Matching Items (276)
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Currently Java is making its way into the embedded systems and mobile devices like androids. The programs written in Java are compiled into machine independent binary class byte codes. A Java Virtual Machine (JVM) executes these classes. The Java platform additionally specifies the Java Native Interface (JNI). JNI allows Java

Currently Java is making its way into the embedded systems and mobile devices like androids. The programs written in Java are compiled into machine independent binary class byte codes. A Java Virtual Machine (JVM) executes these classes. The Java platform additionally specifies the Java Native Interface (JNI). JNI allows Java code that runs within a JVM to interoperate with applications or libraries that are written in other languages and compiled to the host CPU ISA. JNI plays an important role in embedded system as it provides a mechanism to interact with libraries specific to the platform. This thesis addresses the overhead incurred in the JNI due to reflection and serialization when objects are accessed on android based mobile devices. It provides techniques to reduce this overhead. It also provides an API to access objects through its reference through pinning its memory location. The Android emulator was used to evaluate the performance of these techniques and we observed that there was 5 - 10 % performance gain in the new Java Native Interface.
ContributorsChandrian, Preetham (Author) / Lee, Yann-Hang (Thesis advisor) / Davulcu, Hasan (Committee member) / Li, Baoxin (Committee member) / Arizona State University (Publisher)
Created2011
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Reliable extraction of human pose features that are invariant to view angle and body shape changes is critical for advancing human movement analysis. In this dissertation, the multifactor analysis techniques, including the multilinear analysis and the multifactor Gaussian process methods, have been exploited to extract such invariant pose features from

Reliable extraction of human pose features that are invariant to view angle and body shape changes is critical for advancing human movement analysis. In this dissertation, the multifactor analysis techniques, including the multilinear analysis and the multifactor Gaussian process methods, have been exploited to extract such invariant pose features from video data by decomposing various key contributing factors, such as pose, view angle, and body shape, in the generation of the image observations. Experimental results have shown that the resulting pose features extracted using the proposed methods exhibit excellent invariance properties to changes in view angles and body shapes. Furthermore, using the proposed invariant multifactor pose features, a suite of simple while effective algorithms have been developed to solve the movement recognition and pose estimation problems. Using these proposed algorithms, excellent human movement analysis results have been obtained, and most of them are superior to those obtained from state-of-the-art algorithms on the same testing datasets. Moreover, a number of key movement analysis challenges, including robust online gesture spotting and multi-camera gesture recognition, have also been addressed in this research. To this end, an online gesture spotting framework has been developed to automatically detect and learn non-gesture movement patterns to improve gesture localization and recognition from continuous data streams using a hidden Markov network. In addition, the optimal data fusion scheme has been investigated for multicamera gesture recognition, and the decision-level camera fusion scheme using the product rule has been found to be optimal for gesture recognition using multiple uncalibrated cameras. Furthermore, the challenge of optimal camera selection in multi-camera gesture recognition has also been tackled. A measure to quantify the complementary strength across cameras has been proposed. Experimental results obtained from a real-life gesture recognition dataset have shown that the optimal camera combinations identified according to the proposed complementary measure always lead to the best gesture recognition results.
ContributorsPeng, Bo (Author) / Qian, Gang (Thesis advisor) / Ye, Jieping (Committee member) / Li, Baoxin (Committee member) / Spanias, Andreas (Committee member) / Arizona State University (Publisher)
Created2011
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With the introduction of compressed sensing and sparse representation,many image processing and computer vision problems have been looked at in a new way. Recent trends indicate that many challenging computer vision and image processing problems are being solved using compressive sensing and sparse representation algorithms. This thesis assays some applications

