Parametric estimation of complex mixed models based on meta-model approach

Complex biological processes are usually experimented along time among a collection of individuals. Longitudinal data are then available and the statistical challenge is to better understand the underlying biological mechanisms. The standard statistical approach is mixed-effects model, with regression functions that are now highly-developed to describe precisely the biological processes (solutions of multi-dimensional ordinary differential equations or of partial differential equation). When there is no analytical solution, a classical estimation approach relies on the coupling of a stochastic version of the EM algorithm (SAEM) with a MCMC algorithm. This procedure needs many evaluations of the regression function which is clearly prohibitive when a time-consuming solver is used for computing it. In this work a meta-model relying on a Gaussian process emulator is proposed to replace this regression function. The new source of uncertainty due to this approximation can be incorporated in the model which leads to what is called a mixed meta-model. A control on the distance between the maximum likelihood estimates in this mixed meta-model and the maximum likelihood estimates obtained with the exact mixed model is guaranteed. Eventually, numerical simulations are performed to illustrate the efficiency of this approach

Parametric estimation of complex mixed models based on meta-model approach

International audienceComplex biological processes are usually experimented along time among a collection of individuals. Longitudinal data are then available and the statistical challenge is to better understand the underlying biological mechanisms. The standard statistical approach is mixed-effects model, with regression functions that are now highly-developed to describe precisely the biological processes (solutions of multi-dimensional ordinary differential equations or of partial differential equation). When there is no analytical solution, a classical estimation approach relies on the coupling of a stochastic version of the EM algorithm (SAEM) with a MCMC algorithm. This procedure needs many evaluations of the regression function which is clearly prohibitive when a time-consuming solver is used for computing it. In this work a meta-model relying on a Gaussian process emulator is proposed to replace this regression function. The new source of uncertainty due to this approximation can be incorporated in the model which leads to what is called a mixed meta-model. A control on the distance between the maximum likelihood estimates in this mixed meta-model and the maximum likelihood estimates obtained with the exact mixed model is guaranteed. Eventually, numerical simulations are performed to illustrate the efficiency of this approach

HDR-ARtiSt: A 1280x1024-pixel Adaptive Real-time Smart camera for High Dynamic Range video

International audienceStandard cameras capture only a fraction of the information that is visible to the human visual system. This is specifically true for natural scenes including areas of low and high illumination due to transitions between sunlit and shaded areas. When capturing such a scene, many cameras are unable to store the full Dynamic Range (DR) resulting in low quality video where details are concealed in shadows or washed out by sunlight.The imaging technique that can overcome this problem is called HDR (High Dynamic Range) imaging. This paper describes a complete smart camera built around a standard off-the-shelf LDR (Low Dynamic Range) sensor and a Virtex 6 FPGA board. This smart camera called HDR-ARtiSt (High Dynamic Range Adaptive Real-time Smart camera) is able to produce a real-time HDR live video color stream by recording and combining multiple acquisitions of the same scene while varying the exposure time. This technique appears as one of the most appropriate and cheapest solution to enhance the dynamic range of real-life environments. HDR-ARtiSt embeds real-time multiple captures, HDR processing, data display and transfer of a HDR color video for a full sensor resolution (1280 × 1024 pixels) at 60 frames per second. The main contributions of this work are: (1) Multiple Exposure Control (MEC) dedicated to the smart image capture from the sensor with alternating three exposure times that are dynamically evaluated from frame to frame, (2) Multi-streaming Memory Management Unit (MMMU) dedicated to the memory read/write operations of the three parallel video streams

Hardware-based smart camera for recovering high dynamic range video from multiple exposures

International audienceIn many applications such as video surveillance or defect detection, the perception of information related to a scene is limited in areas with strong contrasts. The high dynamic range (HDR) capture technique can deal with these limitations. The proposed method has the advantage of automatically selecting multiple exposure times to make outputs more visible than fixed exposure ones. A real-time hardware implementation of the HDR technique that shows more details both in dark and bright areas of a scene is an important line of research. For this purpose, we built a dedicated smart camera that performs both capturing and HDR video processing from three exposures. What is new in our work is shown through the following points: HDR video capture through multiple exposure control, HDR memory management, HDR frame generation, and rep- resentation under a hardware context. Our camera achieves a real-time HDR video output at 60 fps at 1.3 mega- pixels and demonstrates the efficiency of our technique through an experimental result. Applications of this HDR smart camera include the movie industry, the mass-consumer market, military, automotive industry, and sur- veillanc

High Dynamic Range Adaptive Real-time Smart Camera: an overview of the HDR-ARTiST project

