Browsing by Subject "Wavelets"
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Item Discrete wavelet analysis of acoustic emissions during fatigue loading of carbon fiber reinforced composites(Texas Tech University, 1996-05) Kamala, Girish P.Acoustic Emissions (AE) are generated during operational loading of Fiber Reinforced Composite (FRC) materials due to various sources of fracture. These sources which include matrix fracture, fiber fracture, splitting and delamination could be generated individually or simultaneously. The multiplicity of defects and failure modes creates problems in identifying and distinguishing various sources of emissions. This analysis is further complicated due to the friction related emissions (generated during grating of newly generated damage surfaces and fretting of broken fibers with matrix) that mask the actual signal and in most cases, exceeds the emissions from actual damage. The purpose of this thesis is to investigate the appUcability of discrete wavelet transforms in the analysis and time-frequency breakdown of AE signals detected during fatigue loading of FRC materials. The first objective is to decompose the AE signals into different levels based on the central frequency around which the emissions are generated. The second objective is to identify the frequency at which friction based emissions are generated. The final objective is to determine if a possibility exists to associate various failure modes with specific frequencies.Item Dynamic resource allocation for energy management in data centers(2009-05-15) Rincon Mateus, Cesar AugustoIn this dissertation we study the problem of allocating computational resources and managing applications in a data center to serve incoming requests in such a way that the energy usage, reliability and quality of service considerations are balanced. The problem is motivated by the growing energy consumption by data centers in the world and their overall inefficiency. This work is focused on designing flexible and robust strategies to manage the resources in such a way that the system is able to meet the service agreements even when the load conditions change. As a first step, we study the control of a Markovian queueing system with controllable number of servers and service rates (M=Mt=kt ) to minimize effort and holding costs. We present structural properties of the optimal policy and suggest an algorithm to find good performance policies even for large cases. Then we present a reactive/proactive approach, and a tailor-made wavelet-based forecasting procedure to determine the resource allocation in a single application setting; the method is tested by simulation with real web traces. The main feature of this method is its robustness and flexibility to meet QoS goals even when the traffic behavior changes. The system was tested by simulating a system with a time service factor QoS agreement. Finally, we consider the multi-application setting and develop a novel load consolidation strategy (of combining applications that are traditionally hosted on different servers) to reduce the server-load variability and the number of booting cycles in order to obtain a better capacity allocation.Item Ecological and evolutionary analyses of range limits and biodiversity patterns(2011-12) Behrman, Kathrine Delany; Keitt, Timothy H.; Kirkpatrick, Mark, 1956-The goal of this dissertation is to further our understanding of how spatially heterogeneous landscapes may impact the formation of range boundaries that then aggregate to form large-scale biodiversity patterns. These patterns have been analyzed from many different perspectives by ecologists, evolutionary biologist, and physiologists using a variety of different theoretical, statistical, and mechanistic models. For some species, there is an obvious abrupt change in the environment causing a range boundary. Other environments change gradually, and it is unclear why species fail to adapt and expand their range. The first chapter develops a novel theoretical model of how the establishment of new mutations allows for adaptation to an environmental gradient, when there is no genetic variation for the trait that limits the range. Shallow environmental gradients favor mutations that arise nearer to the range margin, have smaller phenotypic effects, and allow for proportionately larger expansions than steep gradients. Mutations that allow for range expansion tend to have large phenotypic effects causing substantial range expansions. Spatial and temporal variation in climatic and environmental variables is important for understanding species response to climate change. The second chapter uses a mechanistic model to simulate switchgrass (Panicum virgatum L.) productivity across the central and eastern U.S. for current and future climate conditions. Florida and the Gulf Coast of Texas and Louisiana have the highest predicted current and future yields. Regions where future temperature and precipitation are anticipated to increase, larger future yields are expected. Large-scale geographic patterns of biodiversity are documented for many taxa. The mechanisms allowing for the coexistence of more of species in certain regions are poorly understood. The third chapter employs a newly developed wavelet lifting technique to extract scale-dependent patterns from irregularly spaced two-dimensional ecological data and analyzes the relationship between breeding avian richness and four energy variables. Evapotranspiration, temperature, and precipitation are significant predictors of richness at intermediate-to-large scales. Net primary production is the only significant predictor across small-to-large scales, and explains the most variation in richness (~40%) at an intermediate scale. Changes in the species-energy relationship with scale, may indicate a shift in the mechanism governing species richness.Item Fast and efficient progressive image coding and transmission using wavelet decomposition(Texas Tech University, 1999-05) Sharma, MohitWith the recent boom in multimedia and the Iniernel. miage compression and techniques for progressive image transmission have become quite important. This thesis describes the concept and design of a codec for progressixc image transmission highlighted by a new technique SPHIT (Set Partitioning in Hierarchical Trees). This technique works on the principles of partial ordering by magnitude utilizing a sci partitioning sorting algorithms, ordered bit plane transmission, and exploitation of selfsimilarity across different scales of an image wavelet transform. The said principles of SPIHT are no different than what was described in the original EZW by J. P. Shapiro. But the approach for implementation of SPIHT is significantly different. Here the ordering information for image data