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See detailLes bâtiments de l’abbaye du Val-Dieu
Eeckhout, Jérôme ULg

in Le Val-Dieu. Une abbaye, un ordre, une histoire (1998)

Detailed reference viewed: 13 (2 ULg)
See detailLe bâton de christianisation en pays mosan
George, Philippe ULg

in Retour aux sources. Textes, études et documents d’Histoire médiévale offerts à M. PARISSE, Paris, 2004 (2004)

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See detailBâtons percés paléolithiques: décor figuratif, schématique et géométrique
Noiret, Pierre ULg

in Bulletin de l'Association scientifique liégeoise pour la Recherche archéologique (1992), XX

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See detailBaudelaire, analyse textuelle : "Les Hiboux"
Tilkin, Françoise ULg; Mathonet, Anne

in Espace pour un humanisme européen (1998)

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See detailBaudelaire, la photographie, la modernité : discordances paradoxales
Mélon, Marc-Emmanuel ULg

in Streitberger, Alexander (Ed.) Photographie moderne / Modernité photographique (2009)

A rereading of the Baudelaire's famous diatribes against photography in the "Salon de 1859" tries to understand the oversight of the historical part of photography in the baudelairean conception of ... [more ▼]

A rereading of the Baudelaire's famous diatribes against photography in the "Salon de 1859" tries to understand the oversight of the historical part of photography in the baudelairean conception of modernity. [less ▲]

Detailed reference viewed: 370 (6 ULg)
See detail"Bauforschnung" et dendrochronologie
Hoffsummer, Patrick ULg

in de Jonge, Krista; Van Baelen, Koen (Eds.) Preparatory Architectural Investigation in the Restoration of Historical Buildings (2003)

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See detailBauforschung et dendrochronologie
Hoffsummer, Patrick ULg

in De Jonge, Krista; Van Baelen, Koen (Eds.) Preparatory Architectural Investigation in the Restauration of Historical Buildings (2003)

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See detailBauhaus Dream House - Modernity and Globalization
Prina, Daniela ULg

in Journal of Design History (2012), 25(2), 229-231

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See detailBauhinia L. in the Philippine Islands: aspects of diversity and vegetation units
Ruelle, S.; Malaisse, François ULg

in Geo-Eco-Trop (2000), 23(1-4), 49-62

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See detailBaulicher Brandschutz
Schneider, Ulrich; Franssen, Jean-Marc ULg; Lebeda, Christian

Book published by Bauwerk Verlag, GmbH - 2nd edition (2008)

This book contains: fire safety concepts as a base for fire safety of building constructions; fire safety requirements ; etc

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See detailBauschinger effect in thin metallic films by Fem simulations
marandi, kianoosh; vayrette, renaud; Pardoen, Thomas et al

in XII International Conference on Computational Plasticity. Fundamentals and Application COMPLAS XII , Barcelone 3-5 septembre 2013 (2013, September)

Unpassivated free-standing gold and aluminium thin films, subjected to tensile tests show Bauschinger effect (BE) during unloading [1,2]. The focus of this work is to investigate the effect of ... [more ▼]

Unpassivated free-standing gold and aluminium thin films, subjected to tensile tests show Bauschinger effect (BE) during unloading [1,2]. The focus of this work is to investigate the effect of microsstructural heterogeneity such as grain sizes on the BE and the macroscopic deformation behavior in thin metallic films. The finite element code LAGAMINE is used to model the response of films involving sets of grains with different strenghts. The numerical results are compared with experimental results from tensile tests on aluminium thin films from the work of Rajagolapan, et al. [2] [less ▲]

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See detailBayes Adaptive Reinforcement Learning versus Off-line Prior-based Policy Search: an Empirical Comparison
Castronovo, Michaël ULg; Ernst, Damien ULg; Fonteneau, Raphaël ULg

in Proceedings of the 23rd annual machine learning conference of Belgium and the Netherlands (BENELEARN 2014) (2014, June)

This paper addresses the problem of decision making in unknown finite Markov decision processes (MDPs). The uncertainty about the MDPs is modeled using a prior distribution over a set of candidate MDPs ... [more ▼]

