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Articles 1 - 30 of 31
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Microstructural Analysis Of Thermoelastic Response, Nonlinear Creep, And Pervasive Cracking In Heterogeneous Materials, Alden C. Cook
Microstructural Analysis Of Thermoelastic Response, Nonlinear Creep, And Pervasive Cracking In Heterogeneous Materials, Alden C. Cook
Electronic Theses and Dissertations
This dissertation is concerned with the development of robust numerical solution procedures for the generalized micromechanical analysis of linear and nonlinear constitutive behavior in heterogeneous materials. Although the methods developed are applicable in many engineering, geological, and materials science fields, three main areas are explored in this work. First, a numerical methodology is presented for the thermomechanical analysis of heterogeneous materials with a special focus on real polycrystalline microstructures obtained using electron backscatter diffraction techniques. Asymptotic expansion homogenization and finite element analysis are employed for micromechanical analysis of polycrystalline materials. Effective thermoelastic properties of polycrystalline materials are determined and compared …
Three Body Interactions Of Rare Gas Solids Calculated Within The Einstein Model, Dan D'Andrea
Three Body Interactions Of Rare Gas Solids Calculated Within The Einstein Model, Dan D'Andrea
Masters Theses
Three body interactions can become important in solids at higher pressures and densities as the molecules can come into close contact. At low temperatures, accurate studies of three body interactions in solids require averaging the three-body terms over the molecules' zero point motions. An efficient, but approximate, averaging approach is based on a polynomial approximation of the three-body term. The polynomial approximation can be developed as a function of the symmetry coordinates of a triangle displaced from its average geometry and also as a function of the Cartesian zero point displacements from each atom’s average position. The polynomial approximation approach …
Towards Comprehensive Parametric Code Generation Targeting Graphics Processing Units In Support Of Scientific Computation, Ning Xie
Electronic Thesis and Dissertation Repository
The most popular multithreaded languages based on the fork-join concurrency model (CIlkPlus, OpenMP) are currently being extended to support other forms of parallelism (vectorization, pipelining and single-instruction-multiple-data (SIMD)). In the SIMD case, the objective is to execute the corresponding code on a many-core device, like a GPGPU, for which the CUDA language is a natural choice. Since the programming concepts of CilkPlus and OpenMP are very different from those of CUDA, it is desirable to automatically generate optimized CUDA-like code from CilkPlus or OpenMP.
In this thesis, we propose an accelerator model for annotated C/C++ code together with an implementation …
Development Of Anatomical And Functional Magnetic Resonance Imaging Measures Of Alzheimer Disease, Samaneh Kazemifar
Development Of Anatomical And Functional Magnetic Resonance Imaging Measures Of Alzheimer Disease, Samaneh Kazemifar
Electronic Thesis and Dissertation Repository
Alzheimer disease is considered to be a progressive neurodegenerative condition, clinically characterized by cognitive dysfunction and memory impairments. Incorporating imaging biomarkers in the early diagnosis and monitoring of disease progression is increasingly important in the evaluation of novel treatments. The purpose of the work in this thesis was to develop and evaluate novel structural and functional biomarkers of disease to improve Alzheimer disease diagnosis and treatment monitoring. Our overarching hypothesis is that magnetic resonance imaging methods that sensitively measure brain structure and functional impairment have the potential to identify people with Alzheimer’s disease prior to the onset of cognitive decline. …
Identifying Individual Driver Behaviour Using In-Vehicle Can-Bus Signals Of Pre-Turning Maneuvers, Mahboubeh Zardosht
Identifying Individual Driver Behaviour Using In-Vehicle Can-Bus Signals Of Pre-Turning Maneuvers, Mahboubeh Zardosht
Electronic Thesis and Dissertation Repository
All drivers have their own driving style while performing different driving maneuvers. They vary in using vehicle’s control devices such as the steering wheel, pedals, gears etc. In this thesis, we analyze driving behavior in different timeframes prior to turns. We employ data obtained from actual driving behavior in an urban environment collected from the CAN-Bus of an instrumented vehicle. Five CAN-Bus signals, vehicle speed, gas pedal pressure, brake pedal pressure, steering wheel angle, and acceleration, is collected for 5, 10, and 15 seconds of driving prior to each turn. We consider all turns for each driver as well as …
Computerized Classification Of Surface Spikes In Three-Dimensional Electron Microscopic Reconstructions Of Viruses, Younes Benkarroum
Computerized Classification Of Surface Spikes In Three-Dimensional Electron Microscopic Reconstructions Of Viruses, Younes Benkarroum
Dissertations, Theses, and Capstone Projects
The purpose of this research is to develop computer techniques for improved three-dimensional (3D) reconstruction of viruses from electron microscopic images of them and for the subsequent improved classification of the surface spikes in the resulting reconstruction. The broader impact of such work is the following.
