Frg: Collaborative Research: Homotopy Renormalization Of Topological Field Theories,
2017
Utah State University
Frg: Collaborative Research: Homotopy Renormalization Of Topological Field Theories, Nathan Geer
Funded Research Records
No abstract provided.
Improving The Accuracy For The Long-Term Hydrologic Impact Assessment (L-Thia) Model,
2017
Purdue University
Improving The Accuracy For The Long-Term Hydrologic Impact Assessment (L-Thia) Model, Anqi Zhang, Lawrence Theller, Bernard A. Engel
The Summer Undergraduate Research Fellowship (SURF) Symposium
Urbanization increases runoff by changing land use types from less impervious to impervious covers. Improving the accuracy of a runoff assessment model, the Long-Term Hydrologic Impact Assessment (L-THIA) Model, can help us to better evaluate the potential uses of Low Impact Development (LID) practices aimed at reducing runoff, as well as to identify appropriate runoff and water quality mitigation methods. Several versions of the model have been built over time, and inconsistencies have been introduced between the models. To improve the accuracy and consistency of the model, the equations and parameters (primarily curve numbers in the case of this model) …
Predicting Locations Of Pollution Sources Using Convolutional Neural Networks,
2017
Purdue University
Predicting Locations Of Pollution Sources Using Convolutional Neural Networks, Yiheng Chi, Nickolas D. Winovich, Guang Lin
The Summer Undergraduate Research Fellowship (SURF) Symposium
Pollution is a severe problem today, and the main challenge in water and air pollution controls and eliminations is detecting and locating pollution sources. This research project aims to predict the locations of pollution sources given diffusion information of pollution in the form of array or image data. These predictions are done using machine learning. The relations between time, location, and pollution concentration are first formulated as pollution diffusion equations, which are partial differential equations (PDEs), and then deep convolutional neural networks are built and trained to solve these PDEs. The convolutional neural networks consist of convolutional layers, reLU layers …
A Finite Difference Method For Off-Fault Plasticity Throughout The Earthquake Cycle,
2017
Portland State University
A Finite Difference Method For Off-Fault Plasticity Throughout The Earthquake Cycle, Brittany A. Erickson, Eric M. Dunham, Arash Khosravifar
Mathematics and Statistics Faculty Publications and Presentations
We have developed an efficient computational framework for simulating multiple earthquake cycles with off-fault plasticity. The method is developed for the classical antiplane problem of a vertical strike-slip fault governed by rate-and-state friction, with inertial effects captured through the radiationdamping approximation. Both rate-independent plasticity and viscoplasticity are considered, where stresses are constrained by a Drucker-Prager yield condition. The off-fault volume is discretized using finite differences and tectonic loading is imposed by displacing the remote side boundaries at a constant rate. Time-stepping combines an adaptive Runge-Kutta method with an incremental solution process which makes use of an elastoplastic tangent stiffness tensor …
Problem Solving Practice With Problems From Fibonacci's "Liber Abbaci",
2017
Pittsburg State University
Problem Solving Practice With Problems From Fibonacci's "Liber Abbaci", Cynthia J. Huffman Ph.D.
Open Educational Resources - Math
In this activity, problem solving skills are practiced using two well-known problems from Fibonacci's world-changing book "Liber Abbaci". Students are also asked to reflect on the differences and similarities between their solutions and those of Fibonacci. The two problems are the famous rabbit problem which led to what is now know as the Fibonacci sequence and the 30 birds for 30 denarii problem, which is not as well-known to the general public.
Development And Implementation Of An Optimization Model To Improve Airport Security.,
2017
Sunnyside High School
Development And Implementation Of An Optimization Model To Improve Airport Security., Kassandra Guajardo, Angela Waterworth, Robert Brigantic Ph.D.
STAR Program Research Presentations
What if airport security teams across the world could quantify and then minimize the amount of risk throughout areas of an airport? The Operations Research Team at the Pacific Northwest National Laboratory is developing and implementing an optimization model called ARAM (Airport Risk Analysis Model) for the Seattle-Tacoma International Airport. ARAM will provide a recommended optimal deployment of security assets to reduce risk in areas of an airport. The model is based on a risk equation that considers consequences, vulnerabilities, and threat magnitudes at airports. ARAM will also provide the estimated risk buy down percentage, which is how much risk …
Efficient Parameter-Estimating Algorithms For Symmetry-Motivated Models: Econometrics And Beyond,
2017
The University of Texas at El Paso
Efficient Parameter-Estimating Algorithms For Symmetry-Motivated Models: Econometrics And Beyond, Vladik Kreinovich, Anh H. Ly, Olga Kosheleva, Songsak Sriboonchitta
Departmental Technical Reports (CS)
It is known that symmetry ideas can explain the empirical success of many non-linear models. This explanation makes these models theoretically justified and thus, more reliable. However, the models remain non-linear and thus, identification or the model's parameters based on the observations remains a computationally expensive nonlinear optimization problem. In this paper, we show that symmetry ideas can not only help to select and justify a nonlinear model, they can also help us design computationally efficient almost-linear algorithms for identifying the model's parameters.
