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See detailContributions of a 3D numerical environment for architectural sketches.
Mayeur, A.; Darses, F.; Leclercq, Pierre ULg

in Lecture Notes in Computer Science (2008)

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See detailContributions of benthic and planktonic primary producers to nitrate and ammonium uptake fluxes in a nutrient-poor shallow coastal area (Corsica, NW Mediterranean)
Lepoint, Gilles ULg; Gobert, Sylvie ULg; Dauby, Patrick ULg et al

in Journal of Experimental Marine Biology and Ecology (2004), 302(1), 107-122

By using the stable isotope N-15, we have measured in situ the uptake of nitrate and ammonium by the seagrass Posidonia oceanica, its leaf epiphyte community, the brown macroalgae Halopteris scoparia and ... [more ▼]

By using the stable isotope N-15, we have measured in situ the uptake of nitrate and ammonium by the seagrass Posidonia oceanica, its leaf epiphyte community, the brown macroalgae Halopteris scoparia and the suspended particulate organic matter (SPOM). In Revellata Bay (Gulf of Calvi, Westem Corsica), which is a very nutrient-poor region, the specific uptake rates (V) (mug N g N 1 h(- 1)) of SPOM measured at ambient concentrations are 10-1000 higher than those of benthic primary producers. Macroalgae have intermediary v, between the seagrass leaf and leaf epiphytes. V are quite variable and the reasons for this variability remain unclear. Despite the difference of specific uptake rates found between benthic and pelagic primary producers, when integrating the uptake fluxes for a water Column of 10 m depth, the contribution of benthic primary producers to N uptake fluxes (g N m(-) (2) h(-) (1)) is significant, corresponding on average to 40% of total uptake flux. This results from the dominance in terms of N biomass of benthic primary producers in this shallow nutrient-poor area. When reported for the entire volume of the Revellata Bay, the contribution of benthic primary producers is reduced to 5 - 10% of total N uptake flux. Although this contribution could appear relatively low, it results in a significant direct transfer of inorganic nitrogen from the water column to the benthic compartment. By this transfer, the benthic plants act as a biological pump incorporating the pelagic N into the benthic compartment for a time longer than the characteristic time of phytoplankton dynamics (month-years vs. day-week). (C) 2003 Elsevier B.V. Alt rights reserved. [less ▲]

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See detailContributions of collaborative e-annotations in project-based teaching
Leclercq, Pierre ULg; Ben Rajeb, Samia ULg

Scientific conference (2012, December)

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See detailContributions of experimental mouse models to the understanding of African trypanosomiasis.
Antoine-Moussiaux, Nicolas ULg; Magez, Stefan; Desmecht, Daniel ULg

in Trends in Parasitology (2008), 24(9), 411-8

African trypanosomiasis is the collective name for a wide variety of trypanosome infections that affect humans and livestock. In recent years, experimental mice infection models have provided new insights ... [more ▼]

African trypanosomiasis is the collective name for a wide variety of trypanosome infections that affect humans and livestock. In recent years, experimental mice infection models have provided new insights into both human and animal trypanosomiasis. Mouse models seem to be a valuable and versatile tool in trypanosomiasis-associated pathology and immunology research and highlight the variety shown by African trypanosomiases. Indeed, inbred mouse strains have enabled the study of genetic determinants of susceptibility and of the roles of anti-parasite antibodies, inflammatory mediators and anti-inflammatory mediators for each trypanosome species. Remarkable advances relating to the encephalitic stage of sleeping sickness have also been achieved thanks to murine models. The different contributions of murine models to the African trypanosomiases knowledge are presented here. Future search directions are finally proposed, with respect to mouse model opportunities and limitations. [less ▲]

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See detailThe contributions of pairs of parallel surfaces in a simple analytical model of room reverberation
Embrechts, Jean-Jacques ULg

in I.C.A. (Ed.) Proceedings of the 2013 ICA Congress (2013, June)

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See detailContributions of the driven process and the loading-unloading process during substorms: A study based on the IMAGE-SI12 imager
Blockx, Caroline ULg; Gérard, Jean-Claude ULg; Coumans, Valérie ULg et al

in Journal of Geophysical Research (2009), 114

Substorm energetics has been shown to have two components, the "loading-unloading'' component releasing energy previously stored in the tail and the "directly driven'' component dissipating simultaneously ... [more ▼]

Substorm energetics has been shown to have two components, the "loading-unloading'' component releasing energy previously stored in the tail and the "directly driven'' component dissipating simultaneously fed solar wind energy. Previous studies disagree about the relative importance of each process. The SI12 spectral imager onboard the IMAGE satellite provides images of the Doppler-shifted Lyman alpha auroral emission at 121.8 nm every 2 min. It has been used to determine the auroral intensity during substorms, which may be compared to the solar wind characteristics and interplanetary magnetic field components before and/or after substorm onsets. In this study, we analyze 256 substorms between June 2000 and December 2002, which satisfy criteria relative to the viewing conditions. We compare the mean nightside intensity during the expansion phase with the magnetic open flux, the epsilon parameter, and other coupling functions (used as proxies of transfer of solar wind energy to the magnetosphere) integrated over the growth phase or the expansion phase. The mean auroral intensity during the expansion phase correlates well with coupling functions integrated over the growth phase. We also find that the correlation between the auroral precipitation during the expansion phase and the coupling functions integrated over the expansion phase is lower but still significant. This implies that, even though both mechanisms contribute to the energy precipitated during substorms, the loading-unloading process is statistically dominant. [less ▲]