This paper addresses the problem of decision making in unknown finite Markov decision processes (MDPs). The uncertainty about the MDPs is modeled using a prior distribution over a set of candidate MDPs. The performance criterion is the expected sum of discounted rewards collected over an infinite length trajectory. Time constraints are defined as follows: (i) an off-line phase with a given time budget can be used to exploit the prior distribution and (ii) at every time step of the on-line phase, decisions have to be computed within a given time budget. In this setting, we compare two decision-making strategies: OPPS, a recently proposed meta-learning scheme which mainly exploits the off-line phase to perform policy search and BAMCP, a state-of-the-art model-based Bayesian reinforcement learning algorithm, which mainly exploits the on-line time budget. We empirically compare these approaches in a real Bayesian setting by computing their performances over a large set of problems. To the best of our knowledge, it is the first time that this is done in the reinforcement learning literature. Several settings are considered by varying the prior distribution and the distribution from which test problems are drawn. The main finding of these experiments is that there may be a significant benefit of having an off-line prior-based optimization phase in the case of informative and accurate priors, especially when on-line time constraints are tight. [less ▲]

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See detailA Bayesian Approach for Modeling Origin-Destination Matrices
Perrakis, Konstantinos; Karlis, Dimitris; Cools, Mario ULg et al

in Proceedings of the 90th Annual Meeting of the Transportation Research Board (DVD-ROM) (2011)

The majority of Origin Destination (OD) matrix estimation methods focus on situations where weak or partial information, derived from sample travel surveys, is available. Information derived from travel ... [more ▼]

The majority of Origin Destination (OD) matrix estimation methods focus on situations where weak or partial information, derived from sample travel surveys, is available. Information derived from travel census studies, in contrast, covers the entire population of a specific study area of interest. In such cases where reliable historical data exist, statistical methodology may serve as a flexible alternative to traditional travel demand models by incorporating estimation of trip-generation, trip-attraction and trip-distribution in one model. In this research, a statistical Bayesian approach on OD matrix estimation is presented, where modeling of OD flows, derived from census data, is related only to a set of general explanatory variables. The assumptions of a Poisson model and of a Negative-Binomial model are investigated on a realistic application area concerning the region of Flanders on the level of municipalities. Problems related to the absence of closed-form expressions are bypassed with the use of a Markov Chain Monte Carlo algorithm, known as the Metropolis-Hastings algorithm. Additionally, a strategy is proposed in order to obtain predictions from the hierarchical, Poisson-Gamma structure of the Negative-Binomial model conditional on the posterior expectations of the mixing parameters. In general, Bayesian methodology reduces the overall uncertainty of the estimates by delivering posterior distributions for the parameters of scientific interest as well as predictive distributions for future OD flows. Predictive goodness-of-fit tests suggest a good fit to the data and overall results indicate that the approach is applicable on large networks, with relatively low computational and explanatory data-gathering costs. [less ▲]

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See detailA Bayesian approach for modeling origin–destination matrices
Perrakis, Konstantinos; Karlis, Dimitris; Cools, Mario ULg et al

in Transportation Research. Part A : Policy & Practice (2012), 46(1), 200212

The majority of origin destination (OD) matrix estimation methods focus on situations where weak or partial information, derived from sample travel surveys, is available. Information derived from travel ... [more ▼]

The majority of origin destination (OD) matrix estimation methods focus on situations where weak or partial information, derived from sample travel surveys, is available. Information derived from travel census studies, in contrast, covers the entire population of a specific study area of interest. In such cases where reliable historical data exist, statistical methodology may serve as a flexible alternative to traditional travel demand models by incorporating estimation of trip-generation, trip-attraction and trip-distribution in one model. In this research, a statistical Bayesian approach on OD matrix estimation is presented, where modeling of OD flows derived from census data, is related only to a set of general explanatory variables. A Poisson and a negative binomial model are formulated in detail, while emphasis is placed on the hierarchical Poisson-gamma structure of the latter. Problems related to the absence of closed-form expressions are bypassed with the use of a Markov Chain Monte Carlo method known as the Metropolis–Hastings algorithm. The methodology is tested on a realistic application area concerning the Belgian region of Flanders on the level of municipalities. Model comparison indicates that negative binomial likelihood is a more suitable distributional assumption than Poisson likelihood, due to the great degree of overdispersion present in OD flows. Finally, several predictive goodness-of-fit tests on the negative binomial model suggest a good overall fit to the data. In general, Bayesian methodology reduces the overall uncertainty of the estimates by delivering posterior distributions for the parameters of scientific interest as well as predictive distributions for future OD flows. [less ▲]

