This thesis includes two topics. The first topic is a CMOS SRAM using dynamic threshold voltage wordline-transistors, which is focused on high speed applications. The second one is a high voltage generator for FLASH memories. The generated high voltages are applied to the wordline controlled transistors during access and verification operations. By taking advantage of the large current provided by low Vth and low leakage current provided by high Vth, a CMOS SRAM using dynamic threshold voltage wordline transistors is presented. The design of a 4-Kb SRAM is measured to possess a 2.2 ns access time, and consume 43.6 mW in the standby mode. The highest operating clock rate is estimated to be 667 MHz. A high voltage generator using 4 clocks with two phases is presented to provide a high voltage supply required by FLASH memories during programming mode and erase mode operations. The circuit is implemented by TSMC 0.25um 1P5M CMOS process. It can provide as high as +11.7 V and -11.6 V by given VDD=2.5 V.

The trustworthiness of the blood pressure (BP) readings acquired by oscillometric home-based monitoring systems is a challenging issue that requires patients to see the doctor for trusted measurements, especially those who are obese or have cardiovascular diseases such as hypertension or atrial fibrillation. Even with the most accurate monitors one may get different readings if BP is repeatedly measured. Trusted BP readings are those measured with accurate devices at proper measurement conditions. The accurate monitors need an indicator to assure the trustworthiness of the measured BP. In this work, a novel algorithm called the Dynamic Threshold Algorithm (DTA) is proposed that calculates trusted boundaries of the measured systolic and diastolic pressures from the recorded oscillometric waveforms. The DTA determines a threshold from the heart rate of subjects to locate the oscillometric pulse at the mean arterial pressure (PULSEMAP) and uses the peak, trough, and pressure of the located pulse to calculate the trusted boundaries. In terms of accuracy, a modeling approach is employed to estimate BP from the arterial lumen area oscillations model in the diastolic region (ALA-based). The model requires compliance parameter ‘c’ to estimate BP. To this end, a pre-developed linear regression model between ‘c’ and the corresponding amplitude ratio of the PULSEMAP is employed to evaluate ‘c’. The proposed method uses ‘c’ and estimates BP by minimizing differences between peak and trough amplitudes of the actual and corresponding simulated waveforms. The proposed DTA and ALA-based methods were tested on two datasets of healthy subjects and one dataset of sick subjects with cardiovascular diseases, and results were validated against corresponding references and compared with two popular maximum amplitude and maximum/minimum slope algorithms. Mean absolute error (MAE) and standard deviation of errors (STDE) are used to evaluate and compare the results. For healthy subjects, the MAE of the estimated systolic (SBP) and diastolic (DBP) blood pressures was improved up to 57% and 57% with an STDE of 55% and 62%, respectively. For sick subjects, the MAE was improved up to 40% and 29% with an STDE of 36% and 20% for SBP and DBP, respectively.

No description available.

No description available.

The tarnished plant bug, Lygus lineolaris (Palisot de Beauvois), is considered the most economically important pest of midsouth cotton. This study was designed to understand the impact of tarnished plant bug populations in the later weeks of flowering cotton and residual effects of novaluron with subsequent applications. Experiments evaluated dynamic threshold approaches in the later flowering period of midsouth cotton, the impacts of novaluron plus subsequent applications at the 3rd week of square, as well as residual properties in a laboratory experiment. Results suggest that a dynamic late season approach can reduce the amount of insecticide applications targeting tarnished plant bug with no penalty to yield. Populations were observed at lowest densities where applications of novaluron were tank mixed with an adulticide (acephate) at the 3rd week of square. Results of this experiment will be important in refining seasonal management recommendations for tarnished plant bug in midsouth cotton production systems.