Maximum Entropy Beyond Selecting Probability Distributions,
2017
Banking University of Ho Chi Minh City
Maximum Entropy Beyond Selecting Probability Distributions, Thach N. Nguyen, Olga Kosheleva, Vladik Kreinovich
Departmental Technical Reports (CS)
Traditionally, the Maximum Entropy technique is used to select a probability distribution in situations when several different probability distributions are consistent with our knowledge. In this paper, we show that this technique can be extended beyond selecting probability distributions, to explain facts, numerical values, and even types of functional dependence.
Almost All Diophantine Sets Are Undecidable,
2017
The University of Texas at El Paso
Almost All Diophantine Sets Are Undecidable, Vladik Kreinovich
Departmental Technical Reports (CS)
The known 1970 solution to the 10th Hilbert problem says that no algorithm is possible that would decide whether a given Diophantine equation has a solution. In set terms, this means that not all Diophantine sets are decidable. In a posting to the Foundations of Mathematica mailing list, Timothy Y. Chow asked for possible formal justification for his impression that most Diophantine equations are not decidable. One such possible justification is presented in this paper.
A Study On Traveling Wave Solutions In The Shallow-Water-Type System,
2017
University of Texas at Arlington
A Study On Traveling Wave Solutions In The Shallow-Water-Type System, Ting Luo
Mathematics Dissertations - Archive
The study of water waves reveals the physical principles of many phenomena of scientific and engineering interest. In this dissertation I consider three models: two-component Camassa-Holm system(2CH), generalized two-component Camassa-Holm equation(g2CH) and rotation-Camassa-Holm equation(R-CH). In the first part, we consider the stability of the Camassa-Holm peakons and antipeakons in the dynamics of the two-component Camassa-Holm system. The second part shows that the train of $N$-smooth traveling waves of this system is dynamically stable to perturbations in energy space with a range of parameters. In the third part, we formally derive the simplified phenomenological models with the Coriolis effect due to …
Stability Study On Shear Flow And Vortices In Late Boundary Layer Transition,
2017
University of Texas at Arlington
Stability Study On Shear Flow And Vortices In Late Boundary Layer Transition, Jie Tang
Mathematics Dissertations - Archive
Turbulence is still an unsolved scientific problem, it has been regarded as “the most important unsolved problem of classical physics”. Dr. Liu proposed a new mechanism about turbulence generation and sustenance after decades of research on turbulence and transition. His new idea challenged the classical theorem in many aspects. One of them is the flow stability of transition. Dr. Liu believes that inside the flow field, shear (dominant in laminar) is very unstable while rotation (dominant in turbulence) is relative stable. This inherent property of flow creates the trend that non-vertical vorticity must transfer to vertical vorticity, and causes the …
Image Reconstruction From Incomplete Radon Data And Generalized Principal Component Analysis,
2017
University of Texas at Arlington
Image Reconstruction From Incomplete Radon Data And Generalized Principal Component Analysis, Sl Ghi Choi
Mathematics Dissertations - Archive
Image reconstruction in various types of tomography requires inversion of the Radon transform and its generalizations. While there are many stable and robust algorithms for such inversions from reasonably well sampled data, most of these algorithms fail when applied to limited view data. In the dissertation we develop a new method of stable reconstruction from limited view data for functions, whose support is a union of finitely many circles. Such images, among other things, are good approximations of tomograms of certain types of tumors in lungs. Our method is based on a modified version of GPCA (General Principle Component Analysis) …
Evoked And Spontaneous Neurotransmitter Releases For Independent Synaptic Currents: Mathematical Modeling And Analysis,
2017
University of Texas at Arlington
Evoked And Spontaneous Neurotransmitter Releases For Independent Synaptic Currents: Mathematical Modeling And Analysis, Sat Byul Seo
Mathematics Dissertations - Archive
Synapses play a major role in neuron communications in the brain. The synapses act through a chemical process called synaptic fusion between pre-synaptic and post-synaptic terminals. Presynaptic terminals release neurotransmitters either in response to action potential or spontaneously independent of presynaptic activity. In the case of glutamate, released neurotransmitters acivate N-methyl-D-asparate (NMDA) receptors within a single postsynaptic site and give rise to miniature postsynaptic currents. In this dissertation, we develop a mathematical model in 3-D to emulate spontaneous and evoked neurotransmissions resulted from glutamate release within a single synapse. We propose numerical methods for solving piecewise continuous heat diffusion equation, …
Simple Weight Modules Of The Lie Algebra Of Vector Fields Of C2,
2017
University of Texas at Arlington
Simple Weight Modules Of The Lie Algebra Of Vector Fields Of C2, Andrew Cavaness
Mathematics Dissertations - Archive
Classification of the weight modules of the Lie algebra Wn of vector fields on C n has been a long-standing problem in the area of representation theory. In this thesis, a classification of all simple weight modules of W2 with a uniformly bounded set of weight multiplicities is provided, and much of the theory that will be needed to classify all simple weight modules of Wn with a uniformly bounded set of weight multiplicities will also be developed. To achieve this classification, a new family of generalized tensor Wn-modules is introduced, and a twisted localization functor is applied.
