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See detailDécoder les nouveaux instruments de gestion de l’enseignement supérieur
Fallon, Catherine ULg

Scientific conference (2011, December 09)

Les processus de gestion de la qualité sont relativement récents dans l'enseignement universitaire en Belgique francophone. Sous la pression européenne, avec le soutien des responsables des universités ... [more ▼]

Les processus de gestion de la qualité sont relativement récents dans l'enseignement universitaire en Belgique francophone. Sous la pression européenne, avec le soutien des responsables des universités, les autorités ont mis en places des dispositifs d''évaluation tout à fait nouveaux. Après quelques années de rodage, ces instruments semblent se stabiliser, bien qu'ils continuent encore à susciter çà et là des réactions de rejet. Pour mieux comprendre ces dynamiques, c'est par la base qu'il convient de démarrer l'analyse, pour suivre au plus près les instruments d'évaluation, leur mode d'emploi et comprendre leurs effets inattendus au sein des universités, mais pour observer l'émergence de nouveaux modes de coordination entre universités, avec l'administration, ou avec les autres acteurs sociaux. Ce chapitre présente en détail le processus d'évaluation, après un bref rappel de ses origines et du contexte qui a favorisé son émergence. Ensuite, il proposera un analyse transversale de cet instrument d'action publique : en quoi les nouvelles formes de coopération qui se mettent en place sont emblématiques à la fois d'un nouveau rapport entre gouvernants et gouvernés mais aussi entre les universités et la société qui les nourrit tout en lui fiant leurs enfants. [less ▲]

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See detailDécoder les verrous d’apprentissage d’une discipline
Verpoorten, Dominique ULg; Devyver, Julie ULg; Duchâteau, Dominique ULg et al

Conference (2017, February 21)

L’ULg a conduit une expérience pilote avec quelques enseignants. Elle vise à estimer le potentiel didactique et pédagogique d’un travail sur les « verrous d’apprentissage » (traduction délibérément ... [more ▼]

L’ULg a conduit une expérience pilote avec quelques enseignants. Elle vise à estimer le potentiel didactique et pédagogique d’un travail sur les « verrous d’apprentissage » (traduction délibérément adaptée de « bottleneck ») pour lutter contre l’échec, ou plutôt pour relever le défi de l’intégration intellectuelle du plus grand nombre. [less ▲]

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See detailDecoding Directed Brain Activity in fMRI using Support Vector Machines and Gaussian Processes
Schrouff, Jessica ULg; Kussé, Caroline ULg; Wehenkel, Louis ULg et al

Poster (2011, June 26)

Predicting a particular cognitive state from a specific pattern of fMRI voxel values is still a methodological challenge. Decoding brain activity is usually performed in highly controlled experimental ... [more ▼]

Predicting a particular cognitive state from a specific pattern of fMRI voxel values is still a methodological challenge. Decoding brain activity is usually performed in highly controlled experimental paradigms characterized by a series of distinct states induced by a temporally constrained experimental design. In more realistic conditions, the number, sequence and duration of mental states are unpredictably generated by the individual, resulting in complex and imbalanced fMRI data sets. This study tests the classification of brain activity, acquired on 16 volunteers using fMRI, during mental imagery, a condition in which the number and duration of mental events were not externally imposed but self-generated. To deal with these issues, two classification techniques were considered (Support Vector Machines, SVM, and Gaussian Processes, GP), as well as different feature extraction methods (General Linear Model, GLM and SVM). These techniques were combined in order to identify the procedures leading to the highest accuracy measures. Our results showed that 12 data sets out of 16 could be significantly modeled by either SVM or GP. Model accuracies tended to be related to the degree of imbalance between classes and to task performance of the volunteers. We also conclude that the GP technique tends to be more robust than SVM to model unbalanced data sets. [less ▲]

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See detailDecoding implicit information from the soil map of Belgium and implications for spatial modelling and soil classification
Dondeyne, Stefaan; Legrain, Xavier ULg; Colinet, Gilles ULg et al

Conference (2014, April 29)

A systematic soil survey of Belgium was conducted from 1948 to 1991. Field surveys were done at the detailed scale of 1:5000 with the final maps published at a 1:20,000 scale. Soil surveyors were ... [more ▼]

