Evaluating perceptual maps of asymmetries for gait symmetry quantification and pathology detection

Le mouvement de la marche est un processus essentiel de l'activité humaine et aussi le résultat de nombreuses interactions collaboratives entre les systèmes neurologiques, articulaires et musculo-squelettiques fonctionnant ensemble efficacement. Ceci explique pourquoi une analyse de la marche est aujourd'hui de plus en plus utilisée pour le diagnostic (et aussi la prévention) de différents types de maladies (neurologiques, musculaires, orthopédique, etc.). Ce rapport présente une nouvelle méthode pour visualiser rapidement les différentes parties du corps humain liées à une possible asymétrie (temporellement invariante par translation) existant dans la démarche d'un patient pour une possible utilisation clinique quotidienne. L'objectif est de fournir une méthode à la fois facile et peu dispendieuse permettant la mesure et l'affichage visuel, d'une manière intuitive et perceptive, des différentes parties asymétriques d'une démarche. La méthode proposée repose sur l'utilisation d'un capteur de profondeur peu dispendieux (la Kinect) qui est très bien adaptée pour un diagnostique rapide effectué dans de petites salles médicales car ce capteur est d'une part facile à installer et ne nécessitant aucun marqueur. L'algorithme que nous allons présenter est basé sur le fait que la marche saine possède des propriétés de symétrie (relativement à une invariance temporelle) dans le plan coronal.

FPGA-based object detection using classification circuits

Dans l'apprentissage machine, la classification est le processus d’assigner une nouvelle observation à une certaine catégorie. Les classifieurs qui mettent en œuvre des algorithmes de classification ont été largement étudié au cours des dernières décennies. Les classifieurs traditionnels sont basés sur des algorithmes tels que le SVM et les réseaux de neurones, et sont généralement exécutés par des logiciels sur CPUs qui fait que le système souffre d’un manque de performance et d’une forte consommation d'énergie. Bien que les GPUs puissent être utilisés pour accélérer le calcul de certains classifieurs, leur grande consommation de puissance empêche la technologie d'être mise en œuvre sur des appareils portables tels que les systèmes embarqués. Pour rendre le système de classification plus léger, les classifieurs devraient être capable de fonctionner sur un système matériel plus compact au lieu d'un groupe de CPUs ou GPUs, et les classifieurs eux-mêmes devraient être optimisés pour ce matériel. Dans ce mémoire, nous explorons la mise en œuvre d'un classifieur novateur sur une plate-forme matérielle à base de FPGA. Le classifieur, conçu par Alain Tapp (Université de Montréal), est basé sur une grande quantité de tables de recherche qui forment des circuits arborescents qui effectuent les tâches de classification. Le FPGA semble être un élément fait sur mesure pour mettre en œuvre ce classifieur avec ses riches ressources de tables de recherche et l'architecture à parallélisme élevé. Notre travail montre que les FPGAs peuvent implémenter plusieurs classifieurs et faire les classification sur des images haute définition à une vitesse très élevée.

Characterization of Selected Photonic Materials and Systems Using Photoacoustic Technique

