Operations Research, Systems Engineering and Industrial Engineering Commons^™

A2s Uplink Latency Minimization For Wildfire Monitoring Systems Using Mbse And Stochastic Modeling, Luis Giovanni Wang

Master's Theses

Wildfire response depends on how quickly a detection reaches the people who act on it, and the slowest remaining step is often the link that carries an alert from a remote sensing platform to a satellite. This thesis models the latency of that link, the Air-to-Space uplink, for a wildfire-monitoring UAV that carries a Starlink terminal and sends an ALERT packet to a serving Low Earth Orbit satellite. The uplink is difficult to predict because both the UAV and the satellite move, and because the wildfire environment degrades the channel at the moment the data matters most.

The thesis uses …

Exploring The Effectiveness Of Virtual Reality Learning Through Use Of Visual Eye-Tracking Analytics (Veta) And Biological Measurements, Mckinley Anne Sherman

Master's Theses

Virtual Reality (VR) offers an immersive and interactive platform for experiential learning. The purpose of this thesis was to evaluate the relationship between physiological responses and cognitive workload within a VR learning environment and to explore VR as an effective instructional tool. This research compared participant engagement, stress, and learning performance within a 6th-grade science module developed in VR by incorporating biometric data collected via Polar H10 heart rate monitor and Varjo Areo VR headset eye-tracking. Thirty-three participants completed a pre-lesson demographic survey, post-lesson survey, VR sickness questionnaire, and the NASA Task Load Index (NASA-TLX). While completing the lesson, the …

Data-Driven Product Recommendations: A Decision Support Framework Utilizing Customer Reviews, Tyler A. Lopez

Master's Theses

With the considerable presence of e-commerce in society, vast number of purchasable goods, and increasing brand variety, consumers are faced with the challenge of buying products that they perceive to be of greatest value to them. To assist consumers with making better informed decisions, e-commerce websites allow individuals to post their own experiences and score the products that they purchase. Despite this information, the variety of experiences and feedback that consumers share do not always lead to clarity on whether a product is best suited for the purchaser. To help guide customers through a simplified purchasing process from the perspective …

A Data-Driven Framework For Analyzing And Predicting Social Media Engagement During Rumor Propagation, Joseph E. Faza

Master's Theses

The spread of rumors on social media has become a significant concern, as platforms like X (formerly known as Twitter) enable rapid dissemination of unverified information. These rumors can shape public perception and behavior, making it crucial to understand the dynamics of their spread. The main objective of this study is to explore how users interact with rumor-related tweets and identify key factors that predict tweet engagement. By analyzing tweets from seven different rumor events, this research aims to uncover patterns in user engagement and provide insights into the spread of misinformation. The study utilized a dataset of tweets from …

Application Of Agent-Based Simulation And Game Theory In Evaluating Implementation Of Whole Genome Sequencing In Treating Lung Cancer, Fateme Ghalenoei

Master's Theses

Cancer, particularly lung cancer, presents significant diagnostic and economic challenges globally. Timely diagnosis and cost management play pivotal roles in treatment success. A biomarker is any measurable molecule in blood, bodily fluids, or tissues, indicating the potential presence of an abnormal bodily process, condition, or disease. Biomarker testing is a laboratory test in oncology that is used in the selection of targeted cancer treatments and to help avoid ineffective treatments. Whole Genome Sequencing (WGS), is a biomarker test which while more comprehensive, comes at a higher cost. This study proposes an agent-based simulation model within a game-theoretic framework to examine …

A Screening Life Cycle Analysis Of One-Way And Reusable Crate Designs – Estimating Environmental Impacts Via Lca Software, Nicolas R. Corona

Master's Theses

A comparison analysis conducted via COMPASS life cycle analysis software has indicated that a one-way crate design, rather than a reusable crate design, is in fact the more environmentally friendly packaging system. These results can be interpreted differently, however, as the manufacturer of said crate designs must confirm what impact indicators they would like to reference as environmental goalposts. The conducted analysis provides insight into what the environmental impacts of each packaging system look like as packaging at all three system levels has been identified as a means of reducing environmental impacts globally. As such, the manufacturer of said crate …

Effective And Sustainable Strategies For Federally Qualified Health Centers To Engage Young Adults, Olivia Mcnulty

Master's Theses

Federally qualified health centers (FQHCs) are instrumental in providing top tier healthcare and other resources to underserved populations. Whether they administer services in house or refer patients to other providers, FQHCs aim to provide comprehensive primary and preventative care services to people of all ages. They offer a range of services, from doctor and dental appointments to mental health and substance abuse counseling, regardless of a patient’s insurance status. To receive funding, FQHCs must follow the regulations and quality standards set forth by groups like the Joint Commission on Accreditation of Healthcare Organizations (JCAHO) and the Health Resources and Services …

