<p>Vulnerabilities discovered in software are not only due to programming errors but also due to designflaws. There are a number of methods to avoid design flaws which are all manual processes and needexpertise. We believe that the study of models of classes of vulnerabilities would give developerssufficient knowledge in how to avoid these vulnerabilities. A model of class of vulnerability can alsohelp in the decision making process during the software development process.In this thesis, we present a procedure for modeling a class of vulnerabilities given instances ofVulnerability Cause Graphs (VCGs). Using VCGs will structure the representation of causes tovulnerabilities.The approach presented in this thesis makes it possible to divide the work of modeling a class ofvulnerability without any permanent dependence on any specific persons. The approach is also flexible enough to accommodate new causes of vulnerabilities in software when being discovered.</p>

Vulnerabilities discovered in software are not only due to programming errors but also due to designflaws. There are a number of methods to avoid design flaws which are all manual processes and needexpertise. We believe that the study of models of classes of vulnerabilities would give developerssufficient knowledge in how to avoid these vulnerabilities. A model of class of vulnerability can alsohelp in the decision making process during the software development process.In this thesis, we present a procedure for modeling a class of vulnerabilities given instances ofVulnerability Cause Graphs (VCGs). Using VCGs will structure the representation of causes tovulnerabilities.The approach presented in this thesis makes it possible to divide the work of modeling a class ofvulnerability without any permanent dependence on any specific persons. The approach is also flexible enough to accommodate new causes of vulnerabilities in software when being discovered.

This dissertation is directed towards improving the state of art cardiac monitoring methods and automatic diagnosis of cardiac anomalies through modern engineering approaches such as adaptive signal processing, and machine learning methods. The dissertation will describe the invention and associated methods of a cardiac rhythm monitor dubbed the Integrated Vectorcardiogram (iVCG). In addition, novel machine learning approaches are discussed to improve diagnoses and prediction accuracy of cardiac diseases. It is estimated that around 17 million people in the world die from cardiac related events each year. It has also been shown that many of such deaths can be averted with long-term continuous monitoring and actuation. Hence, there is a growing need for better cardiac monitoring solutions. Leveraging the improvements in computational power, communication bandwidth, energy efficiency and electronic chip size in recent years, the Integrated Vectorcardiogram (iVCG) was invented as an answer to this problem. The iVCG is a miniaturized, integrated version of the Vectorcardiogram that was invented in the 1930s. The Vectorcardiogram provides full diagnostic quality cardiac information equivalent to that of the gold standard, 12-lead ECG, which is restricted to in-office use due to its bulky, obtrusive form. With the iVCG, it is possible to provide continuous, long-term, full diagnostic quality information, while being portable and unobtrusive to the patient. Moreover, it is possible to leverage this ‘Big Data’ and create machine learning algorithms to deliver better patient outcomes in the form of patient specific machine diagnosis and timely alerts. First, we present a proof-of-concept investigation for a miniaturized vectorcardiogram, the iVCG system for ambulatory on-body applications that continuously monitors the electrical activity of the heart in three dimensions. We investigate the minimum distance between a pair of leads in the X, Y and Z axes such that the signals are distinguishable from the noise. The target dimensions for our prototype iVCG are 3x3x2 cm and based on our experimental results we show that it is possible to achieve these dimensions. Following this, we present a solution to the problem of transforming the three VCG component signals to the familiar 12-lead ECG for the convenience of cardiologists. The least squares (LS) method is employed on the VCG signals and the reference (training) 12-lead ECG to obtain a 12x3 transformation matrix to generate the real-time ECG signals from the VCG signals. The iVCG is portable and worn on the chest of the patient and although a physician or trained technician will initially install it in the appropriate position, it is prone to subsequent rotation and displacement errors introduced by the patient placement of the device. We characterize these errors and present a software solution to correct the effect of the errors on the iVCG signals. We also describe the design of machine learning methods to improve automatic diagnosis and prediction of various heart conditions. Methods very similar to the ones described in this dissertation can be used on the long term, full diagnostic quality ‘Big Data’ such that the iVCG will be able to provide further insights into the health of patients. The iVCG system is potentially breakthrough and disruptive technology allowing long term and continuous remote monitoring of patient’s electrical heart activity. The implications are profound and include 1) providing a less expensive device compared to the 12-lead ECG system (the “gold standard”); 2) providing continuous, remote tele-monitoring of patients; 3) the replacement of current Holter shortterm monitoring system; 4) Improved and economic ICU cardiac monitoring; 5) The ability for patients to be sent home earlier from a hospital since physicians will have continuous remote monitoring of the patients.

