This paper deals with the effect of the MR pulse sequences on the temperature of the measured object. The theoretical part is dedicated to basic principle of magnetic resonance, the selected pulse sequences and risks that are connected with MRI. There is also described the draft of the testing phantom and information about the measurement and record of temperature during MR measurement. In the experimental part the effect of RF coils, pulse sequences and parameters of pulse sequences are tested on drafted phantom with experimental MR device located at the Institut of Scientific Instruments of the AS CR in Brno. These findings are then tested on live laboratory mouse. All results are analyzed and used as default data for developed simulation program.

<p>With the development of wireless communication technology, second-, third-, fourth-generation transmission systems based on electromagnetic (EM) waves are widely used. At the same time, public concerns have been raised about whether the use of such systems will have an impact on health and safety standards. The heating effect is the most prominent and scientifically verifiable biological effect. So, the influence of EM waves on human body is addressed by studying the heating characteristics on head models.</p> <p>The objective of this thesis is to study the effects of radio frequency (RF) waves radiation from mobile phones on the human head under different transmission generations. The six-layer head model is used to evaluate the specific absorption rate (SAR) distribution and thermal effect. This model allows to study the effects of SAR and temperature rise without the need for high computational resources. In order to find the effect of temperature rise and exposure time, the finite difference time domain (FDTD) method was used to solve the biothermal equation with appropriate boundary conditions.</p> <p>Also, different age-dependent head models are used to study the differences of SAR for children at different ages.</p> <p>In general, the results show that with the increase in frequency, the influence of the EM wave is more pronounced, as demonstrated by the SAR and temperature rise distribution. In addition, SAR distribution of younger ages show a significant increase, which indicates that children exposed to EM waves are subject to more harmed. </p>

Energy efficiency is a key requirement for wireless sensor nodes, biomedical implants, and wearable devices. The energy consumption of the sensor node needs to be minimized to avoid battery replacement, or even better, to enable the device to survive on energy harvested from the ambient. Capacitive sensors do not consume static power; thus, they are attractive from an energy efficiency perspective. In addition, they can be employed in a wide range of sensing applications. However, the sensor readout circuit–i.e., the capacitance-to-digital converter (CDC)–can be the dominant source of energy consumption in the system. Thus, the development of energy-efficient CDCs is crucial to minimizing the energy consumption of capacitive sensor nodes. In the first part of this dissertation, we propose several energy-efficient CDC architectures for low-energy sensor nodes. First, we propose a digitally-controlled coarsefine multislope CDC that employs both current and frequency scaling to achieve significant improvement in energy efficiency. Second, we analyze the limitations of successive approximation (SAR) CDC, and we address these limitations by proposing a robust parasitic-insensitive opamp-based SAR CDC. Third, we propose an inverter-based SAR CDC that achieves an energy efficiency figure-of-merit (FoM) of 31fJ/Step, which is the best energy efficiency FoM reported to date. Fourth, we propose a differential SAR CDC with quasi-dynamic operation to maintain excellent energy efficiency for a scalable sample rate. In the second part of this dissertation, we study the matching properties of small integrated capacitors, which are an integral component of energy-efficient CDCs. Despite conventional wisdom, we experimentally illustrate that the mismatch of small capacitors can be directly measured, and we report mismatch measurements for subfemtofarad integrated capacitors. We also correct the common misconception that lateral capacitors match better than vertical capacitors, and we identify the conditions that make one implementation preferable. In the third and last part of this dissertation, we investigate the potential of novel metal-organic framework (MOF) thin films in capacitive gas sensing. We provide sensitivity-based optimization and simple fabrication flow for capacitive interdigitated electrodes. We use a custom flexible gas sensor test setup that is designed and built in-house to characterize MOF-based capacitive gas sensors.

The key requirements of a reliable neural signal recording system include low power to support long-term monitoring, low noise, minimum tissue damage, and wireless transmission. The neural spikes are also detected and sorted on-chip/off-chip to implement closed-loop neuromodulation in a high channel count setup. All these features together constitute an empirical neural recording system for neuroscience research. In this prospectus, we propose to develop a neural signal acquisition system with wireless transmission and feature extraction. We start by designing a prototype entirely built with commercial-off-the-shelf components, which includes recording and wireless transmission of synthetic neural data and feature extraction. We then conduct the CMOS implementation of the low-power multi-channel neural signal recording read-out circuit, which enables the in-vivo recording with a small form factor. Another direction of this thesis is to design a self-powered motion tracking read-out circuit for wearable sensors. As the wearable industry continues to advance, the need for self-powered medical devices is growing significantly. In this line of research, we propose a self-powered motion sensor based on reverse electrowetting-on-dielectric (REWOD) with low-power integrated electronics for remotely monitoring health conditions. We design the low-power read-out circuit for a wide range of input charges, which is generated from the REWOD sensor.

