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Peer Reviewed
See detailCombining Full Transients and Phasor Approximation Models in Power System Time Simulation
Plumier, Frédéric ULg; Fabozzi, Davide ULg; Geuzaine, Christophe ULg et al

in Proceedings of the 21th International Conference on Domain Decomposition Methods (DD21) (2012, June)

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See detailCombining genotype with allelic association as input for iterative pruning principal component analysis (ipPCA) to resolve population substructures
Chaichoompu, Kridsadakorn ULg; Fouladi, Ramouna ULg; Wangkumhang, Pongsakorn et al

Poster (2014, August 28)

Single Nucleotide Polymorphisms (SNPs) are commonly used to capture variations between populations and often genome-wide SNP data are pruned based on linkage disequilibrium (LD) patterns. Notably ... [more ▼]

Single Nucleotide Polymorphisms (SNPs) are commonly used to capture variations between populations and often genome-wide SNP data are pruned based on linkage disequilibrium (LD) patterns. Notably, haplotype composition and the pattern of LD between markers may vary between larger populations but may also play a role within more confined geographic regions. Indeed, knowledge about haplotypes in unrelated individuals can reveal useful information about genetic ancestry. Here, we use iterative pruning principal component analysis (ipPCA) [Intarapanich 2009] to identify and characterize subpopulations in an unsupervised way using a rich set of genetic markers since using reduced sets of genetic markers for these purposes can become challenging, especially when similar geographic regions are involved or when spurious patterns are likely to exist. As input data, either pruned genome-wide SNP data are used or multilocus haplotype information derived from the genome-wide SNP panel. These approaches are applied to real-life data from 4028 Vietnamese individuals [Khor 2012]. Preliminary results indicate that ipPCA applied to pruned SNP data or ipPCA that explicitly uses multilocus information (haplotypes) give complementary information about population substructure for geographically confined populations. Both methods address different aspects of population structure. In conclusion, we propose to combine an LD-based haplotype encoding scheme with the ipPCA machinery to retrieve fine population substructures. Despite the complexities that are associated with haplotype inference, added value can be obtained when the LD structure between SNPs is exploited in the search for relevant population strata. [less ▲]

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See detailCombining Genotype with LD-based haplotype information as input for iterative pruning principal component analysis (ipPCA) to improve population clustering
Chaichoompu, Kridsadakorn ULg; Fouladi, Ramouna ULg; Wangkumhang, Pongsakorn et al

Conference (2014, November 26)

Single Nucleotide Polymorphisms (SNPs) are commonly used to capture variations between populations and often genome-wide SNP data are pruned based on linkage disequilibrium (LD) patterns. To identify and ... [more ▼]

Single Nucleotide Polymorphisms (SNPs) are commonly used to capture variations between populations and often genome-wide SNP data are pruned based on linkage disequilibrium (LD) patterns. To identify and differentiate between subpopulations using a rich set of genetic markers, as using reduced sets of genetic markers for these purposes, can become challenging especially when similar geographic regions are involved or when spurious patterns are likely to exist. Notably, haplotype composition and the pattern of LD between markers may vary between larger populations but may also play a role within more confined geographic regions. Indeed, the structure of haplotypes in unrelated individuals can reveal useful information about genetic ancestry. Here, we use iterative pruning principal component analysis (ipPCA) [1] to identify and characterize subpopulations in an unsupervised way. Furthermore, we purpose to combine an LD-based haplotype encoding scheme with the ipPCA machinery to retrieve fine population substructures. Despite the complexities that are associated with haplotype inference, added value can be obtained when the LD structure between SNPs is exploited in the search for relevant population strata. As input data, either pruned genome-wide SNP data are used or multilocus haplotype information derived from the genome-wide SNP panel. Preliminary results indicate that ipPCA applied to pruned SNP data or ipPCA that explicitly uses multilocus information (haplotypes) give complementary information about population substructure for geographically confined populations. In fact, both methods address different aspects of population structure. [1] Intarapanich, A. et al. (2009), BMC Bioinformatics. 10: p. 382. [less ▲]