En dépit du développement rapide de la médecine, les maladies cardiovasculaires restent la première cause de mortalité dans le monde. En France, chaque année, plus de 50 000 personnes meurent subitement en raison d'arythmies cardiaques. L'identification des patients à risque élevé de décès soudain est toujours un défi. Pour détecter les arythmies cardiaques, actuellement Holter est généralement utilisé pour enregistrer les signaux électrocardiogramme (ECG) à 1~3 dérivations pendant 24h à 72h. Cependant l'utilisation de Holter est limitée parmi la population en raison de son encombrement (pas convivial) et de son coût. Un Holter mono puce portable nommé SoC-Holter qui permet d'enregistrer 1 à 4 dérivations est introduit. Le déploiement d'un réseau de capteurs sans fil exige que chaque SoC-Holter soit peu encombrant et peu cher, et consomme peu d’énergie. Afin de minimiser la consommation d'énergie et le coût du système, la technologie Complementary Metal Oxide Semiconductor (CMOS) (0.35μm) est utilisée pour la première implémentation de SoC-Holter. Puis une nouvelle méthode de détection basée sur Acquisition Comprimée (CS) est introduite pour résoudre les problèmes de consommation d'énergie et de capacité de stockage de SoC-Holter. Le principe premier de cette plate-forme est d'échantillonner les signaux ECG sous la fréquence de Nyquist ‘sub-Nyquist’ et par la suite de classer directement les mesures compressées en états normal et anormal. Minimiser le nombre de fils qui relient les électrodes à la plate-forme peut rendre l’utilisateur de SoC-Holter plus confortable, car deux électrodes sont très proches sur la surface du corps. La différence ECG enregistrée est analysée à l'aide de Vectocardiogramme (VCG). Les résultats expérimentaux montrent qu'une approche intégrée, à faible coût et de faible encombrement (SoC-Holter) est faisable. Le SoC-Holter consomme moins de 10mW en fonctionnement. L'estimation des paramètres du signal acquis est effectuée directement à partir de mesures compressées, éliminant ainsi l'étape de la reconstruction et réduisant la complexité et le volume des calculs. En outre, le système fournit les signaux ECG compressés sans perte d'information, de ce fait il réduit significativement la consommation d'énergie pour l'envoi de message et l’espace de stockage mémoire. L'effet de placement des électrodes est évalué sur la QRS complexe lorsqu'il a enregistré avec deux électrodes adjacentes. La méthode est basée sur l'algorithme de ‘QRS-VCG loop alignment’. La méthode moindre carré est utilisée pour estimer la corrélation entre une boucle VCG observée et une boucle de référence en respectant les transformations de rotation et la synchronisation du temps. Les emplacements d'électrodes les moins sensibles aux interférences sont étudiés. / According to the figures released by World Health Organization (WHO), cardiovascular disease is the number one cause of death in the world. In France every year more than 50,000 people die suddenly due cardiac arrhythmias. Identification of high risk sudden death patients is still a challenge. To detect cardiac arrhythmias, currently Holter is generally used to record 1~4 leads electrocardiogram (ECG) signals during 24h to 72h. However the use of Holter is limited among the population due to its form factor (not user-friendly) and cost. An integrated single chip wearable Holter named SoC-Holter that enables to record 1 to 4 leads ECG is introduced. Deployment of wireless sensor network requires each SoC-Holter with less power consumption, low-cost charging system and less die area.To minimize energy consumption and system cost, Complementary Metal Oxide Semiconductor (CMOS) technology (0.35μm) is used to prototype the first implementation of SoC-Holter. Then a novel method based on Compressed Sensing (CS) technique is introduced for solving the problems of power consumption and storage capacity of SoC-Holter. The main principle underlying this framework is to sample analog signals at sub-Nyquist rate and to classify directly compressed measurement into normal and abnormal state. Minimizing the wire connected electrodes to the platform can make the carrier more comfortable because two electrodes are attached closely on the surface of the body. Recording difference ECG is analyzed using Vectorcardiogram (VCG) theory. Experimental results show that an integrated, low cost, and user-friendly SoC-Holter is feasible. SoC-Holter consumes less than 10mW while the device is operating. It takes advantage of estimating parameters directly from compressed measurements, thereby eliminating the reconstruction stage and reducing the computational complexity on the platform. In addition, the framework provides compressed ECG signals without loss of information, reducing significantly the power consumption for message sending and memory storage space. The effect of electrode placement is evaluated by estimating QRS complex in recorded ECG signals by two adjacent electrodes. The method is based on the QRS-VCG loop alignment algorithm that estimates Least Square (LS) between an observed VCG loop and a reference loop with respect to the transformations of rotation and time synchronization. The electrode location with less sensitive to interference is investigated.