Influenza is an infectious disease caused by rapidly-changing viruses that appear seasonally in the human population. New strains of influenza viruses appear every year, with the potential to cause a serious global pandemic. Two kinds of spikes – hemagglutinin (HA) and neuraminidase (NA) – decorate the surface of the virus particles and these proteins …
Improving The Performance Of Ice Sheet Modeling Through Embedded Simulation, Christopher G. Dufour
Improving The Performance Of Ice Sheet Modeling Through Embedded Simulation, Christopher G. Dufour
Electronic Theses and Dissertations
Understanding the impact of global climate change is a critical concern for society at large. One important piece of the climate puzzle is how large-scale ice sheets, such as those covering Greenland and Antarctica, respond to a warming climate. Given such ice sheets are under constant change, developing models that can accurately capture their dynamics represents a significant challenge to researchers. The problem, however, is properly capturing the dynamics of an ice sheet model requires a high model resolution and simulating these models is intractable even for state-of-the-art supercomputers.
This thesis presents a revolutionary approach to accurately capture ice sheet …
Bayesian Networks To Assess The Newborn Stool Microbiome, William E. Bennett Jr.
Bayesian Networks To Assess The Newborn Stool Microbiome, William E. Bennett Jr.
McKelvey School of Engineering Theses & Dissertations
In human stool, a large population of bacterial genes and transcripts from hundreds of genera coexist with host genes and transcripts. Assessments of the metagenome and transcriptome are particularly challenging, since there is a great deal of sequence overlap among related species and related genes. We sequenced the total RNA content from stool samples in a neonate using previously-described methods. We then performed stepwise alignment of different populations of RNA sequence reads to different indices, including ribosomal databases, the human genome, and all sequenced bacterial genomes. Each pool of RNA at each alignment step was subjected to compression to assess …
An Algorithm For The Machine Calculation Of Minimal Paths, Robert Whitinger
An Algorithm For The Machine Calculation Of Minimal Paths, Robert Whitinger
Electronic Theses and Dissertations
Problems involving the minimization of functionals date back to antiquity. The mathematics of the calculus of variations has provided a framework for the analytical solution of a limited class of such problems. This paper describes a numerical approximation technique for obtaining machine solutions to minimal path problems. It is shown that this technique is applicable not only to the common case of finding geodesics on parameterized surfaces in R3, but also to the general case of finding minimal functionals on hypersurfaces in Rn associated with an arbitrary metric.
Novel Monte Carlo Methods For Large-Scale Linear Algebra Operations, Hao Ji
Novel Monte Carlo Methods For Large-Scale Linear Algebra Operations, Hao Ji
Computer Science Theses & Dissertations
Linear algebra operations play an important role in scientific computing and data analysis. With increasing data volume and complexity in the "Big Data" era, linear algebra operations are important tools to process massive datasets. On one hand, the advent of modern high-performance computing architectures with increasing computing power has greatly enhanced our capability to deal with a large volume of data. One the other hand, many classical, deterministic numerical linear algebra algorithms have difficulty to scale to handle large data sets.
Monte Carlo methods, which are based on statistical sampling, exhibit many attractive properties in dealing with large volume of …
Machine Learning Methods For Brain Image Analysis, Ahmed Fakhry
Machine Learning Methods For Brain Image Analysis, Ahmed Fakhry
Computer Science Theses & Dissertations
Understanding how the brain functions and quantifying compound interactions between complex synaptic networks inside the brain remain some of the most challenging problems in neuroscience. Lack or abundance of data, shortage of manpower along with heterogeneity of data following from various species all served as an added complexity to the already perplexing problem. The ability to process vast amount of brain data need to be performed automatically, yet with an accuracy close to manual human-level performance. These automated methods essentially need to generalize well to be able to accommodate data from different species. Also, novel approaches and techniques are becoming …
Experimental Building Demonstration Model With Viscous Fluid Dampers, Blake Thomas Reeve, Brianna Jean Kufa, Aden Malek Stepanians, Sophie Carmion Ratkovich
Experimental Building Demonstration Model With Viscous Fluid Dampers, Blake Thomas Reeve, Brianna Jean Kufa, Aden Malek Stepanians, Sophie Carmion Ratkovich
Architectural Engineering
The Architectural Engineering major places a heavy emphasis on structural dynamics and the role of wind and seismic loading in building analysis and design. Buildings of high importance that are critical to community function, such as hospitals, often utilize supplemental damping devices like supplemental viscous fluid dampers or base isolators to reduce the overall demands on the structural system. The design and analysis of these dampers are typically not taught at the undergraduate level, and is frequently performed by mechanical engineers, in lieu of structural engineers.