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See detailBayesian approach to integrate molecular data into genetic evaluations
Gengler, Nicolas ULg; Verkenne, Catherine

in Interbull Bulletin (2007), 37

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See detailBayesian data fusion applied to water table spatial mapping
Fasbender, D.; Peeters, Luk; Bogaert, P. et al

in Water Resources Research (2008), 44

Water table elevations are usually sampled in space using piezometric measurements that are unfortunately expensive to obtain and are thus scarce over space. Most of the time, piezometric data are ... [more ▼]

Water table elevations are usually sampled in space using piezometric measurements that are unfortunately expensive to obtain and are thus scarce over space. Most of the time, piezometric data are sparsely distributed over large areas, thus providing limited direct information about the level of the corresponding water table. As a consequence, there is a real need for approaches that are able at the same time to (1) provide spatial predictions at unsampled locations and (2) enable the user to account for all potentially available secondary information sources that are in some way related to water table elevations. In this paper, a recently developed Bayesian data fusion (BDF) framework is applied to the problem of water table spatial mapping. After a brief presentation of the underlying theory, specific assumptions are made and discussed to account for a digital elevation model and for the geometry of a corresponding river network. On the basis of a data set for the Dijle basin in the north part of Belgium, the suggested model is then implemented and results are compared to those of standard techniques such as ordinary kriging and cokriging. Respective accuracies and precisions of these estimators are finally evaluated using a ‘‘leave-one-out’’ cross-validation procedure. Although the BDF methodology was illustrated here for the integration of only two secondary information sources (namely, a digital elevation model and the geometry of a river network), the method can be applied for incorporating an arbitrary number of secondary information sources, thus opening new avenues for the important topic of data integration in a spatial mapping context. [less ▲]

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See detailBayesian Data Fusion for water table interpolation: incorporating a hydrogeological conceptual model in kriging
Peeters, Luk; Fasbender, Dominique; Batelaan, Okke et al

in Water Resources Research (2010), 46(8), 08532

The creation of a contour map of the water table in an unconfined aquifer based on head measurements is often the first step in any hydrogeological study. Geostatistical interpolation methods (e.g ... [more ▼]

The creation of a contour map of the water table in an unconfined aquifer based on head measurements is often the first step in any hydrogeological study. Geostatistical interpolation methods (e.g. kriging) may provide exact interpolated groundwater levels at the measurement locations, but often fail to represent the hydrogeological flow system. A physically based, numerical groundwater model with spatially variable parameters and inputs is more adequate in representing a flow system. Due to the difficulty in parameterization and solving the inverse problem however, an often considerable difference between calculated and observed heads will remain. In this study the water table interpolation methodology presented by Fasbender et al. (2008), in which the results of a kriging interpolation are combined with information from a drainage network and a Digital Elevation Model (DEM), using the Bayesian Data Fusion framework (Bogaert and Fasbender, 2007), is extended to incorporate information from a tuned analytic element groundwater model. The resulting interpolation is exact at the measurement locations while the shape of the head contours is in accordance with the conceptual information incorporated in the groundwater flow model. The Bayesian Data Fusion methodology is applied to a regional, unconfined aquifer in Central Belgium. A cross-validation procedure shows that the predictive capability of the interpolation at unmeasured locations benefits from the Bayesian Data Fusion of the three data sources (kriging, DEM and groundwater model), compared to the individual data sources or any combination of two data sources. [less ▲]

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See detailBayesian density estimation from grouped continuous data
Lambert, Philippe ULg; Eilers, Paul H.C.

in Computational Statistics & Data Analysis (2009), 53

Grouped data occur frequently in practice, either because of limited resolution of instruments, or because data have been summarized in relatively wide bins. A combination of the composite link model with ... [more ▼]

Grouped data occur frequently in practice, either because of limited resolution of instruments, or because data have been summarized in relatively wide bins. A combination of the composite link model with roughness penalties is proposed to estimate smooth densities from such data in a Bayesian framework. A simulation study is used to evaluate the performances of the strategy in the estimation of a density, of its quantiles and rst moments. Two illustrations are presented: the rst one involves grouped data of lead concentrations in the blood and the second one the number of deaths due to tuberculosis in The Netherlands in wide age classes. [less ▲]

