposed to solve the issue of missing data in activity-based diaries. Here two SVM models are established to predict the missing elements of ‘number of cars’ and ‘driver license’. The inputs of the former SVM model include five variables (Household composition, household income, Age oldest household member, Children age class and Number of household members). The inputs of the latter SVM model include three variables (personal age, work status and gender). The SVM models to predict the ‘number of cars’ and ‘driver license’ can achieve accuracies of 69% and 83% respectively. The initial experimental results show that missing elements of observed activity diaries can be accurately inferred by relating different pieces of information. Therefore, the proposed SVM data imputation method serves as an effective data imputation method in the case of missing information. [less ▲]

Detailed reference viewed: 46 (2 ULg)
See detailData in astronomy -- Carlos Jaschek
Manfroid, Jean ULg

in Ciel et Terre (1990), 106

Not Available

Detailed reference viewed: 8 (0 ULg)
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Peer Reviewed
See detailData Interpolating Empirical Orthogonal Functions (DINEOF): a tool for geophysical data analyses
Alvera Azcarate, Aïda ULg; Barth, Alexander ULg; Sirjacobs, Damien ULg et al

in Mediterranean Marine Science (2011), 12(3), 5-11

An overview of the technique called DINEOF (Data Interpolating Empirical Orthog- onal Functions) is presented. DINEOF reconstructs missing information in geophys- ical data sets, such as satellite imagery ... [more ▼]

An overview of the technique called DINEOF (Data Interpolating Empirical Orthog- onal Functions) is presented. DINEOF reconstructs missing information in geophys- ical data sets, such as satellite imagery or time series. A summary of the technique is given, with its main characteristics, recent developments and future research di- rections. DINEOF has been applied to a large variety of oceanographic variables in various domains of different sizes. This technique can be applied to a single variable (monovariate approach), or to several variables together (multivariate approach), with no complexity increase in the application of the technique. Error fields can be computed to establish the accuracy of the reconstruction. Examples are given to illustrate the capabilities of the technique. DINEOF is freely offered to download, and help is provided to users in the form of a wiki and through a discussion email list. [less ▲]

Detailed reference viewed: 183 (26 ULg)