Kernel-based Mapping of Meteorological Fields in Complex Orography

Due to the advances in sensor networks and remote sensing technologies, the acquisition and storage rates of meteorological and climatological data increases every day and ask for novel and efficient processing algorithms. A fundamental problem of data analysis and modeling is the spatial prediction of meteorological variables in complex orography, which serves among others to extended climatological analyses, for the assimilation of data into numerical weather prediction models, for preparing inputs to hydrological models and for real time monitoring and short-term forecasting of weather.In this thesis, a new framework for spatial estimation is proposed by taking advantage of a class of algorithms emerging from the statistical learning theory. Nonparametric kernel-based methods for nonlinear data classification, regression and target detection, known as support vector machines (SVM), are adapted for mapping of meteorological variables in complex orography.With the advent of high resolution digital elevation models, the field of spatial prediction met new horizons. In fact, by exploiting image processing tools along with physical heuristics, an incredible number of terrain features which account for the topographic conditions at multiple spatial scales can be extracted. Such features are highly relevant for the mapping of meteorological variables because they control a considerable part of the spatial variability of meteorological fields in the complex Alpine orography. For instance, patterns of orographic rainfall, wind speed and cold air pools are known to be correlated with particular terrain forms, e.g. convex/concave surfaces and upwind sides of mountain slopes.Kernel-based methods are employed to learn the nonlinear statistical dependence which links the multidimensional space of geographical and topographic explanatory variables to the variable of interest, that is the wind speed as measured at the weather stations or the occurrence of orographic rainfall patterns as extracted from sequences of radar images. Compared to low dimensional models integrating only the geographical coordinates, the proposed framework opens a way to regionalize meteorological variables which are multidimensional in nature and rarely show spatial auto-correlation in the original space making the use of classical geostatistics tangled.The challenges which are explored during the thesis are manifolds. First, the complexity of models is optimized to impose appropriate smoothness properties and reduce the impact of noisy measurements. Secondly, a multiple kernel extension of SVM is considered to select the multiscale features which explain most of the spatial variability of wind speed. Then, SVM target detection methods are implemented to describe the orographic conditions which cause persistent and stationary rainfall patterns. Finally, the optimal splitting of the data is studied to estimate realistic performances and confidence intervals characterizing the uncertainty of predictions.The resulting maps of average wind speeds find applications within renewable resources assessment and opens a route to decrease the temporal scale of analysis to meet hydrological requirements. Furthermore, the maps depicting the susceptibility to orographic rainfall enhancement can be used to improve current radar-based quantitative precipitation estimation and forecasting systems and to generate stochastic ensembles of precipitation fields conditioned upon the orography.

Ambulatory gait analysis results after total knee arthroplasty : arguments for mobile or fixed bearing?

Background: Mobile-bearing knee replacements have some theoretical advantages over fixed-bearing devices. However, very few randomized controlled clinical trials have been published to date, and studies showed little clinical and subjective advantages for the mobile-bearing using traditional systems of scoring. The choice of the ideal outcome measure to assess total joint replacement remains a complex issue. However, gait analysis provides objective and quantifying evidences of treatment evaluation. Significant methodological advances are currently made in gait analysis laboratories and ambulatory gait devices are now available. The goal of this study was to provide gait parameters as a new objective method to assess total knee arthroplasty outcome between patients with fixed- and mobile-bearing, using an ambulatory device with minimal sensor configuration. Methods: This randomized controlled double-blind study included to date 31 patients: the gait signatures of 12 patients with mobile-bearing were compared to the gait signatures of 19 patients with fixed-bearing pre-operatively and post-operatively at 6 weeks, 3 months and 6 months. Each participant was asked to perform two walking trials of 30m long at his/her preferred speed and to complete a EQ-5D questionnaire, a WOMAC and Knee Society Score (KSS). Lower limbs rotations were measured by four miniature angular rate sensors mounted respectively, on each shank and thigh. Results: Better relative differences between pre-operative and post-operative 3 months and 6 months KSS (122% vs 34% at 3 months, 138% vs 36% at 6 months) and KSS function (154% vs 8% at 3 months, 183% vs 42% at 6 months) scores were observed for the fixed-bearing compared to the mobile-bearing. The same better improvements for fixed-bearing were also found with the range of knee angles (Affected side: 31% vs -5% at 3 months, 47% vs 5% at 6 months), (Unaffected side: 16% vs 5% at 3 months, 15% vs 6% at 6 months) and peak swing speeds of shank (Affected side: 18% vs -2% at 3 months, 30% vs 4% at 6 months), (Unaffected side: 8% vs -3% at 3 months, 7% vs 4% at 6 months). Conclusions: A new method for a portable system for gait analysis has been developed with very encouraging results regarding the objective outcome of total knee arthroplasty using mobile- and fixed-bearings.

Mobile or fixed bearing for total knee arthroplasty? Ambulatory gait analysis results

Background: Mobile-bearing knee replacements have some theoretical advantages over fixed-bearing devices. However, very few randomized controlled clinical trials have been published to date, and studies showed little clinical and subjective advantages for the mobile-bearing using traditional systems of scoring. The choice of the ideal outcome measure to assess total joint replacement remains a complex issue. However, gait analysis provides objective and quantifying evidences of treatment evaluation. Significant methodological advances are currently made in gait analysis laboratories and ambulatory gait devices are now available. The goal of this study was to provide gait parameters as a new objective method to assess total knee arthroplasty outcome between patients with fixed- and mobile-bearing, using an ambulatory device with minimal sensor configuration. This randomized controlled double-blind study included to date 14 patients: the gait signatures of four patients with mobile-bearing were compared to the gait signatures of nine patients with fixed-bearing pre-operatively and post-operatively at 6 weeks, 3 months and 6 months. Each participant was asked to perform two walking trials of 30m long at his/her preferred speed and to complete a EQ-5D questionnaire, a WOMAC and Knee Society Score (KSS). Lower limbs rotations were measured by four miniature angular rate sensors mounted respectively, on each shank and thigh. A new method for a portable system for gait analysis has been developed with very encouraging results regarding the objective outcome of total knee arthroplasty using mobile- and fixed-bearings.