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See detailContributions possibles des innovations genetiques pour l'amelioration de la competitivite des filieres cotonnieres africaines.
Mergeai, Guy ULg

in Biotechnologie, Agronomie, Société et Environnement = Biotechnology, Agronomy, Society and Environment [=BASE] (2006), 10(4), 345-350

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See detailContributions théorique et expérimentale au calcul de la résistance à l'avancement des convois poussés en navigation dans les voies d'eau de sections limitées
Marchal, Jean ULg

in Annales des Travaux Publics de Belgique = Tijdschrift der Openbare Werken van Belgie (1977), (1 et 2), 77

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See detailContributions to Batch Mode Reinforcement Learning
Fonteneau, Raphaël ULg

Doctoral thesis (2011)

This dissertation presents various research contributions published during these four years of PhD in the field of batch mode reinforcement learning, which studies optimal control problems for which the ... [more ▼]

This dissertation presents various research contributions published during these four years of PhD in the field of batch mode reinforcement learning, which studies optimal control problems for which the only information available on the system dynamics and the reward function is gathered in a set of trajectories. We first focus on deterministic problems in continuous spaces. In such a context, and under some assumptions related to the smoothness of the environment, we propose a new approach for inferring bounds on the performance of control policies. We also derive from these bounds a new inference algorithm for generalizing the information contained in the batch collection of trajectories in a cautious manner. This inference algorithm as itself lead us to propose a min max generalization framework. When working on batch mode reinforcement learning problems, one has also often to consider the problem of generating informative trajectories. This dissertation proposes two different approaches for addressing this problem. The first approach uses the bounds mentioned above to generate data tightening these bounds. The second approach proposes to generate data that are predicted to generate a change in the inferred optimal control policy. While the above mentioned contributions consider a deterministic framework, we also report on two research contributions which consider a stochastic setting. The first one addresses the problem of evaluating the expected return of control policies in the presence of disturbances. The second one proposes a technique for selecting relevant variables in a batch mode reinforcement learning context, in order to compute simplified control policies that are based on smaller sets of state variables. [less ▲]

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See detailContributions to combinatorics on words in an abelian context and covering problems in graphs
Vandomme, Elise ULg

Doctoral thesis (2015)

This thesis dissertation is divided into two (distinct but connected) parts that reflect the joint PhD. We study and we solve several questions regarding on the one hand combinatorics on words in an ... [more ▼]

This thesis dissertation is divided into two (distinct but connected) parts that reflect the joint PhD. We study and we solve several questions regarding on the one hand combinatorics on words in an abelian context and on the other hand covering problems in graphs. Each particular problem is the topic of a chapter. In combinatorics on words, the first problem considered focuses on the 2-regularity of sequences in the sense of Allouche and Shallit. We prove that a sequence satisfying a certain symmetry property is 2-regular. Then we apply this theorem to show that the 2-abelian complexity functions of the Thue--Morse word and the period-doubling word are 2-regular. The computation and arguments leading to these results fit into a quite general scheme that we hope can be used again to prove additional regularity results. The second question concerns the notion of return words up to abelian equivalence, introduced by Puzynina and Zamboni. We obtain a characterization of Sturmian words with non-zero intercept in terms of the finiteness of the set of abelian return words to all prefixes. We describe this set of abelian returns for the Fibonacci word but also for the Thue--Morse word (which is not Sturmian). We investigate the relationship existing between the abelian complexity and the finiteness of this set. In graph theory, the first problem considered deals with identifying codes in graphs. These codes were introduced by Karpovsky, Chakrabarty and Levitin to model fault-diagnosis in multiprocessor systems. The ratio between the optimal size of an identifying code and the optimal size of a fractional relaxation of an identifying code is between 1 and 2 ln(|V|)+1 where V is the vertex set of the graph. We focus on vertex-transitive graphs, since we can compute the exact fractional solution for them. We exhibit infinite families, called generalized quadrangles, of vertex-transitive graphs with integer and fractional identifying codes of order |V|^a with a in {1/4,1/3,2/5}. The second problem concerns (r,a,b)-covering codes of the infinite grid already studied by Axenovich and Puzynina. We introduce the notion of constant 2-labellings of weighted graphs and study them in four particular weighted cycles. We present a method to link these labellings with covering codes. Finally, we determine the precise values of the constants a and b of any (r,a,b)-covering code of the infinite grid with |a-b|>4. This is an extension of a theorem of Axenovich. [less ▲]

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See detailContributions to decision tree induction: bias/variance tradeoff and time series classification
Geurts, Pierre ULg

