Bounded PCA based Multi Sensor Image Fusion Employing Curvelet Transform Coefficients

The fusion of thermal and visible images acts as an important device for target detection. The quality of the spectral content of the fused image improves with wavelet-based image fusion. However, compared to PCA-based fusion, most wavelet-based methods provide results with a lower spatial resolution. The outcome gets better when the two approaches are combined, but they may still be refined. Compared to wavelets, the curvelet transforms more accurately depict the edges in the image. Enhancing the edges is a smart way to improve spatial resolution and the edges are crucial for interpreting the images. The fusion technique that utilizes curvelets enables the provision of additional data in both spectral and spatial areas concurrently. In this paper, we employ an amalgamation of Curvelet Transform and a Bounded PCA (CTBPCA) method to fuse thermal and visible images. To evidence the enhanced efficiency of our proposed technique, multiple evaluation metrics and comparisons with existing image merging methods are employed. Our approach outperforms others in both qualitative and quantitative analysis, except for runtime performance. Future Enhancement-The study will be based on using the fused image for target recognition. Future work should also focus on this method’s continued improvement and optimization for real-time video processing

Principal Component Analysis based Image Fusion Routine with Application to Stamping Split Detection

This dissertation presents a novel thermal and visible image fusion system with application in online automotive stamping split detection. The thermal vision system scans temperature maps of high reflective steel panels to locate abnormal temperature readings indicative of high local wrinkling pressure that causes metal splitting. The visible vision system offsets the blurring effect of thermal vision system caused by heat diffusion across the surface through conduction and heat losses to the surroundings through convection. The fusion of thermal and visible images combines two separate physical channels and provides more informative result image than the original ones. Principal Component Analysis (PCA) is employed for image fusion to transform original image to its eigenspace. By retaining the principal components with influencing eigenvalues, PCA keeps the key features in the original image and reduces noise level. Then a pixel level image fusion algorithm is developed to fuse images from the thermal and visible channels, enhance the result image from low level and increase the signal to noise ratio. Finally, an automatic split detection algorithm is designed and implemented to perform online objective automotive stamping split detection. The integrated PCA based image fusion system for stamping split detection is developed and tested on an automotive press line. It is also assessed by online thermal and visible acquisitions and illustrates performance and success. Different splits with variant shape, size and amount are detected under actual operating conditions

Face recognition in 2D and 2.5D using ridgelets and photometric stereo

A new technique for face recognition - Ridgefaces - is presented. The method combines the well-known Fisherface method with the ridgelet transform and high-speed Photometric Stereo (PS). The paper first derives ridgelet projections for 2D/2.5D face images before the Fisherface approach is used to reduce the dimensionality and increase the spread of the resulting feature vectors. The ridgelet transform is attractive because it is efficient at extracting highly discriminating low-frequency directional features. Best recognition is obtained when Ridgefaces is performed on surface normals acquired from PS, although good results are also found using standard 2D images and PS-derived albedo maps. © 2012 Elsevier Ltd. All rights reserved

Development of novel 3D porous melt-derived bioactive glass scaffolds

The aim of this thesis is to develop a method to produce melt-derived bioactive glass scaffolds, without the glass crystallizing into a glass-ceramic, while establishing an interconnected pore network suitable for bone tissue regeneration. In order to achieve this, the scaffold must have the ability to closely mimic the porous structure of cancellous bone and its mechanical properties. Two bioactive glasses were used in this project, both are modified from the Bioglass® composition: ICIE 16 (49.46% SiO2, 36.27% CaO, 6.6% Na2O, 6.6% K2O and 1.07% P2O5, all in mol%) and ICIE 16M (49.46% SiO2, 27.27% CaO, 6.6% Na2O, 6.6% K2O, 3% ZnO, 3% MgO, 3% SrO and 1.07% P2O5, all in mol%). Gel-cast foaming produced improved pore networks over alternative methods for producing porous scaffolds. There are many variables in the process. An initial protocol was established and each of the variables assessed systematically. The relationships between each component, the gelling time and the foam body volume were evaluated to develop an optimized protocol for the process. The size of the glass powder was critical in determining the sintering efficiency. A suitable drying and sintering program was also determined to prevent crystallization of the glass and formation of crystal species from by-products of the process. The scaffolds were characterized in terms of the interconnect size, the rate of hydroxycarbonate apatite (HCA) formation in simulated body fluid (SBF) solutions, the ion release rate and the compressive strength. The results showed that ICIE 16M sintered better and was stronger than ICIE 16, however in the bioactivity aspect of view, the rate of HCA formation in SBF was faster for ICIE 16 than ICIE 16M

Optimized state feedback regulation of 3DOF helicopter system via extremum seeking

In this paper, an optimized state feedback regulation of a 3 degree of freedom (DOF) helicopter is designed via extremum seeking (ES) technique. Multi-parameter ES is applied to optimize the tracking performance via tuning State Vector Feedback with Integration of the Control Error (SVFBICE). Discrete multivariable version of ES is developed to minimize a cost function that measures the performance of the controller. The cost function is a function of the error between the actual and desired axis positions. The controller parameters are updated online as the optimization takes place. This method significantly decreases the time in obtaining optimal controller parameters. Simulations were conducted for the online optimization under both fixed and varying operating conditions. The results demonstrate the usefulness of using ES for preserving the maximum attainable performance

Volume variation in a thermochemical material- An experimental study

The research focuses on swelling and shrinkage during cycling of a thermochemical material. Potassium carbonate has been cycled and the change in size has been monitored over subsequent cycles with the help of in-situ measurement in the micro-climate chamber. The experiments have been performed for different operating conditions and the resultant images were processed to calculate the equivalent diameter of the salt grains. Micro -CT scans were performed for both the samples to compare the two-dimensional results from in-situ experiments to a complete three-dimensional analysis

