Éditeur(s) : HAL CCSD
Résumé : National audience
INTRODUCTION: Pulmonary arterial hypertension (PAH) is a severe complication of systemic sclerosis and detecting PAH efficiently remains challenging. The DETECT study has offered in 2013 a composite screening tool for PAH. The objective of our study was to compare the indication of right heart catheterisation (RHC) as suggested by the DETECT algorithm with the decisions of a multidisciplinary team. METHODS: This prospective monocentric non-interventional study consecutively included systemic sclerosis patients when data required to apply DETECT algorithm were available. We evaluate the number of RHC as requested by this algorithm and confronted it with the indications of RHC suggested by a multidisciplinary group blinded for the result of DETECT algorithm. RESULTS: In total, 117 systemic sclerosis patients were included. When DETECT algorithm was applied to all patients, RHC was suggested by this algorithm for 70 patients, whereas only 15 indications were required by the multidisciplinary group; among those patients only 7 had PAH. When DETECT algorithm was applied only to the 42 patients with DLCO<60% and disease duration of more than 3 years, RHC was suggested for 31 patients whereas only 13 were indicated by the multidisciplinary group; among those patients only 7 had PAH. CONCLUSION: The DETECT algorithm is able to efficiently detect all PAH patients finally diagnosed by our multidisciplinary team. However, it increases by 3 the number of RHC that should be performed.
La Revue de Médecine Interne

hal-01579606
https://hal-univ-rennes1.archives-ouvertes.fr/hal-01579606
DOI : 10.1016/j.revmed.2017.04.005
PUBMED : 28545856

Éditeur(s) : HAL CCSD
Résumé : The research presented in this thesis aims at determining the possibility of partial or total automatic ship detection in High Resolution optical satellite images. At first, we expose the industrial context of our study, which fixes the constraints in terms of performances and processing time. Then, we present the available satellite data for our study (SPOT 5 panchromatic images of 5m per pixel resolution). Then we detail our approach for ship detection : the first stage is a pre-detection of targets that gives us candidates. The second stage is a precise segmentation of each candidate and the third stage is a classification of candidates. Our pre-detection method is based on the Bayesian decision theory. This pre-detection supplies a set of regions of interests (ROI). Among them, we have ships, but also false alarms due to clouds and to crests of waves. The purpose of the following stage is to eliminate the false alarms and to characterize the pre-detected ships. Then, we detail the method used to segment candidates. It uses active contours and also uses the Bayesian decision theory. After a brief description of the characteristics extracted for the classication of ships, we present the classifier that we used. We complete the ship characterization by presenting two methods of wave ship detection. The first approach uses active contours and the second is based on an a contrario approach. We compare the results of these two approaches. To complete the study and replace it in the industrial and operational context, we present experiments of the complete algorithm on complete images to estimate the performances and the processing time of the whole method.
Les travaux présentés dans cette thèse ont pour but de déterminer la possibilité d'automatiser, partiellement ou totalement, la détection de bateaux à partir d'images satellitaires optiques haute résolution. Nous exposons tout d'abord le contexte industriel dans lequelle s'insère notre étude, qui fixe les contraintes en termes de performances et de temps de traitement. Puis, nous présentons les données satellitaires disponibles dans le cadre de notre étude (images SPOT 5 panchromatique de résolution 5m). Après avoir illustré le contenu des scènes, nous présentons la démarche adoptée pour la détection des navires : une phase de pré-détection suivie d'une étape de segmentation et d'une étape de classification. La méthode de pré-détection utilisée s'appuie sur la théorie bayésienne de la décision. Après avoir présenté le modèle classique, nous discutons du modèle que nous avons utilisé. Cette pré-détection fournit un ensemble de régions d'intérêts. Parmi elles, nous n'avons pas uniquement des bateaux, nous avons également des fausses alarmes dues aux nuages et aux crêtes de vagues. Le but de l'étape suivante est à la fois d'éliminer les fausses alarmes et de caractériser les bateaux pré-détectés. Ensuite, nous détaillons la méthode utilisée pour segmenter les bateaux. Elle s'appuie sur des contours actifs et utilise également la théorie bayésienne de la décision. Après avoir décrit les caractéristiques extraites pour la classification des bateaux, nous présentons le classifieur utilisé. Nous complétons la caractérisation des navires en présentant deux méthodes de détection des sillages différentes des méthodes classiques. La première approche s'appuie sur l'utilisation de contours actifs et la seconde est basée sur une approche a contrario. Nous comparons les résultats des ces deux approches. An de compléter l'étude et se replacer dans le contexte industriel et opérationnel de la thèse, nous présentons des expérimentations de l'ensemble de l'algorithme sur des images complètes pour évaluer les performances et le temps de traitement.
https://tel.archives-ouvertes.fr/tel-00560119