International audienceStandard cameras capture only a fraction of the information that is visible to the human visual system. This is specifically true for natural scenes including areas of low and high illumination due to transitions between sunlit and shaded areas. When capturing such a scene, many cameras are unable to store the full Dynamic Range (DR) resulting in low quality video where details are concealed in shadows or washed out by sunlight. The imaging technique that can overcome this problem is called HDR (High Dynamic Range) imaging. This paper describes a complete smart camera built around a standard off-the-shelf LDR (Low Dynamic Range) sensor and a Virtex-6 FPGA board. This smart camera called HDR-ARtiSt (High Dynamic Range Adaptive Real-time Smart camera) is able to produce a real-time HDR live video color stream by recording and combining multiple acquisitions of the same scene while varying the exposure time. This technique appears as one of the most appropriate and cheapest solution to enhance the dynamic range of real-life environments. HDR-ARtiSt embeds real-time multiple captures, HDR processing, data display and transfer of a HDR color video for a full sensor resolution (1280 1024 pixels) at 60 frames per second. The main contributions of this work are: (1) Multiple Exposure Control (MEC) dedicated to the smart image capture with alternating three exposure times that are dynamically evaluated from frame to frame, (2) Multi-streaming Memory Management Unit (MMMU) dedicated to the memory read/write operations of the three parallel video streams, corresponding to the different exposure times, (3) HRD creating by combining the video streams using a specific hardware version of the Devebecs technique, and (4) Global Tone Mapping (GTM) of the HDR scene for display on a standard LCD monitor

Étude comparative in vivo de la compression statique et dynamique sur des vertèbres caudales de rat : effets sur le taux de croissance et sur l’histomorphométrie de la plaque de croissance

RÉSUMÉ La croissance longitudinale des os a lieu au droit des plaques de croissance, tissus conjonctifs situés à l’extrémité des os et histologiquement divisés en trois zones (réserve, proliférative et hypertrophique). Alors que les chargements mécaniques sont essentiels pour la croissance normale des os, un chargement excessif peut mener à une croissance anormale. Ce phénomène réfère à la modulation mécanique de la croissance osseuse, impliquée dans la progression de nombreuses déformations musculosquelettiques et dans le développement de nouvelles approches minimalement invasives pour leur traitement. Ces nouvelles techniques sont basées sur la modulation de croissance locale et visent à préserver la croissance et la mobilité segmentaire. De nombreuses études in vivo ont investigué la réponse mécanobiogique de la plaque de croissance. Alors que les effets du chargement statique sur la croissance sont bien caractérisés, les études comparant les effets du chargement statique versus dynamique sont peu nombreuses et utilisent des chargements non contrôlés, non normalisés ou non équivalents. Ces limites méthodologiques pourraient être la cause des résultats contradictoires reportés dans la littérature. Basé sur nos connaissances, il n’est donc pas possible de déterminer quel type de régime, statique ou dynamique, offre le meilleur potentiel de modulation mécanique de croissance et présente le moins de dommages pour la plaque de croissance. L’objectif de cette étude est de caractériser et comparer les effets d’un chargement in vivo en compression statique et dynamique sur le taux de croissance osseuse et sur l’histomorphométrie de la plaque de croissance dans un modèle animal de rat. Vingt-quatre rats ont été aléatoirement répartis en quatre groupes: contrôle, sham, statique et dynamique. Aucune manipulation n’a été effectuée sur les rats du groupe contrôle tandis que les rats des autres groupes ont été opérés à l’âge de 28 jours, suite à une période d’acclimatation d’une semaine. Une compression normalisée a été appliquée sur la 7ème vertèbre caudale (Cd7), de manière soutenue pour le groupe statique (0,2 MPa - 0,0 Hz) et sinusoïdale (0,2 MPa ± 30% - 0,1 Hz) pour le groupe dynamique. Afin d’évaluer l’effet de la procédure chirurgicale, le groupe sham a également été opéré mais sans aucune application de charge. Deux injections de calcéine (marqueur de minéralisation active) ont été effectuées, cinq jours et deux jours avant le sacrifice. Les rats ont été euthanasiés à l’âge de 43 jours, après 15 jours d’expérience. Les vertèbres ont été----------ABSTRACT Longitudinal bone growth occurs at the end of bones, in growth plates, a connective tissue histologically divided into three zones (reserve, proliferative and hypertrophic). Loads are essential to normal bone growth, yet, if too elevated, these loads can result in abnormal growth. This phenomenon refers to the mechanical modulation of bone growth and is involved in the progression of several musculoskeletal deformities. This process also plays a key role in the development of new minimally invasive approaches for their treatment. These new techniques locally target the modulation of growth while preserving growth and segment motion. Several in vivo studies have examined the mechanobiological response of growth plates. While the effects of static loading are well characterized, the few reported static/dynamic comparative studies are using load parameters which are not well controlled, normalized or matched. These methodological limitations could explain inconsistent results currently reported in the literature. Based on our knowledge, it is not possible to determine which regimen, static or dynamic, provides the best growth modulation potential and the less detrimental effect on the growth plate histomorphometry. The aim of this in vivo study is to characterize and compare the effects of static versus dynamic compression on the growth rate and on the growth plate histomorphometry using a rat animal model. Twenty-four rats were randomly divided into four groups: control, sham, static and dynamic. Control rats underwent no manipulation while other rats were operated at 28 days old, following one week of acclimatization. A normalized compression was applied on the seventh caudal vertebra (Cd7). The load was sustained (0.2 MPa, 0.0 Hz) in the static group and sinusoidally oscillating (0.2 MPa ± 30%, 0.1 Hz) in the dynamic group. To determine the effects of the surgical procedure, sham rats were also operated but no load was applied. All rats were injected with calcein (a mineralizing bone label) five days and two days prior to euthanasia. The rats were euthanized at 43 days old, after a 15-day period. Vertebrae were immediately collected, processed and embedded in methylmetacrylate. The growth rate (measured between the two calcein labels) and the histomorphometry of the growth plate (toluidine blue staining) were evaluated and compared in a statistical study