A systematic soil survey of Belgium was conducted from 1948 to 1991. Field surveys were done at the detailed scale of 1:5000 with the final maps published at a 1:20,000 scale. Soil surveyors were classifying soils in the field according to physical and morphogenetic characteristics such as texture, drainage class and profile development. Mapping units are defined as a combination of these characteristics but to which modifiers can be added such as parent material, stoniness or depth to substrata. Interpretation of the map towards predicting soil properties seems straight forward. Consequently, since the soil map has been digitized, it has been used for e.g. hydrological modelling or for estimating soil organic carbon content at sub-national and national level. Besides the explicit information provided by the legend, a wealth of implicit information is embedded in the map. Based on three cases, we illustrate that by decoding this information, properties pertaining to soil drainage or soil organic carbon content can be assessed more accurately. First, the presence/absence of fragipans affects the soil hydraulic conductivity. Although a dedicated symbol exits for fragipans (suffix “...m”), it is only used explicitly in areas where fragipans are not all that common. In the Belgian Ardennes, where fragipans are common, their occurrence is implicitly implied for various soil types mentioned in explanatory booklets. Second, whenever seasonal or permanent perched water tables were observed, these were indicated by drainage class “.h.” or “.i.”, respectively. Stagnic properties have been under reported as typical stagnic mottling – i.e. when the surface of soil peds are lighter and/or paler than the more reddish interior – were not distinguished from mottling due to groundwater gley. Still, by combining information on topography and the occurrence of substratum layers, stagnic properties can be inferred. Thirdly, soils with deep anthropogenic enriched organic matter (Anthrosols) are distinguished for their specific profile development (code “..m”). Obviously, when assessing soil organic carbon content these soil types need particular consideration. Soils in the Campine region with anthropogenic layers only 30 to 40 cm thick, not being Anthrosols, got a specific suffix code (“. . . 3”). Still, as these soils may have a buried Ah horizon of up to 20 cm, their soil organic carbon content can be comparable to those of Anthrosols. The buried Ah horizon is however not explicitly mapped; its presence needs to be inferred from other environmental information. In conclusion, conventional soil maps convey more information than what transpires from just the explicit legend’s semantics. Although a challenge, decoding the implicit information should be particularly useful for spatial modeling. The cases also point to the importance of classifying soil characteristics explicitly, wherever possible, and in particularly when soil maps are integrated into geographical information systems. [less ▲]

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See detailDecoding intracranial EEG data with multiple kernel learning method
Schrouff, Jessica ULg; Mourao-Miranda, Janaina; Phillips, Christophe ULg et al

in Journal of Neuroscience Methods (2016), 261

Machine learning models have been successfully applied to neuroimaging data to make predictions about behavioral and cognitive states of interest. While these multivariate methods have greatly advanced ... [more ▼]

Machine learning models have been successfully applied to neuroimaging data to make predictions about behavioral and cognitive states of interest. While these multivariate methods have greatly advanced the field of neuroimaging, their application to electrophysiological data has been less common especially in the analysis of human intracranial electroencephalography (iEEG, also known as electrocorticography or ECoG) data, which contains a rich spectrum of signals recorded from a relatively high number of recording sites. In the present work, we introduce a novel approach to determine the contribution of different bandwidths of EEG signal in different recording sites across different experimental conditions using the Multiple Kernel Learning (MKL) method. To validate and compare the usefulness of our approach, we applied this method to an ECoG dataset that was previously analysed and published with univariate methods. Our findings proved the usefulness of the MKL method in detecting changes in the power of various frequency bands during a given task and selecting automatically the most contributory signal in the most contributory site(s) of recording. With a single computation, the contribution of each frequency band in each recording site in the estimated multivariate model can be highlighted, which then allows formulation of hypotheses that can be tested a posteriori with univariate methods if needed. [less ▲]

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See detailDecoding memory processing from electro-corticography in human posteromedial cortex
Schrouff, Jessica ULg; Foster, Brett L.; Rangarajan, Vinitha et al

in International Workshop on Pattern Recognition in Neuroimaging (2014, June)

Recently machine learning models have been applied to neuroimaging data, which allow predictions about a variable of interest based on the pattern of activation or anatomy over a set of voxels. These ... [more ▼]

