Operations Research, Systems Engineering and Industrial Engineering Commons^™

Drivers’ Hazard Avoidance During Vehicle Automation: Impact Of Mental Models And Implications For Training, Ganesh Pai Mangalore

Doctoral Dissertations

Advanced Driver Assistance Systems (ADAS) are vehicle automation systems that have become more accessible and prevalent in vehicles in recent years. But the introduction of such technologies introduces new human factors challenges. Past literature suggests that users of vehicle automation lack the necessary and appropriate knowledge about their automation system. This may play a negative role in their hazard avoidance abilities when driving with automation features. Improving mental models and knowledge could generally lead to safer interactions with vehicle automation systems, but any effort to develop hazard avoidance skills when driving with vehicle automation is impeded by the lack of …

Mining High Impact Combinations Of Conditions From The Medical Expenditure Panel Survey, Arjun Mohan

Masters Theses

The condition of multimorbidity — the presence of two or more medical conditions in an individual — is a growing phenomenon worldwide. In the United States, multimorbid patients represent more than a third of the population and the trend is steadily increasing in an already aging population. There is thus a pressing need to understand the patterns in which multimorbidity occurs, and to better understand the nature of the care that is required to be provided to such patients.

In this thesis, we use data from the Medical Expenditure Panel Survey (MEPS) from the years 2011 to 2015 to identify …

A Digital Twin Framework For Production Planning Optimization: Applications For Make-To-Order Manufacturers, Ron Mallach

Doctoral Dissertations

In this dissertation, we develop a Digital Twin framework for manufacturing systems and apply it to various production planning and scheduling problems faced by Make-To-Order (MTO) firms. While this framework can be used to digitally represent a particular manufacturing environment with high fidelity, our focus is in using it to generate realistic settings to test production planning and scheduling algorithms in practice. These algorithms have traditionally been tested by either translating a practical situation into the necessary modeling constructs, without discussion of the assumptions and inaccuracies underlying this translation, or by generating random instances of the modeling constructs, without assessing …

Decision-Analytic Models Using Reinforcement Learning To Inform Dynamic Sequential Decisions In Public Policy, Seyedeh Nazanin Khatami

Doctoral Dissertations

We developed decision-analytic models specifically suited for long-term sequential decision-making in the context of large-scale dynamic stochastic systems, focusing on public policy investment decisions. We found that while machine learning and artificial intelligence algorithms provide the most suitable frameworks for such analyses, multiple challenges arise in its successful adaptation. We address three specific challenges in two public sectors, public health and climate policy, through the following three essays. In Essay I, we developed a reinforcement learning (RL) model to identify optimal sequence of testing and retention-in-care interventions to inform the national strategic plan “Ending the HIV Epidemic in the US”. …

Improving Young Driver Perceptions Of Vulnerable Road Users Through A Persuasive Intervention, Shashank Mehrotra

Doctoral Dissertations

Vulnerable road users (VRUs), including bicyclists, pedestrians, and road users of other modalities, are at a higher risk of collision with young drivers when a complex traffic situation presents itself. Past research has established the importance of young drivers’ perceptions about VRUs that would encourage safe behavior. This research designed and evaluated a novel persuasive intervention that can help improve the perceptions of young drivers while they interact with VRUs. The study identified young drivers’ perceptions towards VRUs who have been licensed in the past 12 to 18 months through structured interviews. Based on these findings, an interactive intervention was …

Comparing And Improving The Design Of Physical Activity Data Visualizations, Peter M. Frackleton

Masters Theses

Heart disease is a leading cause of death in the United States, and older adults are at highest risk of being diagnosed with heart disease. Consistent physical exercise is an effective means of deterring onset of heart disease, and physical activity tracking devices can inspire greater activity in older adults. However, physical activity tracking device abandonment is quite common due to limitations on what can be learned from the activity data that is collected. Better data visualization of physical data presents an opportunity to surpass these limitations. In this thesis, a task-based human subject study was performed with three different …

