Matching Items (123)
Description
Functional magnetic resonance imaging (fMRI) has been widely used to measure the retinotopic organization of early visual cortex in the human brain. Previous studies have identified multiple visual field maps (VFMs) based on statistical analysis of fMRI signals, but the resulting geometry has not been fully characterized with mathematical models. This thesis explores using concepts from computational conformal geometry to create a custom software framework for examining and generating quantitative mathematical models for characterizing the geometry of early visual areas in the human brain. The software framework includes a graphical user interface built on top of a selected core conformal flattening algorithm and various software tools compiled specifically for processing and examining retinotopic data. Three conformal flattening algorithms were implemented and evaluated for speed and how well they preserve the conformal metric. All three algorithms performed well in preserving the conformal metric but the speed and stability of the algorithms varied. The software framework performed correctly on actual retinotopic data collected using the standard travelling-wave experiment. Preliminary analysis of the Beltrami coefficient for the early data set shows that selected regions of V1 that contain reasonably smooth eccentricity and polar angle gradients do show significant local conformality, warranting further investigation of this approach for analysis of early and higher visual cortex.
ContributorsTa, Duyan (Author) / Wang, Yalin (Thesis advisor) / Maciejewski, Ross (Committee member) / Wonka, Peter (Committee member) / Arizona State University (Publisher)
Created2013
Description
In blindness research, the corpus callosum (CC) is the most frequently studied sub-cortical structure, due to its important involvement in visual processing. While most callosal analyses from brain structural magnetic resonance images (MRI) are limited to the 2D mid-sagittal slice, we propose a novel framework to capture a complete set of 3D morphological differences in the corpus callosum between two groups of subjects. The CCs are segmented from whole brain T1-weighted MRI and modeled as 3D tetrahedral meshes. The callosal surface is divided into superior and inferior patches on which we compute a volumetric harmonic field by solving the Laplace's equation with Dirichlet boundary conditions. We adopt a refined tetrahedral mesh to compute the Laplacian operator, so our computation can achieve sub-voxel accuracy. Thickness is estimated by tracing the streamlines in the harmonic field. We combine areal changes found using surface tensor-based morphometry and thickness information into a vector at each vertex to be used as a metric for the statistical analysis. Group differences are assessed on this combined measure through Hotelling's T2 test. The method is applied to statistically compare three groups consisting of: congenitally blind (CB), late blind (LB; onset > 8 years old) and sighted (SC) subjects. Our results reveal significant differences in several regions of the CC between both blind groups and the sighted groups; and to a lesser extent between the LB and CB groups. These results demonstrate the crucial role of visual deprivation during the developmental period in reshaping the structural architecture of the CC.
ContributorsXu, Liang (Author) / Wang, Yalin (Thesis advisor) / Maciejewski, Ross (Committee member) / Ye, Jieping (Committee member) / Arizona State University (Publisher)
Created2013
Description
Sparsity has become an important modeling tool in areas such as genetics, signal and audio processing, medical image processing, etc. Via the penalization of l-1 norm based regularization, the structured sparse learning algorithms can produce highly accurate models while imposing various predefined structures on the data, such as feature groups or graphs. In this thesis, I first propose to solve a sparse learning model with a general group structure, where the predefined groups may overlap with each other. Then, I present three real world applications which can benefit from the group structured sparse learning technique. In the first application, I study the Alzheimer's Disease diagnosis problem using multi-modality neuroimaging data. In this dataset, not every subject has all data sources available, exhibiting an unique and challenging block-wise missing pattern. In the second application, I study the automatic annotation and retrieval of fruit-fly gene expression pattern images. Combined with the spatial information, sparse learning techniques can be used to construct effective representation of the expression images. In the third application, I present a new computational approach to annotate developmental stage for Drosophila embryos in the gene expression images. In addition, it provides a stage score that enables one to more finely annotate each embryo so that they are divided into early and late periods of development within standard stage demarcations. Stage scores help us to illuminate global gene activities and changes much better, and more refined stage annotations improve our ability to better interpret results when expression pattern matches are discovered between genes.
