There are various kinds of noise that affects DNA array data and it is a challenge to obtain high quality data from an experiment. Background correction is a first step for DNA array data processing; however, current methods for background correction have disadvantages. In this thesis, I propose a mixture model to facilitate the background correction for DNA array data generated by ImaGene. The corresponding software is also provided.

The covalent modifications to the histone 2A, 2B, 3, and 4 N-terminal tails that affect gene expression have been deemed the “Histone Code.” Mis-regulation of these signalling pathways is of great interest as are important in human disease. A variety of peptides containing post-translationally modified histone 3 and 4 sequences were read using a supramolecular sensor array approach, where two or three sensors gave a unique response for each analyte when compared to others. These sequences were chosen to determine what type of modifications could be read (phosphorylation, acetylation, methylation) and if this type of array would be suitable for reading analytes on which antibodies—the leading technology—typically perform poorly. It was found that three sensors, which operate in neutral aqueous solution, were able to discriminate 16 different histone analytes. Additionally, it was shown that this array could report simultaneously on both concentration and the identities of histone analytes. / Graduate

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.

Numerous applications in the present day ranging from testing humidity in air to detecting miniscule quantities of potentially hazardous chemical and biological agents in the air or water supplies require the development of chemical sensors capable of analyte detection with high sensitivity and selectively. Further, it has become desirable to create lab-on-chip systems that can detect multiple chemical agents and allow for sampling and testing of environments at locations distant from conventional laboratory facilities. Current challenges in this area include design, development and characterization of low detection limit sensors, development of low-noise readout methods, positive identification of analytes and, identification and reduction of the effect of various noise sources - both intrinsic and extrinsic to the sensor. The current work examines the performance limits of a 10-cantilever piezoresistive microcantilever array (PµCA) sensor. The microcantilevers measure analyte concentration in terms of the surface stress associated with analyte binding to the functionalized cantilever surface. The design, fabrication, characterization and testing of this measurement platform is presented. A novel aspect of the sensors developed is the use of n-type doping which increases the sensitivity of the device by one order of magnitude. In addition, design rules for surface stress-based chemical sensors have been developed. Extensive thermal characterization of the piezoresistive microcantilevers has been performed for DC and AC electrical excitation and values of heat transfer coefficient for the associated microscale phenomena are reported. Further, a method of low-noise measurement of cantilever resistance has been developed based on phase-sensitive detection techniques and this has been integrated with a multiplexing circuit to measure piezoresistance change in multiple cantilevers. Finally, the two novel techniques of chemical sensing- double-sided sensing and thermal array-based sensing have been investigated. These methods are presented as a means of extending the applicability and functionality of piezoresistive microcantilever sensors for chemical sensing.

This doctoral thesis deals with designs and developments of multi(wide)-band multifunctional antennas based on folded dipoles. In the beginning, the concept of Orthogonal Folded Dipoles (OFD) are put forward. Orthogonal folded dipoles are formed by two identical two-port folded dipoles orthogonally joining with each other at the center, and can be fed through different combinations of feed nodes to offer dual- and wide-band modes, respectively. The impedances of the 2 modes are studied both by analytical models and by commercial electromagnetic simulation tools. The properties of the linearly polarized radiation patterns in the two modes vary quite little, except for ±45◦  rotation of two principal planes. In this way, orthogonal folded dipoles can possibly provide pattern reconfigurability in a context of switchable types and orientations of polarizations. Next, the concept of Log-Periodic Folded Dipole Array (LPFDA) is proposed. It stems from the traditional log-periodic dipole array, whereas folded dipoles instead of straight dipoles are applied as the elements of the array. Two configurations, i.e. partly-scaled LPFDA and fully-scaled LPFDA, are studied through simulations and optimizations. The comparison shows that the latter outperforms the former in terms of higher directivity, reduced front-to-back ratio and lower crosspolar level. The key parts of this thesis focus on exploiting Eleven antennas, based on the LPFDAs, in a variety of applications. First, the 4-port L-band lab model for use in satellite terminals demonstrates that the radiation patterns for monopulse tracking can be achieved through different excitation combinations of the multiport Eleven antenna. Second, a decade bandwidth, an unchanged phase center and nearly constant directivities over the whole band can be regarded as the major figure-of-merit of the Eleven antenna, which makes it suitable as feed for prime-fed reflector antennas. Through endeavors of using Genetic Algorithms, the wideband Eleven antennas have been gradually optimized in term of matching as well as efficiencies. Besides, the rotationally symmetric circular Eleven feed is a very promising solution for improving the BOR1 efficiency and therefore the aperture efficiency by a fraction of dB. Last but not least, the two multiport L-band lab models measured in a reverberation chamber demonstrate that the Eleven antenna with MIMO diversity ports can possibly overcome narrowband multipath fading in a real radio link and improve the link quality in terms of a significant diversity gain and high maximum available capacity.

