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Digital-to-Analog Converters (DAC) form the feedback element in sigma-delta modulators. Any non-linearity in the DAC directly degrades the linearity of the modulator at low and medium frequencies. Hence, there is a need for designing highly linear DACs when used in high performance sigma-delta modulators. In this work, the impact of current mismatch on the linearity performance (IM3 and SQNR) of a 4-bit current steering DAC is analyzed. A selective calibration technique is proposed that is aimed at reducing the area occupancy of conventional linearization circuits. A statistical element selection algorithm for linearizing DACs is proposed. Current sources within the required accuracy are selected from a large set of current sources available. As compared with existing calibration techniques, this technique achieves higher accuracy and is more robust to variations in process and temperature. In contrast to existing data weighted averaging techniques, this technique does not degrade SNR performance of the ADC. A 5th order, 500 MS/s, 20 MHz sigma-delta modulator macro-model was used to test the linearity of the DAC.

Breast cancer is one of the most prevalent forms of cancer in the world today. The search for effective treatment and screening methods is a highly active area of research. The Digital Image-based ElastoTomography (DIET) project is a new breast cancer screening system under development, where surface motion from the mechanically actuated breast is measured in 3D, and used as input to an inverse problem solving for breast elasticity. Cancerous lesions appear as high contrast features, being an order of magnitude stiffer than healthy tissue. The 3D motion capture is measured by an array of digital cameras using computer vision techniques. This thesis presents a complete imaging system and algorithms for the capture of 3D breast surface motion. The main components of the 3D motion capture system are the hardware and software image capture system, camera calibration, intra-image feature tracking, and 3D surface and motion reconstruction. Accurate algorithms for each of these components are developed, with a view to future development and potential modifications needed for a clinically-appropriate system. A number of the algorithms developed have potential applications outside of the DIET system. Proof of concept studies demonstrate the viability of the system, with full motion reconstruction being performed on silicone gel phantoms, designed to approximate human soft tissue, in a number of laboratory experiments.

The Central United States Seismic Observatory (CUSSO), is a fifteen-element array of three-component accelerometers and seismometers in the New Madrid seismic zone, within the upper Mississippi embayment. Its location within the thick (up to 1 km) sequences of unlithified sediment comprising the embayment, make CUSSO a unique array in its ability to directly measure seismic wave propagation, including ground motion site effect; however, before the observational data can be used for analysis, the orientation and instrument response of the CUSSO array must be defined. This study used cross-correlation and direct comparisons to filter out the instrument response and determine the instrument orientation, making CUSSO data ready for analysis, and making CUSSO a viable calibration site for other free-field sensors in the area. The corrected waveforms from five far-field earthquakes with magnitudes ranging between 2.5 and 4.7, which were recorded at CUSSO, were used to validate the site’s proposed dynamic soil model. The corrected bedrock motions were also numerically propagated through the CUSSO soil profile (transfer function) and compared, in terms of both peak acceleration and amplitude spectra, to the recorded surface observations.

In this thesis, an innovative algorithm for improving the accuracy of variational space-time stereoscopic reconstruction of ocean surfaces is presented. The space-time reconstruction method, developed based on stereo computer vision principles and variational optimization theory, takes videos captured by synchronized cameras as inputs and produces the shape and superficial pattern of an overlapped region of interest as outputs. These outputs are designed to be the minimizers of the variational optimization framework and are dependent on the estimation of the camera parameters. Therefore, from the perspective of computer vision, the proposed algorithm adjusts the estimation of camera parameters to lower the disagreement between the reconstruction and 2-D camera recordings. From a mathematical perspective, since the minimizers of the variational framework are determined by a set of partial differential equations (PDEs), the algorithm modifies the coefficients of the PDEs based on the current numerical solutions to reduce the minimum of the optimization framework. Our algorithm increases the tolerance to the errors of camera parameters, so the joint operations of our algorithm and the variational reconstruction method can generate accurate space-time models even using videos captured by perturbed cameras as input. This breakthrough prompts the realization of ocean surface reconstruction using videos filmed by remotely-controlled helicopters in the future. A number of techniques, technical or theoretical, are explored to fulfill the development and implementation of the algorithm and relative computation issues. The effectiveness of the proposed algorithm is validated through the statistics applied to real ocean surface reconstructions of data collected from an offshore platform at the Crimean Peninsula, the Black Sea. Moreover, synthetic data generated using computer graphics are customized to simulate various situations that are not recorded in the Crimea dataset for the demonstration of the algorithm.