Modular support for developing mobile ad hoc applications

Abstract This PhD thesis addresses the issue of alleviating the burden of developing ad hoc applications. Such applications have the particularity of running on mobile devices, communicating in a peer-to-peer manner and implement some proximity-based semantics. A typical example of such application can be a radar application where users see their avatar as well as the avatars of their friends on a map on their mobile phone. Such application become increasingly popular with the advent of the latest generation of mobile smart phones with their impressive computational power, their peer-to-peer communication capabilities and their location detection technology. Unfortunately, the existing programming support for such applications is limited, hence the need to address this issue in order to alleviate their development burden. This thesis specifically tackles this problem by providing several tools for application development support. First, it provides the location-based publish/subscribe service (LPSS), a communication abstraction, which elegantly captures recurrent communication issues and thus allows to dramatically reduce the code complexity. LPSS is implemented in a modular manner in order to be able to target two different network architectures. One pragmatic implementation is aimed at mainstream infrastructure-based mobile networks, where mobile devices can communicate through fixed antennas. The other fully decentralized implementation targets emerging mobile ad hoc networks (MANETs), where no fixed infrastructure is available and communication can only occur in a peer-to-peer fashion. For each of these architectures, various implementation strategies tailored for different application scenarios that can be parametrized at deployment time. Second, this thesis provides two location-based message diffusion protocols, namely 6Shot broadcast and 6Shot multicast, specifically aimed at MANETs and fine tuned to be used as building blocks for LPSS. Finally this thesis proposes Phomo, a phone motion testing tool that allows to test proximity semantics of ad hoc applications without having to move around with mobile devices. These different developing support tools have been packaged in a coherent middleware framework called Pervaho.

System-level Support for Mobile Ad hoc Communications: an Algorithmic & Practical Approach

A mobile ad hoc network (MANET) is a decentralized and infrastructure-less network. This thesis aims to provide support at the system-level for developers of applications or protocols in such networks. To do this, we propose contributions in both the algorithmic realm and in the practical realm. In the algorithmic realm, we contribute to the field by proposing different context-aware broadcast and multicast algorithms in MANETs, namely six-shot broadcast, six-shot multicast, PLAN-B and ageneric algorithmic approach to optimize the power consumption of existing algorithms. For each algorithm we propose, we compare it to existing algorithms that are either probabilistic or context-aware, and then we evaluate their performance based on simulations. We demonstrate that in some cases, context-aware information, such as location or signal-strength, can improve the effciency. In the practical realm, we propose a testbed framework, namely ManetLab, to implement and to deploy MANET-specific protocols, and to evaluate their performance. This testbed framework aims to increase the accuracy of performance evaluation compared to simulations, while keeping the ease of use offered by the simulators to reproduce a performance evaluation. By evaluating the performance of different probabilistic algorithms with ManetLab, we observe that both simulations and testbeds should be used in a complementary way. In addition to the above original contributions, we also provide two surveys about system-level support for ad hoc communications in order to establish a state of the art. The first is about existing broadcast algorithms and the second is about existing middleware solutions and the way they deal with privacy and especially with location privacy. - Un réseau mobile ad hoc (MANET) est un réseau avec une architecture décentralisée et sans infrastructure. Cette thèse vise à fournir un support adéquat, au niveau système, aux développeurs d'applications ou de protocoles dans de tels réseaux. Dans ce but, nous proposons des contributions à la fois dans le domaine de l'algorithmique et dans celui de la pratique. Nous contribuons au domaine algorithmique en proposant différents algorithmes de diffusion dans les MANETs, algorithmes qui sont sensibles au contexte, à savoir six-shot broadcast,six-shot multicast, PLAN-B ainsi qu'une approche générique permettant d'optimiser la consommation d'énergie de ces algorithmes. Pour chaque algorithme que nous proposons, nous le comparons à des algorithmes existants qui sont soit probabilistes, soit sensibles au contexte, puis nous évaluons leurs performances sur la base de simulations. Nous montrons que, dans certains cas, des informations liées au contexte, telles que la localisation ou l'intensité du signal, peuvent améliorer l'efficience de ces algorithmes. Sur le plan pratique, nous proposons une plateforme logicielle pour la création de bancs d'essai, intitulé ManetLab, permettant d'implémenter, et de déployer des protocoles spécifiques aux MANETs, de sorte à évaluer leur performance. Cet outil logiciel vise à accroître la précision desévaluations de performance comparativement à celles fournies par des simulations, tout en conservant la facilité d'utilisation offerte par les simulateurs pour reproduire uneévaluation de performance. En évaluant les performances de différents algorithmes probabilistes avec ManetLab, nous observons que simulateurs et bancs d'essai doivent être utilisés de manière complémentaire. En plus de ces contributions principales, nous fournissons également deux états de l'art au sujet du support nécessaire pour les communications ad hoc. Le premier porte sur les algorithmes de diffusion existants et le second sur les solutions de type middleware existantes et la façon dont elles traitent de la confidentialité, en particulier celle de la localisation.