ContributorsYuan, Lei (Author) / Ye, Jieping (Thesis advisor) / Wang, Yalin (Committee member) / Xue, Guoliang (Committee member) / Kumar, Sudhir (Committee member) / Arizona State University (Publisher)
Created2013
Description
Over 2 billion people are using online social network services, such as Facebook, Twitter, Google+, LinkedIn, and Pinterest. Users update their status, post their photos, share their information, and chat with others in these social network sites every day; however, not everyone shares the same amount of information. This thesis explores methods of linking publicly available data sources as a means of extrapolating missing information of Facebook. An application named "Visual Friends Income Map" has been created on Facebook to collect social network data and explore geodemographic properties to link publicly available data, such as the US census data. Multiple predictors are implemented to link data sets and extrapolate missing information from Facebook with accurate predictions. The location based predictor matches Facebook users' locations with census data at the city level for income and demographic predictions. Age and relationship based predictors are created to improve the accuracy of the proposed location based predictor utilizing social network link information. In the case where a user does not share any location information on their Facebook profile, a kernel density estimation location predictor is created. This predictor utilizes publicly available telephone record information of all people with the same surname of this user in the US to create a likelihood distribution of the user's location. This is combined with the user's IP level information in order to narrow the probability estimation down to a local regional constraint.
ContributorsMao, Jingxian (Author) / Maciejewski, Ross (Thesis advisor) / Farin, Gerald (Committee member) / Wang, Yalin (Committee member) / Arizona State University (Publisher)
Created2012
Description
This document presents a new implementation of the Smoothed Particles Hydrodynamics algorithm using DirectX 11 and DirectCompute. The main goal of this document is to present to the reader an alternative solution to the largely studied and researched problem of fluid simulation. Most other solutions have been implemented using the NVIDIA CUDA framework; however, the proposed solution in this document uses the Microsoft general-purpose computing on graphics processing units API. The implementation allows for the simulation of a large number of particles in a real-time scenario. The solution presented here uses the Smoothed Particles Hydrodynamics algorithm to calculate the forces within the fluid; this algorithm provides a Lagrangian approach for discretizes the Navier-Stockes equations into a set of particles. Our solution uses the DirectCompute compute shaders to evaluate each particle using the multithreading and multi-core capabilities of the GPU increasing the overall performance. The solution then describes a method for extracting the fluid surface using the Marching Cubes method and the programmable interfaces exposed by the DirectX pipeline. Particularly, this document presents a method for using the Geometry Shader Stage to generate the triangle mesh as defined by the Marching Cubes method. The implementation results show the ability to simulate over 64K particles at a rate of 900 and 400 frames per second, not including the surface reconstruction steps and including the Marching Cubes steps respectively.
ContributorsFigueroa, Gustavo (Author) / Farin, Gerald (Thesis advisor) / Maciejewski, Ross (Committee member) / Wang, Yalin (Committee member) / Arizona State University (Publisher)
Created2012
Description
Alzheimer's Disease (AD) is the most common form of dementia observed in elderly patients and has significant social-economic impact. There are many initiatives which aim to capture leading causes of AD. Several genetic, imaging, and biochemical markers are being explored to monitor progression of AD and explore treatment and detection options. The primary focus of this thesis is to identify key biomarkers to understand the pathogenesis and prognosis of Alzheimer's Disease. Feature selection is the process of finding a subset of relevant features to develop efficient and robust learning models. It is an active research topic in diverse areas such as computer vision, bioinformatics, information retrieval, chemical informatics, and computational finance. In this work, state of the art feature selection algorithms, such as Student's t-test, Relief-F, Information Gain, Gini Index, Chi-Square, Fisher Kernel Score, Kruskal-Wallis, Minimum Redundancy Maximum Relevance, and Sparse Logistic regression with Stability Selection have been extensively exploited to identify informative features for AD using data from Alzheimer's Disease Neuroimaging Initiative (ADNI). An integrative approach which uses blood plasma protein, Magnetic Resonance Imaging, and psychometric assessment scores biomarkers has been explored. This work also analyzes the techniques to handle unbalanced data and evaluate the efficacy of sampling techniques. Performance of feature selection algorithm is evaluated using the relevance of derived features and the predictive power of the algorithm using Random Forest and Support Vector Machine classifiers. Performance metrics such as Accuracy, Sensitivity and Specificity, and area under the Receiver Operating Characteristic curve (AUC) have been used for evaluation. The feature selection algorithms best suited to analyze AD proteomics data have been proposed. The key biomarkers distinguishing healthy and AD patients, Mild Cognitive Impairment (MCI) converters and non-converters, and healthy and MCI patients have been identified.
