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See detailPatronage, Devotion and Gender Roles in Burgundian Court Art
L'Estrange, Elizabeth ULg

in Art History (2008), 31(1), 117-122

Review of Pearson's book Envisioning Gender in Burgundian Devotional Art, 1350-1530 and the exhibition and related catalogue, Women of Distinction: Margaret of York and Margaret of Austria, held in ... [more ▼]

Review of Pearson's book Envisioning Gender in Burgundian Devotional Art, 1350-1530 and the exhibition and related catalogue, Women of Distinction: Margaret of York and Margaret of Austria, held in Mechelen in 2005 [less ▲]

Detailed reference viewed: 64 (4 ULg)
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See detailPatrones de evolución morfológica de la región cefálica en damiselas (Perciformes, Pomacentridae) del Pacífico Oriental
Aguilar-Medrano, Rosalia; Frederich, Bruno ULg; De Luna, Efrain et al

Conference (2010, October)

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See detailPatrons, gens d'affaires et banquiers. Hommages à Ginette Kurgan-van Hentenryk
Geerkens Provin, Eric ULg

in Cahiers d'Histoire du Temps Présent = Bijdragen tot de Eigentijdse Geschiedenis (2006), 17

Detailed reference viewed: 50 (5 ULg)
See detailPattern and process in landscape ecology
Bogaert, Jan ULg

Scientific conference (2006)

Detailed reference viewed: 8 (3 ULg)
See detailPattern and process in landscape ecology.
Bogaert, Jan ULg

Scientific conference (2006)

Detailed reference viewed: 3 (2 ULg)
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See detailPattern extraction for time-series classification
Geurts, Pierre ULg

in Proceedings of PKDD 2001, 5th European Conference on Principles of Data Mining and Knowledge Discovery (2001)

In this paper, we propose some new tools to allow machine learning classifiers to cope with time series data. We first argue that many time-series classification problems can be solved by detecting and ... [more ▼]

In this paper, we propose some new tools to allow machine learning classifiers to cope with time series data. We first argue that many time-series classification problems can be solved by detecting and combining local properties or patterns in time series. Then, a technique is proposed to find patterns which are useful for classification. These patterns are combined to build interpretable classification rules. Experiments, carried out on several artificial and real problems, highlight the interest of the approach both in terms of interpretability and accuracy of the induced classifiers. [less ▲]

Detailed reference viewed: 104 (2 ULg)
See detailPattern granulomateux dans les pathologies inflammatoires cutanées
QUATRESOOZ, Pascale ULg

Scientific conference (2011)

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See detailPattern of early eukaryote evolution in Precambrian oceans
Javaux, Emmanuelle ULg

Poster (2010, December)

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See detailPattern of morpho-functional diversifcation of damselfishes (Pomacentridae)
Frederich, Bruno ULg

Conference (2013, December 18)

Coral reef fishes represent one of the most outstandingly diverse assemblages of vertebrates on the planet but our understanding of their mode of diversification remains limited. Currently, some ... [more ▼]

Coral reef fishes represent one of the most outstandingly diverse assemblages of vertebrates on the planet but our understanding of their mode of diversification remains limited. Currently, some biologists are testing various hypotheses about the evolutionary history of coral reef fishes and are exploring the factors driving their diversification. During my post-doctoral research, I explored the pattern of morphological diversification of damselfishes (Pomacentridae, 386 species). I produced a time-calibrated phylogeny based on 8 loci including 208 species and collected eco-morphological data (trophic data, body shape and oral jaws shape) in more than 120 species. Using various phylogenetic comparative methods, I have illusrated that the Pomacentridae observed repeated ecological radiation and morphological convergence during their evolutionary history. I have also highlighted the primary role of a ligament joining the mandible and the hyoid in the evolution and the morpho-functional diversification of pomacentrids. [less ▲]

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See detailPattern Recognition for Neuroimaging
Phillips, Christophe ULg

Scientific conference (2013, April 24)

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See detailPattern Recognition for Neuroimaging Toolbox
Schrouff, Jessica ULg; Rosa, Maria; Rondina, Jane et al

in Suykens, J.A.K.; Argyriou, A.; De Brabanter, K. (Eds.) et al International workshop on advances in Regularization, Optimization, Kernel Methods and Support Vector Machines: theory and applications (ROKS 2013), Book of Abstracts (2013)

In the past years, mass univariate statistical analyses of neuroimaging data have been complemented by the use of multivariate pattern analyses, especially based on machine learning models. While these ... [more ▼]

In the past years, mass univariate statistical analyses of neuroimaging data have been complemented by the use of multivariate pattern analyses, especially based on machine learning models. While these allow an increased sensitivity for the detection of spatially distributed e ffects compared to univariate techniques, they lack an established and accessible software framework. Here we introduce the \Pattern Recognition for Neuroimaging Toolbox" (PRoNTo), an open-source, cross-platform and MATLAB-based software comprising many necessary functionalities for machine learning modelling of neuroimaging data. [less ▲]

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See detailPattern Recognition in NeuroImaging: What can machine learning classifiers bring to the analysis of functional brain imaging?
Schrouff, Jessica ULg

Doctoral thesis (2013)

The study of the brain development and functioning raises many question that are tracked using neuroimaging techniques such as positron emission tomography or (functional) magnetic resonance imaging ... [more ▼]