Modeling Portfolios Of Low Carbon Energy Generation Under Deep Uncertainty, Franklyn Kanyako

Doctoral Dissertations

In the 2015 Paris Agreement, nearly every country pledge through the Nationally Determined Contributions (NDCs) increased adoption of low carbon energy technologies in their energy system. However, allocating investments to different low carbon energy technologies under rising demand for energy and budget constraints, uncertain technical change in these technologies involves maneuvering significant uncertainties among experts, models, and decision-makers. We examine the interactions of low carbon energy sources (LCES) under the condition of deep uncertainty. Deep uncertainty directly impacts the understanding of the role of low carbon energy technologies in climate change mitigation and how much R&D investment should be allocated …

Factors Affecting Drivers’ Off-Road Glance Behavior While Interacting With In-Vehicle Voice Interfaces – Insights From A Secondary Data Analysis, Fangda Zhang

Doctoral Dissertations

Given the prevalence of in-vehicle technologies and the critical role of visual attention plays in driving safety, this dissertation work aimed to fill the research gap that 1) little was known about the visual demands associated with a driver engaging with in-vehicle voice interfaces; 2) the concurrent effect of interacting with in-vehicle voice interfaces and other commonly discussed individual-level factors has barely been targeted. This research work was a secondary data analysis based on a large-scale field experiment wherein 144 participants had been recruited and driven a test vehicle while performing a series of tasks using voice-based interfaces. Pre- and …

Optimal Mammography Schedule Estimates Under Varying Disease Burden, Infrastructure Availability, And Other Cause Mortality: A Comparative Analyses Of Six Low- And Middle- Income Countries, Shifali Shifali

Masters Theses

Low-and-middle-income countries (LMICs) have a higher mortality-to-incidence ratio for breast cancer compared to high-income countries (HICs) because of late-stage diagnosis. Mammography screening is recommended for early diagnosis, however, current screening guidelines are only generalized by economic disparities, and are based on extrapolation of data from randomized controlled trials in HICs, which have different disease burdens and all-cause mortality compared to LMICs. Moreover, the infrastructure capacity in LMICs is far below that needed for adopting current screening guidelines. This study analyzes the impact of disease burden, infrastructure availability, and other cause mortality on optimal mammography screening schedules for LMICs. Further, these …

Improving Drivers’ Behaviour When Partial Driving Automation Fails, Yalda Ebadi

Doctoral Dissertations

With the advent of automated vehicle systems, the role of drivers has changed to a more supervisory role. However, it is known that all vehicles with Level 2 (L2) systems have a very specific operational design domain (ODD) and can only function on limited conditions. Hence, it is important for drivers to perceive the situations properly and regain the control from the L2 system when needed. As suggested by past research, designing an informative interface could help drivers in their new supervision and intervention role while driving with L2 vehicles by providing feedback to drivers when hazards or event that …

Robust And Sustainable Energy Pathways To Reach Mexico’S Climate Goals, Rodrigo Mercado Fernandez

Doctoral Dissertations

As countries set climate change goals for adaptation and mitigation efforts, there are many questions regarding to how to reach these targets. These efforts will necessitate the transition of our electricity infrastructure from relying on conventional electricity generation technologies including natural gas, coal and oil, to clean energy generation with renewables. Through the three essays presented in this dissertation, we explore various pathways of development for the electricity system to reach long term climate change goals. We are interested in identifying: Is there a unique optimal development option or are there various? How do different mixes of electricity generation technologies …

Modeling Of Electrical Grid Systems To Evaluate Sustainable Electricity Generation In Pakistan, Muhammad Mustafa Amjad