The photoacoustic investigations carried out on different photonic materials are presented in this thesis. Photonic materials selected for the investigation are tape cast ceramics, muItilayer dielectric coatings, organic dye doped PVA films and PMMA matrix doped with dye mixtures. The studies are performed by the measurement of photoacoustic signal generated as a result of modulated cw laser irradiation of samples. The gas-microphone scheme is employed for the detection of photoacoustic signal. The different measurements reported here reveal the adaptability and utility of the PA technique for the characterization of photonic materials.Ceramics find applications in the field of microelectronics industry. Tape cast ceramics are the building blocks of many electronic components and certain ceramic tapes are used as thermal barriers. The thermal parameters of these tapes will not be the same as that of thin films of the same materials. Parameters are influenced by the presence of foreign bodies in the matrix and the sample preparation technique. Measurements are done on ceramic tapes of Zirconia, Zirconia-Alumina combination, barium titanate, barium tin titanate, silicon carbide, lead zirconate titanateil'Z'T) and lead magnesium niobate titanate(PMNPT). Various configurations viz. heat reflection geometry and heat transmission geometry of the photoacoustic technique have been used for the evaluation of different thermal parameters of the sample. Heat reflection geometry of the PA cell has been used for the evaluation of thermal effusivity and heat transmission geometry has been made use of in the evaluation of thermal diffusivity. From the thermal diffusivity and thermal effusivity values, thermal conductivity is also calculated. The calculated values are nearly the same as the values reported for pure materials. This shows the feasibility of photoacoustic technique for the thermal characterization of ceramic tapes.Organic dyes find applications as holographic recording medium and as active media for laser operations. Knowledge of the photochemical stability of the material is essential if it has to be used tor any of these applications. Mixing one dye with another can change the properties of the resulting system. Through careful mixing of the dyes in appropriate proportions and incorporating them in polymer matrices, media of required stability can be prepared. Investigations are carried out on Rhodamine 6GRhodamine B mixture doped PMMA samples. Addition of RhB in small amounts is found to stabilize Rh6G against photodegradation and addition of Rh6G into RhB increases the photosensitivity of the latter. The PA technique has been successfully employed for the monitoring of dye mixture doped PMMA sample. The same technique has been used for the monitoring of photodegradation ofa laser dye, cresyl violet doped polyvinyl alcohol also.Another important application of photoacoustic technique is in nondestructive evaluation of layered samples. Depth profiling capability of PA technique has been used for the non-destructive testing of multilayer dielectric films, which are highly reflecting in the wavelength range selected for investigations. Eventhough calculation of thickness of the film is not possible, number of layers present in the system can be found out using PA technique. The phase plot has clear step like discontinuities, the number of which coincides with the number of layers present in the multilayer stack. This shows the sensitivity of PA signal phase to boundaries in a layered structure. This aspect of PA signal can be utilized in non-destructive depth profiling of reflecting samples and for the identification of defects in layered structures.

Variation in radio refractivity index associated with formation of low - pressure systems

Numerous low - pressure systems form in the Arabian Sea and Bay of Bengal. These low-pressure systems are highly useful in bringing the rainfall over the Indian sub continent. The developments of these systems are accompanied by the reduction in air temperature and an increase in atmospheric humidity. The radio refractivity, which is a function of the atmospheric pressure, temperature and humidity, also changes following the development of these systems. Variation of radio refractive index and its vertical gradient are analysed for many low pressure systems formed over the Arabian Sea and Bay of Bengal. It is found that the atmosphere becomes super refractive associated with the formation of these systems, caused by the increase in humidity and decrease in temperature. The maximum gradient is observed near the surface layers, especially in the lowest 1 km. Super refraction leads to increased radar detection range and extension of radio horizon

Anomaly Detection Using System Call Sequence Sets.

This paper discusses our research in developing a generalized and systematic method for anomaly detection. The key ideas are to represent normal program behaviour using system call frequencies and to incorporate probabilistic techniques for classification to detect anomalies and intrusions. Using experiments on the sendmail system call data, we demonstrate that concise and accurate classifiers can be constructed to detect anomalies. An overview of the approach that we have implemented is provided.

Effectiveness Of Feature Detection Operators On The Performance Of Iris Biometric Recognition System

Iris Recognition is a highly efficient biometric identification system with great possibilities for future in the security systems area.Its robustness and unobtrusiveness, as opposed tomost of the currently deployed systems, make it a good candidate to replace most of thesecurity systems around. By making use of the distinctiveness of iris patterns, iris recognition systems obtain a unique mapping for each person. Identification of this person is possible by applying appropriate matching algorithm.In this paper, Daugman’s Rubber Sheet model is employed for irisnormalization and unwrapping, descriptive statistical analysis of different feature detection operators is performed, features extracted is encoded using Haar wavelets and for classification hammingdistance as a matching algorithm is used. The system was tested on the UBIRIS database. The edge detection algorithm, Canny, is found to be the best one to extract most of the iris texture. The success rate of feature detection using canny is 81%, False Accept Rate is 9% and False Reject Rate is 10%.