tel-00560119
https://tel.archives-ouvertes.fr/tel-00560119
https://tel.archives-ouvertes.fr/tel-00560119/document
https://tel.archives-ouvertes.fr/tel-00560119/file/These_NadiaProia_Version_Finale.pdf

Éditeur(s) : HAL CCSD Publisher : Paris : Baillière [1980-. Latest Publisher : Paris : Elsevier
Résumé : National audience
Introduction L’hypertension artérielle pulmonaire précapillaire constitue l’une des premières causes de décès au cours de la sclérodermie systémique. Le pronostic dépend de la précocité du diagnostic et de l’introduction rapide du traitement ciblé. En 2013, l’algorithme DETECT a été élaboré en vue d’un dépistage plus précoce de l’hypertension artérielle pulmonaire. Le but de notre étude est d’évaluer l’impact de l’utilisation de l’algorithme DETECT en comparant les pratiques actuelles d’un centre de compétence français à celles recommandées par ce nouvel outil de dépistage. Patients et méthodes Il s’agit d’une étude transversale monocentrique. Les patients sclérodermiques ayant bénéficié d’un bilan viscéral au cours de l’année 2014–2015, contenant les données nécessaires au calcul du score DETECT, ont été inclus. Conformément aux pratiques habituelles du service, l’ensemble des patients avait bénéficié d’une échographie cardiaque transthoracique et l’indication du cathétérisme cardiaque droit était posée au cours d’une réunion de concertation pluridisciplinaire. En parallèle, l’algorithme DETECT était calculé avec une première étape posant ou non l’indication théorique de l’échographie cardiaque transthoracique, puis une seconde décidant de l’indication théorique d’un cathétérisme droit. Les résultats des deux étapes de l’algorithme étaient inconnus des médecins participant à la prise en charge des patients ou à la réunion de concertation pluridisciplinaire. À la fin de la période d’inclusion, les décisions proposées par l’algorithme étaient comparées à celles issues de la réunion de concertation pluridisciplinaire. Résultats Cent dix-sept patients ont été inclus dans l’étude. Quatre-vingt-onze pour cent (n = 106) répondaient aux critères ACR 2013. Si l’algorithme DETECT était appliqué à l’ensemble de la population, l’indication de l’échographie cardiaque transthoracique était retenue chez 80 % d’entre eux (n = 94). Parmi les 94 patients sélectionnés à la première étape, il était retenu l’indication d’un cathétérisme droit chez 70 d’entre eux, soit 60 % de la population initiale. Au cours du suivi annuel, l’indication du cathétérisme droit avait été retenue par la réunion de concertation pluridisciplinaire chez 15 des 117 patients. Le diagnostic d’hypertension artérielle pulmonaire avait été retenu chez 9 d’entre eux, dont 7 avec une hypertension artérielle pulmonaire précapillaire. Si l’algorithme DETECT n’était appliqué qu’aux patients répondant aux critères initialement proposés pour la mise au point de l’algorithme (patients avec DLCO inférieure à 60 % de la valeur prédite, et symptômes – autres que phénomène de Raynaud – évoluant depuis plus de 3 ans), 42 patients étaient alors éligibles (36 % de la population totale). Les épreuves fonctionnelles respiratoires retrouvaient une DLCO moyenne à 46 % de la valeur prédite. L’indication de l’échographie cardiaque transthoracique était retenue chez 36 patients (31 % de la population totale). Parmi les 36 patients sélectionnés à la première étape, l’algorithme retenait l’indication d’un cathétérisme droit chez 31 d’entre eux (26 % de la population totale). Au cours du suivi annuel, l’indication avait été retenue par la réunion de concertation pluridisciplinaire chez 13 des 42 patients. Le diagnostic d’hypertension artérielle pulmonaire avait été posé chez 9 d’entre eux, dont 7 avec une hypertension artérielle pulmonaire précapillaire. Discussion L’application de l’algorithme DETECT à la cohorte d’un centre de compétence français confirme son efficacité en termes de dépistage de l’hypertension artérielle pulmonaire dans la population suivie pour une sclérodermie systémique car elle permet de retenir la réalisation d’un cathétérisme droit diagnostique chez tous les patients pour lesquels l’indication avait été portée en réunion de concertation pluridisciplinaire. Ces résultats sont confortés par ceux récemment publiés par une équipe tchèque. D’après nos résultats, il semble que l’application de l’algorithme à une population plus restreinte (selon les critères de l’étude DETECT) fasse aussi bien que l’application de l’algorithme à tous les patients sclérodermiques (indifféremment de la DLCO ou de l’ancienneté des symptômes). Il reste maintenant à déterminer quel suivi et quel dépistage proposer aux patients ayant une DLCO de plus de 60 %. Enfin, il restera à déterminer si l’algorithme permettra un dépistage plus précoce de l’hypertension artérielle pulmonaire chez les patients sclérodermiques, et donc d’améliorer à terme la survie. Conclusion Jusqu’en 2016, les patients suivis pour sclérodermie systémique bénéficiaient d’un dépistage de l’hypertension artérielle pulmonaire selon les recommandations internationales. L’application du nouvel algorithme DETECT aux patients sclérodermiques (avec une DLCO de plus de 60 % et les premiers symptômes autres que phénomène de Raynaud de plus de 3 ans) permettrait de limiter le nombre d’ échographies cardiaques transthoraciques (moins 70 % environ) et augmenterait le nombre de cathétérismes cardiaques droits (par un facteur 3 environ). Il permettrait donc un dépistage au moins aussi efficace que celui réalisé jusqu’à présent, avec cependant un coût probablement plus élevé et un caractère plus invasif
ISSN: 0248-8663

