Numerical Analysis and Scientific Computing Commons^™

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 …

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 …

Stereographic Visualization Of Bose-Einstein Condensate Clouds To Measure The Gravitational Constant, Ed Wesley Wells

College of Graduate Studies: Theses & 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 …

Geometric Consideration Of Nanostructures For Energy Storage Systems, Jonghyun Park, Jie Li, Wei Lu, Ann Marie Sastry

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Battery performance and its fade are determined by various aspects such as the transport of ions and electrons through heterogeneous internal structures; kinetic reactions at the interfaces; and the corresponding interplay between mechanical, chemical, and thermal responses. The fundamental factor determining this complex multiscale and multiphysical nature of a battery is the geometry of active materials. In this work, we systematically consider the tradeoffs among a selection of limiting geometries of media designed to store ions or other species via a diffusion process. Specifically, we begin the investigation by considering diffusion in spheres, rods, and plates at the particle level, …

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.

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 …

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 …

High-Fidelity Simulations Of Long-Term Beam-Beam Dynamics On Gpus, B. Terzić, K. Arumugam, M. Aturban, C. Cotnoir, A. Godunov, D. Ranjan, M. Stefani, M. Zubair, F. Lin, V. Morozov, Y. Roblin, H. Zhang

Physics Faculty Publications

Future machines such as the Electron Ion Collider (MEIC), linac-ring machines (eRHIC) or LHeC are particularly sensitive to beam-beam effects. This is the limiting factor for long-term stability and high luminosity reach. The complexity of the non-linear dynamics makes it challenging to perform such simulations typically requiring millions of turns. Until recently, most of the methods have involved using linear approximations and/or tracking for a limited number of turns. We have developed a framework which exploits a massively parallel Graphical Processing Units (GPU) architecture to allow for tracking millions of turns in a sympletic way up to an arbitrary order. …

Coupled Crystal Orientation-Size Effects On The Strength Of Nano Crystals, Rui Yuan, Irene J. Beyerlein, Caizhi Zhou

Materials Science and Engineering Faculty Research & Creative Works

We study the combined effects of grain size and texture on the strength of nanocrystalline copper (Cu) and nickel (Ni) using a crystal-plasticity based mechanics model. Within the model, slip occurs in discrete slip events exclusively by individual dislocations emitted statistically from the grain boundaries. We show that a Hall-Petch relationship emerges in both initially texture and non-textured materials and our values are in agreement with experimental measurements from numerous studies. We find that the Hall-Petch slope increases with texture strength, indicating that preferred orientations intensify the enhancements in strength that accompany grain size reductions. These findings reveal that texture …

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

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 …

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 …

Demo: Smartwatch Based Food Diary And Eating Analytics, Sougata Sen, Vigneshwaran Subbaraju, Archan Misra, Youngki Lee, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

Monitoring an individual’s daily dietary intake can provide various insights regarding the health of the individual. Applications such as My Fitness Pal exists, which allows individuals to monitor all items that the individual consumed. However, manual monitoring can be labour intensive. To overcome this limitation, wrist worn sensor based eating habit monitoring has been studied by various researchers. These systems can detect eating gesture, but they cannot determine what is being eaten. We have built a system which can (i) detect eating gesture using the smartwatch's inertial sensors (ii) use the smartwatch's camera to capture images of food consumed at …

Emerging Adaptive Architectures For Biomolecular Computation, Matthew Fleetwood

Maseeh Summer Undergraduate Research Experience

The goal of this work is to explore applications of reservoir computing in biomolecular computation. Reservoir computing is a unique model for representing a mapping from one instance in time to a specific output. A neural network of randomly connected neurons is linked with a single output neuron or multiple output neurons. The output neurons are capable of mapping inputs to desired outputs using adaptable algorithms. This framework is investigated by using the Python programming language and object oriented design and programming. Neurons are created in programs by bundling information like input data and attributes of the network, which utilize …

Synthesis Of Satellite Microwave Observations For Monitoring Global Land-Atmosphere Co2 Exchange, Lucas Alan Jones

Graduate Student Theses, Dissertations, & Professional Papers

This dissertation describes the estimation, error quantification, and incorporation of land surface information from microwave satellite remote sensing for modeling global ecosystem land-atmosphere net CO₂ exchange. Retrieval algorithms were developed for estimating soil moisture, surface water, surface temperature, and vegetation phenology from microwave imagery timeseries. Soil moisture retrievals were merged with model-based soil moisture estimates and incorporated into a light-use efficiency model for vegetation productivity coupled to a soil decomposition model. Results, including state and uncertainty estimates, were evaluated with a global eddy covariance flux tower network and other independent global model- and remote-sensing based products.

A Study On Singapore Haze, Bingtian Dai, Kasthuri Jayarajah, Ee-Peng Lim, Archan Misra, Shriguru Nayak

Research Collection School Of Computing and Information Systems

In 2015, Singaporean have experienced one of the worse air pollution crises in history. With datasets from a well-known photo sharing social network, we analyze how this haze affects Singaporean's daily life. We will share our preliminary results in this paper.

The R Journal (December 2015) 7(2): Complete Issue, The R Foundation

The R Journal

Editorial, Bettina Grün

Contributed Research Articles

Fitting Conditional and Simultaneous Autoregressive Spatial Models in hglm, Moudud Alam, Lars Rönnegård, and Xia Shen

VSURF: An R Package for Variable Selection Using Random Forests, Robin Genuer, Jean-Michel Poggi, and Christine Tuleau-Malot

zoib: An R Package for Bayesian Inference for Beta Regression and Zero/One Inflated Beta Regression, Fang Liu, and Yunchuan Kong

apc: An R Package for Age-Period-Cohort Analysis, Bent Nielsen

QuantifQuantile: An R Package for Performing Quantile Regression Through Optimal Quantization, Isabelle Charlier, Davy Paindaveine, and Jérôme Saracco

Numerical Evaluation of the Gauss Hypergeometric Function with the hypergeo Package, Robin K. S. …

An R Package For The Panel Approach Method For Program Evaluation: Pampe, Ainhoa Vega-Bayo

The R Journal

The pampe package for R implements the panel data approach method for program evaluation designed to estimate the causal effects of political interventions or treatments. This procedure exploits the dependence among cross-sectional units to construct a counterfactual of the treated unit(s), and it is an appropriate method for research events that occur at an aggregate level like countries or regions and that affect only one or a small number of units. The implementation of the pampe package is illustrated using data from Hong Kong and 24 other units, by examining the economic impact of the political and economic integration of …

Energy Forecasting For Event Venues: Big Data And Prediction Accuracy, Katarina Grolinger, Alexandra L'Heureux, Miriam Am Capretz, Luke Seewald

Electrical and Computer Engineering Publications

Advances in sensor technologies and the proliferation of smart meters have resulted in an explosion of energy-related data sets. These Big Data have created opportunities for development of new energy services and a promise of better energy management and conservation. Sensor-based energy forecasting has been researched in the context of office buildings, schools, and residential buildings. This paper investigates sensor-based forecasting in the context of event-organizing venues, which present an especially difficult scenario due to large variations in consumption caused by the hosted events. Moreover, the significance of the data set size, specifically the impact of temporal granularity, on energy …

Changes On Cran, Kurt Hornik, Achim Zeileis

The R Journal

New packages in CRAN task views

New contributed packages

Other changes