The bacterium Vibrio vulnificus is an autochthonous inhabitant of estuarine waters and also found in shellfish such as oysters. It is a human pathogen of importance in the seafood industry, and can also infect recreational water users. Currently, recognized methods of detection rely upon isolation of pure cultures which requires at least 24 hours. To reduce the time needed for identification of the pathogen and simultaneously ascertain the virulence potential of the strains present, real-time PCR assays and sample processing procedures were developed (Chapter 1). These assays discriminate between type A (environmental, generally lower virulence) and type B (clinical, higher virulence) isolates. The genetic relationships between environmental V. vulnificus strains isolated from permitted and prohibited shellfish harvesting areas was determined using BOX-PCR genomic fingerprinting coupled with sequence analysis of three proposed virulence markers: (1) the virulence correlated gene (vcg), (2) 16S rRNA type and (3) presence/absence of the vulnibactin gene (viuB) (Chapter 2). The real-time PCR assays were able to detect the presence of seeded V. vulnificus in environmental water at a concentration of 160 cells 100·ml-1. In seeded oyster homogenates, the assays were able to detect a minimum of 10³ cells and 10² cells per reaction of type A and type B respectively. The phylogenetic analysis separated the majority of type A/ vcgE strains isolated from permitted shellfish harvesting areas from those isolated from prohibited harvesting areas. The genomic (BOX-PCR) fingerprints of type A and type AB isolates were more similar to one another than to type B isolates. Only one type A/ vcgE isolate contained the viuB gene; however, eight type B/ vcgC isolates had that gene. No obvious grouping was discerned between type B/ vcgC isolates from permitted versus prohibited shellfish harvesting areas or between those possessing the viuB gene versus those lacking viuB. These data provide insight into the ecology and correlation between population biology and general water quality, as gauged by the classification of the shellfish growing area waters. The 16S typing assays can be used for routine rapid typing to aid in risk assessment and reduce infection frequency through consumption of contaminated seafood.

This thesis addresses problems in the area of mechanism design. In many settings in winch collective decisions are made, individuals' actual preferences are not publicly observable. As a result, individuals should be relied on to reveal this information. We are interested in an important application of mechanism design, which is the construction of desirable procedures for deciding upon resource allocation or task assignment. We make two main contributions. First, we propose a new mechanism for allocating a divisible commodity between a number of buyers efficiently and fairly. Buyers are assumed to behave as price-anticipators rather than as price-takers. The proposed mechanism is as parsimonious as possible, in the sense that it requires participants to report a one-dimensional message (scalar strategy) instead of an entire utility function, as required by Vickrey-Clarke-Groves (VCG) mechanisms. We show that this mechanism yields efficient allocations in Nash equilibria and moreover, that these equilibria are envy-free. Additionally, we present distinct results that this mechanism is the only simple scalar strategy mechanism that both implements efficient Nash equilibria and satisfies the no envy axiom of fairness. The mechanism's Nash equilibria are proven to satisfy the fairness properties of both Ranking and Voluntary Participation. Our second contribution is to develop optimal VCG mechanisms in order to assign identical economic "bads" (for example, costly tasks) to agents. An optimal VCG mechanism minimizes the largest ratio of budget imbalance to efficient surplus over all cost profiles. The optimal non-deficit VCG mechanism achieves asymptotic budget balance, yet the non-deficit requirement is incompatible with reasonable welfare bounds. If we omit the non-deficit requirement, individual rationality greatly changes the behavior of surplus loss and deficit loss. Allowing a slight deficit, the optimal individually rational VCG mechanism becomes asymptotically budget balanced. Such a phenomenon cannot be found in the case of assigning economic "goods."

This project deals with anatomy and electrophysiology of heart. It describes the structure of cardiac muscle, mechanism of myocard's contraction, heart work, the origin and registration of electric signals of heart – electrocardiogram (ECG) and vectorcardiogram (VCG). Part of the work is design and creation of a software application for calculation and graphical presentation of vectorcardograms, useful for experimental data available on ÚBMI VUT in Brno.