hal-01321852
https://hal-univ-rennes1.archives-ouvertes.fr/hal-01321852
DOI : 10.1016/j.revmed.2016.04.300

Éditeur(s) : HAL CCSD Institute of Electrical and Electronics Engineers
Résumé : International audience
This paper presents our response to the first interna- tional challenge on Facial Emotion Recognition and Analysis. We propose to combine different types of features to automatically detect Action Units in facial images. We use one multi-kernel SVM for each Action Unit we want to detect. The first kernel matrix is computed using Local Gabor Binary Pattern histograms and a histogram intersection kernel. The second kernel matrix is computed from AAM coefficients and an RBF kernel. During the training step, we combine these two types of features using the recently proposed SimpleMKL algorithm. SVM outputs are then averaged to exploit temporal information in the sequence. To eval- uate our system, we perform deep experimentations on several key issues: influence of features and kernel function in histogram- based SVM approaches, influence of spatially-independent in- formation versus geometric local appearance information and benefits of combining both, sensitivity to training data and interest of temporal context adaptation. We also compare our results to those of the other participants and try to explain why our method had the best performance during the FERA challenge.
ISSN: 1083-4419

hal-00731864
http://hal.upmc.fr/hal-00731864
http://hal.upmc.fr/hal-00731864/document
http://hal.upmc.fr/hal-00731864/file/senechal12tsmc_preprint.pdf
DOI : 10.1109/TSMCB.2012.2193567