ContributorsDubey, Rashmi (Author) / Ye, Jieping (Thesis advisor) / Wang, Yalin (Committee member) / Wu, Tong (Committee member) / Arizona State University (Publisher)
Created2012
Description
I travelled and worked in international fisheries policy for 7 months in preparation for this thesis. During this time I completed one internship in Rome, Italy with the Food and Agriculture Organization of the United Nations (UNFAO) and another internship on the island of Pohnpei with the Secretariat of the Western and Central Pacific Fisheries Commission (WCPFC). From these experiences, I selected the subject of this thesis. My thesis analyzes the management system for South Pacific albacore tuna, the source stock for brands like "Chicken of the Sea" and "Starkist". South Pacific albacore tuna pass through international waters and the waters of several Pacific Island countries and territories, necessitating States to cooperate and coordinate to sustain the future viability of the stock. A case study for transboundary natural resource management, I discuss the institutional complexity that arises from managing such a resource. I use common-pool resource (CPR) theory to describe this complexity, which frames natural resource management as a collective-action problem among resource users. I first conceptualize the management system as having multiple institutional scales and multiple levels of organization. Then, employing Ostrom's 8 design principles for successful CPR management, I conduct a multi-institution analysis of the international, regional, and subregional institutions that participate in the management system. Finally, I also conduct a cross-institution analysis by examining the interactions between these institutions. I find that significant space for theoretical development exists in CPR theory for understanding complex management systems for transboundary natural resources. Furthermore, I find that interactions between institutions create linkages that could be retooled to improve the performance of the South Pacific albacore tuna management system.
ContributorsAbolhassani, Angela Maryam (Author) / Abbott, Kenneth (Thesis director) / Schoon, Michael (Committee member) / Barrett, The Honors College (Contributor) / School of Politics and Global Studies (Contributor) / School of Life Sciences (Contributor) / Department of English (Contributor)
Created2015-05
Description
This paper explores two areas of study: Colony Collapse Disorder and urban apiculture--the practice of keeping bees in urban areas. Additionally, this paper discusses the ways in which Colony Collapse Disorder has encouraged an increase in urban beekeeping, and the possible role of urban apiculture as a means of combatting the negative effects of Colony Collapse Disorder. The symptoms, history, and possible causes of Colony Collapse Disorder are presented, as well as the important role that honey bees play in human agriculture. Following the discussion of Colony Collapse Disorder is a description of my urban beekeeping apprenticeship at Desert Marigold School where I kept bees, researched various hives, attended a beekeeping workshop in Tucson, and eventually built a hive and established a colony with my mentor. This paper includes a guide to beekeeping basics, as well as a guide to starting a hive based upon the lessons learned during my apprenticeship.
ContributorsRomero, Madelyn Rattan (Author) / Schoon, Michael (Thesis director) / Silcox, Holly (Committee member) / Barrett, The Honors College (Contributor) / School of Sustainability (Contributor) / School of Geographical Sciences and Urban Planning (Contributor)
Created2015-05
Description
South Mountain is the largest municipal park in the nation. It is a bundled amenity, providing a series of linked services to the surrounding communities. A dataset of 19,209 homes in 155 neighborhoods within three miles of the park was utilized in order to complete a hedonic estimation for two nearby urban villages, Ahwatukee Foothills and South Mountain Village. Measures of access include proximity to the park, trailhead access, and adjacency to the park. Two regressions were estimated, the first including lot characteristics and subdivision fixed effects and the second using the coefficients for each subdivision as the dependent variable. These estimates describe how the location of a house in a subdivision contributes to its conditional mean price. As a result they offer a direct basis for capturing amenities measured at the neighborhood scale on home values. Park proximity, trailhead access and adjacency were found to significantly influence the price of homes at the 5% confidence level in Ahwatukee, but not in South Mountain Village. The results of this study can be applied to issues of environmental justice and park access in determining which areas and attributes of the park are associated with a high premium. Though South Mountain was preserved some time ago, development and future preservation in the City of Phoenix can be informed by such studies.