The creation and classification of segments for object based urban land cover mapping is the key goal of this master thesis. An algorithm based on region growing and merging was developed, implemented and tested. The synergy effects of a fused data set of SAR and optical imagery were evaluated based on the classification results. The testing was mainly performed with data of the city of Beijing China. The dataset consists of SAR and optical data and the classified land cover/use maps were evaluated using standard methods for accuracy assessment like confusion matrices, kappa values and overall accuracy. The classification for the testing consists of 9 classes which are low density buildup, high density buildup, road, park, water, golf course, forest, agricultural crop and airport. The development was performed in JAVA and a suitable graphical interface for user friendly interaction was created parallel to the development of the algorithm. This was really useful during the period of extensive testing of the parameter which easily could be entered through the dialogs of the interface. The algorithm itself treats the pixels as a connected graph of pixels which can always merge with their direct neighbors, meaning sharing an edge with those. There are three criteria that can be used in the current state of the algorithm, a mean based spectral homogeneity measure, a variance based textural homogeneity measure and fragmentation test as a shape measure. The algorithm has 3 key parameters which are the minimum and maximum segments size as well as a homogeneity threshold measure which is based on a weighted combination of relative change due to merging two segments. The growing and merging is divided into two phases the first one is based on mutual best partner merging and the second one on the homogeneity threshold. In both phases it is possible to use all three criteria for merging in arbitrary weighting constellations. A third step is the check for the fulfillment of minimum size which can be performed prior to or after the other two steps. The segments can then in a supervised manner be labeled interactively using once again the graphical user interface for creating a training sample set. This training set can be used to derive a support vector machine which is based on a radial base function kernel. The optimal settings for the required parameters of this SVM training process can be found from a cross-validation grid search process which is implemented within the program as well. The SVM algorithm is based on the LibSVM java implementation. Once training is completed the SVM can be used to predict the whole dataset to get a classified land-cover map. It can be exported in form of a vector dataset. The results yield that the incorporation of texture features already in the segmentation is superior to spectral information alone especially when working with unfiltered SAR data. The incorporation of the suggested shape feature however doesn’t seem to be of advantage, especially when taking the much longer processing time into account, when incorporating this criterion. From the classification results it is also evident, that the fusion of SAR and optical data is beneficial for urban land cover mapping. Especially the distinction of urban areas and agricultural crops has been improved greatly but also the confusion between high and low density could be reduced due to the fusion. / Dragon 2 Project

This thesis further develops a method from ongoing thesis projects with the goal of generating images using synthetic aperture radar (SAR) simulations coded in MATLAB. The project is supervised by Dr. John Saghri and sponsored by Raytheon Space and Airborne Systems. SAR is a type of imaging radar in which the relative movement of the antenna with respect to the target is utilized. Through the simultaneous processing of the radar reflections over the movement of the antenna via the range Doppler algorithm (RDA), the superior resolution of a theoretical wider antenna, termed synthetic aperture, is obtained. The long term goal of this ongoing project is to develop a simulation in which realistic SAR images can be generated and used for SAR Automatic Target Recognition (ATR). Current and past Master’s theses on ATR were restricted to a small data set of Man-portable Surveillance and Target Acquisition Radar (MSTAR) images as most SAR images for military ATR are not released for public use. Also, with an in-house SAR image generation scheme the parameters of noise, target orientation, the elevation angle or look angle to the antenna from the target and other parameters can be directly controlled and modified to best serve ATR purposes or other applications such as three-dimensional SAR holography. At the start of the project in September 2007, the SAR simulation from previous Master’s theses was capable of simulating and imaging point targets in a two dimensional plane with limited mobility. The focus on improvements to this simulation through the course of this project was to improve the SAR simulation for applications to more complex two-dimensional targets and simple three-dimensional targets, such as a cube. The input to the simulation uses a selected two-dimensional, grayscale target image and generates from the input a two-dimensional target profile of reflectivity over the azimuth and range based on the intensity of the pixels in the target image. For three-dimensional simulations, multiple two-dimensional azimuth/range profiles are imported at different altitudes. The output from both the two-dimensional and three-dimensional simulations is the SAR simulated and RDA processed image of the input target profile. Future work on this ongoing project will include an algorithm to calculate line of sight limitations of point targets and processing optimization of the radar information generation implemented in the code so that more complex and realistic targets can be simulated and imaged using SAR for applications in ATR and 3D SAR holography.