Masters Theses

Pakistan has always had a history of severe energy shortfalls, which rose up to an alarming 33% in 2013. This situation was countered by investments in the energy sector through the China Pakistan Economic Corridor (CPEC), which were unfortunately largely based on brown fuels. Although beneficial in the short term, these investments do not bode well for the climate scenario of Pakistan, with various parts of the country already having experienced temperatures rise of 1-3°C. To ensure that the current situation doesn’t exacerbate and is tackled in a timely manner, this research aims to examine how the untapped potential of …

Three Essays On Data-Driven Optimization For Scheduling In Manufacturing And Healthcare, Ekin Koker

Doctoral Dissertations

This dissertation consists of three essays on data-driven optimization for scheduling in manufacturing and healthcare. In Chapter 1, we briefly introduce the optimization problems tackled in these essays. The first of these essays deals with machine scheduling problems. In Chapter 2, we compare the effectiveness of direct positional variables against relative positional variables computationally in a variety of machine scheduling problems and we present our results. The second essay deals with a scheduling problem in healthcare: the team primary care practice. In Chapter 3, we build upon the two-stage stochastic integer programming model introduced by Alvarez Oh (2015) to solve …

Combining Human Factors And Data Science Methods To Evaluate The Use Of Free Text Communication Orders In Electronic Health Records, Swaminathan Kandaswamy

Doctoral Dissertations

Medication errors are a leading cause of death in the United States. Electronic Health Records (EHR) along with Computerized Provider Order Entry (CPOE) are considered promising ways to reduce these errors. However, EHR systems have not eliminated medication errors. Moreover, in some cases they have facilitated errors due to issues such as poor usability and negative effects on clinical workflows. The use of unexpected free text within a CPOE system can serve as a marker that the system does not adequately support clinical workflow. Prior studies have looked at the use of free text within medication orders, but the inclusion …

Topology Network Optimization Of Facility Planning And Design Problems, Ravi Ratan Raj Monga

Masters Theses

The research attempts to provide a graphical theory-based approach to solve the facility layout problem. Which has generally been approached using Quadratic Assignment Problem (QAP) in the past, an algebraic method. It is a very complex problem and is part of the NP-Hard optimization class, because of the nonlinear quadratic objective function and (0,1) binary variables. The research is divided into three phases which together provide an optimal facility layout, block plan solution consisting of MHS (material handling solution) projected onto the block plan. In phase one, we solve for the position of departments in a facility based on flow …

Power System Planning In Disparate Systems: Modeling Sustainability And Electricity Access, Destenie Nock

Doctoral Dissertations

Electricity goals around the world tend to focus on increasing social benefit through one of two avenues: (1) increasing overall system sustainability or (2) increasing access to electricity. These goals guide the transition of the power system. In pursuit of these goals decision makers will need modeling tools that can inform decisions, in a way that is flexible enough to include a wide range of preferences and goals. It is clear that the future generation mix of the power system will change, but the most sustainable solution, will change based on a country's goals. This dissertation will explore the various …

A Computational Simulation Model For Predicting Infectious Disease Spread Using The Evolving Contact Network Algorithm, Buyannemekh Munkhbat

Masters Theses

Commonly used simulation models for predicting outbreaks of re-emerging infectious diseases (EIDs) take an individual-level or a population-level approach to modeling contact dynamics. These approaches are a trade-off between the ability to incorporate individual-level dynamics and computational efficiency. Agent-based network models (ABNM) use an individual-level approach by simulating the entire population and its contact structure, which increases the ability of adding detailed individual-level characteristics. However, as this method is computationally expensive, ABNMs use scaled-down versions of the full population, which are unsuitable for low prevalence diseases as the number of infected cases would become negligible during scaling-down. Compartmental models use …

Evaluation And Validation Of Distraction Detection Algorithms On Multiple Data Sources, Shashank Mehrotra

Masters Theses

This study aims to evaluate algorithms designed to detect distracted driving. This includes the comparison of how efficiently they detect the state of distraction and likelihood of a crash. Four algorithms that utilize measures of cumulative glance, past glance behavior, and glance eccentricity were used to understand the distracted state of the driver and were validated on two separate data sources (i.e., simulator and naturalistic data). Additionally, an independent method for distraction detection was designed using data mining methods. This approach utilized measures like steering degree, lane offset, lateral and longitudinal velocity, and acceleration. The results showed a higher likelihood …

