1,720,973 research outputs found
Advanced forecasting model on land market value based on USA real estate market
Full text linkThesis (Ph.D.)-- Wichita State University, College of Liberal Arts and Sciences, Dept. of Mathematics, Statistics and PhysicsThis research presents a time series estimation and prediction methods with the use of classic
and advanced forecasting tools. Our discussion about di erent time series models is
supported by giving the experimental forecast results, performed on several macroeconomic
variables. Also, the main section deal with the experience of using such data in econometric
analysis. Besides, the implementation of SAS and R software improve the parameter estimation
and forecasting accuracy.
The objective in providing crucial statistical techniques is to enable government and investors
to make informed decisions regarding real estate. Most importantly, we obtain how
to add value to business and apply skills set real estate in a real world environment. Eventually,
the summary of various existing forecasting models can provide information to develop
an appropriate forecasting model which describes the inherent feature of the series
Modeling the melt pool during powder bed fusion additive manufacturing
No full textThesis (Ph.D.)-- Wichita State University, College of Liberal Arts and Sciences, Dept. of Mathematics, Statistics, and PhysicsIn powder bed fusion additive manufacturing properties of the melt pool are
of deep interest to ensure the structure of the nal product is as desired.
Speci cally of concern in this work is estimating the melt pool with regards to
width and depth considering also maximum temperature. Because analytic
estimation formulas require simpli ed assumptions, OpenFOAM is used to
numerically simulate the melt pool as well. The approximation formulas are
compared to the numerical simulations and experiment data to validate
Superconvergence of discontinuous Galerkin method for linear hyperbolic equations
No full textThesis (Ph.D.)-- Wichita State University, College of Liberal Arts and Sciences, Dept. of Mathematics, Statistics and PhysicsThis thesis is concerned with the investigation of the superconvergence of the Discontinuous
Method for linear conservation laws. We use Fourier analysis to study the superconvergence
of the semi-discrete discontinuous Galerkin method for scalar linear advection
equations in one spatial dimension.
We provide the error bounds and asymptotic errors for initial di erent initial discretizations.
For the pedagogical purpose, the errors are computed in two di erent ways. In
the rst approach, we compute the di erence between the numerical solution and a special
interpolation of the exact solution, and show that it consists of an asymptotic error of order
2k + 1 (where k is the order of polynomial approximation) and a transient error of lower
order.
In the second approach, we compute the error directly by decomposing it into physical
and nonphysical modes, and obtain agreement with the rst approach. We then extend the
analysis to vector conservation laws, solved using the Lax-Friedrichs
ux. We prove that the
superconvergence holds with the same order. The error bounds and asymptotic errors are
demonstrated by various numerical experiments for scalar and vector advection equations
Pellet ablation in Tokamak reactors
Full text linkThesis (Ph.D.)-- Wichita State University, Fairmount College of Liberal Arts and Sciences, Dept. of Mathematics, Statistics and PhysicsWe implemented a rotational cloud model for the simulation of pellet ablation in a Tokamak reactor. We have shown that the ablation rate in the rotational cloud model converges quickly to a steady state value independent of the plasma warmup time. In contrast, the ablation rate in the non-rotating cloud model converges slowly to a value that depends upon the warmup time. We have also extended the neutral gas shielding (NGS) model for Maxwellian plasma electrons. A tumbling pellet model has been implemented. We have also compared the simulation results using a MUSCL scheme and a Discontinuous Galerkin (DG) scheme with a specialized nonuniform grid suited to the pellet problem in one space dimension, and developed a localized Discontinuous Galerkin method to solve the pellet ablation problem. One and two dimensional results are presented
A pair of stationary stochastic processes with application to Wichita temperature data
No full textThesis (M.S.)--Wichita State University, College of Liberal Arts and Sciences, Dept. of Mathematics and StatisticsThe thesis investigates a pair of stationary stochastic process models whose domains
are the set of integers and the set of real numbers respectively. The stationary processes
with our specific correlation functions include the discrete and continuous first and second
order autoregressive processes as their special cases. The maximum likelihood method is
then applied to obtain the nonlinear equation system for the maximum likelihood estimators
of the model parameters and the solutions are found by using the deepest gradient algorithm.