With the introduction of compressed sensing and sparse representation,many image processing and computer vision problems have been looked at in a new way. Recent trends indicate that many challenging computer vision and image processing problems are being solved using compressive sensing and sparse representation algorithms. This thesis assays some applications of compressive sensing and sparse representation with regards to image enhancement, restoration and classication. The first application deals with image Super-Resolution through compressive sensing based sparse representation. A novel framework is developed for understanding and analyzing some of the implications of compressive sensing in reconstruction and recovery of an image through raw-sampled and trained dictionaries. Properties of the projection operator and the dictionary are examined and the corresponding results presented. In the second application a novel technique for representing image classes uniquely in a high-dimensional space for image classification is presented. In this method, design and implementation strategy of the image classification system through unique affine sparse codes is presented, which leads to state of the art results. This further leads to analysis of some of the properties attributed to these unique sparse codes. In addition to obtaining these codes, a strong classier is designed and implemented to boost the results obtained. Evaluation with publicly available datasets shows that the proposed method outperforms other state of the art results in image classication. The final part of the thesis deals with image denoising with a novel approach towards obtaining high quality denoised image patches using only a single image. A new technique is proposed to obtain highly correlated image patches through sparse representation, which are then subjected to matrix completion to obtain high quality image patches. Experiments suggest that there may exist a structure within a noisy image which can be exploited for denoising through a low-rank constraint.
ContributorsKulkarni, Naveen (Author) / Li, Baoxin (Thesis advisor) / Ye, Jieping (Committee member) / Sen, Arunabha (Committee member) / Arizona State University (Publisher)
Created2011
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Description
There are many wireless communication and networking applications that require high transmission rates and reliability with only limited resources in terms of bandwidth, power, hardware complexity etc.. Real-time video streaming, gaming and social networking are a few such examples. Over the years many problems have been addressed towards the goal

There are many wireless communication and networking applications that require high transmission rates and reliability with only limited resources in terms of bandwidth, power, hardware complexity etc.. Real-time video streaming, gaming and social networking are a few such examples. Over the years many problems have been addressed towards the goal of enabling such applications; however, significant challenges still remain, particularly, in the context of multi-user communications. With the motivation of addressing some of these challenges, the main focus of this dissertation is the design and analysis of capacity approaching coding schemes for several (wireless) multi-user communication scenarios. Specifically, three main themes are studied: superposition coding over broadcast channels, practical coding for binary-input binary-output broadcast channels, and signalling schemes for two-way relay channels. As the first contribution, we propose an analytical tool that allows for reliable comparison of different practical codes and decoding strategies over degraded broadcast channels, even for very low error rates for which simulations are impractical. The second contribution deals with binary-input binary-output degraded broadcast channels, for which an optimal encoding scheme that achieves the capacity boundary is found, and a practical coding scheme is given by concatenation of an outer low density parity check code and an inner (non-linear) mapper that induces desired distribution of "one" in a codeword. The third contribution considers two-way relay channels where the information exchange between two nodes takes place in two transmission phases using a coding scheme called physical-layer network coding. At the relay, a near optimal decoding strategy is derived using a list decoding algorithm, and an approximation is obtained by a joint decoding approach. For the latter scheme, an analytical approximation of the word error rate based on a union bounding technique is computed under the assumption that linear codes are employed at the two nodes exchanging data. Further, when the wireless channel is frequency selective, two decoding strategies at the relay are developed, namely, a near optimal decoding scheme implemented using list decoding, and a reduced complexity detection/decoding scheme utilizing a linear minimum mean squared error based detector followed by a network coded sequence decoder.
ContributorsBhat, Uttam (Author) / Duman, Tolga M. (Thesis advisor) / Tepedelenlioğlu, Cihan (Committee member) / Li, Baoxin (Committee member) / Zhang, Junshan (Committee member) / Arizona State University (Publisher)
Created2011
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Description

Papago Park in Tempe, Arizona (USA) is host to several buttes composed of landslide breccias. The focus of this thesis is a butte called “Contact Hill,” which is composed of metarhyolitic debris flows, granitic debris flows, and Barnes Butte Breccia. The Barnes Butte Breccia can be broken down into several

Papago Park in Tempe, Arizona (USA) is host to several buttes composed of landslide breccias. The focus of this thesis is a butte called “Contact Hill,” which is composed of metarhyolitic debris flows, granitic debris flows, and Barnes Butte Breccia. The Barnes Butte Breccia can be broken down into several different compositional categories that can be dated based on their relative ages. The depositional timeline of these rocks is explored through their mineral and physical properties. The rhyolitic debris flow is massively bedded and dips at 26° to the southeast. The granitic debris flow is not bedded and exhibits a mixture of granite clasts of different grain sizes. In thin section analysis, five mineral types were identified: opaque inclusions, white quartz, anhedral and subhedral biotite, yellow stained K-feldspar, and gray plagioclase. It is hypothesized that regional stretching and compression of the crust, accompanied with magmatism, helped bring the metarhyolite and granite to the surface. Domino-like fault blocks caused large brecciation, and collapse of a nearby quartzite and granite mountain helped create the Barnes Butte Breccia: a combination of quartzite, metarhyolite, and granite clasts. Evidence of Papago Park’s ancient terrestrial history is seen in metarhyolite clasts containing sand grains. These geologic events, in addition to erosion, are responsible for Papago Park’s unique appearance today.