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See detailCombining in vivo and in silico experiments to unravel root water uptake dynamics
Lobet, Guillaume ULg; Bhowmick, Suman; Couvreur, Valentin et al

Poster (2012)

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Peer Reviewed
See detailCombining intercropping with semiochemical releases: optimization of alternative control of Sitobion avenae 1 in wheat crops in China
Wang, Guang; Cui, Liang-Liang; Dong, Jie et al

in Entomologia Experimentalis et Applicata (2011)

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See detailCombining Ionosonde and GPS TEC Data to Assess NeQuick Formulation
Bidaine, Benoît ULg

Report (2008)

The main topic which was investigated during the mission is related to the validation of the NeQuick model using different data sets. The discussions were based on former work dealing with the comparison ... [more ▼]

The main topic which was investigated during the mission is related to the validation of the NeQuick model using different data sets. The discussions were based on former work dealing with the comparison of the first version of the model recommended by the ITU-R and its second version recently published. In addition the NeQuick formulation and its physical behaviour were discussed considering the bottomside and topside representations and the interaction between both. This will constitute the basis for future investigation of ingestion techniques using NeQuick as well as the ionospheric correction algorithm for Galileo single frequency users. [less ▲]

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Peer Reviewed
See detailCombining lazy learning, racing and subsampling for effective feature selection
Bontempi, Gianluca; Birattari, Mauro; Meyer, Patrick ULg

in Adaptive and Natural Computing Algorithms (2005)

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See detailCombining magnetic and seismic studies to constrain processes in massive stars
Neiner, C.; Degroote, P.; Coste, B. et al

in IAUS 302 - Magnetic Fields Throughout Stellar Evolution (2014, August)

The presence of pulsations influences the local parameters at the surface of massive stars and thus it modifies the Zeeman magnetic signatures. Therefore it makes the characterisation of a magnetic field ... [more ▼]

The presence of pulsations influences the local parameters at the surface of massive stars and thus it modifies the Zeeman magnetic signatures. Therefore it makes the characterisation of a magnetic field in pulsating stars more difficult and the characterisation of pulsations is thus required for the study of magnetic massive stars. Conversely, the presence of a magnetic field can inhibit differential rotation and mixing in massive stars and thus provides important constraints for seismic modelling based on pulsation studies. As a consequence, it is necessary to combine spectropolarimetric and seismic studies for all massive classical pulsators. Below we show examples of such combined studies and the interplay between physical processes. [less ▲]

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See detailCombining mesh refinement and XFEM for fracture mechanics simulations: contradiction or strength?
Henrard, Christophe; Bruyneel, Michaël ULg; Delsemme, Jean-Pierre

in NAFEMS (Ed.) proceedings of the NAFEMS World Congress 2013 (2013, June)

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Peer Reviewed
See detailCombining mesoporosity and Ti-doping in hematite films for water splitting
Toussaint, Caroline ULg; Tran, Hoang Son ULg; Colson, Pierre ULg et al

in Journal of Physical Chemistry C (2015), 119(4), 1642-1650

(Graph Presented). In this study, we report the synthesis of Ti-doped mesoporous hematite films by soft-templating for application as photoanodes in the photoelectrolysis of water (water splitting ... [more ▼]

(Graph Presented). In this study, we report the synthesis of Ti-doped mesoporous hematite films by soft-templating for application as photoanodes in the photoelectrolysis of water (water splitting). Because the activation of the dopant requires a heat treatment at high temperature (≥800°C), it usually results in the collapse of the mesostructure. We have overcome this obstacle by using a temporary SiO2 scaffold to hinder crystallite growth and thereby maintain the mesoporosity. The beneficial effect of the activated dopant has been confirmed by comparing the photocurrent of doped and undoped films treated at different temperatures. The role of the mesostructure was investigated by comparing dense, collapsed, and mesoporous films heated at different temperatures and characterized under front and back illumination. It turns out that the preservation of the mesotructure enables a better penetration of the electrolyte into the film and therefore reduces the distance that the photogenerated holes have to travel to reach the electrolyte. As a result, we found that mesoporous films with dopant activation at 850°C perform better than comparable dense and collapsed films. [less ▲]