Predicting Rheology Of Uv-Curable Nanoparticle Ink Components And Compositions For Inkjet Additive Manufacturing, Cameron D. Lutz

Master's Theses

Inkjet additive manufacturing is the next step toward ubiquitous manufacturing by enabling multi-material printing that can exhibit various mechanical, electronic, and thermal properties. These characteristics are realized in the careful formulation of the inks and their functional materials, but there are many constraints that need to be satisfied to allow optimal jetting performance and build quality when used in an inkjet 3-D printer. Previous research has addressed the desirable rheology characteristics to enable stable drop formation and how the metallic nanoparticles affect the viscosity of inks. The contending goals of increasing nanoparticle-loading to improve material deposition rates while trying to …

Cost-Risk Analysis Of The Ercot Region Using Modern Portfolio Theory, Megan Sickinger

Master's Theses

In this work, we study the use of modern portfolio theory in a cost-risk analysis of the Electric Reliability Council of Texas (ERCOT). Based upon the risk-return concepts of modern portfolio theory, we develop an n-asset minimization problem to create a risk-cost frontier of portfolios of technologies within the ERCOT electricity region. The levelized cost of electricity for each technology in the region is a step in evaluating the expected cost of the portfolio, and the historical data of cost factors estimate the variance of cost for each technology. In addition, there are several constraints in our minimization problem to …

Trace Dna Detection Using Diamond Dye: A Recovery Technique To Yield More Dna, Leah Davis

Master's Theses

This study aspires to find a new screening approach to trace DNA recovery techniques to yield a higher quantity of trace DNA from larger items of evidence. It takes the path of visualizing trace DNA on items of evidence with potential DNA so analysts can swab a more localized area rather than attempting to recover trace DNA through the general swabbing technique currently used for trace DNA recovery. The first and second parts consisted of observing trace DNA interaction with Diamond Dye on porous and non-porous surfaces.

The third part involved applying the Diamond Dye solution by spraying it onto …

Rattus Norvegicus As A Biological Detector Of Clandestine Remains And The Use Of Ultrasonic Vocalizations As A Locating Mechanism, Gabrielle M. Johnston

Master's Theses

In investigations, locating missing persons and clandestine remains are imperative. One way that first responder and police agencies can search for the remains is by using cadaver dogs as biological detectors. Cadaver dogs are typically used due to their olfactory sensitivity and ability to detect low concentrations of volatile organic compounds produced by biological remains. Cadaver dogs are typically chosen for their stamina, agility, and olfactory sensitivity. However, what is not taken into account often is the size of the animal and the expense of maintaining and training the animal. Cadaver dogs are typically large breeds that cannot fit in …

The Rise Of Terrorism In Africa And What It Means For U.S. Policymakers, Bridget Mary Hughes

Master's Theses

This thesis utilizes three case studies to measure the rise of terrorism in Africa. This qualitative data leads the reader to one ultimate question: what does the rise in terrorism in Africa mean for the United States (U.S.) and U.S. policymakers, National Security academia, students in National Security, if anything at all? The answer is: if civilian and military compounds are being targeted by these violent extremists, as these three case studies demonstrate, it is my recommendation that U.S. policymakers cease sending troops to the African theater and, instead, allocate funding to the citizens and nonprofits of the countries whom …

Simulating Electric Vehicle Short-Notice Wildfire Evacuation In California Rural Communities, Gudrun Derickson

Master's Theses

The transportation sector in California has begun a shift toward adopting Electric Vehicles (EVs) as a primary source of individual and corporate mobility. The US Government and the State of California are initiating public-sector financed charging station infrastructure to help in this change-over to EVs. Automobile companies and private enterprises are also heavily investing in Battery Electric Vehicle (BEV) infrastructure going forward. The state of California is subject to natural disasters such as Fire, Earthquakes, and periodic flooding. Increasing numbers of BEVs may add new challenges to mass evacuations that are often associated with natural disasters. This work focuses on …

Subnational Map Of Poverty Generated From Remote-Sensing Data In Africa: Using Machine Learning Models And Advanced Regression Methods For Poverty Estimation, Lionel N. Hanke