Éditeur(s) : HAL CCSD Hong Kong : World Academic Publishing
Résumé : International audience
In automatic image analysis, when using natural images, it is important to select the elements in a scene that can lead to correct characterization. Extraneous elements can result in poor values in the parameter evaluation for recognition. Irrelevant elements also increase the processing time, because they can be used incorrectly by the algorithms for characterization or identification. The goal of this paper is to offer identification algorithms and characterizations that will allow effective recognition. We base our procedure on the photographer focus areas to identify those relevant elements in a scene. In this work, we propose a procedure to select the relevant shape from natural images. The treatment uses focal depth with edge detectors. The resulting points are combined with a region partition to obtain relevant shapes.
ISSN: 2309-0650

hal-01278550
https://hal.archives-ouvertes.fr/hal-01278550

Éditeur(s) : HAL CCSD
Résumé : International audience
More and more animal species are endangered. In order to study and protect them, several measures have been taken, which now seem to show their limit. This work focuses on the counting process, a key issue for any project that aims to protect animals. Indeed, this paper proposes an algorithm for automatic counting of singing birds in their habitat by using wireless sensors fitted with microphone. Sensors are used to record audio samples of bird songs. These samples are used to extract some kinds of song fingerprint that are thereafter used to recognize the bird species, through a classification process. Afterwards, by analyzing data which have been collected by a central base, the network structure derived from detection fields of sensors, allows our algorithm to propose an estimate of singing birds in the habitat. This paper details the counting algorithm which uses graph theory and audio inputs comparison. Finally, we demonstrate our scheme efficiency through experimentations.
Local Computer Networks (LCN)
Clearwater, United States

hal-00786165
https://hal.archives-ouvertes.fr/hal-00786165
DOI : 10.1109/LCNW.2012.6424060

Éditeur(s) : HAL CCSD Oxford University Press (OUP)
Résumé : International audience
OBJECTIVES: The aims of the study were to assess in patients with advanced HIV disease receiving antiretroviral therapy (ART) intensification with enfuvirtide (i) resistance at virological failure (VF), (ii) impact of baseline tropism on immunovirological response, and (iii) HIV-1 DNA tropism evolution during ART. METHODS: The ANRS 130 APOLLO randomized trial evaluated in naive patients the immunovirological impact of standard ART without (control arm) or with enfuvirtide. Tropism was determined on RNA and DNA by V3-loop sequencing interpreted using the Geno2Pheno algorithm. RESULTS: At baseline the median CD4 cell count was 30 cells/mm(3). Among the 170 patients assessable in this virological substudy, HIV-1 RNA tropism was as follows: 60% of viruses were R5 and 40% were R5X4/X4. HIV-1 DNA tropism was as follows: 54% were R5 and 46% were R5X4/X4. At week 24, 39% and 49% of patients experienced VF in the enfuvirtide and control arms, respectively. In the enfuvirtide arm, only resistance-associated mutations to enfuvirtide were detected. In the control arm, two patients displayed drug-resistant viruses at the time of VF. No impact of baseline tropism was observed on immunovirological response, regardless of the study arm. Among the 25 patients experiencing DNA tropism switch between baseline and week 24, 16 (64%) switched from R5 to R5X4/X4. These latter were mostly successfully suppressed patients receiving enfuvirtide and exhibiting poorer immunological response. CONCLUSIONS: Baseline RNA tropism had no impact on the immunovirological response. Drug resistance mutations were only detected for the fusion inhibitor. Finally, the mechanism of replenishment of the viral cellular reservoir with X4 viruses observed needs to be further analysed.
ISSN: 0305-7453

hal-00875130
https://hal.archives-ouvertes.fr/hal-00875130
DOI : 10.1093/jac/dks455
PUBMED : 23152480