Recently machine learning models have been applied to neuroimaging data, which allow predictions about a variable of interest based on the pattern of activation or anatomy over a set of voxels. These pattern recognition based methods present clear benefits over classical (univariate) techniques, by providing predictions for unseen data, as well as the weights of each feature in the model. Machine learning methods have been applied to a range of data, from MRI to EEG. However, these multivariate techniques have scarcely been applied to electrocorticography (ECoG) data to investigate cognitive neuroscience questions. In this work, we used previously published ECoG data from 8 subjects to show that machine learning techniques can complement univariate techniques and be more sensitive to certain effects. [less ▲]

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See detailDecoding neural correlates of verbal working memory by attention-based visual working memory.
Majerus, Steve ULg; Cowan, N.; Péters, N. et al

Scientific conference (2014)

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See detailDecoding of the light changes in eclipsing Wolf-Rayet binaries. I. A non-classical approach to the solution of light curves
Perrier, C.; Breysacher, J.; Rauw, Grégor ULg

in Astronomy and Astrophysics (2009), 503

Aims. We present a technique to determine the orbital and physical parameters of eclipsing eccentric Wolf-Rayet + O-star binaries, where one eclipse is produced by the absorption of the O-star light by ... [more ▼]

Aims. We present a technique to determine the orbital and physical parameters of eclipsing eccentric Wolf-Rayet + O-star binaries, where one eclipse is produced by the absorption of the O-star light by the stellar wind of the W-R star. Methods: Our method is based on the use of the empirical moments of the light curve that are integral transforms evaluated from the observed light curves. The optical depth along the line of sight and the limb darkening of the W-R star are modelled by simple mathematical functions, and we derive analytical expressions for the moments of the light curve as a function of the orbital parameters and the key parameters of the transparency and limb-darkening functions. These analytical expressions are then inverted in order to derive the values of the orbital inclination, the stellar radii, the fractional luminosities, and the parameters of the wind transparency and limb-darkening laws. Results: The method is applied to the SMC W-R eclipsing binary HD 5980, a remarkable object that underwent an LBV-like event in August 1994. The analysis refers to the pre-outburst observational data. A synthetic light curve based on the elements derived for the system allows a quality assessment of the results obtained. [less ▲]

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See detailDecoding Semi-Constrained Brain Activity from fMRI Using Support Vector Machines and Gaussian Processes
Schrouff, Jessica ULg; Kussé, Caroline ULg; Wehenkel, Louis ULg et al

in PLoS ONE (2012), 7(4),

Predicting a particular cognitive state from a specific pattern of fMRI voxel values is still a methodological challenge. Decoding brain activity is usually performed in highly controlled experimental ... [more ▼]

Predicting a particular cognitive state from a specific pattern of fMRI voxel values is still a methodological challenge. Decoding brain activity is usually performed in highly controlled experimental paradigms characterized by a series of distinct states induced by a temporally constrained experimental design. In more realistic conditions, the number, sequence and duration of mental states are unpredictably generated by the individual, resulting in complex and imbalanced fMRI data sets. This study tests the classification of brain activity, acquired on 16 volunteers using fMRI, during mental imagery, a condition in which the number and duration of mental events were not externally imposed but self-generated. To deal with these issues, two classification techniques were considered (Support Vector Machines, SVM, and Gaussian Processes, GP), as well as different feature extraction methods (General Linear Model, GLM and SVM). These techniques were combined in order to identify the procedures leading to the highest accuracy measures. Our results showed that 12 data sets out of 16 could be significantly modeled by either SVM or GP. Model accuracies tended to be related to the degree of imbalance between classes and to task performance of the volunteers. We also conclude that the GP technique tends to be more robust than SVM to model unbalanced data sets. [less ▲]

Detailed reference viewed: 90 (23 ULg)
See detailDecoding semi-constrained brain activity from fMRI using SVM and GP
Schrouff, Jessica ULg; Kussé, Caroline ULg; Wehenkel, Louis ULg et al

Scientific conference (2011, November 22)

Predicting a particular cognitive state from a specific pattern of fMRI voxel values is still a methodological challenge. Decoding brain activity is usually performed in highly controlled experimental ... [more ▼]

