Physical Sciences and Mathematics Commons^™

Plasmonic Devices Based On Transparent Conducting Oxides For Near Infrared Applications, Kim Jongbum

Open Access Dissertations

In the past decade, there have been many breakthroughs in the field of plasmonics and nanophotonics that have enabled optical devices with unprecedented functionalities. Even though remarkable demonstration of at photonic devices has been reported, constituent materials are limited to the noble metals such as gold (Au) and silver (Ag) due to their abundance of free electrons which enable the support of plasmon resonances in the visible range. With the strong demand for extension of the optical range of plasmonic applications, it is now a necessity to explore and develop alternative materials which can overcome intrinsic issues of noble metals …

Nanophotonics For Dark Materials, Filters, And Optical Magnetism, Mengren Man

Open Access Dissertations

Research on nanophotonic structures for three application areas is described, a near perfect optical absorber based on a graphene/dielectric stack, an ultraviolet bandpass filter formed with an aluminum/dielectric stack, and structures exhibiting homogenizable magnetic properties at infrared frequencies. The graphene stack can be treated as a effective, homogenized medium that can be designed to reflect little light and absorb an astoundingly high amount per unit thickness, making it an ideal dark material and providing a new avenue for photonic devices based on two-dimensional materials. Another material stack arrangement with thin layers of metal and insulator forms a multi-cavity filter that …

Exploring Spin-Transfer-Torque Devices And Memristors For Logic And Memory Applications, Zoha Pajouhi

Open Access Dissertations

As scaling CMOS devices is approaching its physical limits, researchers have begun exploring newer devices and architectures to replace CMOS.

Due to their non-volatility and high density, Spin Transfer Torque (STT) devices are among the most prominent candidates for logic and memory applications. In this research, we first considered a new logic style called All Spin Logic (ASL). Despite its advantages, ASL consumes a large amount of static power; thus, several optimizations can be performed to address this issue. We developed a systematic methodology to perform the optimizations to ensure stable operation of ASL.

Second, we investigated reliable design of …

Learning From Minimally Labeled Data With Accelerated Convolutional Neural Networks, Aysegul Dundar

Open Access Dissertations

The main objective of an Artificial Vision Algorithm is to design a mapping function that takes an image as an input and correctly classifies it into one of the user-determined categories. There are several important properties to be satisfied by the mapping function for visual understanding. First, the function should produce good representations of the visual world, which will be able to recognize images independently of pose, scale and illumination. Furthermore, the designed artificial vision system has to learn these representations by itself. Recent studies on Convolutional Neural Networks (ConvNets) produced promising advancements in visual understanding. These networks attain significant …

Effect Of Bioenergy Crops And Fast Growing Trees On Hydrology And Water Quality In The Little Vermilion River Watershed, Tian Guo

Open Access Dissertations

Energy security and sustainability require a suite of biomass crops, including woody species. Short rotation woody crops (SRWCs) such as Populus have great potential as biofuel feedstocks. Quantifying biomass yields of bioenergy crop and hydrologic and water quality responses to growth is important should it be widely planted in the Midwestern U.S. Subsurface tile drainage systems enable the Midwest area to become highly productive agricultural lands, but also create environmental problems like nitrate-N contamination of the water it drains. The Soil and Water Assessment Tool (SWAT) has been used to model watersheds with tile drainage, but the new tile drainage …

Optimal Monitoring And Mitigation Of Systemic Risk In Lending Networks, Zhang Li

Open Access Dissertations

This thesis proposes optimal policies to manage systemic risk in financial networks. Given a one-period borrower-lender network in which all debts are due at the same time and have the same seniority, we address the problem of allocating a fixed amount of cash among the nodes to minimize the weighted sum of unpaid liabilities. Assuming all the loan amounts and cash flows are fixed and that there are no bankruptcy costs, we show that this problem is equivalent to a linear program. We develop a duality-based distributed algorithm to solve it which is useful for applications where it is desirable …

On The 3d Point Cloud For Human-Pose Estimation, Kai-Chi Chan

Open Access Dissertations

This thesis aims at investigating methodologies for estimating a human pose from a 3D point cloud that is captured by a static depth sensor. Human-pose estimation (HPE) is important for a range of applications, such as human-robot interaction, healthcare, surveillance, and so forth. Yet, HPE is challenging because of the uncertainty in sensor measurements and the complexity of human poses. In this research, we focus on addressing challenges related to two crucial components in the estimation process, namely, human-pose feature extraction and human-pose modeling.

In feature extraction, the main challenge involves reducing feature ambiguity. We propose a 3D-point-cloud feature called …

Supervised Learning-Based Explicit Nonlinear Model Predictive Control And Unknown Input Estimation In Biomedical Systems, Ankush Chakrabarty

Open Access Dissertations

Application of nonlinear control theory to biomedical systems involves tackling some unique and challenging problems. The mathematical models that describe biomedical systems are typically large and nonlinear. In addition, biological systems exhibit dynamics which are not reflected in the model (so-called 'un-modeled dynamics') and hard constraints on the states and control actions, which exacerbate the difficulties in designing model-based controllers or observers.

This thesis investigates the design of scalable fast explicit nonlinear model predictive controllers (ENMPCs). The design involves (i) the estimation of a feasible region using Lyapunov stability methods and support vector machines; and (ii) within the estimated feasible …