Éditeur(s) : HAL CCSD
Résumé : This paper presents the experimental results obtained for an automatic detection of ships in High Resolution optical satellite images. Our images are panchromatic SPOT 5 images, whose resolution is 5m per pixel. Our detection method is part of an industrial project of maritime surveillance. It is based on the Bayesian decision theory and does not need any preprocessing.The detection is composed of three stages. The first one is a pre-detection of targets that gives us candidates. The second one is a precise segmentation of each candidate. The third one is a classification of candidates into three classes : real small targets, real big targets and false alarms. The two first stages are based on the bayesian theory, using a very simple image model that leads to very fast algorithms. For now, the classification is based on multivariate decision tree. Finally, the overall results of the method are given for a set of images, as close as possible to the operational conditions and show the performances of the proposed method (detection of almost all the ships, false alarms due to crests of waves and an acceptable computing time).
Journée Nationale de Photogrammétrie et Télédétection

hal-00601854
https://hal.archives-ouvertes.fr/hal-00601854

Éditeur(s) : HAL CCSD
Résumé : Session "Articles"
National audience
Dans cet article, nous présentons une méthode robuste et précise pour détecter 17 points caractéristiques du visage sur des images expressives. Une nouvelle architecture multi-résolution basée sur les récents algorithmes multi-noyau est introduite. Les patches de faibles résolutions codent les informations globales du visage donnant lieu à une détection grossière mais robuste du point désiré. Les patches de grandes résolutions quant à eux utilisent les détails locaux afin d'affiner cette localisation. En combinant une détection indépendante de points et des informations a priori sur les distributions de points, nous proposons un détecteur robuste aux changements d'expressions ainsi qu'aux variations d'illuminations. Ce système a été évalué sur plusieurs bases de données de la littérature. Les résultats présentés améliorent les performances des détecteurs de l'état de l'art
Actes de la conférence RFIA 2012
Lyon, France

hal-00656522
https://hal.archives-ouvertes.fr/hal-00656522
https://hal.archives-ouvertes.fr/hal-00656522/document
https://hal.archives-ouvertes.fr/hal-00656522/file/rfia2012_submission_99.pdf

Éditeur(s) : HAL CCSD Wiley
Résumé : Revue de rang A
International audience
This paper studies how to detect anomalies in a distributed manner by using wireless sensor networks (WSNs). We focus on a medical context, where the existing works generally provide large environments to monitor patients using sensors as simple transducers. Those devices forward sensed health parameters to a main base station. This station collects received data and may perform some computations. In this paper, we perform some distributed tasks on the sensors. We propose a distributed algorithm, which allows to raise alarms under some initial rules to alert efficiently medical staff in case of critical situations without needless warnings. Each mote monitors a parameter. When this parameter reaches an abnormal value, the mote communicates with other motes in order to check if it is a ‘local' anomaly or if the patient is in an abnormal situation. In such cases an alarm is raised. We implemented our algorithm over a network of micaZ sensors running under TinyOS. The obtained results show promising perspectives.
ISSN: 1532-0626

hal-00519594
https://hal.archives-ouvertes.fr/hal-00519594
DOI : 10.1002/cpe.1583

Éditeur(s) : HAL CCSD
Résumé : International audience
The aim of this study is to suggest two automated techniques able to help medical staff to detect earlier than usual some diseases using wireless sensor networks (WSNs). In this context, a patient is equipped with physical sensors (for temperature, pressure, ..). This WSN will perform some computations and will run an alarm when a disease is suspected. The first technique uses a population protocol to handle data exchanged between motes and provides an efficient algorithm to suggest that a disease is diagnosed on a patient. The algorithm is distributed, i.e., the decision may be done by any mote dealing with the disease detection. The second technique uses a token algorithm where, some motes, denoted as masters. Each of them is in charge of deciding if a specific disease occurs. This technique is not totally distributed but enhances the network efficiency regarding to the energy consumption, the time execution and the number of exchanged messages.
Proceedings of The Ninth IEEE International Symposium on Networking Computing and Applications
Cambridge, MA, United States