The advantage of the algorithm lies in the calculation could be divided into several steps at
a cost of O(n) calculations per step. Finally, predictions are given for both simulated data
and Wichita temperature data.This research is supported in part by the Kansas NSF EPSCoR under Grant EPS
0903806 and in part by a Kansas Technology Enterprize Corporation grant on Understanding
Climate Change in the Great Plains: Source, Impact, and Mitigation
Pellet ablation in tokamak reactors
No full textSecond Place winner of oral presentations at the 8th Annual Symposium on Graduate Research and Scholarly Projects (GRASP) held at the Marcus Welcome Center, Wichita State University, April 18, 2012.Research completed at the Department of Mathematics, Statistics and Physics,Fairmount College of Liberal Arts and SciencesInjecting frozen hydrogen pellets has been proposed as a method of efficiently refueling Tokamak fusion reactors. The intense heat of the reactor causes the pellet to lose mass in a process called ablation. This process creates a cloud-like area around the pellet which partially shields it from further ablation. We are interested in modelling the behavior of the pellet and the resulting flow numerically. We will present the effect of physical parameters such as magnetic field strength, pellet rotation, and pellet surface conditions on the rate of pellet ablation. Improvements made to older models will be discussed. Data and conclusion will be presented for the one-dimensional and two-dimensional case. Areas of further research will be explained.Graduate School,
Office of Research Administration,
University Librarie
Optimal design of complex systems with low sensitivity to time delay
No full textThesis (Ph.D.)-- Wichita State University, College of Liberal Arts and Sciences, Dept. of Mathematics, Statistics, and PhysicsIn this dissertation, two optimal control strategies are investigated for a large-scale decentralized
system in order to optimize and study the system. The main objective of the optimization
and analysis is to reduce the effect of time delay on the system. This can be accomplished by
adding the sensitivity function to the optimal control design and inserting it into the performance
index function. In this way, the effect of the time delay can be reduced. The first strategy is
to create a nearly optimal composite control by using the singular perturbation method as a
reduction method. The singular perturbation utilizes the separation of slow and fast dynamic
systems and decomposing full-order systems into reduced-order slow and fast subsystems to reduce
the complexity of the large-scale system and simplify the problem. Then, after solving
each subsystem individually, the optimal solution for the nearly optimal composite control can
be obtained by combining the solutions of the subsystems. The Stackelberg game strategy is
applied to the reduced order model and then implemented in order to optimize the performance
index function. This is the second strategy. The design can be completed successfully based on
the reduced-order model, which allow for the attainment of optimal results. It is shown through
the use of numerical examples how well the design performs and how successfully it alleviates the
impact of the sensitivity
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
An open-source implementation of the quick CSF method for rapid evaluation of contrast sensitivity
Full text linkPresented to the 15th Annual Symposium on Graduate Research and Scholarly Projects (GRASP) held at the Rhatigan Student Center, Wichita State University, April 26, 2019.Research completed in the Department of Psychology and Department of Mathematics, Statistics and Physics, Fairmount College of Liberal Arts and SciencesContrast sensitivity is an important feature of functional vision, but traditional psychometric assessment methods require an excessive number of trials to estimate a complete contrast sensitivity function across the full range of spatial frequencies relevant to normal vision in humans. These traditional methods often sacrifice precision, range, and/or accuracy as a trade-off for testing duration. To overcome this challenge, Quick CSF (qCSF), a Bayesian adaptive procedure to estimate an observer's complete contrast sensitivity function (Lesmes, Lu, Baek, & Albright, 2010), assumes a four-parameter model of the human contrast sensitivity function (Watson & Ahumada, 2005). The parametric nature of this model allows for a more rapid evaluation through Bayesian inference. Stimuli parameters of contrast and spatial frequency are adaptively selected based on previous responses. As few as 25-50 trials can be collected to give a usable broad sensitivity metric across the frequency range. With 100-300 trials, contrast sensitivity function estimates reach similar precision levels of traditional laboratory CSF measurements, which would require over 1,000 trials (Lesmes, et al., 2010). We present an open-source implementation of the Quick CSF method. Our implementation of Quick CSF is written in the Python programming language as a standard Python package. The software operates as a typical full-screen desktop application, presenting a 2AFC detection task. Many settings are configurable, including stimulus size, orientation, eccentricity, color, display time, etc. Alternatively, the software can be used as a library to generate stimuli contrast/spatial frequency values and calculate the parameters of the contrast sensitivity function estimation. This allows the qCSF method to be easily integrated with new or existing software projects. The open source nature of our qCSF implementation makes it accessible to any researchers or clinicians interested in using it for their work. Acknowledgment: Research reported in this abstract was partially supported by the Cognitive and Neurobiological Approaches to Plasticity (CNAP) Center of Biomedical Research Excellence (COBRE) of the National Institutes of Health under grant number P20GM113109.Graduate School, Academic Affairs, University Librarie
- …