Hydrogeology and hydrochemistry of the aquifer systems of Kuttanad area, Kerala: Their role in understanding the evolution of groundwaters

This is an attempt to understand the important factors that control the occurrence, development and hydrochemical evolution of groundwater resources in sedimentary multi aquifer systems. The primary objective of this work is an integrated study of the hydrogeology and hydrochemistry with a view to elucidate the hydrochemical evolution of groundwater resources in the aquifer systems. The study is taken up in a typical coastal sedimentary aquifer system evolved under fluvio-marine environment in the coastal area of Kerala, known as the Kuttanad. The present study has been carried out to understand the aquifer systems, their inter relationships and evolution in the Kuttanad area of Kerala. The multi aquifer systems in the Kuttanad basin were formed from the sediments deposited under fluvio-marine and fluvial depositional environments and the marine transgressions and regressions in the geological past and palaeo climatic conditions influenced the hydrochemical environment in these aquifers. The evolution of groundwater and the hydrochemical processes involved in the formation of the present day water quality are elucidated from hydrochemical studies and the information derived from the aquifer geometry and hydraulic properties. Kuttanad area comprises of three types of aquifer systems namely phreatic aquifer underlain by Recent confined aquifer followed by Tertiary confined aquifers. These systems were formed by the deposition of sediments under fluvio-marine and fluvial environment. The study of the hydrochemical and hydraulic properties of the three aquifer systems proved that these three systems are separate entities. The phreatic aquifers in the area have low hydraulic gradients and high rejected recharge. The Recent confined aquifer has very poor hydraulic characteristics and recharge to this aquifer is very low. The Tertiary aquifer system is the most potential fresh water aquifer system in the area and the groundwater flow in the aquifer is converging towards the central part of the study area (Alleppey town) due to large scale pumping of water for water supply from this aquifer system. Mixing of waters and anthropogenic interferences are the dominant processes modifying the hydrochemistry in phreatic aquifers. Whereas, leaching of salts and cation exchange are the dominant processes modifying the hydrochemistry of groundwater in the confined aquifer system of Recent alluvium. Two significant chemical reactions modifying the hydrochemistry in the Recent aquifers are oxidation of iron in ferruginous clays which contributes hydrogen ions and the decomposition of organic matter in the aquifer system which consumes hydrogen ions. The hydrochemical environment is entirely different in the Tertiary aquifers as the groundwater in this aquifer system are palaeo waters evolved during various marine transgressions and regressions and these waters are being modified by processes of leaching of salts, cation exchange and chemical reactions under strong reducing environment. It is proved that the salinity observed in the groundwaters of Tertiary aquifers are not due to seawater mixing or intrusion, but due to dissolution of salts from the clay formations and ion exchange processes. Fluoride contamination in this aquifer system lacks a regional pattern and is more or less site specific in natureThe lowering of piezometric heads in the Tertiary aquifer system has developed as consequence of large scale pumping over a long period. Hence, puping from this aquifer system is to be regulated as a groundwater management strategy. Pumping from the Tertiary aquifers with high capacity pumps leads to well failures and mixing of saline water from the brackish zones. Such mixing zones are noticed from the hydrochemical studies. This is the major aquifer contamination in the Tertiary aquifer system which requires immediate attention. Usage of pumps above 10 HP capacities in wells taping Tertiary aquifers should be discouraged for sustainable development of these aquifers. The recharge areas need to be identified precisely for recharging the aquifer systems throughartificial means.

Trend detection in folksonomies

As the number of resources on the web exceeds by far the number of documents one can track, it becomes increasingly difficult to remain up to date on ones own areas of interest. The problem becomes more severe with the increasing fraction of multimedia data, from which it is difficult to extract some conceptual description of their contents. One way to overcome this problem are social bookmark tools, which are rapidly emerging on the web. In such systems, users are setting up lightweight conceptual structures called folksonomies, and overcome thus the knowledge acquisition bottleneck. As more and more people participate in the effort, the use of a common vocabulary becomes more and more stable. We present an approach for discovering topic-specific trends within folksonomies. It is based on a differential adaptation of the PageRank algorithm to the triadic hypergraph structure of a folksonomy. The approach allows for any kind of data, as it does not rely on the internal structure of the documents. In particular, this allows to consider different data types in the same analysis step. We run experiments on a large-scale real-world snapshot of a social bookmarking system.