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See detailCombining microCT-based characterization with empirical modelling as a robust screening approach for the design of optimized CaP-containing scaffolds for progenitor cell-mediated bone formation.
Kerckhofs, G.; Chai, Y. C.; Luyten, F. P. et al

in Acta Biomaterialia (2016), 35

Biomaterials are a key ingredient to the success of bone tissue engineering (TE), which focuses on the healing of bone defects by combining scaffolds with cells and/or growth factors. Due to the widely ... [more ▼]

Biomaterials are a key ingredient to the success of bone tissue engineering (TE), which focuses on the healing of bone defects by combining scaffolds with cells and/or growth factors. Due to the widely variable material characteristics and patient-specificities, however, current bone TE strategies still suffer from low repeatability and lack of robustness, which hamper clinical translation. Hence, optimal TE construct (i.e. cells and scaffold) characteristics are still under debate. This study aimed to reduce the material-specific variability for cell-based construct design, avoiding trial-and-error, by combining microCT characterization and empirical modelling as an innovative and robust screening approach. Via microCT characterization we have built a quantitative construct library of morphological and compositional properties of six CE approved CaP-based scaffolds (CopiOs(R), BioOss, Integra Mozaik, chronOS Vivify, MBCP and ReproBone), and of their bone forming capacity and in vivo scaffold degradation when combined with human periosteal derived cells (hPDCs). The empirical model, based on the construct library, allowed identification of the construct characteristics driving optimized bone formation, i.e. (a) the percentage of beta-TCP and dibasic calcium phosphate, (b) the concavity of the CaP structure, (c) the average CaP structure thickness and (d) the seeded cell amount (taking into account the seeding efficiency). Additionally, the model allowed to quantitatively predict the bone forming response of different hPDC-CaP scaffold combinations, thus providing input for a more robust design of optimized constructs and avoiding trial-and error. This could improve and facilitate clinical translation. STATEMENT OF SIGNIFICANCE: Biomaterials that support regenerative processes are a key ingredient for successful bone tissue engineering (TE). However, the optimal scaffold structure is still under debate. In this study, we have provided a useful innovative approach for robust screening of potential biomaterials or constructs (i.e. scaffolds seeded with cells and/or growth factors) by combining microCT characterization with empirical modelling. This novel approach leads to a better insight in the scaffold parameters influencing progenitor cell-mediated bone formation. Additionally, it serves as input for more controlled and robust design of optimized CaP-containing bone TE scaffolds. Hence, this novel approach could improve and facilitate clinical translation. [less ▲]

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Peer Reviewed
See detailCombining microsatellite and pedigree data to estimate relationships among Skyros ponies.
Bömcke, Elisabeth ULg; Gengler, Nicolas ULg

in Journal of Applied Genetics (2009), 50(2), 133-43

Relationship coefficients are particularly useful to improve genetic management of endangered populations. These coefficients are traditionally based on pedigree data, but in case of incomplete or ... [more ▼]

Relationship coefficients are particularly useful to improve genetic management of endangered populations. These coefficients are traditionally based on pedigree data, but in case of incomplete or inexistent pedigrees they are replaced by coefficients calculated from molecular data. The main objective of this study was to develop a new method to estimate relationship coefficients by combining molecular with pedigree data, which is useful for specific situations where neither pedigree nor molecular data are complete. The developed method was applied to contribute to the conservation of the Skyros pony breed, which consists of less than 200 individuals, divided into 3 main herds or subpopulations. In this study, relationships between individuals were estimated using traditional estimators as well as the newly developed method. For this purpose, 99 Skyros ponies were genotyped at 16 microsatellite loci. It appeared that the limitation of the most common molecular-based estimators is the use of weights that assume relationships equal to 0. The results showed that, as a consequence of this limitation, negative relationship values can be obtained in small inbred populations, for example. By contrast, the combined estimator gave no negative values. Using principal component analysis, the combined estimator also enabled a better graphic differentiation between the 3 subpopulations defined previously. In conclusion, this new estimator can be a promising alternative to traditionally used estimators, especially in inbred populations, with both incomplete pedigree and molecular information. [less ▲]