To better understand and research building behavior with supplemental damping devices, our multi-disciplinary team …
Exploring Data Mining Techniques For Tree Species Classification Using Co-Registered Lidar And Hyperspectral Data, Julia K. Marrs
Exploring Data Mining Techniques For Tree Species Classification Using Co-Registered Lidar And Hyperspectral Data, Julia K. Marrs
Theses and Dissertations
NASA Goddard’s LiDAR, Hyperspectral, and Thermal imager provides co-registered remote sensing data on experimental forests. Data mining methods were used to achieve a final tree species classification accuracy of 68% using a combined LiDAR and hyperspectral dataset, and show promise for addressing deforestation and carbon sequestration on a species-specific level.
Identifying Relationships Between Scientific Datasets, Abdussalam Alawini
Identifying Relationships Between Scientific Datasets, Abdussalam Alawini
Dissertations and Theses
Scientific datasets associated with a research project can proliferate over time as a result of activities such as sharing datasets among collaborators, extending existing datasets with new measurements, and extracting subsets of data for analysis. As such datasets begin to accumulate, it becomes increasingly difficult for a scientist to keep track of their derivation history, which complicates data sharing, provenance tracking, and scientific reproducibility. Understanding what relationships exist between datasets can help scientists recall their original derivation history. For instance, if dataset A is contained in dataset B, then the connection between A and B could be that A was …
Performance Analysis And Modeling Of Task-Based Runtimes, Blake Andrew Haugen
Performance Analysis And Modeling Of Task-Based Runtimes, Blake Andrew Haugen
Doctoral Dissertations
The shift toward multicore processors has transformed the software and hardware landscape in the last decade. As a result, software developers must adopt parallelism in order to efficiently make use of multicore CPUs. Task-based scheduling has emerged as one method to reduce the complexity of parallel computing. Although task-based scheduling has been around for many years, the inclusion of task dependencies in OpenMP 4.0 suggests the paradigm will be around for the foreseeable future.
While task-based schedulers simplify the process of parallel software development, they can obfuscate the performance characteristics of the execution of an algorithm. Additionally, they can create …
A Support Vector Machine Base Model For Predicting Heparin-Binding Proteins Using Biological Metrics And Xb Patterns As Features, Joseph W. Sirrianni
A Support Vector Machine Base Model For Predicting Heparin-Binding Proteins Using Biological Metrics And Xb Patterns As Features, Joseph W. Sirrianni
Computer Science and Computer Engineering Undergraduate Honors Theses
Heparin is a highly sulphated and negatively charged polysaccharides belonging to the glycosamino- glycans(GAGs) family. It is widely used in medical treatments as an injectable anticoagulant. Although many heparin-binding proteins have been identified through experimental studies, there are still many proteins needing to be classified as heparin-binding or not. Many studies have been aimed at prediction of heparin binding patterns or motifs in the primary structure of proteins. For example XBBXBX and XBBBXXBX are two well-known patterns or motifs. In spite of intensive studies, still no good model has emerged which reasonably predicts proteins in the protein database as heparin-binding …
Acceleration Of Ddscat Computation By Parallelization On A Supercomputer, Manoj V. Seeram
Acceleration Of Ddscat Computation By Parallelization On A Supercomputer, Manoj V. Seeram
Chemical Engineering Undergraduate Honors Theses
The DDSCAT software is enabled for use of MPI or OpenMP to distribute calculation of different particle orientations amongst multiple processors on a high performance system. Run times for these simulations have been tested to take hours or days however and simulating varying orientations is not always necessary. If a simulation with only one particle orientation is submitted, DDSCAT could still potentially parallelize the simulation by wavelength calculations but it is unknown if this is the case. In this paper, we will be (i) quantifying the reduction in computation time that MPI provides relative to an equivalent MPI disabled simulation …
Nanoscale Frictional Properties Of Nickel With One-Dimensional And Two-Dimensional Materials, Timothy K. Schlenger
Nanoscale Frictional Properties Of Nickel With One-Dimensional And Two-Dimensional Materials, Timothy K. Schlenger
Mechanical Engineering Undergraduate Honors Theses
When looking at the nanoscale, material interface interactions have been observed to exhibit particularly interesting properties. Our research looks into various combinations of carbyne and graphene atop a nickel block to look into the interface friction properties between them. Both the carbyne and graphene are tested using steered molecular dynamics (SMD) in sheering and peeling directions along the surface of the nickel block. These tests are then analyzed by comparing the magnitude of the acting force versus the displacement of the carbon allotrope sample across the nickel block. It is found that as the width of a carbon allotrope sample …
A Survey On Hadamard Matrices, Adam J. Laclair
A Survey On Hadamard Matrices, Adam J. Laclair
Chancellor’s Honors Program Projects
No abstract provided.