The Application Of Usability Engineering Methods To Evaluate And Improve A Clinical Decision Support System, Kristine Desotto

Masters Theses

Delays in the process of diagnosing and treating cancer are common and lead to confusion and undesirable outcomes. Care coordinators are often embedded within the system of care to manage follow-up care. Electronic and real-time reminder systems can be used to support the care coordinator’s work, but electronic health record (EHR) usability is known to be poor. This study, completed in collaboration with the Department of Veterans Affairs (VA) Connecticut Healthcare System, evaluated the Cancer Coordination and Tracking System (CCTS), an EHR-linked, web-based tool for cancer care management.

A set of expert-driven and user-driven usability engineering methods was applied to …

Does The Elicitation Mode Matter? Comparing Different Methods For Eliciting Expert Judgement, Claire Cruickshank

Masters Theses

An expert elicitation is a method of eliciting subjective probability distributions over key parameters from experts. Traditionally an expert elicitation has taken the form of a face-to-face interview; however, interest in using online methods has been growing. This thesis compares two elicitation modes and examines the effectiveness of an interactive online survey compared to a face-to-face interview. Differences in central values, overconfidence, accuracy and satisficing were considered. The results of our analysis indicated that, in instances where the online and face-to-face elicitations were directly comparable, the differences between the modes was not significant. Consequently, a carefully designed online elicitation may …

Theory And Practice Of Supply Chain Synchronization, Michael Prokle

Doctoral Dissertations

In this dissertation, we develop strategies to synchronize component procurement in assemble-to-order (ATO) production and overhaul operations. We focus on the high-tech and mass customization industries which are not only considered to be very important to create or keep U.S. manufacturing jobs, but also suffer most from component inventory burden. In the second chapter, we address the deterministic joint replenishment inventory problem with batch size constraints (JRPB). We characterize system regeneration points, derive a closed-form expression of the average product inventory, and formulate the problem of finding the optimal joint reorder interval to minimize inventory and ordering costs per unit …

Modeling The Economic And Environmental Performance Of Offshore Wind Energy, Alexana Cranmer

Doctoral Dissertations

Offshore wind is a growing source of energy globally. Like any energy technology, it has impacts on the environment. In the case of renewable energy, we need a way to consider the environmental benefits as well as the environmental costs. This dissertation develops a set of models to examine the economic and environmental costs and benefits and the trade-offs between them. We ask how much offshore wind energy should be sited, and where should that offshore wind energy be located? The first model estimates the economic impact of wake interactions between wind farms. Wind farm sites are chosen through a …

Explorations Into Machine Learning Techniques For Precipitation Nowcasting, Aditya Nagarajan

Masters Theses

Recent advances in cloud-based big-data technologies now makes data driven solutions feasible for increasing numbers of scientific computing applications. One such data driven solution approach is machine learning where patterns in large data sets are brought to the surface by finding complex mathematical relationships within the data. Nowcasting or short-term prediction of rainfall in a given region is an important problem in meteorology. In this thesis we explore the nowcasting problem through a data driven approach by formulating it as a machine learning problem.