hal-00519599
https://hal.archives-ouvertes.fr/hal-00519599

Éditeur(s) : HAL CCSD ACM
Résumé : International audience
This study presents two algorithms that count birds with wireless sensors equipped with microphones. Audio inputs are parametrized to get some kind of fingerprints which are used to recognize the song of the birds in a classification process. Afterward, counting algorithms derive an estimate of the number of singing birds in the habitat. Unlike traditional approaches which leverage the audio waveform to get the location of the targets, we use a trilateration technique on graphs derived from the detection of the birds. These graphs exhibit nice properties which enable the finding of the estimate in polynomial time. Further, experiments are conducted and confirmm the efficiency of our counting algorithms even in the presence of noise.
Proceedings of the 6th ACM symposium on Performance evaluation of wireless ad hoc, sensor, and ubiquitous networks
New York, United States

hal-00602263
https://hal.archives-ouvertes.fr/hal-00602263
DOI : 10.1145/1641876.1641891

Éditeur(s) : HAL CCSD
Résumé : International audience
In this paper we study how to detect anomalies in a distributed manner by using wireless sensor networks (WSN). We focus on a medical context, where existing works generally provide large environments to monitor patients using sensors as simple transducers. Those devices forward sensed health parameters to a main base station. This station collects received data and may perform some computations. In this paper, we perform some distributed tasks on the sensors. We propose a distributed algorithm which allows to raise alarms under some initial rules to alert efficiently medical staff in case of critical situations without needles warnings.
10th IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks, WOWMOM 2009.
KOS, Greece

hal-00519589
https://hal.archives-ouvertes.fr/hal-00519589

Éditeur(s) : Elsevier
Résumé : Sea cruises were conducted for 57 days over 16 months to characterise pelagic fish aggregations around 2 moored fish aggregating devices (FADs) in Martinique (Lesser Antilles). Echosounder surveys run in a star pattern were used in conjunction with obliquely beamed sonar observations. An echo-integration-by-shoal algorithm was implemented to isolate pelagic fish shoals from sound scattering layers and to compute mean morphometric, positional and density parameters. Tree regressions were used to select and classify pelagic fish Target Strengths (TS), with reference to their spatial and temporal characteristics. The main type of pelagic fish aggregation was a large sub-surface aggregation. It was observed during all daytime periods within a radius of 400 m of the FAD. A smaller type of aggregation was observed closer to the surface and to the FAD in 65% of daytime periods. Large scattered fish were observed in 16% of daytime periods. At night, a medium-sized aggregation was detected in the sub-surface in 75% of night-time periods. The sizes of the fish inside the aggregations (determined from TS values) were lower in the small near-surface aggregation than in the large sub-surface aggregation. Mean packing densities of sub-surface medium fish and near-surface small fish aggregations (determined from TS and shoal acoustic density) were respectively 0.2 fish per m3 and 1.3 fish per m3. The acoustic methodology and results are discussed with reference to the characteristics and performance of the echosounder and to the spatial structure of pelagic fish aggregations around moored FADs in Martinique.
Fisheries Research (0165-7836) (Elsevier), 2006-06 , Vol. 82 , N. 1-3 , P. 162-175

Droits : Elsevier 2006
http://archimer.ifremer.fr/doc/2006/publication-1734.pdf
DOI:10.1016/j.fishres.2006.06.025
http://archimer.ifremer.fr/doc/00000/1734/

Éditeur(s) : HAL CCSD
Résumé : International audience
The aim of this study is to suggest an automated technique for distributed decision. It is based on protocol population deployed on Wireless Sensor Networks (WSN). This approach is able to help medical staff to detect earlier than usual some diseases on patients. It could be easily adapted for many other fields (fire monitoring, environment supervising, ...) In this context, a patient is equipped with health parameter transducers which are connected to a WSN. This WSN will perform some computations and raise an alarm when some diseases are suspected. The algorithm is distributed, i.e., the decision may be done by any mote dealing with the disease detection. The experimentations show promising results.
a venir
Denver, Colorado, United States