ContributorsRamakrishna, Saritha Kambhampati (Author) / Abbott, Joshua (Thesis director) / Smith, V. Kerry (Committee member) / Schoon, Michael (Committee member) / Barrett, The Honors College (Contributor) / School of Sustainability (Contributor) / Economics Program in CLAS (Contributor) / Department of English (Contributor)
Created2015-05
Hiking and Hegemony: Destabilizing the nature/culture and gender binaries through outdoor recreation
Description
This paper explores the contested relationships between nature, culture, and gender. In order to analyze these relationships, we look specifically at outdoor recreation. Furthermore, we employ poststructuralist feminist theory in order to produce three frameworks; the first of which is titled Mother Nature’s Promiscuous Past. Rooted in Old World and colonial values, this framework illustrates the flawed feminization of nature by masculinity, and its subsequent extortion of anything related to femininity — including women and nature itself. This belief barred women from nature, resulting in a lack of access for women to outdoor recreation.
Our second framework, titled The Pleasurable Potential of Outdoor Recreation, cites second-wave feminism as a catalyst for women’s participation in wilderness exploration and outdoor recreation. The work of radical feminists and the women’s liberation movement in 1960s and 1970s empowered women at home, in the workplace, and eventually, in the outdoors; women reclaimed their wilderness, yet they continued to employ Framework One’s feminization of nature. Ecofeminsim brought together nature and women, seeking to bring justice to two groups wronged by the same entity: masculinity. In this context, outdoor recreation is empowering for women.
Despite the potential of Framework Two to reinscribe and better the experiences of women in outdoor recreation, we argue that both Frameworks One and Two perpetuate the gender binary and the nature/culture binary, because they are based upon the notion that women are in fact fundamentally different and separate from men, the notion that nature is an entity separate from culture, or human society, as well as the notion that nature is in fact a feminine entity.
Our third framework, Deer Pay No Mind to Your Genitals, engages poststructuralism, asserting that outdoor recreation and activities that occur in nature can serve to destabilize and deconstruct notions of the gender binary. However, we argue that care must be exercised during this process as not to perpetuate the problematic nature/culture binary, a phenomenon that is unproductive in terms of both sustainability and gender liberation. Outdoor recreation has been used by many as a tool to deconstruct numerous societal constraints, including the gender binary; this, however, continues to attribute escapist and isolationist qualities toward nature, and therefore perpetuating the nature/culture divide. Ultimately, we argue outdoor recreation can and should be used as a tool deconstruct the gender binary, however needs to account for the fact that if nature is helping to construct elements of culture, then the two cannot be separate.
Our second framework, titled The Pleasurable Potential of Outdoor Recreation, cites second-wave feminism as a catalyst for women’s participation in wilderness exploration and outdoor recreation. The work of radical feminists and the women’s liberation movement in 1960s and 1970s empowered women at home, in the workplace, and eventually, in the outdoors; women reclaimed their wilderness, yet they continued to employ Framework One’s feminization of nature. Ecofeminsim brought together nature and women, seeking to bring justice to two groups wronged by the same entity: masculinity. In this context, outdoor recreation is empowering for women.
Despite the potential of Framework Two to reinscribe and better the experiences of women in outdoor recreation, we argue that both Frameworks One and Two perpetuate the gender binary and the nature/culture binary, because they are based upon the notion that women are in fact fundamentally different and separate from men, the notion that nature is an entity separate from culture, or human society, as well as the notion that nature is in fact a feminine entity.
Our third framework, Deer Pay No Mind to Your Genitals, engages poststructuralism, asserting that outdoor recreation and activities that occur in nature can serve to destabilize and deconstruct notions of the gender binary. However, we argue that care must be exercised during this process as not to perpetuate the problematic nature/culture binary, a phenomenon that is unproductive in terms of both sustainability and gender liberation. Outdoor recreation has been used by many as a tool to deconstruct numerous societal constraints, including the gender binary; this, however, continues to attribute escapist and isolationist qualities toward nature, and therefore perpetuating the nature/culture divide. Ultimately, we argue outdoor recreation can and should be used as a tool deconstruct the gender binary, however needs to account for the fact that if nature is helping to construct elements of culture, then the two cannot be separate.
ContributorsPolick-Kirkpatrick, Kaelyn (Co-author) / Downing, Haley Marie (Co-author) / Dove-Viebahn, Aviva (Thesis director) / Schoon, Michael (Committee member) / School of Sustainability (Contributor) / School of Social Transformation (Contributor) / Economics Program in CLAS (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05