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See detailCombining mindfulness and ACT to learn how to manage emotions and to engage in valued activities: Assessment of the feasibility of a training group and its efficiency
Wagener, Aurélie ULg; Dierickx, Christophe; Blairy, Sylvie ULg

Poster (2015, July 18)

BACKGROUND Managing painful emotions could be an issue for a lot of adults. Indeed, learning how to manage painful emotions is an often-requested demand in psychotherapy. Mindfulness-based programs and ... [more ▼]

BACKGROUND Managing painful emotions could be an issue for a lot of adults. Indeed, learning how to manage painful emotions is an often-requested demand in psychotherapy. Mindfulness-based programs and acceptance and commitment therapy (ACT) offer useful tools which aim to guide in this learning process. ACT also provide guidelines to engage in valued activities. In order to help community adults to manage their painful emotions and to engage themselves in valued activities, we offer training group cycles combining tools of mindfulness-based programs and ACT. This study aims to assess the feasibility of such training groups and their efficiency. METHODS A longitudinal design with three assessment-times (T0, T1 and T2) is employed. Participants to the training group attend to three three-hours training sessions on a six-weeks period. They are assessed before the training sessions (T0), directly after (T1) and at three-months follow-up (T2). Questionnaires assess these variables: sociodemographic data, mood, mindfulness, psychological flexibility, cognitive coping strategies and behavioural activation. Student t tests for paired samples are conducted. RESULTS Fifty-four adults participated to four training cycles (the cycles are all identical). Until now, 28 participants (21 women) completed the T0 and the T1 (mean age = 41.43, SD = 11.83). Student t test indicate a significant decrease of depression (t(25) = 4.53, p < 0,001), anxiety (t(25) = 6.23, p < 0.001) and non-adaptive cognitive coping strategies (t(24) = 3.76, p < 0.001). Student t test also indicate a significant increase in mindfulness (t(26) = -3.87, p < 0.001), psychological flexibility (t(26)) = -5.48, p < 0.001) and behavioural activation (t(26) = -4.86, p < 0.001). DISCUSSION Preliminary results indicate the feasibility of training groups combining tools of mindfulness-based programs and ACT. Results show a decrease in several variables (depression, anxiety and non-adaptive cognitive coping strategies) and an increase in other variables (mindfulness, psychological flexibility and behavioural activation). These results seem to indicate that participants benefit from the training groups. Data collection is still ongoing and a control group (waiting-list) is currently being composed. Results and clinical implications will be further discussed during the congress. [less ▲]

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See detailCombining Mixed Integer Programming and Supervised Learning for Fast Re-planning
Rachelson, Emmanuel ULg; Ben Abbes, Ala; Diemer, Sébastien

in Proceedings of the 22nd IEEE International Conference on Tools with Artificial Intelligence (2010)

We introduce a new plan repair method for problems cast as Mixed Integer Programs. In order to tackle the inherent complexity of these NP-hard problems, our approach relies on the use of Supervised ... [more ▼]

We introduce a new plan repair method for problems cast as Mixed Integer Programs. In order to tackle the inherent complexity of these NP-hard problems, our approach relies on the use of Supervised Learning method for the offline construction of a predictor which takes the problem’s parameters as input and infers values for the discrete optimization variables. This way, the online resolution time of the plan repair problem can be greatly decreased by avoiding a large part of the combinatorial search among discrete variables. This contribution was motivated by the large-scale problem of intra-daily recourse strategy computation in electrical power systems. We report and discuss results on this benchmark, illustrating the different aspects and mechanisms of this new approach which provided close-to-optimal solutions in only a fraction of the computational time necessary for existing solvers. [less ▲]