ContributorsScheller, Jessica Rose (Author) / Reynolds, Stephen (Thesis director) / Johnson, Julia (Committee member) / School of Earth and Space Exploration (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Stardust grains can provide useful information about the Solar System environment before the Sun was born. Stardust grains show distinct isotopic compositions that indicate their origins, like the atmospheres of red giant stars, asymptotic giant branch stars, and supernovae (e.g., Bose et al. 2010). It has been argued that some

Stardust grains can provide useful information about the Solar System environment before the Sun was born. Stardust grains show distinct isotopic compositions that indicate their origins, like the atmospheres of red giant stars, asymptotic giant branch stars, and supernovae (e.g., Bose et al. 2010). It has been argued that some stardust grains likely condensed in classical nova outbursts (e.g., Amari et al. 2001). These nova candidate grains contain 13C, 15N and 17O-rich nuclides which are produced by proton burning. However, these nuclides alone cannot constrain the stellar source of nova candidate grains. Nova ejecta is rich in 7Be that decays to 7Li (which has a half-life of ~53 days). I want to measure 6,7Li isotopes in nova candidate grains using the NanoSIMS 50L (nanoscale secondary ion mass spectrometry) to establish their nova origins without ambiguity. Several stardust grains that are nova candidate grains were identified in meteorite Acfer 094 on the basis of their oxygen isotopes. The identified silicate and oxide stardust grains are <500 nm in size and exist in the meteorite surrounded by meteoritic silicates. Therefore, 6,7Li isotopic measurements on these grains are hindered because of the large 300-500 nm oxygen ion beam in the NanoSIMS. I devised a methodology to isolate stardust grains by performing Focused Ion Beam milling with the FIB – Nova 200 NanoLab (FEI) instrument. We proved that the current FIB instrument cannot be used to prepare stardust grains smaller than 1 𝜇m due to lacking capabilities of the FIB. For future analyses, we could either use the same milling technique with the new and improved FIB – Helios 5 UX or use the recently constructed duoplasmatron on the NanoSIMS that can achieve a size of ~75 nm oxygen ion beam.

ContributorsDuncan, Ethan Jay (Author) / Bose, Miatrayee (Thesis director) / Starrfield, Sumner (Committee member) / Desch, Steve (Committee member) / School of Earth and Space Exploration (Contributor) / Department of Physics (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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In this study, the influence of fluid mixing on temperature and geochemistry of hot spring fluids is investigated. Yellowstone National Park (YNP) is home to a diverse range of hot springs with varying temperature and chemistry. The mixing zone of interest in this paper, located in Geyser Creek, YNP, has

In this study, the influence of fluid mixing on temperature and geochemistry of hot spring fluids is investigated. Yellowstone National Park (YNP) is home to a diverse range of hot springs with varying temperature and chemistry. The mixing zone of interest in this paper, located in Geyser Creek, YNP, has been a point of interest since at least the 1960’s (Raymahashay, 1968). Two springs, one basic (~pH 7) and one acidic (~pH 3) mix together down an outflow channel. There are visual bands of different photosynthetic pigments which suggests the creation of temperature and chemical gradients due to the fluids mixing. In this study, to determine if fluid mixing is driving these changes of temperature and chemistry in the system, a model that factors in evaporation and cooling was developed and compared to measured temperature and chemical data collected downstream. Comparison of the modeled temperature and chemistry to the measured values at the downstream mixture shows that many of the ions, such as Cl⁻, F⁻, and Li⁺, behave conservatively with respect to mixing. This indicates that the influence of mixing accounts for a large proportion of variation in the chemical composition of the system. However, there are some chemical constituents like CH₄, H₂, and NO₃⁻, that were not conserved, and the concentrations were either depleted or increased in the downstream mixture. Some of these constituents are known to be used by microorganisms. The development of this mixing model can be used as a tool for predicting biological activity as well as building the framework for future geochemical and computational models that can be used to understand the energy availability and the microbial communities that are present.