State-of-the-art nowcasting systems today are based on numerical models which describe the physical processes leading to …

The Effect Of Interruptions On Primary Task Performance In Safety-Critical Environments, Cheryl Ann Nicholas

Doctoral Dissertations

Safety critical systems in medicine utilize alarms to signal potentially life threatening situations to professionals and patients. In particular, in the medical field multiple alarms from equipment are activated daily and often simultaneously. There are a number of alarms which require caregivers to take breaks in complex, primary tasks to attend to the interruption task which is signaled by the alarm. The motivation for this research is the knowledge that, in general, interrupting tasks can have a potentially negative impact on performance and outcomes of the primary task. The focus of this research is on the effect of an interrupting …

Design, Implementation, And Evaluation Of A User Training Program For Integrating Health Information Technology Into Clinical Processes, Ze He

Doctoral Dissertations

Health information technology (IT) implementation can be costly, and remains a challenging problem with mixed outcomes on patient safety and quality of care. Systems engineering and IT management experts have advocated the use of sociotechnical models to understand the impact of health IT on user and organizational factors. Sociotechnical models suggest the need for user-centered implementation approaches, such as user training and support, and focus on processes to mitigate the negative impact and facilitate optimal IT use during training. The training design and development should also follow systematic processes guided by instructional development models. It should take into account of …

Aircraft Demand Forecasting, Kayla M. Monahan

Masters Theses

This thesis aims to forecast aircraft demand in the aerospace and defense industry, specifically aircraft orders and deliveries. Orders are often placed by airline companies with aircraft manufacturers, and then suddenly canceled due to changes in plans. Therefore, at some point during the three-year lead time, the number of orders placed and realized deliveries may be quite different. As a result, orders and deliveries are very difficult to predict and are influenced by many different factors. Among these factors are past trends, macroeconomic indicators as well as aircraft sales measures. These predictor variables were analyzed thoroughly, then used with time …

Strategies For Reducing Supplier Risk: Inputs Into The Supply Chain, Christopher A. Greene

Masters Theses

There are many aspects to consider when managing an entire supply chain from procurement to fulfillment. Complex assemblies require hundreds of components, sourced from all corners of the globe, to come together in a synchronized fashion. Given the magnitude of the supply chain, high quality standards, and significantly increased outsourcing, there is a strong need to monitor supplier risk and quickly identify and mitigate potential problems. Moreover, the continuous pressure to reduce resources and pressure to cut costs, further increases the need for the development of procedures and tools that can quickly and efficiently address these potential supply chain risks. …

Evaluation Of A Training Program (Strap) Designed To Decrease Young Drivers Secondary Task Engagement In High Risk Scenarios, Akhilesh Krishnan

Masters Theses

Distracted driving involving secondary tasks is known to lead to an increased likelihood of being involved in motor vehicle crashes. Some secondary tasks are unnecessary and should never be performed. But other secondary tasks, e.g., operating the defroster, are critical to safe driving. Ideally, the driver should schedule when to perform the critical tasks such that the likelihood of a hazard materializing is relatively small during the performance of the secondary task. The current study evaluates a training program -- STRAP (Secondary Task Regulatory & Anticipatory Program) -- which is designed to make drivers aware of latent hazards …

Guidelines For Scheduling In Primary Care: An Empirically Driven Mathematical Programming Approach, Hyun Jung Alvarez Oh

Doctoral Dissertations

Primary care practices play a vital role in healthcare delivery since they are the first point of contact for most patients, and provide health prevention, counseling, education, diagnosis and treatment. Practices, however, face a complex appointment scheduling problem because of the variety of patient conditions, the mix of appointment types, the uncertain service times with providers and non-provider staff (nurses/medical assistants), and no-show rates which all compound into a highly variable and unpredictable flow of patients. The end result is an imbalance between provider idle time and patient waiting time. To understand the realities of the scheduling problem we analyze …

Model-Based Guidance For Human-Intensive Processes, Stefan Christov

Doctoral Dissertations

Human-intensive processes (HIPs), such as medical processes involving coordination among doctors, nurses, and other medical staff, often play a critical role in society. Despite considerable work and progress in error reduction, human errors are still a major concern for many HIPs. To address this problem of human errors in HIPs, this thesis investigates two approaches for online process guidance, i.e., for guiding process performers while a process is being executed. Both approaches rely on monitoring a process execution and base the guidance they provide on a detailed formal process model that captures the recommended ways to perform the corresponding HIP. …