UMBC Graduate School
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Combining Knowledge and Data in Symbolic Regression
(2022-01-01)Symbolic regression (SR) is a machine learning tool that aims to generate models that fit data, by constructing equations from variables of interest, constants, and mathematical operators. SR has inspired applications for ... -
Building Robust Human Activity Recognition Models from Unlabeled Data
(2022-01-01)Machine learning-driven wearable sensor-based human activity recognition (HAR) systems have experienced meteoric popularity in recent years in healthcare, entertainment, and physical fitness applications, but their large-scale ... -
Structural & Functional Investigations of Arginyltransferases
(2022-01-01)Arginylation, or the transfer of the amino acid arginine from a charged tRNA to a substrate protein, is a post-translational modification (PTM) that is catalyzed by an essential eukaryotic enzyme known as arginyltransferase ... -
ACCORDING TO MY TRUE MEANING: EMOTIONS AND WILL-MAKERS IN SOUTHERN ENGLAND DURING THE SEVENTEENTH CENTURY
(2022-01-01)Early modern wills have often been dismissed by early modern social historians as sources for individual voice and perspective due to the collaborative nature of their creation and will-makers’ reliance on formulaic language. ... -
Interweave Cognitive Radio for 4G Long Term Evolution and 5G New Radio Self-Reliant Networks
(2022-01-01)Existing cellular networks have untapped radio frequency resources, also known as white space, available for cognitive radio applications. A secondary network can opportunistically interweave communication within the white ... -
"It's About Damn Time": Lizzo and the Rhetoric of Body Positivity
(2022-01-01)Through rhetorical analysis, I argue that popular culture sensation Lizzo emulatesrestorative literacy practices for fat, Black women to navigate harmful cultural norms manifested as anti-blackness, misogynoir, and fatphobia ... -
Factors Affecting OptiX Performance in Ray Tracing for Metrology
(2022-01-01)With the increasing prevalence of ray tracing cores in modern graphics cards, ray tracing based applications can see huge running time improvements. Simulations for x-rays and other electromagnetic radiation have long used ... -
INTERPRETABLE DEEP LEARNING MODELS FOR ELECTRONIC HEALTH RECORDS
(2022-01-01)Analysis of healthcare data could help reduce cost, improve patient outcomes and understand the best practices related to diseases.However,with rapid increase of massive amounts of health-related data, such as Electronic ... -
Quantum Optical State Preparation for Quantum Communication
(2022-01-01)Nonclassical states of light are essential for long-distance quantum communication. In this dissertation, we theoretically analyze the state preparation of nonclassical states of light, resource-efficient quantum optical ... -
USING FACIAL EMOTION READING TO ASSIST IN THE EXTRACTION OF EEG EMOTIONAL BIOMARKERS
(2022-01-01)While electroencephalograms (EEG) have been used for decades in various areas of research, very little has been accomplished when it comes to how emotional states are reflected in EEG readings of test subjects. In this ... -
BACKDOOR ATTACKS IN COMPUTER VISION: TOWARDS ADVERSARIALLY ROBUST MACHINE LEARNING MODELS
(2022-01-01)Deep Neural Networks (DNNs) have become the standard building block in numerous machine learning applications, including computer vision, speech recognition, machine translation, and robotic manipulation, achieving ... -
Reformation or Retribution: Daily Life and the Landscape of Two Maryland Industrial Schools for Girls, 1916-1989
(2022-01-01)The scholarship on American industrial schools can be clearly characterized by a large gap in knowledge, especially in the state of Maryland. This research focuses on two major industrial schools in and around the Baltimore, ... -
Building Textual Fuzzy Interpretive Structural Modeling to Analyze Complex Problems
(2022-01-01)Organizations regularly make decisions on complex issues with multiple variables or parameters. Hence, there is a strong motivation for the organization’s Management to formalize and adopt a scientific approach to their ... -
Evaluating Malware Classifiers on Unknown Malware Families
(2022-01-01)Due to the number of daily malware attacks, we have been relying on machinelearning to detect them. Lots of people sell systems that claim to do this, which we refer to as malware classifiers. Evaluating malware classifiers ... -
Robust Deep Semi-supervised Clustering with Cauchy Mixture
(2022-01-01)In this paper, we present using Cauchy Mixture Model (CMM) as the activation function of deep neural networks for pseudo-labeling in semi-supervised classification. Unlike SoftMax, which is universally used as the final ... -
Lifelong Multitask Learning Algorithms: Nonlinearity, Scalability and Applications
(2022-01-01)With the deluge of data in the modern world, machine learning has become a mainstay of industry and science. Machine learning algorithms aim to find underlying relationships hidden in a task that agree with prior knowledge ... -
The Hyper-Angular Rainbow Polarimeter: Pre-Launch Calibration, Validation, and Advancements in Cloud Science
(2022-01-01)Studying the climate requires comprehensive, accurate, and global measurements of the atmosphere and surface. Small, economical, and powerful platforms, like the Hyper-Angular Rainbow Polarimeter (HARP), are part of a new ... -
Three Papers Exploring Trends in Mathematics Achievement and Policy Implications for Improving Outcomes
(2022-01-01)Mathematics achievement remains a primary focus of education policy in the US. Achievement improved quite substantially for 9- and 13-year-olds over 50 years of education reform from 1971 – 2012 according to the National ... -
Susceptibility of Shellfish Aquaculture Species in the Chesapeake Bay and Maryland Coastal Bays to the Ostreid Herpesvirus-1 Microvariants
(2022-01-01)The Ostreid herpesvirus 1(OsHV-1) and its microvariants are highly virulent pathogens that cause mass mortalities of oysters and pose a threat to the shellfish aquaculture industry globally. OsHV-1 causes economically ... -
Three Papers Examining The Experience, Value Frameworks And Value-Based Purchasing Of Novel Drugs
(2022-01-01)This dissertation explores real-world experience, value assessment frameworks, and value-based purchasing arrangements for novel medications. The first paper is a systematic literature review of outcomes of these novel ...