hal-00519597
https://hal.archives-ouvertes.fr/hal-00519597

Résumé : Ce travail vise à mettre en place un système de fusion de sources d'information basé sur la Théorie des Fonctions de Croyance (TFC) et adapté aux contextes des images forestières. La TFC engendre des temps de calcul importants lorsque la cardinalité du cadre de discernement devient grande. Ainsi, nous avons proposé en premier lieu une méthode de réduction du référentiel de définition permettant d'éviter l'explosion combinatoire en restreignant le calcul sur les hypothèses estimées pertinentes et déterminées à partir des histogrammes des classes issues de la phase d'apprentissage. Ensuite, nous avons proposé des techniques d'estimation de fonctions de masse spectrales, texturales, contextuelles et structurelles. L'information multi-fractale a été utilisée comme signature de texture, ainsi l'image de Hôlder a constitué une source d'information pour l'estimation de la masse texturale. Un autre apport consiste à proposer une approche de transfert de masse basée sur l'information contextuelle, en exploitant l'image des couronnes d'arbres comme une source déduite. L'implémentation d'algorithmes de détection de couronnes d'arbres nous a permis d'extraire des mesures sur les couronnes que nous avons utilisées en tant qu'attributs pour l'estimation des fonctions de masse. Nos expérimentations montrent des taux de classification assez satisfaisants et une adéquation de notre approche de fusion à une classification à l'arbre près
This thesis aims to develop an information source fusion system based on belief functions theory (BFT) and adapted t forest images context (especially high resolution images). Applications of BFT to image classification result in th assignment of each image point to a c1ass or a subset of classes based on the mass functions estimation expressing th belief of an event. BFT leads to significant computation time when the cardinality of the set of definition become large. Thus, we first proposed a method to reduce the frame of discernment in order te avoid the combinatorial explosio by restricting the calculation on the hypotheses of the set of definition deduced from the classes histograms determine from the learning phase. Then, we proposed spectral, texturai, contextual and structural mass functions technique estimation. Multi-fractal information was used as texture signature and Hôlder image has been a source ( information for estimating the texturai mass. Another contribution is the integration of trees crowns image as derive source and the proposai of an approach to mass transfer based on contextual information inside and outside a crown. Th implementation of detection trees crowns algorithms allowed us to extract measurements on trees. These measurement are used as attributes for mass functions estimation. Our experiments and comparisons with other methods show quit satisfactory classification rate with spectral and textural approaches and adequacy of our fusion approach to contextu and structural information for trees classification

http://www.theses.fr/2011AGUY0434/document

Éditeur(s) : HAL CCSD
Résumé : International audience
“Affective Computing is computing that relates to, arises from, or deliberately influences emotions” (R.W. Picard, MIT Press, 1997). Specifically, psychosocial equilibrium is now considered as a major issue for both individual and public health. Predicting human emotions via non-intrusive methods is a great challenge triggered by the rise of intelligent assisting systems. In order to determine the emotional state of a subject having a potential psychosocial disorder, it is required to process both neutral and expressive emotions. A computer-engineered method aiming to provide emotional information from videos is proposed. An original approach for affect classification and its interpretation is presented.The database is part of the HUMAINE database, and consists of a large volume of video clips, each displaying individuals, depressed or not, talking with a conversational agent. Both the high-dimensionality of data and its temporal aspect require a pre-training that consists of cleaning, sorting and feature selection, in order to make relevant information usable for further processing by MachineLearning methods. Next step consists in classifying the affective state of subjects according to their positivity or negativity (Russell's model, 1980). By means of six independent classifiers, each running a Support Vector Machine algorithm, separate performances are obtained for each class of emotions. The results reveal an interesting “neutral area phenomenon”, where emotions tend to be harder to be detected.Though more frequent, neutral emotions seem to carry less discriminant information than expressive ones. This issue will be a key for designing a tuning step in further research.
Caribbean Academy Of Science
Deshaies, France

