abstract: Genomic and proteomic sequences, which are in the form of deoxyribonucleic acid (DNA) and amino acids respectively, play a vital role in the structure, function and diversity of every living cell. As a result, various genomic and proteomic sequence processing methods have been proposed from diverse disciplines, including biology, chemistry, physics, computer science and electrical engineering. In particular, signal processing techniques were applied to the problems of sequence querying and alignment, that compare and classify regions of similarity in the sequences based on their composition. However, although current approaches obtain results that can be attributed to key biological properties, they require pre-processing and lack robustness to sequence repetitions. In addition, these approaches do not provide much support for efficiently querying sub-sequences, a process that is essential for tracking localized database matches. In this work, a query-based alignment method for biological sequences that maps sequences to time-domain waveforms before processing the waveforms for alignment in the time-frequency plane is first proposed. The mapping uses waveforms, such as time-domain Gaussian functions, with unique sequence representations in the time-frequency plane. The proposed alignment method employs a robust querying algorithm that utilizes a time-frequency signal expansion whose basis function is matched to the basic waveform in the mapped sequences. The resulting WAVEQuery approach is demonstrated for both DNA and protein sequences using the matching pursuit decomposition as the signal basis expansion. The alignment localization of WAVEQuery is specifically evaluated over repetitive database segments, and operable in real-time without pre-processing. It is demonstrated that WAVEQuery significantly outperforms the biological sequence alignment method BLAST for queries with repetitive segments for DNA sequences. A generalized version of the WAVEQuery approach with the metaplectic transform is also described for protein sequence structure prediction. For protein alignment, it is often necessary to not only compare the one-dimensional (1-D) primary sequence structure but also the secondary and tertiary three-dimensional (3-D) space structures. This is done after considering the conformations in the 3-D space due to the degrees of freedom of these structures. As a result, a novel directionality based 3-D waveform mapping for the 3-D protein structures is also proposed and it is used to compare protein structures using a matched filter approach. By incorporating a 3-D time axis, a highly-localized Gaussian-windowed chirp waveform is defined, and the amino acid information is mapped to the chirp parameters that are then directly used to obtain directionality in the 3-D space. This mapping is unique in that additional characteristic protein information such as hydrophobicity, that relates the sequence with the structure, can be added as another representation parameter. The additional parameter helps tracking similarities over local segments of the structure, this enabling classification of distantly related proteins which have partial structural similarities. This approach is successfully tested for pairwise alignments over full length structures, alignments over multiple structures to form a phylogenetic trees, and also alignments over local segments. Also, basic classification over protein structural classes using directional descriptors for the protein structure is performed. / Dissertation/Thesis / Ph.D. Electrical Engineering 2011

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Radars have been under steady development to track, identify, image, and classify targets. Modern radar systems, with the help of embedded systems, have additional comprehensive signal processing capabilities. They can extract useful information from very noisy data, e.g. interference from the environment and unwanted echoes which is collectively known as clutter in radar terms. Concerning the healthcare industry, radar applications for detection of vital signs, i.e. breathing and heart rate, have been extensively developed during the last few decades. Modern radar systems are expected to be a large part of non-intrusive monitoring in the coming smart home industry, where vital signs need to be monitored in the currently aging population. The research presented here is to break new ground in the radar-based healthcare technology, enabling detection of cold-induced shivering to such level that the micro-shivering can be clearly identified. To simplify the radar software optimization, a commercially available radar kit with demo application and a muscle model system using a vibration generator is used. The model is quantified through precise measurements. A simulated human body vital sign plus shivering is applied. By optimizing the radar software, the shivering amplitude and frequency are measured.

An advanced laser-Doppler velocimeter is designed to acquire fully-resolved turbulence structural measurements in high Reynolds number two- and three-dimensional turbulent boundary layers. The new instrument combines, for the first time, new techniques allowing for the direct measurement of particle acceleration and sub-measurement-volume-scale position resolution so that second-order 3D particle trajectories may be measured at high repetitions. Using these measurements, several terms in the Reynolds stress transport equations may be directly estimated, giving new data for modeling and understanding the processes leading to the transport of turbulence in boundary layer flows. Due to the unique performance of the probe, many aspects of LDV instrumentation development were addressed. The LDV configuration was optimized for lowest uncertainties by considering the demanding applications of particle position and acceleration measurements. Low noise light detection and signal conditioning was specified for the three electronic channels. A high-throughput data acquisition system allows for exceptional burst rate acquisition. Signal detection and processing algorithms have been implemented which draw from previous techniques but also address distinctive problems with the current system. In short, the instrument was designed to advance the state-of-the-art in LDV systems. Measurements presented include turbulence dissipation rate and fluctuating velocity-pressure gradient correlations that have been measured in 2D and 3D turbulent boundary layers using the unique capabilities of the CompLDV--many of these measurements are the first of their kind ever acquired in high Reynolds number turbulent flows. The flat-plate turbulent boundary layer is studied at several momentum thickness Reynolds numbers up to 7500 to examine Reynolds numbers effects on terms such as the velocity-pressure gradient correlation and the dissipation rate in the Reynolds transport equations. Measurements are also presented in a pressure-driven three-dimensional turbulent boundary layer created upstream from a wing-body junction. The current results complement the extensive data from previous studies and provide even richer depth of knowledge on the most-completely-documented 3D boundary layer flow in existence. Further measurements include the wakes of three circular-cylinder protuberances submerged in a constant pressure turbulent boundary layer. / Ph. D.