Iterative Search with Local Visual Features for Computer Assisted Plant Identification

To support computer assisted plant species identification in a realistic, uncontrolled picture-taking condition, we put forward an approach relying on local image features. It combines query by example and relevance feedback to support both the localization of potentially interesting image regions and the classification of these regions as representing or not the target species. We show that this approach is successful, and makes prior segmentation unnecessary

L'identification des adventices assistée par ordinateur avec le système IDAO

Identification of crop weeds is essential to get the information needed for elaborating efficient control methods. Non specialised people had difficulties to do this identification with classical tools, such as floras or field guides (too technical, unsuitable for seedlings or partial samples, process difficult to follow...). That brought us to develop a new system for plant recognition assisted by computer that was called IDAO (IDentification Assistée par Ordinateur). This software has the distinctive feature to use a graphical identification system by identikit. This identikit allows the user to build the image of the plant from traits freely chosen according to the specimen or to the user. It tolerates observation errors or polymorphism. Species are listed by their probability of similarity with the identikit. Descriptions, illustrations and information (biology, ecology, control...) are available at any time in local or online Html pages. These descriptive files can be regularly updated on the Web site. IDAO is a multilingual and multiplatform system. It can be used on PC (from cdrom or downloaded) or directly in the field on ultra mobile computer. Several applications have been published on weed floras of different cropping systems (rice, cotton, food crops, sugarcane...) and for different world areas (Africa, Asia, India, Indian Ocean), and also for other kinds of plants (trees, orchids...). The IDAO system will evolve during the Pl@ntnet project that will start in early 2009. IDAO will be available as free software on an Internet platform, for every body can develop by himself or under collaboration new applications available for all the user community. This identification system will be linked to an automatic recognition tool, using image analysis.L’identification des adventices d’une culture est une phase primordiale pour accéder à l’information nécessaire à l’élaboration de moyens de lutte performants. Les difficultés rencontrées par les non botanistes pour réaliser cette identification avec les outils classiques comme les flores ou les manuels (trop techniques, inefficaces pour les plantules ou les spécimens incomplets, processus difficile à suivre…) nous ont amené à développer un nouveau système de reconnaissance assistée par ordinateur appelé IDAO (IDentification Assistée par Ordinateur). Ce logiciel a la particularité d’utiliser un système d’identification graphique par portrait robot qui permet à l’utilisateur de construire l’image de la plante à partir de caractères choisis librement en fonction du spécimen ou de l’utilisateur et de tolérer les erreurs d’observation ou le polymorphisme. Les espèces sont listées en permanence en fonction de leur similitude avec ce portrait robot. Descriptions, illustrations et informations (biologie, écologie, lutte…) sont accessibles à tout moment sous la forme de pages au format Html disponibles localement ou sur un site Internet, et donc régulièrement actualisables. IDAO est multilingue et multiplateformes informatique. Il peut être utilisé sur PC (installable à partir de cdrom ou téléchargeable) ou directement au champ sur ordinateur ultra mobile. Une série d’applications a déjà été développée pour des flores de différents systèmes de cultures (riz, cotonnier, vivrier, canne à sucre…) et de différentes régions du monde (Afrique, Inde, Asie, Océan Indien) ainsi que pour d’autres types de plantes (arbres, orchidées…). Le système IDAO va évoluer dans le cadre du projet Pl@ntnet qui démarrera début 2009. Il sera mis à disposition sous forme de logiciel libre sur une plateforme Internet permettant ainsi à tout utilisateur de développer seul ou en partenariat une application et de la mettre à disposition de la communauté d’utilisateurs. Ce système d’identification sera associé à un outil de reconnaissance automatique par analyse d’images

DATA ASSIMILATION ON A FLOOD WAVE PROPAGATION MODEL : EMULATION OF A KALMAN FILTER ALGORITHM

International audienceThis study describes the assimilation of synthetically-generated river water level observations in a flood wave propagation model. For this approach to be applied in the framework of real-time flood forecasting, the cost of the data assimilation procedure, mostly related to the estimation of the background error covariance matrix, should be bound. An Ensemble Kalman Filter (EnKF) algorithm is applied, with a steady observation network, to demonstrate how the assimilation modifies the background correlation function at the observation point. It is shown that an initially Gaussian correlation function turns into an anisotropic function at the observation point, with a shorter correlation length-scale downstream of the observation point than upstream, and that the variance of the error in the water level state is significantly reduced downstream of the observation point. The covariance matrix resulting from the EnKF is then used as an invariant background error covariance matrix for a series of successive Best Linear Unbiased Estimation (BLUE) algorithms which emulate an EnKF at a lower cost. This study shows how the background error covariance matrix can be computed off-line, with an advanced algorithm, and then used with a cheaper algorithm for real-time application