Doctoral thesis (2002)

Because of the rapid progress of computer and information technology, large amounts of data are nowadays available in a lot of domains. Automatic learning aims at developing algorithms able to produce ... [more ▼]

Because of the rapid progress of computer and information technology, large amounts of data are nowadays available in a lot of domains. Automatic learning aims at developing algorithms able to produce synthetic high-level information, or models, from this data. Learning algorithms are generally evaluated according to three different criteria: interpretability (how well the model helps to understand the data), predictive accuracy (how well the model can predict unseen situations), and computational efficiency (how fast is the algorithm and how it scales to large databases). This thesis explores two issues in automatic learning: the improvement of the well-known decision tree induction method and the problem of learning classification models for time series data. Decision tree induction method is an automatic learning algorithm which focuses on the modeling of input/output relationships. While this algorithm is among the fastest and most interpretable methods, its accuracy is not always competitive with respect to other algorithms. It is commonly admitted that this suboptimality is due to the excessive variance of this method. We first carry out an empirical study which shows quantitatively how important this variance is, i.e. how strongly decision trees depend on the random nature of the database used to infer them. These experiments confirm that this variance is detrimental not only from the point of view of accuracy but also from the point of view of interpretability. With the goal of improving both interpretability and accuracy, we consider three variance reduction techniques for decision trees. First, in the goal of improving mainly interpretability, we propose several methods which try to stabilize the parameters chosen during tree induction. While these methods succeed in reducing the variability of the parameters, they produce only a slight improvement of the accuracy. Then, we consider perturb and combine algorithms (e.g. bagging, boosting) which consist in combining the predictions of several models obtained by randomizing in some way the learning process. Inspired by the high variance of the parameters defining a decision tree, we propose an extremely randomized decision tree induction algorithm, called extra-tree, which chooses all parameters at random during induction. The aggregation of several of these extra-trees gives an important reduction of variance and this algorithm compares favorably in terms of accuracy and computational efficiency with both bagging and boosting. Because of the randomization of the parameters, the resulting method is also competitive with classical decision tree induction in terms of computational efficiency. In addition to these two approaches, we propose a ``dual'' perturb and combine algorithm which delays the perturbation at the prediction stage and hence requires only one model. In combination with decision tree, this method actually bridges the gap between single decision trees and perturb and combine algorithms. Of the first, it saves the interpretability (by using only one model), and with perturb and combine algorithm, it shares some of the accuracy (by reducing the variance). The second topic of the thesis is the problem of time series classification. The most direct way to solve this problem is to apply existing learning algorithms on low-level variables which correspond to the values of a time series at several time points. Experiments with the tree-based algorithms studied in the first part of the thesis shows that this approach is limited. A variance reduction techniques is then proposed specifically for this kind of data which consists in aggregating the prediction given by a classification model for subsequences of time series. Since this method does not provide interpretable models, we propose a second method which extends decision tree tests by allowing them to detect local shift invariant properties, or patterns, in time series. The study proposed in this part of the thesis is only a first step in the domain but our conclusions give some future work directions for handling complex type of data with automatic learning methods. [less ▲]

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See detailContributions to early land plant research (XIV IBC).
Gerrienne, Philippe ULg; Berry, Christopher M.

in Review of Palaeobotany and Palynology (2001), 116

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See detailContributions to early land plant research.
Gerrienne, Philippe ULg; Berry, Christopher M.

Book (2001)

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See detailContributions to Monte Carlo Search
Lupien St-Pierre, David ULg

Doctoral thesis (2013)

This research is motivated by improving decision making under uncertainty and in particular for games and symbolic regression. The present dissertation gathers research contributions in the field of Monte ... [more ▼]

This research is motivated by improving decision making under uncertainty and in particular for games and symbolic regression. The present dissertation gathers research contributions in the field of Monte Carlo Search. These contributions are focused around the selection, the simulation and the recommendation policies. Moreover, we develop a methodology to automatically generate an MCS algorithm for a given problem. For the selection policy, in most of the bandit literature, it is assumed that there is no structure or similarities between arms. Thus each arm is independent from one another. In several instances however, arms can be closely related. We show both theoretically and empirically, that a significant improvement over the state-of-the-art selection policies is possible. For the contribution on simulation policy, we focus on the symbolic regression problem and ponder on how to consistently generate different expressions by changing the probability to draw each symbol. We formalize the situation into an optimization problem and try different approaches. We show a clear improvement in the sampling process for any length. We further test the best approach by embedding it into a MCS algorithm and it still shows an improvement. For the contribution on recommendation policy, we study the most common in combination with selection policies. A good recommendation policy is a policy that works well with a given selection policy. We show that there is a trend that seems to favor a robust recommendation policy over a riskier one. We also present a contribution where we automatically generate several MCS algorithms from a list of core components upon which most MCS algorithms are built upon and compare them to generic algorithms. The results show that it often enables discovering new variants of MCS that significantly outperform generic MCS algorithms. [less ▲]

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