Vision-based positioning systems are founded primarily on a simple image processing technique of identifying various visually significant key-points in an image and relating them to a known coordinate system in a scene. Fiducial markers are used as a means of providing the scene with a number of specific key-points, or features, such that computer vision algorithms can quickly identify them within a captured image. This thesis proposes a reliable vision-based positioning system which utilizes a unique pseudo-random fiducial marker. The marker itself offers 49 distinct feature points to be used in position estimation. Detection of the designed marker occurs after an integrated process of adaptive thresholding, k-means clustering, color classification, and data verification. The ultimate goal behind such a system would be for indoor localization implementation in low cost autonomous mobile platforms.

A new structure for the implementation of bit/serial adaptive IIR filter is presented. The bit level system consists of gated full adders for the arithmetic unit and data latches for the data path. This approach allows recursive operation of the IIR filter to be implemented without any global interconnections, minimal delay time, chip area and I/O pins. The coefficients of the filter can be updated serially in real time for time invariant and adaptive filtering. A fourth order bit/serial IIR filter is implemented on a 2 micron CMOS technology clocked at 55 MHz. / Graduation date: 1992

<p>A digital microfluidic biochip (DMFB) is a device that digitizes fluidic samples into tiny droplets and operates chemical processes on a single chip. Movement control of droplets can be realized by using electrowetting-on-dielectric (EWOD) technology. DMFBs have high configurability, high sensitivity, low cost and reduced human error as well as a promising future in the applications of point-of-care medical diagnostic, and DNA sequencing. As the demands of scalability, configurability and portability increase, a new DMFB architecture called Microelectrode Dot Array (MEDA) has been introduced recently to allow configurable electrodes shape and more precise control of droplets.</p> <p>The objective of this work is to investigate a routing algorithm which can not only handle the routing problem for traditional DMFBs, but also be able to route different sizes of droplets and incorporate diagonal movements for MEDA. The proposed droplet routing algorithm is based on 3D-A* search algorithm. The simulation results show that the proposed algorithm can reduce the maximum latest arrival time, average latest arrival time and total number of used cells. By enabling channel-based routing in MEDA, the equivalent total number of used cells can be significantly reduced. Compared to all existing algorithms, the proposed algorithm can achieve so far the least average latest arrival time.</p>

DNA copy number variations (CNVs), which involve the deletion or duplication of subchromosomal segments of the genome, have become a focus of genetics research. This dissertation develops Bayesian HMMs for finding CNVs from single nucleotide polymorphism (SNP) arrays. A Bayesian framework to reconstruct the DNA copy number sequence from the observed sequence of SNP array measurements is proposed. A Markov chain Monte Carlo (MCMC) algorithm, with a forward-backward stochastic algorithm for sampling DNA copy number sequences, is developed for estimating model parameters. Numerous versions of Bayesian HMMs are explored, including a discrete-time model and different models for the instantaneous transition rates of change among copy number states of a continuous-time HMM. The most general model proposed makes no restrictions and assumes the rate of transition depends on the current state, whereas the nested model fixes some of these rates by assuming that the rate of transition is independent of the current state. Each model is assessed using a subset of the HapMap data. More general parameterizations of the transition intensity matrix of the continuous-time Markov process produced more accurate inference with respect to the length of CNV regions. The observed SNP array measurements are assumed to be stochastic with distribution determined by the underlying DNA copy number. Copy-number-specific distributions, including a non-symmetric distribution for the 0-copy state (homozygous deletions) and mixture distributions for 2-copy state (normal), are developed and shown to be more appropriate than existing implementations which lead to biologically implausible results. Compared to existing HMMs for SNP array data, this approach is more flexible in that model parameters are estimated from the data rather than set to a priori values. Measures of uncertainty, computed as simulation-based probabilities, can be determined for putative CNVs detected by the HMM. Finally, the dissertation concludes with a discussion of future work, with special attention given to model extensions for multiple sample analysis and family trio data.

This thesis presents the VLSI implementation and characterization of a 256-channel bidirectional integrated neural interface for adaptive cortical stimulation. The microsystem consists of 64 stimulation and 256 recording channels, implemented in a 0.35um CMOS technology with a cell pitch of 200um and total die size of 3.5mm x3.65mm. The stimulator is a current driver with an output current range of 20uA – 250uA. The current memory in every stimulator allows for simultaneous stimulation on multiple active channels. Circuit reuse in the stimulator and utilization of a single DAC yields a compact and low-power implementation. The recording channel has two stages of signal amplification and conditioning and a single-slope ADC. The measured input-referred noise is 7.99uVrms over a 5kHz bandwidth. The total power consumption is 13.3mW. A new approach to CMOS-microelectrode hybrid integration by on-chip Au multi-stud-bumping is also presented. It is validated by in vitro experimental measurements.

This thesis presents the VLSI implementation and characterization of a 256-channel bidirectional integrated neural interface for adaptive cortical stimulation. The microsystem consists of 64 stimulation and 256 recording channels, implemented in a 0.35um CMOS technology with a cell pitch of 200um and total die size of 3.5mm x3.65mm. The stimulator is a current driver with an output current range of 20uA – 250uA. The current memory in every stimulator allows for simultaneous stimulation on multiple active channels. Circuit reuse in the stimulator and utilization of a single DAC yields a compact and low-power implementation. The recording channel has two stages of signal amplification and conditioning and a single-slope ADC. The measured input-referred noise is 7.99uVrms over a 5kHz bandwidth. The total power consumption is 13.3mW. A new approach to CMOS-microelectrode hybrid integration by on-chip Au multi-stud-bumping is also presented. It is validated by in vitro experimental measurements.