Predicting a particular cognitive state from a specific pattern of fMRI voxel values is still a methodological challenge. Decoding brain activity is usually performed in highly controlled experimental paradigms characterized by a series of distinct states induced by a temporally constrained experimental design. In more realistic conditions, the number, sequence and duration of mental states are unpredictably generated by the individual, resulting in complex and imbalanced fMRI data sets. This study tests the classification of brain activity, acquired on 16 volunteers using fMRI, during mental imagery, a condition in which the number and duration of mental events were not externally imposed but self-generated. To deal with these issues, two classification techniques were considered (Support Vector Machines, SVM, and Gaussian Processes, GP), as well as different feature extraction methods (General Linear Model, GLM and SVM). These techniques were combined in order to identify the procedures leading to the highest accuracy measures. Our results showed that 12 data sets out of 16 could be significantly modeled by either SVM or GP. Model accuracies tended to be related to the degree of imbalance between classes and to task performance of the volunteers. We also conclude that the GP technique tends to be more robust than SVM to model unbalanced data sets. [less ▲]

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See detailDecoding spontaneous brain activity from fMRI using Gaussian Processes: tracking brain reactivation
Schrouff, Jessica ULg; Kussé, Caroline ULg; Wehenkel, Louis ULg et al

in 2012 Second International Workshop on Pattern Recognition in NeuroImaging (PRNI 2012): proceedings (2012, July 03)

While Multi-Variate Pattern Analysis techniques based on machine learning have now been regularly applied to neuroimaging data, decoding brain activity is usually performed in highly controlled ... [more ▼]

While Multi-Variate Pattern Analysis techniques based on machine learning have now been regularly applied to neuroimaging data, decoding brain activity is usually performed in highly controlled experimental paradigms. In more realistic conditions, the number, sequence and duration of mental states are unpredictably generated by the individual, resulting in complex and imbalanced fMRI data sets. Moreover, in the case of spontaneous brain activity, the mental states can not be linked to any external or internal stimulation, which makes it a highly difficult condition to decode. This study tests the classification of brain activity, acquired on 14 volunteers using fMRI, during mental imagery, a condition in which the number and duration of mental events were not externally imposed but self-generated. Application of the obtained model on rest sessions allowed classifying spontaneous brain activity linked to the task which, overall, correlated with their behavioural performance to the task. [less ▲]

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See detailDecoding the disciplines – A pilot study at the University of Liège (Belgium)
Verpoorten, Dominique ULg; Devyver, Julie ULg; Duchâteau, Dominique ULg et al

in Andersson, Roy (Ed.) Proceedings of the 2nd EuroSoTL Conference (2017, June)

This paper reports on a first attempt to apply the two first stages of the “Decoding the disciplines” framework (Pace, 2017) at the University of Liège (Belgium). In this context, 7 professors volunteered ... [more ▼]

This paper reports on a first attempt to apply the two first stages of the “Decoding the disciplines” framework (Pace, 2017) at the University of Liège (Belgium). In this context, 7 professors volunteered to reflect, through a structured process, upon “bottlenecks” in their courses, with the help of IFRES’ (Institute for Training and Research in Higher Education) pedagogical advisers. This pilot delivered contrasted observations: while participants granted value to their exposure to this approach, especially in terms of enhanced awareness of possible discrepancies between what experts and newcomers in the field might consider as obvious, none of them activated the possibility offered to tackle the identified bottlenecks, according to the systematic approach (stages 3-7) suggested by the framework. The paper presents the pedagogical setting, analyses the interviews of participants and the outcomes of the project, outlines explanations for its results, and shares some lessons learnt. [less ▲]

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See detailDecoding the folding of Burkholderia glumae lipase: folding intermediates en route to kinetic stability
Pauwels, Kris; Sanchez del Pino, Manuel M.; Feller, Georges ULg et al

in PLoS ONE (2012), 7(5), 36999

Detailed reference viewed: 30 (4 ULg)
See detailDecoherence of an Entangled Atomic Pair
Agarwal, G. S.; Bastin, Thierry ULg; von Zanthier, J.

Conference (2006)

Detailed reference viewed: 9 (1 ULg)
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See detailDecoherence, entanglement and irreversibility in quantum dynamical systems with few degrees of freedom
Jacquod, Ph; Petitjean, Cyril ULg

in Advances in Physics (2009), 58(2), 67-196

In this review we summarize and amplify recent investigations of coupled quantum dynamical systems with few degrees of freedom in the short-wavelength, semiclassical limit. Focusing on the correspondence ... [more ▼]