Numerical Feasibility Study for Treated Wastewater Recharge as a Tool to Impede Saltwater Intrusion in the Coastal Aquifer of Gaza – Palestine

The ongoing depletion of the coastal aquifer in the Gaza strip due to groundwater overexploitation has led to the process of seawater intrusion, which is continually becoming a serious problem in Gaza, as the seawater has further invaded into many sections along the coastal shoreline. As a first step to get a hold on the problem, the artificial neural network (ANN)-model has been applied as a new approach and an attractive tool to study and predict groundwater levels without applying physically based hydrologic parameters, and also for the purpose to improve the understanding of complex groundwater systems and which is able to show the effects of hydrologic, meteorological and anthropogenic impacts on the groundwater conditions. Prediction of the future behaviour of the seawater intrusion process in the Gaza aquifer is thus of crucial importance to safeguard the already scarce groundwater resources in the region. In this study the coupled three-dimensional groundwater flow and density-dependent solute transport model SEAWAT, as implemented in Visual MODFLOW, is applied to the Gaza coastal aquifer system to simulate the location and the dynamics of the saltwater–freshwater interface in the aquifer in the time period 2000-2010. A very good agreement between simulated and observed TDS salinities with a correlation coefficient of 0.902 and 0.883 for both steady-state and transient calibration is obtained. After successful calibration of the solute transport model, simulation of future management scenarios for the Gaza aquifer have been carried out, in order to get a more comprehensive view of the effects of the artificial recharge planned in the Gaza strip for some time on forestall, or even to remedy, the presently existing adverse aquifer conditions, namely, low groundwater heads and high salinity by the end of the target simulation period, year 2040. To that avail, numerous management scenarios schemes are examined to maintain the ground water system and to control the salinity distributions within the target period 2011-2040. In the first, pessimistic scenario, it is assumed that pumping from the aquifer continues to increase in the near future to meet the rising water demand, and that there is not further recharge to the aquifer than what is provided by natural precipitation. The second, optimistic scenario assumes that treated surficial wastewater can be used as a source of additional artificial recharge to the aquifer which, in principle, should not only lead to an increased sustainable yield of the latter, but could, in the best of all cases, revert even some of the adverse present-day conditions in the aquifer, i.e., seawater intrusion. This scenario has been done with three different cases which differ by the locations and the extensions of the injection-fields for the treated wastewater. The results obtained with the first (do-nothing) scenario indicate that there will be ongoing negative impacts on the aquifer, such as a higher propensity for strong seawater intrusion into the Gaza aquifer. This scenario illustrates that, compared with 2010 situation of the baseline model, at the end of simulation period, year 2040, the amount of saltwater intrusion into the coastal aquifer will be increased by about 35 %, whereas the salinity will be increased by 34 %. In contrast, all three cases of the second (artificial recharge) scenario group can partly revert the present seawater intrusion. From the water budget point of view, compared with the first (do nothing) scenario, for year 2040, the water added to the aquifer by artificial recharge will reduces the amount of water entering the aquifer by seawater intrusion by 81, 77and 72 %, for the three recharge cases, respectively. Meanwhile, the salinity in the Gaza aquifer will be decreased by 15, 32 and 26% for the three cases, respectively.

ACTORS: A Model of Concurrent Computation in Distributed Systems

A foundational model of concurrency is developed in this thesis. We examine issues in the design of parallel systems and show why the actor model is suitable for exploiting large-scale parallelism. Concurrency in actors is constrained only by the availability of hardware resources and by the logical dependence inherent in the computation. Unlike dataflow and functional programming, however, actors are dynamically reconfigurable and can model shared resources with changing local state. Concurrency is spawned in actors using asynchronous message-passing, pipelining, and the dynamic creation of actors. This thesis deals with some central issues in distributed computing. Specifically, problems of divergence and deadlock are addressed. For example, actors permit dynamic deadlock detection and removal. The problem of divergence is contained because independent transactions can execute concurrently and potentially infinite processes are nevertheless available for interaction.