Teaching Numerical Methods In The Context Of Galaxy Mergers, Maria Kourjanskaia
Teaching Numerical Methods In The Context Of Galaxy Mergers, Maria Kourjanskaia
Physics
Methods of teaching numerical methods to solve ordinary differential equations in the context of galaxy mergers were explored. The research published in a paper by Toomre and Toomre in 1972 describing the formation of galactic tails and bridges from close tidal interactions was adapted into a project targeting undergraduate physics students. Typically undergraduate physics students only take one Computational Physics class in which various techniques and algorithms are taught. Although it is important to study computational physics techniques, it is just as important to apply this knowledge to a problem that is representative of what computational physics researchers are investigating …
Computational Progress Towards Maximum Distinguishability Of Bell States By Linear Evolution And Local Measurement, Victor Shang
Computational Progress Towards Maximum Distinguishability Of Bell States By Linear Evolution And Local Measurement, Victor Shang
HMC Senior Theses
Many quantum information protocols rely on the ability to distinguish between entangled quantum states known as Bell states. However, theoretical limits exist on the maximal distinguishability of these entangled states using linear evolution and local measurement (LELM) devices. In the case of two particles entangled in multiple qubit variables, the maximum number of distinguishable Bell states is known. However, in the more general case of two particles entangled in multiple qudit variables, only an upper bound is known under additional assumptions. I have written software in Matlab and Mathematica to explore computationally the maximum number of Bell states that can …
An Optical Character Recognition Engine For Graphical Processing Units, Jeremy Reed
An Optical Character Recognition Engine For Graphical Processing Units, Jeremy Reed
Theses and Dissertations--Computer Science
This dissertation investigates how to build an optical character recognition engine (OCR) for a graphical processing unit (GPU). I introduce basic concepts for both building an OCR engine and for programming on the GPU. I then describe the SegRec algorithm in detail and discuss my findings.
Stereographic Visualization Of Bose-Einstein Condensate Clouds To Measure The Gravitational Constant, Ed Wesley Wells
Stereographic Visualization Of Bose-Einstein Condensate Clouds To Measure The Gravitational Constant, Ed Wesley Wells
Electronic Theses and Dissertations
This thesis describes a set of tools that can be used for the rapid design of atom interferometer schemes suitable for measuring Newton's Universal Gravitation constant also known as "Big G". This tool set is especially applicable to Bose--Einstein--condensed systems present in NASA's Cold Atom Laboratory experiment to be deployed to the International Space Station in 2017. These tools include a method of approximating the solutions of the nonlinear Schrödinger or Gross--Pitaevskii equation (GPE) using the Lagrangian Variational Method. They also include a set of software tools for translating the approximate solutions of the GPE into images of the optical …
Using A Data Warehouse As Part Of A General Business Process Data Analysis System, Amit Maor
Using A Data Warehouse As Part Of A General Business Process Data Analysis System, Amit Maor
CMC Senior Theses
Data analytics queries often involve aggregating over massive amounts of data, in order to detect trends in the data, make predictions about future data, and make business decisions as a result. As such, it is important that a database management system (DBMS) handling data analytics queries perform well when those queries involve massive amounts of data. A data warehouse is a DBMS which is designed specifically to handle data analytics queries.