This study presents a comprehensive overview of the significance and results of implementing a data analysis for the calibration of an iodine neutrino detector. Previous neutrino detectors have failed to confirm the standard solar model or settle the question of a massive neutrino. An iodine detector, which was proposed in 1988, is being constructed to hopefully resolve these issues. Before the iodine detector can give conclusive results, it must first be calibrated. Because there is no standard neutrino source, these calibrations must be done indirectly. The method for calibrating the 127-Iodine detector is by using a (p,n) reaction at 0' on an iodine target and a proton beam provided by the Indiana University Cyclotron FacHity (IUCF). When a neutrino is captured by 127-Iodine, the nucleus becomes an excited state of 127-Xenon at an energy of 125 keV. By measuring the Gwnow Teller strength fimction of the transition from the ground state in 127-Iodine to the 125 keV excited state in 127-Xenon, the iodine detector can be suitably calibrated. / Department of Physics and Astronomy

名古屋大学年代測定総合研究センターシンポジウム報告

The development of remote sensing satellite-borne instrumentation for the study of the Earth’s atmosphere has provided an immense increase in our understanding of atmospheric trends and processes. The Canadian built OSIRIS satellite instrument uses the limb scatter technique to measure scattered sunlight for the retrieval of vertical profiles of atmospheric species such as ozone. Recently, the next generation instrument, CATS, based on the OSIRIS design, is under development to continue OSIRIS measurements into the future. One key optical design change for CATS is the ability to measure simultaneously over multiple fields of view. However, this new optical design concept needs to be tested and evaluated. To achieve this, a prototype slit plate was installed into the preflight developmental version of OSIRIS, called OSIRIS-DM, for testing in the laboratory and on a stratospheric balloon. In this thesis work, an evaluation of the performance of this multi-slit instrument was undertaken through laboratory calibrations and limb scatter measurement collection. The calibration process includes a wavelength registration, a spectral point spread function analysis, a relative calibration and an absolute calibration, all performed with laboratory equipment. Along with laboratory calibrations, this thesis work involved preparation for the stratospheric balloon mission including the development of a flight ready electronic control and communication system to operate OSIRIS-DM during the mission. The upgraded instrument was launched on September 19, 2014, and ascended to a stable float altitude of 36.5 km. The collected flight measurements were used to evaluate the calibrations and general instrument performance. Overall, the laboratory calibrations proved to be sufficiently accurate and the measurement collection produced multiple spectra that may be used for atmospheric analysis in the future. These results show that the multi-slit design of the slit plate produces an instrument that can be reliably calibrated and implemented for limb scatter measurement collection.

The main aim of this thesis is to generate 3D models of human heads from uncalibrated images. In order to extract geometric values of a human head, we find camera parameters using camera auto calibration. However, some image sequences generate non-unique (degenerate) solutions. An algorithm for removing degeneracy from the most common form of camera movement in face image acquisition is described. The geometric values of main facial features are computed initially. The model is then generated by gradual deformation of a generic polygonal model of a head. The accuracy of the models is evaluated using ground truth data from a range scanner. 3D models are covered with cylindrical texture values obtained from images. The models are appropriate for animation or identification applications.

An attempt was made to calibrate a steady state activated sludge model (ASM2d) for the biological nutrient removal process at the Gold bar wastewater treatment plant. This calibrated model could be used on a regular basis to test various operational strategies and predict effluent quality under different scenario. To achieve this historic data from the plant database was collected based on 24 composite samples. A trial and error method of wastewater characterization of the primary effluent was attempted using the influent advisor module of the GPS-[X] software. Sensitivity analysis of kinetic parameters was carried out and the most important ones identified were calibrated (default values were modified) based on literature. After calibration it was observed that the model was overestimating the concentrations of carbonaceous biological oxygen demand, total suspended solids and orthophosphate in the effluent, compared to the actual value measured at the plant. Similarly the effluent ammonia concentration was underestimated for most days along with the nitrate and nitrite concentration. This clearly indicated the need for a more accurate calibration based on experimental data to improve prediction capabilities and the reliability of the model. / Environmental Science