Research Objective:
Determine if disparities in the allocation of lifesaving organs, specifically the kidney and liver, exist between low and non-low socioeconomic status (SES) groups in the US.
Study Design:
A literature review will be conducted to examine anticipated inequalities between patients of different SES. Potential causes of the disparity...
Hepatocellular carcinoma (HCC) is one of the leading causes of cancer death in the United States. Patients with cirrhosis are more likely to develop HCC. More than 80% of HCC patients are found have preexisting cirrhosis. The prevalence of cirrhosis increased from 0.26% to 0.3.% between 1999 to 2010 and...
The enactment of the Patient Protection and Affordable Care Act (ACA) can be considered an important policy intervention in the context of the U.S. health care. The ACA supported non-elderly adults to obtain health insurance coverage. While Medicare provided health insurance to almost all elderly-adults (persons over 65), the ACA...
The purpose of this dissertation was to examine the effects of war stressors and psychosocial factors on negative and positive mental health outcomes among Korean Vietnam War veterans. The sample consisted of 367 male veterans who completed a self-reported survey conducted in 2017 (Mage = 72, SD = 2.66, range...
The overall focus of this thesis is on the distribution of specific lipids and membrane proteins of the external and internal membranes of plant cells, in the context of the roles that those lipids and proteins may play in microbe-plant interactions. The work includes the development of several new tools,...
Multiple-input multiple-output wireless systems promise significant capacity gain
and/or diversity gain over single antenna systems. If channel state information (CSI)
is available at both the transmitter and the receiver, the performance can be further
improved. In this thesis, first, we study binary index feedback problem in beamforming
systems when the...
This thesis describes compensation techniques for cascaded delta-sigma A/D
converters (ADCs) and high-performance switched-capacitor (SC) circuits. Various
correlated-double-sampling (CDS) techniques are presented to reduce the effects of the
nonidealities, such as clock feedthrough, charge injection, opamp input-referred noise and
offset, and finite opamp gain, in SC circuits. A CDS technique...
This dissertation presents a low-power high-resolution delta-sigma ADC. Two new architectural design techniques are proposed to reduce the power dissipation of the ADC. Compared to the conventional active adder, the direct charge transfer (DCT) adder greatly saves power by keeping the feedback factor of the active adder unity. However, the...
The purpose of this research is to hydraulically characterize an engineered wetland in Albany, Oregon. The wetland receives treated wastewater from both Albany Millersburg Water Reclamation Facility (AMWRF) and ATI Wah Chang. AMWRF's water is municipal waste water. ATI Wah Chang's water comes from its nearby metal processing plant. The...
Successive approximation register analog-to-digital converters (SAR ADCs) have been widely used for medium-speed, medium-resolution applications due to their excellent power efficiency and digital compatibility. Recently, SAR ADCs are also penetrating into the applications which have been earlier dominated by delta-sigma ADCs and pipeline ADCs. However, the resolution of SAR ADCs...
Ultra-high-speed (>10GS/s), medium-resolution (5~6bit), low-power (<50mW) analog-to-digital converter can find it application in the areas of digital oscilloscopes and next-generation serial link receivers. There are several challenges to enable a successful design, however. First, the time-interleaved architecture is required in order to achieve over 10GS/s sampling rate, with the trade-off...
Threshold-based time of arrival (TOA) estimation is a technique for high-precision indoor localization. Existing threshold selection methods, such as xed thresh- old and normalized threshold methods, do not consider the signal-to-noise radio (SNR) value at the receiver. This is not desired for high-precision positioning. A proper threshold value depends on...
Two framework oxide materials of the MO₃ network type have been synthesized and structurally characterized by synchrotron and X-ray powder diffraction and the Rietveld method in the temperature range 25~500 K. The results show one of them to be a low thermal expansion material. Theoretical studies of negative thermal expansion...
Delta-sigma modulators are currently a very popular technique for making high-resolution
analog-to-digital converters (ADCs) and digital-to-analog converters (DACs).
These oversampled data converters have several advantages over conventional Nyquist-rate
converters, including an insensitivity to many analog component imperfections, a
simpler antialiasing filter and reduced accuracy requirements in the sample and hold....
An accurate state estimation plays an essential role in power system operation and planning in energy management systems. However, existing multi-area state estimation researches have not focused on the importance of system clustering. The clustering mechanism divides or partitions a system according to user-defined criteria. Few published research works have...
The use of double-diffused n-type MOS transistor
(DN-MOS) in a complementary MOS random-access-memory (CMOS
RAM) cell is the main objective of this investigation.
DN-MOS transistors and conventional p-channel MOS
transistors on the same chip have been successfully fabricated.
Process sequence effects on device threshold voltage
and channel length are discussed....
Labeling videos is costly, time-consuming and tedious. These costs can escalate in applications such as medical diagnosis or autonomous driving where we need domain expertise for annotation. Few-shot action recognition aims to solve this problem by annotation-efficient learning mechanisms.
This thesis presents MetaUVFS as the first Unsupervised Meta-learning algorithm for...
In this thesis, we introduce a novel Explanation Neural Network (XNN) to explain the predictions made by a deep network. The XNN works by embedding a high-dimensional activation vector of a deep network layer non-linearly into a low-dimensional explanation space while retaining faithfulness i.e., the original deep learning predictions can...
Learning to recognize objects is a fundamental and essential step in human perception and understanding of the world. Accordingly, research of object discovery across diverse modalities plays a pivotal role in the context of computer vision. This field not only contributes significantly to enhancing our understanding of visual information but...