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- Genre: Academic theses
- Creators: Vasileska, Dragica
Description
As urban populations become increasingly dense, massive amounts of new 'big' data that characterize human activity are being made available and may be characterized as having a large volume of observations, being produced in real-time or near real-time, and including a diverse variety of information. In particular, spatial interaction (SI) data - a collection of human interactions across a set of origins and destination locations - present unique challenges for distilling big data into insight. Therefore, this dissertation identifies some of the potential and pitfalls associated with new sources of big SI data. It also evaluates methods for modeling SI to investigate the relationships that drive SI processes in order to focus on human behavior rather than data description.
A critical review of the existing SI modeling paradigms is first presented, which also highlights features of big data that are particular to SI data. Next, a simulation experiment is carried out to evaluate three different statistical modeling frameworks for SI data that are supported by different underlying conceptual frameworks. Then, two approaches are taken to identify the potential and pitfalls associated with two newer sources of data from New York City - bike-share cycling trips and taxi trips. The first approach builds a model of commuting behavior using a traditional census data set and then compares the results for the same model when it is applied to these newer data sources. The second approach examines how the increased temporal resolution of big SI data may be incorporated into SI models.
Several important results are obtained through this research. First, it is demonstrated that different SI models account for different types of spatial effects and that the Competing Destination framework seems to be the most robust for capturing spatial structure effects. Second, newer sources of big SI data are shown to be very useful for complimenting traditional sources of data, though they are not sufficient substitutions. Finally, it is demonstrated that the increased temporal resolution of new data sources may usher in a new era of SI modeling that allows us to better understand the dynamics of human behavior.
A critical review of the existing SI modeling paradigms is first presented, which also highlights features of big data that are particular to SI data. Next, a simulation experiment is carried out to evaluate three different statistical modeling frameworks for SI data that are supported by different underlying conceptual frameworks. Then, two approaches are taken to identify the potential and pitfalls associated with two newer sources of data from New York City - bike-share cycling trips and taxi trips. The first approach builds a model of commuting behavior using a traditional census data set and then compares the results for the same model when it is applied to these newer data sources. The second approach examines how the increased temporal resolution of big SI data may be incorporated into SI models.
Several important results are obtained through this research. First, it is demonstrated that different SI models account for different types of spatial effects and that the Competing Destination framework seems to be the most robust for capturing spatial structure effects. Second, newer sources of big SI data are shown to be very useful for complimenting traditional sources of data, though they are not sufficient substitutions. Finally, it is demonstrated that the increased temporal resolution of new data sources may usher in a new era of SI modeling that allows us to better understand the dynamics of human behavior.
ContributorsOshan, Taylor Matthew (Author) / Fotheringham, A. S. (Thesis advisor) / Farmer, Carson J.Q. (Committee member) / Rey, Sergio S.J. (Committee member) / Nelson, Trisalyn (Committee member) / Arizona State University (Publisher)
Created2017
Description
Semiconductor nanowires have the potential to emerge as the building blocks of next generation field-effect transistors, logic gates, solar cells and light emitting diodes. Use of Gallium Nitride (GaN) and other wide bandgap materials combines the advantages of III-nitrides along with the enhanced mobility offered by 2-dimensional confinement present in nanowires. The focus of this thesis is on developing a low field mobility model for a GaN nanowire using Ensemble Monte Carlo (EMC) techniques. A 2D Schrödinger-Poisson solver and a one-dimensional Monte Carlo solver is developed for an Aluminum Gallium Nitride/Gallium Nitride Heterostructure nanowire. A GaN/AlN/AlGaN heterostructure device is designed which creates 2-dimensional potential well for electrons. The nanowire is treated as a quasi-1D system in this work. A self-consistent 2D Schrödinger-Poisson solver is designed which determines the subband energies and the corresponding wavefunctions of the confined system. Three scattering mechanisms: acoustic phonon scattering, polar optical phonon scattering and piezoelectric scattering are considered to account for the electron phonon interactions in the system. Overlap integrals and 1D scattering rate expressions are derived for all the mechanisms listed. A generic one-dimensional Monte Carlo solver is also developed. Steady state results from the 1D Monte Carlo solver are extracted to determine the low field mobility of the GaN nanowires.
ContributorsKumar, Viswanathan Naveen (Author) / Vasileska, Dragica (Thesis advisor) / Goodnick, Stephen (Committee member) / Zhao, Yuji (Committee member) / Arizona State University (Publisher)
Created2017
Description
Amorphous materials can be uniformly deposited over a large area at lower cost compared to crystalline semiconductors (Silicon or Germanium). This property along with its high resistivity and wide band-gap found many applications in devices like rectifiers, xerography, xero-radiography, ultrahigh sensitivity optical cameras, digital radiography, and mammography (2D and 3D tomosynthesis). Amorphous selenium is the only amorphous material that undergoes impact ionization where only holes avalanche at high electric fields. This leads to a small excess noise factor which is a very important performance comparison matrix for avalanche photodetectors. Thus, there is a need to model high field avalanche process in amorphous selenium. At high fields, the transport in amorphous selenium changes from low values of activated trap-limited drift mobility to higher values of band transport mobility, via extended states. When the transport shifts from activated mobility with a high degree of localization to extended state band transport, the wavefunction of the amorphous material resembles that of its crystalline counterpart. To that effect, crystalline monoclinic selenium which has the closest resemblance to vapor deposited amorphous selenium has been studied. Modelling a crystalline semiconductor makes calculations simpler. The transport phenomena in crystalline monoclinic selenium is studied by using a bulk Monte Carlo technique to solve the semi-classical Boltzman Transport equation and thus calculate vital electrical parameters like mobility, critical field and mobility variations against temperatures. The band structure and the density of states function for monoclinic selenium was obtained by using an atomistic simulation tool, the Atomistic Toolkit in the Virtual Nano Lab, Quantum Wise, Copenhagen, Denmark. Moreover, the velocity and energy against time characteristics have been simulated for a wide range of electric fields (1-1000 $\frac{kV}{cm}$), which is further used to find the hole drift mobility. The low field mobility is obtained from the slope of the velocity vs. electric field plot. The low field hole mobility was calculated to be 5.51 $\frac{cm^{2}}{Vs}$ at room temperature. The experimental value for low field hole mobility is 7.29 $\frac{cm^{2}}{Vs}$. The energy versus electric field simulation at high fields is used to match the experimental onset of avalanche (754 $\frac{kV}{cm}$) for an ionization threshold energy of 2.1 eV. The Arrhenius plot for mobility against temperature is simulated and compared with published experimental data. The experimental and simulation results show a close match, thus validating the study.
ContributorsMukherjee, Atreyo (Author) / Vasileska, Dragica (Thesis advisor) / Goldan, Amirhossein (Thesis advisor) / Goodnick, Stephen (Committee member) / Arizona State University (Publisher)
Created2017