An integrative and systems biology approach to Drosophila melanogaster transcriptomes

The availability of fully sequenced genomes of the model organisms including Drosophila, and their subsequent annotation has afforded seamless opportunities for reverse genetics in a complex model organism. With the advent of DNA microarrays to assay the levels of tens of thousands of genes in a single sample, functional genomics has been significantly aided to understand the functions in systems context. These microarrays have been employed predominantly on the RNA samples that are extracted from the whole animals for example at different developmental stages or in response to external stimuli. However, these approaches relied on the expression patterns that represent the sum of transcription coming from all the organs, which do not estimate the tissue-specificity of transcription. The purpose of this thesis is to provide tissue-specific transcriptomes of Drosophila melanogaster that were generated as part of the large FlyAtlas project using Affymetrix Drosophila GeneChips® (or microarrays). These chips, one at a time interrogate the levels of 18,500 transcripts (that represent all known genes) using 18,880 distinct probe sets in a single, total RNA sample. For each tissue, four biological replicates were analysed using the chips and the normalised signal intensities were obtained that represent the relative levels of mRNA expression. Using the transcriptomes, a general analysis was performed for potential novel insights into tissue-specific functions (Chintapalli et al., 2007) (Chapter 3). Then, a comparative analysis of epithelial tissues was performed to understand how the epithelia are organised in terms of their transcriptomes (Chapter 4). The Malpighian tubules are the Drosophila epithelial counterparts of the human kidney. They show asymmetric organisation in the body cavity. FlyAtlas segment-specific tubule transcriptomes allowed the comparison of their potential functional similarities and differences, thus to understand the asymmetry in function (Chapter 5)(Chintapalli, 2012). This identified a human Best vitelliform macular dystrophy (BVMD) disease homolog, Best2 in only the anterior pair of tubules that have the morphologically and functionally distinct enlarged initial (or distal) segment, a storage organ for Ca2+. Bestrophins were accordingly selected as candidate genes to analyse organismal functions, and thus to validate previous two theories that implicated bestrophins as Ca2+-activated Clˉ channels and/or Ca2+ channel regulators (Chapter 6). The confocal microscopy analysis of bestrophin YFP fusion proteins revealed interesting and novel localisations of bestrophins, in that Best1 was found in the apical plasma membranes, Best2 localised to peroxisomes, Best3 and Best4 were found intracellular. The salt survival analysis showed that Best1 is essential in regulating extra salt levels in the body. Furthermore, the fluid secretion analysis showed Best1’s potential role in Ca2+-dependent Clˉ function. Interestingly, the flies with reduced levels of Best2 expression showed increased ability to survive on extra salt food; the basis for this was investigated further in Chapter 7. Best2 was also found abundant in the eyes than anywhere else in the head. A comparative analysis of anterior tubule- and eye-specific transcriptomes revealed a potential overlap of Ca2+ signaling components, in that the PLCβ signaling was one. A neuropeptide Ca2+ agonist, capa1 evoked secondary cytosolic Ca2+ responses were found high in Best2 knockdowns. A quantitative PCR (qPCR) analysis of candidate Ca2+ signaling and homeostasis genes in Best2 mutants revealed their gene expression upregulation, under control-fed and salt-fed conditions than their wildtype controls, fed on similar diet regimes. The norpA that encodes PLCβ was found significantly enriched in the mutants. Cyp6a23 is another gene that was highly upregulated in Best2 mutants; it is a Drosophila homologue of human Cyp11b, a Ca2+-responsive gene implicated in renal salt wasting. Upon the downregulation of Cyp6a23, flies became sensitive to salt diet feeding. Other genes investigated and found to be upregulated in the mutants include transient-receptor-potential (trp) Ca2+ channel and retinal degeneration C (rdgC). Together, these results strongly suggest Best2 as a potential Ca2+ channel regulator, and provide fascinating insight into bestrophin function. Peroxisomal localisation of Best2 in line with the implication that peroxisomes act as dynamic regulators of cell Ca2+ homeostasis led to another aspect of the project (Chapter 8). This study identified two peroxins that are most abundant in the tubules and play essential roles in the novel cyclic nucleotide-regulated peroxisomal Ca2+ sequestration and transport pathway and that are detrimental for peroxisome biogenesis and proliferation

Clean Coal Program Research Activities

Although remarkable progress has been made in developing technologies for the clean and efficient utilization of coal, the biggest challenge in the utilization of coal is still the protection of the environment. Specifically, electric utilities face increasingly stringent restriction on the emissions of NO{sub x} and SO{sub x}, new mercury emission standards, and mounting pressure for the mitigation of CO{sub 2} emissions, an environmental challenge that is greater than any they have previously faced. The Utah Clean Coal Program addressed issues related to innovations for existing power plants including retrofit technologies for carbon capture and sequestration (CCS) or green field plants with CCS. The Program focused on the following areas: simulation, mercury control, oxycoal combustion, gasification, sequestration, chemical looping combustion, materials investigations and student research experiences. The goal of this program was to begin to integrate the experimental and simulation activities and to partner with NETL researchers to integrate the Program's results with those at NETL, using simulation as the vehicle for integration and innovation. The investigators also committed to training students in coal utilization technology tuned to the environmental constraints that we face in the future; to this end the Program supported approximately 12 graduate students toward the completion of their graduate degree in addition to numerous undergraduate students. With the increased importance of coal for energy independence, training of graduate and undergraduate students in the development of new technologies is critical