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See detailBayesian Design Space applied to Pharmaceutical Development
Lebrun, Pierre ULg

Doctoral thesis (2012)

Given the guidelines such as the Q8 document published by the International Conference on Harmonization (ICH), that describe the “Quality by Design” paradigm for the Pharmaceutical Development, the aim of ... [more ▼]

Given the guidelines such as the Q8 document published by the International Conference on Harmonization (ICH), that describe the “Quality by Design” paradigm for the Pharmaceutical Development, the aim of this work is to provide a complete methodology addressing this problematic. As a result, various Design Spaces were obtained for different analytical methods and a manufacturing process. In Q8, Design Space has been defined as the “the multidimensional combination and interaction of input variables (e.g., material attributes) and process parameters that have been demonstrated to provide assurance of quality” for the analytical outputs or processes involved in Pharmaceutical Development. Q8 is thus clearly devoted to optimization strategies and robustness studies. In the beginning of this work, it was noted that existing statistical methodolo- gies in optimization context were limited as the predictive framework is based on mean response predictions. In such situations, the data and model uncertainties are generally completely ignored. This often leads to increase the risks of taking wrong decision or obtaining unreliable manufactured product. The reasons why it happens are also unidentified. The “assurance of quality” is clearly not addressed in this case. To improve the predictive nature of statistical models, the Bayesian statistical framework was used to facilitate the identification of the predictive distribution of new outputs, using numerical simulations or mathematical derivations when possi- ble. By use of the improved models in a risk-based environment, separation analytical methods such as the high performance liquid chromatography were studied. First, optimal solutions of separation of several compounds in mixtures were identified. Second, the robustness of the methods was simultaneously assessed thanks to the risk-based Design Space identification. The usefulness of the methodology was also demonstrated in the optimization of the separation of subsets of relevant compounds, without additional experiments. The high guarantee of quality of the optimized methods allowed easing their use for their very purpose, i.e., the tracing of compounds and their quantification. Transfer of robust methods to high-end equipments was also simplified. In parallel, one sub-objective was the total automation of analytical method de- velopment and validation. Some data treatments including the Independent Com- ponent Analysis and clustering methodologies were found more than promising to provide accurate automated results. Next, the Design Space methodology was applied to a small-scale spray-dryer manufacturing process. It also allowed the expression of guarantees about the quality of the obtained powder. Finally, other predictive models including mixed-effects models were used for the validation of analytical and bio-analytical quantitative methods. [less ▲]

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See detailA Bayesian Design Space for analytical methods based on multivariate models and predictions
Lebrun, Pierre ULg; Boulanger, Bruno ULg; Debrus, Benjamin ULg et al

in Journal of Biopharmaceutical Statistics (2013), 23

The International Conference for Harmonization (ICH) has released regulatory guidelines for Pharmaceutical Development. In the document ICH Q8, The Design Space of a process is presented as the set of ... [more ▼]

The International Conference for Harmonization (ICH) has released regulatory guidelines for Pharmaceutical Development. In the document ICH Q8, The Design Space of a process is presented as the set of factor settings providing satisfactory results. However, ICH Q8 does not propose any practical methodology to define, derive and compute Design Space. In parallel, in the last decades, it has been observed that the diversity and the quality of analytical methods have evolved exponentially allowing substantial gains in selectivity and sensitivity. However, there is still a lack for a rationale towards the development of robust separation methods in a systematic way. Applying ICH Q8 to analytical methods provides a methodology for predicting a region of the space of factors in which results will be reliable. Combining design of experiments and Bayesian standard multivariate regression, an identified form of the predictive distribution of a new response vector has been identified and used, under non-informative as well as informative prior distributions of the parameters. From the responses and their predictive distribution, various critical quality attributes can be easily derived. This Bayesian framework was then extended to the multi-criteria setting to estimate the predictive probability that several critical quality attributes will be jointly achieved in the future use of an analytical method. An example based on a high-performance liquid chromatography (HPLC) method is given. For this example, a constrained sampling scheme was applied to ensure the modeled responses have desirable properties. [less ▲]

Detailed reference viewed: 186 (58 ULg)