<p>In many multiagent settings, a decision must be made based on the preferences of multiple agents, and agents may lie about their preferences if this is to their benefit. In mechanism design, the goal is to design procedures (mechanisms) for making the decision that work in spite of such strategic behavior, usually by making untruthful behavior suboptimal. In automated mechanism design, the idea is to computationally search through the space of feasible mechanisms, rather than to design them analytically by hand. Unfortunately, the most straightforward approach to automated mechanism design does not scale to large instances, because it requires searching over a very large space of possible functions. In this thesis, we adopt an approach to automated mechanism design that is computationally feasible. Instead of optimizing over all feasible mechanisms, we carefully choose a parameterized subfamily of mechanisms. Then we optimize over mechanisms within this family. Finally, we analyze whether and to what extent the resulting mechanism is suboptimal outside the subfamily. We apply (computationally feasible) automated mechanism design to three resource allocation mechanism design problems: mechanisms that redistribute revenue, mechanisms that involve no payments at all, and mechanisms that guard against false-name manipulation.</p> / Dissertation

En dépit du développement rapide de la médecine, les maladies cardiovasculaires restent la première cause de mortalité dans le monde. En France, chaque année, plus de 50 000 personnes meurent subitement en raison d'arythmies cardiaques. L'identification des patients à risque élevé de décès soudain est toujours un défi. Pour détecter les arythmies cardiaques, actuellement Holter est généralement utilisé pour enregistrer les signaux électrocardiogramme (ECG) à 1~3 dérivations pendant 24h à 72h. Cependant l'utilisation de Holter est limitée parmi la population en raison de son encombrement (pas convivial) et de son coût. Un Holter mono puce portable nommé SoC-Holter qui permet d'enregistrer 1 à 4 dérivations est introduit. Le déploiement d'un réseau de capteurs sans fil exige que chaque SoC-Holter soit peu encombrant et peu cher, et consomme peu d'énergie. Afin de minimiser la consommation d'énergie et le coût du système, la technologie Complementary Metal Oxide Semiconductor (CMOS) (0.35μm) est utilisée pour la première implémentation de SoC-Holter. Puis une nouvelle méthode de détection basée sur Acquisition Comprimée (CS) est introduite pour résoudre les problèmes de consommation d'énergie et de capacité de stockage de SoC-Holter. Le principe premier de cette plate-forme est d'échantillonner les signaux ECG sous la fréquence de Nyquist 'sub-Nyquist' et par la suite de classer directement les mesures compressées en états normal et anormal. Minimiser le nombre de fils qui relient les électrodes à la plate-forme peut rendre l'utilisateur de SoC-Holter plus confortable, car deux électrodes sont très proches sur la surface du corps. La différence ECG enregistrée est analysée à l'aide de Vectocardiogramme (VCG). Les résultats expérimentaux montrent qu'une approche intégrée, à faible coût et de faible encombrement (SoC-Holter) est faisable. Le SoC-Holter consomme moins de 10mW en fonctionnement. L'estimation des paramètres du signal acquis est effectuée directement à partir de mesures compressées, éliminant ainsi l'étape de la reconstruction et réduisant la complexité et le volume des calculs. En outre, le système fournit les signaux ECG compressés sans perte d'information, de ce fait il réduit significativement la consommation d'énergie pour l'envoi de message et l'espace de stockage mémoire. L'effet de placement des électrodes est évalué sur la QRS complexe lorsqu'il a enregistré avec deux électrodes adjacentes. La méthode est basée sur l'algorithme de 'QRS-VCG loop alignment'. La méthode moindre carré est utilisée pour estimer la corrélation entre une boucle VCG observée et une boucle de référence en respectant les transformations de rotation et la synchronisation du temps. Les emplacements d'électrodes les moins sensibles aux interférences sont étudiés.

This master’s thesis is bent on comparison of four newest method of analog frequency filter design. After the introductory part, a description of properties and internal structure of active elements (Second-Generation Current Conveyor), VG-CCII (Variable Gain Current Conveyor), VCG-CCII (Voltage and current gained second generation current conveyor) a CFTA (Current Follower Transconductance Amplifier) is mentioned. This active elements are used in subsequent design. At the next part, process of frequency filters design by generalized method of filter design flowing from the full admittance network, by extending autonomous circuits, design using the signal flow graphs theory and design with synthetic high-order elements are presented. Thirty nine autonomous circuits are derived from full admittance networks with one and two active elements CFTA. Selected autonomous circuits are used for direct design of frequency filter and for filter design by extending autonomous circuits. Produced structures guarantee the possibility of controlling the quality factor Q0 independently of the characteristic frequency f0. Three frequency filters are designed by method using the signal flow graph theory. Active elements CFTA, VG-CCI and VCG-CCII are used. Full multifunctional frequency filter with conveyors VG-CCII and VCG-CCII guarantee the possibility of controlling the quality factor Q0 and the characteristic frequency f0 independently of the each other. In last part, from 2nd to 5th order low-pass filters by the method using synthetic high-order elements are designed. The behaviour of the selected filters has been verified by simulations in the PSpice program for all of the mentioned methods separately.