Colour segmentation is the most commonly used method in road signs detection. Road sign contains several basic colours such as red, yellow, blue and white which depends on countries.The objective of this thesis is to do an evaluation of the four colour segmentation algorithms. Dynamic Threshold Algorithm, A Modification of de la Escalera’s Algorithm, the Fuzzy Colour Segmentation Algorithm and Shadow and Highlight Invariant Algorithm. The processing time and segmentation success rate as criteria are used to compare the performance of the four algorithms. And red colour is selected as the target colour to complete the comparison. All the testing images are selected from the Traffic Signs Database of Dalarna University [1] randomly according to the category. These road sign images are taken from a digital camera mounted in a moving car in Sweden.Experiments show that the Fuzzy Colour Segmentation Algorithm and Shadow and Highlight Invariant Algorithm are more accurate and stable to detect red colour of road signs. And the method could also be used in other colours analysis research. The yellow colour which is chosen to evaluate the performance of the four algorithms can reference Master Thesis of Yumei Liu.

Cette thèse a pour but l’étude de la détection basée sur modèle de défauts pour lesmoteurs Diesel produits en grande série. La nécessité d’une surveillance continue del’état de santé des véhicules est maintenant renforcée par la législation Euro VI sur lesémissions polluantes, qui sera probablement rendue encore plus contraignante dans sesprochaines révisions. Dans ce contexte, le développement de stratégies robustes, faciles àcalibrer et valides pour des systèmes dispersés (car produits en grande série) procureraitun avantage considérable aux constructeurs automobile. L’étude développée ici tentede répondre à ces besoins en proposant une méthodologie générique. On utilise desobservateurs adaptatifs locaux pour des systèmes scalaires non linéaires et affines parrapport à l’état, pour résoudre les problèmes de la détection de défauts, de son isolationet de son estimation d’une façon compacte. De plus, les incertitudes liées aux biais demesure et de modèle et aux dérives temporelles nécessitent d’améliorer les méthodes dedétection par l’utilisation de seuils robustes pour éviter les fausses détections. Dans cettethèse, on propose un seuil variable basé sur la condition d’observabilité du paramètreimpacté par le défaut et sur une étude de sensibilité par rapport aux incertitudes surles entrées ou sur le modèle. Cette méthode permet, entre autres, de fournir un outild’analyse pour la sélection des conditions de fonctionnement du système pour lesquelsle diagnostic est plus fiable et plus robuste par rapport aux incertitudes sur les entrées.L’approche présentée a été appliquée avec succès et validée de façon expérimentale surun moteur Diesel pour le problème de détection de fuite dans le système d’admissiond’air, puis dans un environnement de simulation pour le problème de détection dedérive d’efficacité turbine. On montre ainsi ses avantages en termes de fiabilité dedétection, d’effort de calibration, et pour l’analyse des conditions de fonctionnementmoteur adaptées au diagnostic. / The study of model-based fault detection for mass production Diesel engines isthe aim of this thesis. The necessity of continuous vehicles health monitoring is nowenforced by the Euro VI pollutant legislation, which will probably be tightened in itsfuture revisions. In this context developing a robust strategy that could be easilycalibrated and work with different systems (due to production variability) would bea tremendous advantage for car manufacturers. The study developed here tries toanswer to those necessities by proposing a generic methodology based on local adaptiveobservers for scalar nonlinear state-affine systems. The fault detection, isolation andestimation problems are thus solved in a compact way. Moreover, the uncertaintiesdue to measurement or model biases and time drifts lead to the necessity of improvingthe detection methodology by the use of robust thresholds that could avoid undesiredfalse alarms. In this thesis a variable threshold is proposed based on the observabilitycondition and the sensitivity analysis of the parameter impacted by the fault withrespect to input or model uncertainties. This approach allows, among other things, tobe used as an analysis tool for the individuation of the system operating points for whichthe diagnosis is more reliable and more robust to inputs uncertainties. The discussedapproach has been successfully implemented and experimentally tested on a real Dieselengine for the intake leak detection and for the turbine efficiency loss drift detectionin a co-simulation environment showing its advantages in term of detection reliability,calibration effort and engines diagnosis operating condition analysis.