hal-01408029
https://hal.univ-antilles.fr/hal-01408029

Éditeur(s) : HAL CCSD
Résumé : International audience
The aim of this study is to perform a simulation of large scale Wireless Sensor Networks (WSN) working on medical diagnosis. The main feature of this WSN is its density and the fact that all sensors are in the same radio range. Our approach helps medical staff to diagnose diseases in an automatic way. In this context, each patient is equipped to a set of sensors. Each sensor is connected to a transducer dedicated to measure a specific health parameter . This WSN will perform some computations and run an alarm when some diseases are suspected. This technique is based on the population protocol to handle data exchanged between sensors. This approach is in fact an efficient distributed algorithm which implies that the diagnose may be done by any sensor dealing with the disease detection. The main result of this paper is: the method supports large scalability which proves its practicability for real cases.
Computers and Communications (ISCC), 2010 IEEE Symposium on Computers and Communications.
Riccione, Italy

hal-00519595
https://hal.archives-ouvertes.fr/hal-00519595

Éditeur(s) : HAL CCSD Oxford University Press (OUP)
Résumé : International audience
Defining homologous genes is important in many evolutionary studies but raises obvious issues. Some of these issues are conceptual and stem from our assumptions of how a gene evolves, others are practical, and depend on the algorithmic decisions implemented in existing software. Therefore, to make progress in the study of homology, both ontological and epistemological questions must be considered. In particular, defining homologous genes cannot be solely addressed under the classic assumptions of strong tree thinking, according to which genes evolve in a strictly tree-like fashion of vertical descent and divergence and the problems of homology detection are primarily methodological. Gene homology could also be considered under a different perspective where genes evolve as ``public goods,'' subjected to various introgressive processes. In this latter case, defining homologous genes becomes a matter of designing models suited to the actual complexity of the data and how such complexity arises, rather than trying to fit genetic data to some a priori tree-like evolutionary model, a practice that inevitably results in the loss of much information. Here we show how important aspects of the problems raised by homology detection methods can be overcome when even more fundamental roots of these problems are addressed by analyzing public goods thinking evolutionary processes through which genes have frequently originated. This kind of thinking acknowledges distinct types of homologs, characterized by distinct patterns, in phylogenetic and nonphylogenetic unrooted or multirooted networks. In addition, we define `` family resemblances'' to include genes that are related through intermediate relatives, thereby placing notions of homology in the broader context of evolutionary relationships. We conclude by presenting some payoffs of adopting such a pluralistic account of homology and family relationship, which expands the scope of evolutionary analyses beyond the traditional, yet relatively narrow focus allowed by a strong tree-thinking view on gene evolution.
ISSN: 0737-4038

hal-01544794
https://hal.archives-ouvertes.fr/hal-01544794
DOI : 10.1093/molbev/mst228

Éditeur(s) : HAL CCSD European Geosciences Union
Résumé : International audience
Natural disturbances are the dominant form of forest regeneration and dynamics in unmanaged tropical forests. Monitoring the size distribution of treefall gaps is important to better understand and predict the carbon budget in response to land use and other global changes. In this study, we model the size frequency distribution of natural canopy gaps with a discrete power law distribution. We use a Bayesian framework to introduce and test, using Monte Carlo Markov chain and Kuo–Mallick algorithms, the effect of local physical environment on gap size distribution. We apply our methodological framework to an original light detecting and ranging dataset in which natural forest gaps were delineated over 30 000 ha of unmanaged forest. We highlight strong links between gap size distribution and environment, primarily hydrological conditions and topography, with large gaps being more frequent on floodplains and in wind-exposed areas. In the future, we plan to apply our methodological framework on a larger scale using satellite data. Additionally , although gap size distribution variation is clearly under environmental control, variation in gap size distribution in time should be tested against climate variability.
ISSN: 1726-4170

hal-01590729
https://hal-univ-guyane.archives-ouvertes.fr/hal-01590729
https://hal-univ-guyane.archives-ouvertes.fr/hal-01590729/document
https://hal-univ-guyane.archives-ouvertes.fr/hal-01590729/file/bg-14-353-2017.pdf
DOI : 10.5194/bg-14-353-2017