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See detailCombining Non-stably Infinite, Non-first Order Theories
Fontaine, Pascal; Gribomont, Pascal ULg

in Electronic Notes in Theoretical Computer Science (2005), 125(3), 37-51

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Peer Reviewed
See detailCombining numerous uncorrelated MEMS gyroscopes for accuracy improvement based on an optimal Kalman filter
Chang, Honglong; Xue, Liang; Jiang, Chengyu et al

in IEEE Transactions on Instrumentation and Measurement (2012), 61(11), 3084-3093

In this paper, an approach to improve the accuracy of microelectromechanical systems (MEMS) gyroscopes by combining numerous uncorrelated gyroscopes is presented. A Kalman filter (KF) is used to fuse the ... [more ▼]

In this paper, an approach to improve the accuracy of microelectromechanical systems (MEMS) gyroscopes by combining numerous uncorrelated gyroscopes is presented. A Kalman filter (KF) is used to fuse the output signals of several uncorrelated sensors. The relationship between the KF bandwidth and the angular rate input is quantitatively analyzed. A linear model is developed to choose suitable system parameters for a dynamic application of the concept. Simulation and experimental tests of a six-gyroscope array proved that the presented approach was effective to improve the MEMS gyroscope accuracy. The experimental results indicate that six identical gyroscopes with a noise density of 0.11°/s/$\surd$Hz and a bias instability of 62°/h can be combined to form a virtual gyroscope with a noise density of 0.03°/s/$\surd$Hz and a bias instability of 16.8°/h . The accuracy improvement is better than that of a simple averaging process of the individual sensors. [less ▲]

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See detailCombining PET images and neuropsychological test data for automatic diagnosis of Alzheimer’s disease
Segovia-Román, Fermín ULg; Bastin, Christine ULg; Salmon, Eric ULg et al

in PLoS ONE (2014), 9(2),

In recent years, several approaches to develop computer aided diagnosis (CAD) systems for dementia have been proposed. Some of these systems analyze neurological brain images by means of machine learning ... [more ▼]

In recent years, several approaches to develop computer aided diagnosis (CAD) systems for dementia have been proposed. Some of these systems analyze neurological brain images by means of machine learning algorithms in order to find the patterns that characterize the disorder, and a few combine several imaging modalities to improve the diagnostic accuracy. However, they usually do not use neuropsychological testing data in that analysis. The purpose of this work is to measure the advantages of using not only neuroimages as data source in CAD systems for dementia but also neuropsychological scores. To this aim, we compared the accuracy rates achieved by systems that use neuropsychological scores beside the imaging data in the classification step and systems that use only one of these data sources. In order to address the small sample size problem and facilitate the data combination, a dimensionality reduction step (implemented using three different algorithms) was also applied on the imaging data. After each image is summarized in a reduced set of image features, the data sources were combined and classified using three different data combination approaches and a Support Vector Machine classifier. That way, by testing different dimensionality reduction methods and several data combination approaches, we aim not only highlighting the advantages of using neuropsychological scores in the classification, but also implementing the most accurate computer system for early dementia detention. The accuracy of the CAD systems were estimated using a database with records from 46 subjects, diagnosed with MCI or AD. A peak accuracy rate of 89% was obtained. In all cases the accuracy achieved using both, neuropsychological scores and imaging data, was substantially higher than the one obtained using only the imaging data. [less ▲]

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See detailCombining problem structure and basis reduction to solve a class of hard integer programs
Louveaux, Quentin ULg; Wolsey, Laurence A.

in Mathematics of Operations Research (2002), 27(3), 470-484

We consider a hard integer programming problem that is difficult for the standard branch-and-bound approach even for small instances. A reformulation based on lattice basis reduction is known to be more ... [more ▼]

We consider a hard integer programming problem that is difficult for the standard branch-and-bound approach even for small instances. A reformulation based on lattice basis reduction is known to be more effective. However the step to compute the reduced basis, even if it is found in polynomial time, becomes a bottleneck for small to medium instances. By using the structure of the problem, we show that we can decompose the problem and obtain the basis by taking the kronecker product of two smaller bases easier to compute. Furthermore, if the two small bases are reduced, the kronecker product is also reduced up to a reordering of the vectors. Computational results show the gain from such an approach. [less ▲]

Detailed reference viewed: 66 (15 ULg)