In this review we summarize and amplify recent investigations of coupled quantum dynamical systems with few degrees of freedom in the short-wavelength, semiclassical limit. Focusing on the correspondence between quantum and classical physics, we mathematically formulate and attempt to answer three fundamental questions. (i) How can one drive a small dynamical quantum system to behave classically? (ii) What determines the rate at which two single-particle quantum-mechanical subsystems become entangled when they interact? (iii) How does irreversibility occur in quantum systems with few degrees of freedom? These three questions are posed in the context of the quantum-classical correspondence for dynamical systems with few degrees of freedom, and we accordingly rely on two short-wavelength approximations to quantum mechanics to answer them: the trajectory-based semiclassical approach on the one hand, and random matrix theory on the other hand. We construct novel investigative procedures towards decoherence and the emergence of classicality out of quantumness in dynamical systems coupled to external degrees of freedom. In particular, we show how dynamical properties of chaotic classical systems, such as local exponential instability in phase space, also affects their quantum counterparts. For instance, it is often the case that the fidelity with which a quantum state is reconstructed after an imperfect time-reversal operation decays with the Lyapunov exponent of the corresponding classical dynamics. For related reasons, but perhaps more surprisingly, the rate at which two interacting quantum subsystems become entangled can also be governed by the subsystem's Lyapunov exponents. Our method allows us to differentiate quantum coherent effects (those related to phase interferences) from classical ones (those related to the necessarily extended envelope of quantal wavefunctions) at each stage in our investigations. This makes it clear that all occurrences of Lyapunov exponents we witness have a classical origin, although they require rather strong decoherence effects to be observed. We extensively rely on numerical experiments to illustrate our findings and briefly comment on possible extensions to more complex problems involving environments with many interacting dynamical systems, going beyond the uncoupled harmonic oscillators model of Caldeira and Leggett. [less ▲]

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See detailDecoherence-enhanced measurements
Braun, Daniel; Martin, John ULg

Conference (2009, May)

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See detailDecommissioned dates: chemical composition and fermentation substrate for the production of extracellular catalase by an Aspergillus phoenicis mutant
Kacem-Chaouche, N.; Dehimat, L.; Meraihi, Z. et al

in Agriculture and Biology Journal of North America (2013)

The recovery of dates downgraded as a fermentation medium for the production of extracellular catalase by Aspergillus phoenicis K30 was studied. Analysis of the chemical composition of pulp and kernel ... [more ▼]

The recovery of dates downgraded as a fermentation medium for the production of extracellular catalase by Aspergillus phoenicis K30 was studied. Analysis of the chemical composition of pulp and kernel flour of dates showed that the pulp had a considerably greater carbohydrate content compared to the kernel (84 vs 2.93% respectively). However, the kernel flour was richer in nitrogen (0.68% vs 0.34), mineral elements (3.63 vs 1.28%) and in essential fatty acids C18: 2 vs C18: 3 than the pulp flour. The soluble extract of the date flour showed that sugars solubilised at 90% consisted of sucrose, fructose and glucose. Therefore, this extract, being an important source of carbon and energy, was used in the current study as a fermentation medium (after supplementation with 20% of corn steep) for the production of extracellular catalase by A. Phoenicis K30. During the course of this fermentation, the biomass was estimated at 18.6 g / L after 72 h of culture, while the maximum concentration of extracellular catalase (47.5 U / ml) was reached at 96 h of fermentation. The mycelium obtained in pellet form is suitable for industrial exploitation of this process. [less ▲]

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See detailDécompensation cardiaque, fonction rénale et anti-inflammatoires non stéroïdiens
Krzesinski, Jean-Marie ULg; Piront, Patricia ULg

in Revue Médicale de Liège (2002), 57(9), 582-586

Thanks to a case report of heart failure in an old people with a cardiovascular history treated by the new coxib-inhibitors, we would like to remember and insist to the risk of renal and cardiac ... [more ▼]

Thanks to a case report of heart failure in an old people with a cardiovascular history treated by the new coxib-inhibitors, we would like to remember and insist to the risk of renal and cardiac complications which appear to be the same as those with the non specific antiinflammatory drugs. Old age, diuretic or converting enzyme inhibitor treatment, heart failure, liver insufficiency, nephrotic syndrome are risk factors for acute renal failure and cardiac failure during such treatment. [less ▲]

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See detailDecomposing efficiency into its managerial and its regulatory components: The case of European railways
Gathon, Henry-Jean ULg; Pestieau, Pierre ULg

in European Journal of Operational Research (1995), 80

Detailed reference viewed: 253 (2 ULg)