The study of the brain development and functioning raises many question that are tracked using neuroimaging techniques such as positron emission tomography or (functional) magnetic resonance imaging. During the last decades, various techniques have been developed to analyse neuroimaging data. These techniques brought valuable insight on neuroscientific questions, but encounter limitations which make them unsuitable to tackle more complex problems. More recently, machine learning based models, coming from the field of pattern recognition, have been promisingly applied to neuroimaging data. In this work, the assets and limitations of machine learning based models were investigated and compared to previously developed techniques. To this end, two applications involving challenging datasets were defined and the results from widespread methods were compared to the results obtained using machine learning based modelling. More specifically, the first application addressed a research question: Is it possible to detect and characterize mnemonic traces? The fMRI experiment comprised a learning and a control tasks, both flanked by rest sessions. From previous studies, patterns of brain activity generated during the learning task should be spontaneously repeated during the following rest session, while no difference should be observed between the pre- and post-task rest session in the control condition. Using univariate and multivariate feature selection steps before a Gaussian Processes classification, mnemonic traces could be detected and their spatio-temporal evolution characterized. On the contrary, an analysis of the rest sessions based on the detection of independent networks did not provide any results supporting the theory of memory consolidation. The second application tackled a clinical issue: Can a pattern of brain activation characteristic to idiopathic Parkinson’s disease be detected and localized? The dataset considered to address this question comprised the fMRI images of aged healthy subjects and Parkinsonian patients while they were performing a task of mental imagery of gait at three different paces. The signal comprised in a priori selected regions of interest allowed for the support vector machines classification of healthy and diseased volunteers with an accuracy of 86%. To localize the discriminating pattern, a methodology based on the weight in labelled regions (e.g. from the anatomical automatic labelling or Brodmann atlases) was developed, which enabled the comparison between univariate and multivariate results and showed a nice overlap between them. Furthermore, models could then be compared quantitatively in terms of pattern localization, using a specifically defined measure of distance. This measure could then be used to compare the patterns generated from different folds of a same model, from different feature sets, or from different modelling techniques. The present study concluded that machine learning models can clearly and fruitfully complement other analysis techniques to tackle challenging questions in neuroscience. On the other hand, more work is needed in order to render the methodology fully accessible to the neuroscientific community. [less ▲]

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See detailPattern recognition with a digital holographic microscope working in partially coherent illumination
Dubois, Frank; Minetti, Christophe; Monnom, Olivier et al

in Applied Optics (2002), 41(20), 4108-4119

We describe the implementation of the automatic spatial-frequency-selection filter for recognition of patterns obtained with a digital holographic microscope working with a partially coherent source. The ... [more ▼]

We describe the implementation of the automatic spatial-frequency-selection filter for recognition of patterns obtained with a digital holographic microscope working with a partially coherent source. The microscope provides the complex-optical-amplitude field that allows a refocusing plane-by-plane of the sample under investigation by numerical computation of the optical propagation. By inserting a correlation filter in the propagation equation, the correlation between the filter and the propagated optical field is obtained. In this way, the pattern is located in the direction of the optical axis. Owing to the very weak noise level generated by the partially coherent source, the correlation process is shift invariant. Therefore the samples can be located in the three dimensions. To have a robust recognition process, a generalized version of the automatic spatial-frequency-selection filters has been implemented. The method is experimentally demonstrated in a two-class problem for the recognition of protein crystals. (C) 2002 Optical Society of America. [less ▲]

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See detail'Pattern' comportemental de type A : stress et maladie coronarienne : II. Aspects pratiques
Etienne, Anne-Marie ULg; Fontaine, Ovide ULg

in Revue Médicale de Liège (1994), XLIX(1), 36-48

Detailed reference viewed: 5 (0 ULg)
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See detailPattern-learning and pattern-description : An integrated approach to proficiency and research for students of English
Brems, Lieselotte ULg; Olivier, Nele

in Corpora in the foreign language classroom. Selected papers from the Sixth International Conference on Teaching and Language Corpora (TaLC) (2007)

Detailed reference viewed: 3 (1 ULg)
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See detailPatterns in hydraulic ripples with binary granular mixtures
Caps, Hervé ULg; Vandewalle, Nicolas ULg

in Physica A: Statistical Mechanics and its Applications (2002), 313(3-4), 357-364

An experimental study of a binary granular mixture submitted to a transient shear flow in a cylindrical container is reported. The formation of ripples with a spiral shape is observed. The appearance of ... [more ▼]

An experimental study of a binary granular mixture submitted to a transient shear flow in a cylindrical container is reported. The formation of ripples with a spiral shape is observed. The appearance of phase segregation in those spiral patterns is shown. The relative grain size between sand species is found to be a relevant parameter leading to phase segregation. However, the relative repose angle is an irrelevant parameter. The formation of sedimentary structures is also presented. They result from a ripple climbing process. The "sub-critical" or "super-critical" character of the lamination patterns is shown to depend on the rotation speed of the container. (C) 2002 Elsevier Science B.V. All rights reserved. [less ▲]

Detailed reference viewed: 14 (1 ULg)
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See detailPatterns in national policies for support of low achievers in reading across Europe
Motiejunaite, Akvile; Noorani, Sogol; Monseur, Christian ULg

in British Educational Research Journal (2014)

Detailed reference viewed: 14 (4 ULg)
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See detailPatterns of allozymic variation within Calluna vulgaris populations at seed bank and adult stages
Mahy, Grégory ULg; Vekemans, Xavier; Jacquemart, Anne Laure

in Heredity (1999), 82

Detailed reference viewed: 8 (0 ULg)