Browsing by Author "Nicholson, Charles"
Now showing items 21-40 of 73
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Design, Implementation, and Evaluation of Join and Split Strategy for Transmission control protocol running on Software Defined Networks
Guo, Wei (2017-12-15)Software Defined Networks (SDN)-enabled switches of today can be empowered to intelligently forward as well as elastically steer the network traffic. In this work, we focus on developing a SDN-based framework to provide ... -
Designing Reliable Machine Learning Algorithms for Early Prediction of Preeclampsia
Bennett, Rachel (2021-08)Known as a pregnancy complication due to high blood pressure and may be accompanied by damage to another organ system, preeclampsia afflicts between 3 and 6 percent of US pregnancies each year. Studies have shown the ... -
Detection of Overshooting Cloud Tops with Convolutional Neural Networks
Kanneganti, Gowtham Teja (2020-05-08)Overshooting cloud tops can cause severe weather conditions, such as aviation turbulence, lightning, strong winds, heavy rainfall, hail, and tornadoes. Due to hazards caused by overshooting tops, several methods have been ... -
Developing and Applying Hybrid Deep Learning Models for Computer-Aided Diagnosis of Medical Image Data
Mudduluru, Sanjana (2023)The dissertation discusses three methods to address the challenges of applying deep learning models to medical imaging. The first method involves the development of a new joint deep learning model, J-Net, to achieve lesion ... -
Development of Deep Learning Methodologies for Modeling Navigational Features in Continuous Spaces
Hoyt, Zackary (2021-12)This thesis proposes generalized methodologies to model navigational features of continuous spaces using deep learning architectural approaches. Navigational features impact how an entity can effectively travel within a ... -
Development of Multi-objective Optimization Model of Community Resilience on Mitigation Planning
Wen, Yunjie (2021-12)Mitigation planning in many disaster-prone areas has shown success in helping the community to withstand hazardous events, reducing the recovery time and costs, and preventing life losses. This research proposes a ... -
Discovering Accessible Data Visualizations for People with ADHD
Tran, Tien (2024-05-10)There have been many studies on understanding effective data visualizations regarding general users. However, we have a limited understanding on how people with ADHD comprehend data visualizations and how it might differ ... -
Dynamic Uplift Modeling
Talluru, Gowtham (2017-12)In this thesis, a new approach to Uplift modeling which considers time dependent behavior of the customers is analyzed. Uplift modeling attempts to measure the impact of a treatment on an entity in a controlled experiment. ... -
The Effect of Gathering on Sandbox Player Engagement as Defined Using Analytic Methods
Grimes, Emily (2017-05)Player engagement is a concept that is both vital to the online gaming industry and difficult to define. Typically, engagement is defined using social science methodology such that observing, surveying, and interviewing ... -
ENHANCING INFRASTRUCTURE RESILIENCE THROUGH INTEGRATION OF A MAX-MIN FAIRNESS-INSPIRED STRATEGY IN MULTIMODAL TRANSPORTATION AND SUPPLY CHAIN SYSTEMS
Moshebah, Osamah Y (2024-05)This dissertation's primary contribution to Supply Chain and Transportation Network (SCTN) resilience lies in the implementation of a sequence of Multicriteria Mixed Integer liners programming MCMILP models that ... -
Exploring Drug-Use Progression Through Stability Enhanced Clustering
Beattie, Matthew (2022-05)Background and aims: Drug use initiation sequences have been the subject of much research, and theories such as the Gateway Hypothesis have been created to explain patterns of progression from common to dangerous drugs. ... -
Fair Resource Allocation in Macroscopic Evacuation Planning Using Mathematical Programming: Modeling and Optimization
Bin Obaid, Hamoud (2020)Evacuation is essential in the case of natural and manmade disasters such as hurricanes, nuclear disasters, fire accidents, and terrorism epidemics. Random evacuation plans can increase risks and incur more losses. Hence, ... -
Finding key characteristics of promising compounds for anticancer drug discovery
Ribeyre, Pauline (2017-12)Multidrug resistance is the simultaneous resistance to two or more chemically unrelated therapeutics, including some therapeutics the cell has never been exposed to. It is one of the biggest obstacles to effective cancer ... -
Forecasting the COVID-19 pandemic in the United States and Peru using ARIMA, LSTM, GRU, CNN, and a hybrid approach
Hoover, Mary (2023-12-15)The COVID-19 outbreak spread swiftly and infected many individuals resulting in overwhelmed and overfilled hospitals causing an immense loss of life globally. Identifying the number of infected individuals preemptively ... -
A FRAMEWORK OF EPIDEMIC MODELING CONSIDERING PREVENTIVE BEHAVIORS: COMPARTMENTAL MODELING, TEXT ANALYTICS, AND MACHINE LEARNING
Cho, Hyejin (2024-04-25)The goal of this research is to provide a novel framework for epidemic modeling incorporating metrics derived from social media to predict epidemic dynamics and to estimate the impact of preventive behaviors. This study ... -
Game Theory Application of Resilience Community Road-Bridge Transportation System
Wen, Yunjie (2017-12-15)This thesis considers the problem of game theory application in resilience-based road-bridge transportation network. Bridges in a community may be owned and maintained by separated entities. These owners may have different ... -
General supervised learning framework for open world classification
Bhavaraju, Sai Krishna Theja (2020-12-18)In machine learning, the most common scenario for classification modeling is when the training set contains all possible classes and the algorithm learns to identify these classes. The problem setting in which the training ... -
Heuristic Approach to Network Recovery
Chang, Yanbin (2018-05-11)This study addresses optimization modeling for recovery of a transportation system after a major disaster. In particular, a novel metric based on the shape of the recovery curve is introduced as the objective to minimize. ... -
Improving Outcomes in Machine Learning and Data-Driven Learning Systems using Structural Causal Models
Mbogu, Henry Maduka (2023-12-15)The field of causal inference has experienced rapid growth and development in recent years. Its significance in addressing a diverse array of problems and its relevance across various research and application domains are ... -
Informed, Interactive, and Interpretable Machine Learning for Forward Kinematics of Robot Arms
Kanneganti, Sai Teja (2022-08)Machine learning (ML) is becoming increasingly sought after in diverse domains. Unfortunately for this objective, most ML research has focused too much on improving performance on evaluation metrics such as accuracy to the ...