A Trainable Object Detection System: Car Detection in Static Images

This paper describes a general, trainable architecture for object detection that has previously been applied to face and peoplesdetection with a new application to car detection in static images. Our technique is a learning based approach that uses a set of labeled training data from which an implicit model of an object class -- here, cars -- is learned. Instead of pixel representations that may be noisy and therefore not provide a compact representation for learning, our training images are transformed from pixel space to that of Haar wavelets that respond to local, oriented, multiscale intensity differences. These feature vectors are then used to train a support vector machine classifier. The detection of cars in images is an important step in applications such as traffic monitoring, driver assistance systems, and surveillance, among others. We show several examples of car detection on out-of-sample images and show an ROC curve that highlights the performance of our system.

Robust fault detection using consistency techniques for uncertainty handling

Often practical performance of analytical redundancy for fault detection and diagnosis is decreased by uncertainties prevailing not only in the system model, but also in the measurements. In this paper, the problem of fault detection is stated as a constraint satisfaction problem over continuous domains with a big number of variables and constraints. This problem can be solved using modal interval analysis and consistency techniques. Consistency techniques are then shown to be particularly efficient to check the consistency of the analytical redundancy relations (ARRs), dealing with uncertain measurements and parameters. Through the work presented in this paper, it can be observed that consistency techniques can be used to increase the performance of a robust fault detection tool, which is based on interval arithmetic. The proposed method is illustrated using a nonlinear dynamic model of a hydraulic system

Dam wall detection and tracking using a Mechanically Scanned Imaging Sonar

In dam inspection tasks, an underwater robot has to grab images while surveying the wall meanwhile maintaining a certain distance and relative orientation. This paper proposes the use of an MSIS (mechanically scanned imaging sonar) for relative positioning of a robot with respect to the wall. An imaging sonar gathers polar image scans from which depth images (range & bearing) are generated. Depth scans are first processed to extract a line corresponding to the wall (with the Hough transform), which is then tracked by means of an EKF (Extended Kalman Filter) using a static motion model and an implicit measurement equation associating the sensed points to the candidate line. The line estimate is referenced to the robot fixed frame and represented in polar coordinates (rho&thetas) which directly corresponds to the actual distance and relative orientation of the robot with respect to the wall. The proposed system has been tested in simulation as well as in water tank conditions

SQualTrack: A Tool for Robust Fault Detection

One of the techniques used to detect faults in dynamic systems is analytical redundancy. An important difficulty in applying this technique to real systems is dealing with the uncertainties associated with the system itself and with the measurements. In this paper, this uncertainty is taken into account by the use of intervals for the parameters of the model and for the measurements. The method that is proposed in this paper checks the consistency between the system's behavior, obtained from the measurements, and the model's behavior; if they are inconsistent, then there is a fault. The problem of detecting faults is stated as a quantified real constraint satisfaction problem, which can be solved using the modal interval analysis (MIA). MIA is used because it provides powerful tools to extend the calculations over real functions to intervals. To improve the results of the detection of the faults, the simultaneous use of several sliding time windows is proposed. The result of implementing this method is semiqualitative tracking (SQualTrack), a fault-detection tool that is robust in the sense that it does not generate false alarms, i.e., if there are false alarms, they indicate either that the interval model does not represent the system adequately or that the interval measurements do not represent the true values of the variables adequately. SQualTrack is currently being used to detect faults in real processes. Some of these applications using real data have been developed within the European project advanced decision support system for chemical/petrochemical manufacturing processes and are also described in this paper

Fault diagnosis by refining the parameter uncertainty space of nonlinear dynamic systems

This paper deals with fault detection and isolation problems for nonlinear dynamic systems. Both problems are stated as constraint satisfaction problems (CSP) and solved using consistency techniques. The main contribution is the isolation method based on consistency techniques and uncertainty space refining of interval parameters. The major advantage of this method is that the isolation speed is fast even taking into account uncertainty in parameters, measurements, and model errors. Interval calculations bring independence from the assumption of monotony considered by several approaches for fault isolation which are based on observers. An application to a well known alcoholic fermentation process model is presented