is not explicitly transmitted. Instead, the fact that the execution path of any algorithm is defined by the results of the comparisons on its branching points is exploited to obtain ordering information at the decoder. The decoder and the encoder not only share the same sorting algorithm, but also the same execution path. Thus, the decoder can recover the ordering information from its execution path, which happens to be identical to that of the encoder. An attempt to highlight the basic differences between the EZW and SPIHT is made by taking an example of 8 x 8 image section.Item Multi-scale texture analysis of remote sensing images using gabor filter banks and wavelet transforms(2009-05-15) Ravikumar, RahulTraditional remote sensing image classification has primarily relied on image spectral information and texture information was ignored or not fully utilized. Existing remote sensing software packages have very limited functionalities with respect to texture information extraction and utilization. This research focuses on the use of multi-scale image texture analysis techniques using Gabor filter banks and Wavelet transformations. Gabor filter banks model texture as irradiance patterns in an image over a limited range of spatial frequencies and orientations. Using Gabor filters, each image texture can be differentiated with respect to its dominant spatial frequency and orientation. Wavelet transformations are useful for decomposition of an image into a set of images based on an orthonormal basis. Dyadic transformations are applied to generate a multi-scale image pyramid which can be used for texture analysis. The analysis of texture is carried out using both artificial textures and remotely sensed image corresponding to natural scenes. This research has shown that texture can be extracted and incorporated in conventional classification algorithms to improve the accuracy of classified results. The applicability of Gabor filter banks and Wavelets is explored for classifying and segmenting remote sensing imagery for geographical applications. A qualitative and quantitative comparison between statistical texture indicators and multi-scale texture indicators has been performed. Multi-scale texture indicators derived from Gabor filter banks have been found to be very effective due to the nature of their configurability to target specific textural frequencies and orientations in an image. Wavelet transformations have been found to be effective tools in image texture analysis as they help identify the ideal scale at which texture indicators need to be measured and reduce the computation time taken to derive statistical texture indicators. A robust set of software tools for texture analysis has been developed using the popular .NET and ArcObjects. ArcObjects has been chosen as the API of choice, as these tools can be seamlessly integrated into ArcGIS. This will aid further exploration of image texture analysis by the remote sensing community.Item Optimization of vector quantization for large color images(Texas Tech University, 1999-05) Yang, ShuyuImages are produced to record and store infomiation that people want to preserve. As a matter of fact, visual informadon is more easily accepted and understood than other types of informadon, for example, linguistic information, and thus has become a popular way of representing information. However, compared to other types of information processing, images contain much more data and usually takes more processing time and storage space. With more and more wide use of computers and the Intemet, efficient methods of image transmission and storage are needed because of the limitation of the currently available speed of the Intemet. In other applications, such as medical image transmission and storage, video conferencing. Video On Demand (VOD) systems, where huge amounts of image data storage or fast, real-time image transmission are demanded, image compression can provide a major solution. Image compression involves identification of the redundancy of the information contained in images so as to reduce the amount of data to represent the original image, thus achieving a lower bit rate, less transmission time and storage space.Item Smoothing Wavelet Reconstruction(2013-04-23) Garg, DeepakThis thesis present a new algorithm for creating high quality surfaces from large data sets of oriented points, sampled using a laser range scanner. This method works in two phases. In the first phase, using wavelet surface reconstruction method, we calculate a rough estimate of the surface in the form of Haar wavelet coefficients, stored in an Octree. In the second phase, we modify these coefficients to obtain a higher quality surface. We cast this method as a gradient minimization problem in the wavelet domain. We show that the solution to the gradient minimization problem, in the wavelet domain, is a sparse linear system with dimensionality roughly proportional to the surface of the model in question. We introduce a fast inplace method, which uses various properties of Haar wavelets, to solve the linear system and demonstrate the results of the algorithm.Item Statistical inverse estimation of irregular input signals(Texas Tech University, 1997-12) Chandrawansa, KumariNOT AVAILABLEItem Wavelet transform in image compression(Texas Tech University, 1995-12) Muyshondt, Richard AndrewThe past few years have seen a rapid development in the areas of image compression techniques. The evolution in image compression is mainly attributed to the need of rapid and efficient techniques for the storage and transmission of data among individuals. In order to achieve maximal storage and transmission capabilities, different compression algorithms should be compared in order to find an optimal technique for medical image compression. In this research, we studied the performance of different wavelet basis fiinctions and of a Wavelet Transform (WT) image coding algorithm. We characterized the performance of the wavelet coefficients and the coding algorithm by calculating the mean square error, peak signal to noise ratio, and root mean square signal to noise ratio of the reconstmcted images. In addition, we compared the WT algorithm to the current JPEG standard. We performed comparisons on standard as well as radiographic images using the above criteria in order to judge the compression characteristics of both techniques. In addition, we show that the Adelson 15 wavelet coefficients perform better than Daubechies 4 and 12 wavelet coefficients for image compression. Furthermore, we show that JPEG and the WT algorithm had comparable performance in standard image compression, but the WT algorithm outperformed JPEG in all the above criteria and proved to be a versatile coding technique for radiographic images.