L’imagerie RSO circulaire aéroportée permet d’obtenir de nombreuses informations sur les zones imagées et sur les cibles mobiles. Les objets peuvent être observés sous plusieurs angles, et l’illumination continue d’une même scène permet de générer plusieurs images successives de la même zone. L’objectif de cette thèse est de développer une méthode de reconstruction de trajectoire de cibles mobiles en imagerie RSO circulaire monovoie, et d’étudier les performances de la méthode proposée. Nous avons tout d’abord mesuré les coordonnées apparentes des cibles mobiles sur les images RSO et leur paramètre de défocalisation. Ceci permet d’obtenir des informations de mouvement des cibles, notamment de vitesse et d’accélération. Nous avons ensuite utilisé ces mesures pour définir un système d’équations non-linéaires permettant de faire le lien entre les trajectoires réelles des cibles mobiles et leurs trajectoires apparentes. Par une analyse mathématique et numérique de la stabilité de ce système, nous avons montré que seul un modèle de cible mobile avec une vitesse constante permet de reconstruire précisément les trajectoires des cibles mobiles, sous réserve d’une excursion angulaire suffisante. Par la suite, nous avons étudié l’influence de la résolution des images sur les performances de reconstruction des trajectoires, en calculant théoriquement les précisions de mesure et les précisions de reconstruction qui en découlent. Nous avons mis en évidence l’existence théorique d’une résolution azimutale optimale, dépendant de la radiométrie des cibles et de la validité des modèles étudiés. Finalement nous avons validé la méthode développée sur deux jeux de données réelles. / Circular SAR imagery brings a lot of information concerning the illuminated scenes and the moving targets. Objects may be seen from any angle, and the continuity of the illumination allows generating a lot of successive images from the same scene. In the scope of this thesis, we develop a moving target trajectory reconstruction methodology using circular SAR imagery, and we study the performances of this methodology. We have first measured the apparent coordinates of the moving targets on SAR images, and also the defocusing parameter of the targets. This enables us to obtain information concerning target movement, especially the velocity and the acceleration. We then used these measurements to develop a non-linear system that makes the link between the apparent trajectories of the moving targets and the real ones. We have shown, by a mathematical and numerical analysis of the robustness, that only a model of moving target with constant velocity enables us to obtain accurate trajectory reconstructions from a sufficient angular span. Then, we have studied the azimuth resolution influence on the reconstruction accuracy. In order to achieve this, we have theoretically estimated the measurement accuracy and the corresponding reconstruction accuracy. We have highlighted the existence of an optimal azimuth resolution, depending on the target radiometry and on the validity of the two target models. Finally, we have validated the method on two real data sets on X-Band acquired by SETHI and RAMSES NG, the ONERA radar systems, and confirmed the theoretical analyses of its performances.

No description available.

Previous studies have used new angiotensin II (AII) receptor subtype selective compounds to localize AII receptor subtypes within discrete rat brain nuclei. The purpose of this autoradiographic study was to extend these preliminary findings and provide a comprehensive analysis of AII binding sites in 22 rat brain nuclei and the anterior pituitary, to include estimates of the binding affinity for 125I sar1 ile8 AII (125I SIAII) at each nucleus, and determine the fractional distribution of each subtype at each nucleus. Estimates of K(D), in separate experiments revealed that AT1 nuclei had a consistently higher affinity for 125I SIAII than AT2 nuclei (0.66 vs. 2.55 nM). Displacement of subsaturating concentrations of 125I SIAII by 10-8-10-4 M DuP753 (selective for the AT1 subtype) or PD123177 (selective for the AT2 subtype) indicated that approximately half of the brain regions surveyed contained predominantly AT1 sites and half contained predominantly AT2 sites. Binding was partially displaced by both compounds in several regions and two site analyses were performed to estimate the distribution of subtypes within each nucleus. The data were then corrected for differential occupancy by 125I SIAII. Brain nuclei associated with cardiovascular or dipsogenic actions of AII, e.g., subfornical organ, organum vasculosum of the lamina terminalis, median preoptic nucleus, nucleus of the solitary tract and area postrema, contained pure, or almost pure, populations of AT1 receptors. The functions of AII in brain regions containing predominantly AT2 binding sites, e.g., thalamus, colliculi, inferior olive and locus ceruleus, remain undefined. Thus, AII binding sites in the rat brain have been differentiated into two subtypes with similar characteristics to those reported in peripheral tissues. However, the unexpected finding that they can be differentiated on the basis of their affinity for 125I SIAII raises questions concerning their coidentity with peripheral receptor subtypes.

No description available.