Industrial engineering
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Practical Multi-Objective Optimization Approaches for Decision Making in Health Care Considering Infectious Disease Dynamics and Uncertainties
Operations research methods have been commonly used to inform decisions in health care related to inventory management, policy implementation, and resource allocation. However, the current research does not address many ... -
Modeling memory processes in phishing decision making using instance based learning and natural language processing
Phishing is a type of social engineering attack that uses psychological manipulations to influence people into revealing their personal information. Despite advancements in security technologies, phishing attacks continue ... -
Robust Markov decision processes with data-driven, distance-based ambiguity sets
We consider finite- and infinite-horizon Markov decision processes (MDPs), with unknown state-transition probabilities. These transition probabilities are assumed to belong to certain ambiguity sets, and the goal is to ... -
Modeling Students’ Procrastination in Higher Education: Causes, Outcomes, and Prediction
Students spend little time completing tasks when deadlines are far off; however, theytend to increase their work amounts as deadline approaches. This phenomenon, which is called deadline rush, can be modeled by exponential ... -
Incorporating Expert Knowledge into Rule Learning via Reinforcement Learning
Rule learning algorithms have great interpretability compared with other machine learning models. They also express strong power in discovering interactions between diverse variables. However, the performance of rule ... -
Learning Rule-based Decision-Making Systems from Heterogeneous Longitudinal Data
Recent advances in sensing technology have greatly expanded our capacities to collect data from a diverse pool of patients in unprecedented spatial-temporal resolutions and from a variety of different sources. These ... -
Toward Trust-calibrated Customized Vehicle Automation
Vehicle automation has long been an essential component of modern vehicular technologies. From the Advanced Driver Assistance System (ADAS) to fully autonomous vehicles, these technologies are trying to enhance road safety ... -
Information-directed policy sampling for episodic Bayesian Markov decision processes
The research objective of this dissertation is to apply information theoretic methods to design provably efficient approximate solution algorithms for Markov decision processes (MDPs), partially observable MDPs (POMDPs), ... -
Characterising Cryptocurrency Project Networks Using Graph-Based Analysis
With the introduction of smart contracts by the Ethereum blockchain in 2015, cryptocurrencies can now function as decentralized applications (dApps). Over the years, the proliferation of dApps has grown exponential and in ... -
Optimization Modeling Approaches to Evacuations of Isolated Communities
Isolated communities are particularly vulnerable to disasters caused by natural hazards. In many cases, evacuation is the only option to ensure the population's safety. Isolated communities are becoming increasingly aware ... -
Percentile and inverse optimization in Markov decision processes with extensions to convex programs
Infinite-horizon stationary Markov decision processes (MDPs) have been studied extensively in the literature. Over the last sixty years, they have found applications in a broad range of areas such as healthcare, ... -
Decision-Analytic Models for Treatment Optimization in the Presence of Patient Heterogeneity
With the ever-increasing complexity in disease etiology, new therapeutics, healthcare service delivery, and clinical guidelines, selecting the appropriate course of treatment for an individual or population can become a ... -
Evaluating the Effects of Altering Whole-Body Vibration Exposures on Truck Drivers’ Vigilance
Whole-body vibration (WBV) may contribute to truck driver fatigue and increase the potential for vehicular accidents. Previous studies of truck induced WBV exposures have mostly focused on physical discomfort, whereas ... -
Modeling Heterogeneous User Behavior in Interactive Systems by Graphical Model and Collaborative Learning Framework
In recent years, the rapid technological innovations of smart personal technologies have given rise to the growth of smart apps that can interact with users and implement personalized incentives to coordinate and change ... -
Estimating distance between pedestrians from street view images using geometric properties
A National Science Foundation (NSF)-supported Rapid Response Research (RAPID) project was granted in the early months of the COVID-19 lockdown for the purposes of tracking Seattle, Washington through the progression of the ... -
Data-Driven Assessment of Disaster Damage and Recovery Time
Although natural hazards may sometimes be predictable, their occurrence is not preventable, especially in low-frequency-yet-high-impact events such as earthquakes and hurricanes. The catastrophic effects of natural hazards ... -
Data-Driven Polynomial Chaos Expansions for Uncertainty Quantification
Uncertainties exist in both physics-based and data-driven models of systems. Understanding how system inputs affect a system output's uncertainty is essential to improve system outputs such as quality and productivity. ... -
Take-Over Time Modeling and Prediction for Conditional Driving Automation
Autonomous vehicles are designed to enhance the overall driver safety by taking the driver out of the loop. However, the autonomous vehicles that are currently available on the market still require that the driver is ... -
Zero-inflated Models for Semi-continuous Transportation Data
Zero-inflated models have been widely studied and are commonly used in the transportation safety area. Despite the success of zero-inflated models to analyze static data with counting outcomes, challenges remain in the ... -
Simulation and Statistical Methods in Proactive and Strategic Obsolescence Management
In fields with sustainment-dominated systems, where the sustainment costs are larger than the original system costs, managing the life-cycle costs is a non-trivial task. These fields include aviation, power plants, medical, ...