ContributorsOrrill, Brianna Isabel (Author) / Shock, Everett (Thesis director) / Howells, Alta (Committee member) / School of Life Sciences (Contributor) / School of Earth and Space Exploration (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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This research endeavor explores the 1964 reasoning of Irish physicist John Bell and how it pertains to the provoking Einstein-Podolsky-Rosen Paradox. It is necessary to establish the machinations of formalisms ranging from conservation laws to quantum mechanical principles. The notion that locality is unable to be reconciled with the quantum

This research endeavor explores the 1964 reasoning of Irish physicist John Bell and how it pertains to the provoking Einstein-Podolsky-Rosen Paradox. It is necessary to establish the machinations of formalisms ranging from conservation laws to quantum mechanical principles. The notion that locality is unable to be reconciled with the quantum paradigm is upheld through analysis and the subsequent Aspect experiments in the years 1980-1982. No matter the complexity, any local hidden variable theory is incompatible with the formulation of standard quantum mechanics. A number of strikingly ambiguous and abstract concepts are addressed in this pursuit to deduce quantum's validity, including separability and reality. `Elements of reality' characteristic of unique spaces are defined using basis terminology and logic from EPR. The discussion draws directly from Bell's succinct 1964 Physics 1 paper as well as numerous other useful sources. The fundamental principle and insight gleaned is that quantum physics is indeed nonlocal; the door into its metaphysical and philosophical implications has long since been opened. Yet the nexus of information pertaining to Bell's inequality and EPR logic does nothing but assert the impeccable success of quantum physics' ability to describe nature.

ContributorsRapp, Sean R (Author) / Foy, Joseph (Thesis director) / Martin, Thomas (Committee member) / School of Earth and Space Exploration (Contributor) / Department of Physics (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Stellar mass loss has a high impact on the overall evolution of a star. The amount<br/>of mass lost during a star’s lifetime dictates which remnant will be left behind and how<br/>the circumstellar environment will be affected. Several rates of mass loss have been<br/>proposed for use in stellar evolution codes, yielding

Stellar mass loss has a high impact on the overall evolution of a star. The amount<br/>of mass lost during a star’s lifetime dictates which remnant will be left behind and how<br/>the circumstellar environment will be affected. Several rates of mass loss have been<br/>proposed for use in stellar evolution codes, yielding discrepant results from codes using<br/>different rates. In this paper, I compare the effect of varying the mass loss rate in the<br/>stellar evolution code TYCHO on the initial-final mass relation. I computed four sets of<br/>models with varying mass loss rates and metallicities. Due to a large number of models<br/>reaching the luminous blue variable stage, only the two lower metallicity groups were<br/>considered. Their mass loss was analyzed using Python. Luminosity, temperature, and<br/>radius were also compared. The initial-final mass relation plots showed that in the 1/10<br/>solar metallicity case, reducing the mass loss rate tended to increase the dependence of final mass on initial mass. The limited nature of these results implies a need for further study into the effects of using different mass loss rates in the code TYCHO.

ContributorsAuchterlonie, Lauren (Author) / Young, Patrick (Thesis director) / Shkolnik, Evgenya (Committee member) / Starrfield, Sumner (Committee member) / School of Earth and Space Exploration (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
In many classication problems data samples cannot be collected easily, example in drug trials, biological experiments and study on cancer patients. In many situations the data set size is small and there are many outliers. When classifying such data, example cancer vs normal patients the consequences of mis-classication are probably

In many classication problems data samples cannot be collected easily, example in drug trials, biological experiments and study on cancer patients. In many situations the data set size is small and there are many outliers. When classifying such data, example cancer vs normal patients the consequences of mis-classication are probably more important than any other data type, because the data point could be a cancer patient or the classication decision could help determine what gene might be over expressed and perhaps a cause of cancer. These mis-classications are typically higher in the presence of outlier data points. The aim of this thesis is to develop a maximum margin classier that is suited to address the lack of robustness of discriminant based classiers (like the Support Vector Machine (SVM)) to noise and outliers. The underlying notion is to adopt and develop a natural loss function that is more robust to outliers and more representative of the true loss function of the data. It is demonstrated experimentally that SVM's are indeed susceptible to outliers and that the new classier developed, here coined as Robust-SVM (RSVM), is superior to all studied classier on the synthetic datasets. It is superior to the SVM in both the synthetic and experimental data from biomedical studies and is competent to a classier derived on similar lines when real life data examples are considered.
ContributorsGupta, Sidharth (Author) / Kim, Seungchan (Thesis advisor) / Welfert, Bruno (Committee member) / Li, Baoxin (Committee member) / Arizona State University (Publisher)
Created2011