Cayley Graphs Of Groups And Their Applications,
2017
Missouri State University
Cayley Graphs Of Groups And Their Applications, Anna Tripi
Graduate Theses/Dissertations
Cayley graphs are graphs associated to a group and a set of generators for that group (there is also an associated directed graph). The purpose of this study was to examine multiple examples of Cayley graphs through group theory, graph theory, and applications. We gave background material on groups and graphs and gave numerous examples of Cayley graphs and digraphs. This helped investigate the conjecture that the Cayley graph of any group (except Z_2) is hamiltonian. We found the conjecture to still be open. We found Cayley graphs and hamiltonian cycles could be applied to campanology (in particular, to the …
High Order Dns For Vortex Structure In Late Flow Transition,
2017
University of Texas at Arlington
High Order Dns For Vortex Structure In Late Flow Transition, Yong Yang
Mathematics Dissertations - Archive
Turbulence is still a world puzzle after over one hundred years research, and the current and classical theories brim with self-contradictions. C. Liu proposed a new theory on turbulence generation and structure after 28 years research, which are consistent without self-contradictions and well explain turbulence generation and structure. Based on this new theory, this dissertation (1) gives some mathematical explanations for new vortex identify method – Ω method; (2) analyzes the instability of shear layer by applying Chebyshev spectrum method to solve Orr-Sommerfeld eigenvalue equation; (3) investigates the vortex structure development in late flow transition; (4) utilizes the proper orthogonal …
Characterizing College Algebra Students' Mathematical Problem Solving,
2017
University of Texas at Arlington
Characterizing College Algebra Students' Mathematical Problem Solving, R. Cavender Campbell
Mathematics Dissertations - Archive
This study examines the mathematical problem solving (MPS) practices of students enrolled in College Algebra at a large urban university in the southwestern United States. The primary research question explores how to characterize the MPS techniques, strategies or orientations used by College Algebra students. In addition, this study documents MPS approaches that appear to be most prevalent and examines how these approaches relate to student performance. A grounded theory approach is used to formulate a theory for characterizing the MPS of students in College Algebra. Data analysis shows that multiple student-held orientations identified in this theory correlate with improved performance …
Mathematical Methods For Vortex Identification With Application On Shock Wave Vortex Ring Interaction,
2017
University of Texas at Arlington
Mathematical Methods For Vortex Identification With Application On Shock Wave Vortex Ring Interaction, Yinlin Dong
Mathematics Dissertations - Archive
Vortices are seen everywhere in nature, from smoke rings to tornadoes. Vortical structures play an essential role in the turbulence dynamics such as turbulence generation, kinetic energy production and dissipation, enhancement of transport of mass, heat and momentum and so on. In this dissertation, we present several vortex identification methods and compare them by the visualization of the examples studied by direct numerical simulation for flows with different speeds. The comparisons show the Omega method is much close to give vortex a mathematical definition and better visualization for vortical structures. We apply our method on the Micro Vortex Generator (MVG) …
A Mathematical Model Of Hepatitis C Virus Infection Incorporating Immune Responses And Cell Proliferation,
2017
University of Texas at Arlington
A Mathematical Model Of Hepatitis C Virus Infection Incorporating Immune Responses And Cell Proliferation, Huda Amer Hadi
Mathematics Theses - Archive
This thesis introduces a mathematical model of differential equations for the chronic hepatitis C virus (HCV) infection, which is a contagious disease that infects the liver cells. Firstly, we present the early mathematical models for the basic dynamics of virus infection that developed and analyzed to understand the dynamics of human immunodeficiency virus (HIV), hepatitis B virus (HBV), and some other viruses. Next, we present the extended model of the basic HCV virus dynamics that incorporate the effectiveness of a treatment. After that, the mathematical model that includes proliferation terms for both infected and uninfected hepatocytes is discussed. Lastly, the …
Speech Processing Approach For Diagnosing Dementia In An Early Stage,
2017
Harrisburg University of Science and Technology
Speech Processing Approach For Diagnosing Dementia In An Early Stage, Roozbeh Sadeghian, J. David Schaffer, Stephen A. Zahorian
Faculty Works
The clinical diagnosis of Alzheimer’s disease and other dementias is very challenging, especially in the early stages. Our hypothesis is that any disease that affects particular brain regions involved in speech production and processing will also leave detectable finger prints in the speech. Computerized analysis of speech signals and computational linguistics have progressed to the point where an automatic speech analysis system is a promising approach for a low-cost non-invasive diagnostic tool for early detection of Alzheimer’s disease.
We present empirical evidence that strong discrimination between subjects with a diagnosis of probable Alzheimer’s versus matched normal controls can be achieved …