Image reconstruction, in common with many other inverse problems, is often mathematically ill-posed in the sense that solutions are neither stable nor unique. Ultrasonic image reconstruction is particularly notorious in this regard, with narrow transducer bandwidths and limited - sometimes sparsely sampled apertures posing formidable difficulties for conventional signal processing. To overcome these difficulties, some form of regularisation is mandatory, whereby the ill-posed problem is restated as a closely related, well-posed problem, and then solved uniquely. This thesis explores the application of maximum entropy (MaxEnt) regularisation to the problem of reconstructing complex-valued imagery from sparsely sampled coherent ultrasonic field data, with particular emphasis on three-dimensional problems in the non-destructive evaluation (NDE) of materials. MaxEnt has not previously been applied to this class of problem, and yet in comparison with many other approaches to image reconstruction, it emerges as the clear leader in terms of resolution and overall image quality. To account for this performance, it is argued that the default image model used with MaxEnt is particularly meaningful in cases of ultrasonic scattering by objects embedded in homogeneous media. To establish physical and mathematical insights into the forward problem, linear equations describing scattering from both penetrable and impenetrable objects are first derived using the Born and physical optics approximations respectively. These equations are then expressed as a shift-invariant computational model that explicitly incorporates sparse sampling. To validate this model, time-domain scattering responses are computed and compared with analytical solutions for a simple canonical test case drawn from the field of NDE. The responses computed via the numerical model are shown to accurately reproduce the analytical responses. To solve inverse scattering problems via MaxEnt, the robust Cambridge algorithm is generalised to the complex domain and extended to handle broadband (multiple-frequency) data. Two versions of the augmented algorithm are then compared with a range of other algorithms, including several linearly regularised algorithms and lastly, due to its acknowledged status as a competitor with MaxEnt in radio-astronomy, the non-linear CLEAN algorithm. These comparisons are made through simulated 3-D imaging experiments under conditions of both complete and sparse aperture sampling with low and high levels of additive Gaussian noise. As required in any investigation of inverse problems, the experimental confirmation of algorithmic performance is emphasised, and two common imaging geometries relevant to NDE are selected for this purpose. In monostatic synthetic aperture imaging experiments involving side-drilled holes in an aluminium plate and test objects immersed in H2O, MaxEnt image reconstruction is demonstrated to be robust against grating-lobe and side-lobe formation, in addition to temporal bandwidth restriction. This enables efficient reconstruction of 2-D and 3-D images from small numbers of discrete samples in the spatial and frequency domains. The thesis concludes with a description of the design and testing of a novel polyvinylidene fluoride (PVDF) bistatic array transducer that offers advantages over conventional point-sampled arrays in terms of construction simplicity and signal-to-noise ratio. This ultra-sparse orthogonal array is the only one of its kind yet demonstrated, and was made possible by MaxEnt signal processing.

Thesis (Ph. D.)--Ohio University, June, 1990. / Title from PDF t.p.

Zugl.: Erlangen, Nürnberg, Univ., Diss., 2005

Diss. (sammanfattning) Uppsala : Univ., 2002. / Härtill 5 uppsatser.

Diss. Stockholm : Karol. inst., 2004.