DNA copy number variations (CNVs), which involve the deletion or duplication of subchromosomal segments of the genome, have become a focus of genetics research. This dissertation develops Bayesian HMMs for finding CNVs from single nucleotide polymorphism (SNP) arrays. A Bayesian framework to reconstruct the DNA copy number sequence from the observed sequence of SNP array measurements is proposed. A Markov chain Monte Carlo (MCMC) algorithm, with a forward-backward stochastic algorithm for sampling DNA copy number sequences, is developed for estimating model parameters. Numerous versions of Bayesian HMMs are explored, including a discrete-time model and different models for the instantaneous transition rates of change among copy number states of a continuous-time HMM. The most general model proposed makes no restrictions and assumes the rate of transition depends on the current state, whereas the nested model fixes some of these rates by assuming that the rate of transition is independent of the current state. Each model is assessed using a subset of the HapMap data. More general parameterizations of the transition intensity matrix of the continuous-time Markov process produced more accurate inference with respect to the length of CNV regions. The observed SNP array measurements are assumed to be stochastic with distribution determined by the underlying DNA copy number. Copy-number-specific distributions, including a non-symmetric distribution for the 0-copy state (homozygous deletions) and mixture distributions for 2-copy state (normal), are developed and shown to be more appropriate than existing implementations which lead to biologically implausible results. Compared to existing HMMs for SNP array data, this approach is more flexible in that model parameters are estimated from the data rather than set to a priori values. Measures of uncertainty, computed as simulation-based probabilities, can be determined for putative CNVs detected by the HMM. Finally, the dissertation concludes with a discussion of future work, with special attention given to model extensions for multiple sample analysis and family trio data.

Detector arrays are required for many applications in health and defense. Whether searching for contraband or controlling radioactive spread after an event, a "passive" data collection strategy is a key component. This can take the form of portal monitors attached to a fixed location or a movable array, attached to a vehicle or person, which searches for abnormalities in the radiation background. The main goal of this project was to create software that would allow the digiBASE-E to be used to create arrays of gamma detection instruments and gather data over a long span of time. To take full advantage of the digiBASE-E, the software focused on the list mode capabilities of these devices. List mode attaches a timestamp to each detection event. Every particle detected can be traced to a particular point in time, and the full history of the device?s detection over the acquisition period can be reconstructed. The list mode ability of the digiBASE-E is a powerful tool for producing arrays of detectors, as a more familiar spectrum can be generated for any arbitrary section of time, even after-the-fact. The software package, called "CraneWow", was field tested at the Port of Tacoma in August of 2011. Perl scripts included as part of the package were used to partially analyze the data collected, allowing for verification of the proof-of-concept's success. The software was written in C/C++, with supplemental scripts written in Perl to facilitate processing of the data once collected. Additionally, a user manual and programming guide were written to allow easy use and maintenance of the software.

Vision-based positioning systems are founded primarily on a simple image processing technique of identifying various visually significant key-points in an image and relating them to a known coordinate system in a scene. Fiducial markers are used as a means of providing the scene with a number of specific key-points, or features, such that computer vision algorithms can quickly identify them within a captured image. This thesis proposes a reliable vision-based positioning system which utilizes a unique pseudo-random fiducial marker. The marker itself offers 49 distinct feature points to be used in position estimation. Detection of the designed marker occurs after an integrated process of adaptive thresholding, k-means clustering, color classification, and data verification. The ultimate goal behind such a system would be for indoor localization implementation in low cost autonomous mobile platforms.

Phased array antenna has been used for a variety of military and civil applications, over the past five decades. Being structurally conformal and flexible, phased array antenna is highly suitable for mobile applications. Besides, it can form the agile or shaped beams required for interference cancellation or multifunction systems. Moreover, the spatial power combination property increases the effective radiated power of a transmitter phased array system. Similarly, in a receiver phased array, beamforming increases the signal to noise ratio by coherent integration of the desired signals. Despite its impressive potentials and properties, phased array antenna has not become a commercial product yet. Cost and complexity of phased array antenna are beyond the scales of consumer electronics devices. Furthermore, calibration is an essential requirement of such a complex system, which is a fairly time-consuming process and requires skilled man power. Moreover, the narrow bandwidth of microwave components degrades the broadband performance of phased array system. Finally, the majority of the beamforming algorithms developed so far have preconditions, which make them unsuitable for a low-cost system. The objective of this thesis is to provide a novel cost-effective solution to minimize the system complexity of the future intelligent antenna systems, without sacrificing the performance. This research demonstrates that a powerful, robust beamforming algorithm, integrated in an efficient single-receiver architecture, constitutes the essence of a low-cost phased array antenna. Thus, a novel beamforming technique, called Zero-knowledge algorithm is developed. It is investigated, both theoretically and experimentally, that the proposed algorithm can compensate for the hardware errors and imperfections of the low-cost components of the system. Zero-knowledge beamforming algorithm possesses significant properties. Neither a priori knowledge of the incoming signal direction, nor the exact characteristics of the phase control network are required in this method. Proper adjustment of the parameters, makes this algorithm appropriate for mobile systems, particularly those installed on vehicles. The algorithm alleviates the drawbacks of analog phase shifters, such as imbalanced insertion loss and fabrication tolerances. Furthermore, this algorithm can serve as the core of a direction-of-arrival estimation technique, which senses the minor deflections of the array heading. For broadband applications optical delay lines must be used in the phase control network of the phased array systems, which are costly. Nevertheless, employing miniaturized delay lines can significantly reduce the device area, and consequently, the fabrication cost. Thus, in this research four types of miniaturized optical delay lines, designed in slow-wave structures, are analyzed, which can provide a large delay per length. In addition, two novel optical beamforming techniques, based upon the properties of Zero-knowledge algorithm, are developed for transmitter and receiver phased arrays.