This thesis describes the data warehouse Amazon Redshift, and how it was used to design a data analysis system for Laserfiche. Laserfiche is a software company that provides each …
Using Genetic Algorithms To Evolve Artificial Neural Networks, William T. Kearney
Using Genetic Algorithms To Evolve Artificial Neural Networks, William T. Kearney
Honors Theses
This paper demonstrates that neuroevolution is an effective method to determine an optimal neural network topology. I provide an overview of the NeuroEvolution of Augmenting Topologies (NEAT) algorithm, and describe how unique characteristics of this algorithm solve various problem inherent to neuroevolution (namely the competing conventions problem and the challenges associated with protecting topological innovation). Parallelization is shown to greatly speed up efficiency, further reinforcing neuroevolution as a potential alternative to traditional backpropagation. I also demonstrate that appropriate parameter selection is critical in order to efficiently converge to an optimal topology. Lastly, I produce an example solution to a medical …
Hydraulic Conductivity As A Proxy For Drainage System Connectivity In A Subglacial Hydrology Model, Jacob Z. Downs
Hydraulic Conductivity As A Proxy For Drainage System Connectivity In A Subglacial Hydrology Model, Jacob Z. Downs
Graduate Student Theses, Dissertations, & Professional Papers
The link between subglacial hydrology and basal sliding has prompted work on basal hydrology models with water pressure and storage as prognostic variables. We find that a commonly used model of distributed drainage through linked cavities underpredicts winter water pressure when compared to borehole observations from Issunguata Sermia in Western Central Greenland. Possible causes for this discrepancy including unrealistic model inputs or unconstrained parameters are investigated through a series of modeling experiments on both synthetic and realistic ice sheet geometries. We find that conductivity acts as a proxy for the connectivity of the linked cavity system and should therefore change …
Representation And Analysis Of Multi-Modal, Nonuniform Time Series Data: An Application To Survival Prognosis Of Oncology Patients In An Outpatient Setting, Jennifer Winikus
Representation And Analysis Of Multi-Modal, Nonuniform Time Series Data: An Application To Survival Prognosis Of Oncology Patients In An Outpatient Setting, Jennifer Winikus
Dissertations, Master's Theses and Master's Reports
The representation of nonuniform, multi-modal, time-limited time series data is complex and explored through the use of discrete representation, dimensionality reduction with segmentation based techniques, and with behavioral representation approaches. These explorations are done with a focus on an outpatient oncology setting with the classification and regression analysis being used for length of survival prognosis. Each decision of representation and analysis is not independent, with implications of each decision in method for how the data is represented and then which analysis technique is used. One unique aspect of the work is the use of outpatient clinical data for patients, which …
Zipping Towards Stem: Simulation Wind Tunnel, Devon A. Goldberg, Emma Pierson, Brandon Hein, Jeremy Hein, Greg Flohr
Zipping Towards Stem: Simulation Wind Tunnel, Devon A. Goldberg, Emma Pierson, Brandon Hein, Jeremy Hein, Greg Flohr
Williams Honors College, Honors Research Projects
The simulation wind tunnel program created for this project is implemented within a larger, National Science Foundation funded project titled Zipping Towards STEM: Integrating Engineering Design into the Middle School Physical Science Curriculum. Over the course of the next two years, all Akron Public School 8th grade students will go through the Zipping Towards STEM project curriculum. The students will be exposed to the typical steps of engineering design (computer modeling, simulation, building, and testing) and learn about the fundamentals of aerodynamics through the design of their own Soap Box Derby mini-cars. The virtual wind tunnel will be used …
Identifying Parameters For Robust Network Growth Using Attachment Kernels: A Case Study On Directed And Undirected Networks, Ahmed F. Abdelzaher
Identifying Parameters For Robust Network Growth Using Attachment Kernels: A Case Study On Directed And Undirected Networks, Ahmed F. Abdelzaher
Theses and Dissertations
Network growing mechanisms are used to construct random networks that have structural behaviors similar to existing networks such as genetic networks, in efforts of understanding the evolution of complex topologies. Popular mechanisms, such as preferential attachment, are capable of preserving network features such as the degree distribution. However, little is known about such randomly grown structures regarding robustness to disturbances (e.g., edge deletions). Moreover, preferential attachment does not target optimizing the network's functionality, such as information flow. Here, we consider a network to be optimal if it's natural functionality is relatively high in addition to possessing some degree of robustness …
Modeling The Cryosphere With Fenics, Evan M. Cummings
Modeling The Cryosphere With Fenics, Evan M. Cummings
Graduate Student Theses, Dissertations, & Professional Papers
This manuscript is a collection of problems and solutions related to modeling the cryosphere using the finite element software FEniCS. Included is an introduction to the finite element method; solutions to a variety of problems in one, two, and three dimensions; an overview of popular stabilization techniques for numerically-unstable problems; and an introduction to the governing equations of ice-sheet dynamics with associated FEniCS implementations. The software developed for this project, Cryospheric Problem Solver (CSLVR), is fully open-source and has been designed with the goal of simplifying many common tasks associated with modeling the cryosphere. CSLVR possesses the ability to download …