Master's Theses

According to the 2020 poverty estimates from the World Bank, it is estimated that 9.1% - 9.4% of the global population lived on less than $1.90 per day. It is estimated that the Covid-19 pandemic further aggravated the issue by pushing more than 1% of the global population below the international poverty line of $1.90 per day (WorldBank, 2020). To provide help and formulate effective measures, poverty needs to be located as exact as possible. For this purpose, it was investigated whether regression methods with aggregated remote-sensing data could be used to estimate poverty in Africa. Therefore, five distinct regression …

Minimizing Leakage In Thin Walled Structures Printed Through Selective Laser Melting, Andrew Spencer Yap

Master's Theses

In this project, the scan strategy of selective laser melting (SLM) for thin walled structures was investigated by changing laser parameters and tool path. Producing thin walled structures is difficult due to defects such as warpage and porosity. A layer on the SLM 125 consists of hatch volume, fill contours, and borders, however, for thin walls, hatch volume can become unavailable, resulting in a solely border/fill contour laser tool path.

Three central composite designs (CCD) were created to optimize the laser parameters of borders to minimize leakage rate and porosity. The two factors changed were border laser power and scanning …

Modeling And Solving The Outsourcing Risk Management Problem In Multi-Echelon Supply Chains, Arian A. Nahangi

Master's Theses

Worldwide globalization has made supply chains more vulnerable to risk factors, increasing the associated costs of outsourcing goods. Outsourcing is highly beneficial for any company that values building upon its core competencies, but the emergence of the COVID-19 pandemic and other crises have exposed significant vulnerabilities within supply chains. These disruptions forced a shift in the production of goods from outsourcing to domestic methods.

This paper considers a multi-echelon supply chain model with global and domestic raw material suppliers, manufacturing plants, warehouses, and markets. All levels within the supply chain network are evaluated from a holistic perspective, calculating a total …

Perishable Food Waste Reduction Through Technological Implementation At The Retail Level Of The Food Supply Chain, Cassandra Harriman

Master's Theses

Food waste has become a disaster of global proportion that the world can no longer turn a blind eye to. This paper aims to reduce food waste at the retail level of the food supply chain by recommending and quantifying the effects of current technology that can be implemented in traditional supermarkets. This research recommends that retailers implement electronic shelf labels in stores and employ dynamic pricing of perishable products, leading to reduction of food waste. No prior research had considered the primary goal of reducing food waste while preserving retailer profit through technological implementation. This paper quantifies the effects …

Transfer Learning Approach To Powder Bed Fusion Additive Manufacturing Defect Detection, Michael Wu

Master's Theses

Laser powder bed fusion (LPBF) remains a predominately open-loop additive manufacturing process with minimal in-situ quality and process control. Some machines feature optical monitoring systems but lack automated analytical capabilities for real-time defect detection. Recent advances in machine learning (ML) and convolutional neural networks (CNN) present compelling solutions to analyze images in real-time and to develop in-situ monitoring.

Approximately 30,000 selective laser melting (SLM) build images from 31 previous builds are gathered and labeled as either “okay” or “defect”. Then, 14 open-sourced CNN were trained using transfer learning to classify the SLM build images. These models were evaluated by F1 …

Understanding The Impact Of The Covid-19 Pandemic Within Educational Communities Using Longitudinal Analysis, Alexa Steidl

Master's Theses

At California State University, Los Angeles and California Polytechnic University, San Luis

Obispo, a longitudinal survey was created in response to the COVID-19 pandemic for students within their respective engineering departments. A combination of nonparametric and longitudinal analysis is performed to evaluate the impacts of the transition to a virtual educational environment and the stressors brought on by the global pandemic. Additional qualitative evaluation is performed to gain insight and make program recommendations to enhance the resilience of individuals in the academic systems. Results demonstrate a large shift in circumstances immediately at the start of the pandemic, with a variety …

A Method For Visualizing The Structural Complexity Of Organizational Architectures, Jacob Michael B. King

Master's Theses

To achieve a high level of performance and efficiency, contemporary aerospace systems must become increasingly complex. While complexity management traditionally focuses on a product’s components and their interconnectedness, organizational representation in complexity analysis is just as essential. This thesis addresses this organizational aspect of complexity through an Organizational Complexity Metric (OCM) to aid complexity management. The OCM augments Sinha’s structural complexity metric for product architectures into a metric that can be applied to organizations. Utilizing nested numerical design structure matrices (DSMs), a compact visual representation of organizational complexity was developed. Within the nested numerical DSM are existing organizational datasets used …

Operational Decision-Making In Healthcare Using Control Charts, Rohan More

Master's Theses

The primary objective of this thesis was to design a framework supplemented with guidelines for the healthcare managers to select an appropriate type of control chart for operational decision-making. A systematic literature review was conducted to gauge the extent to which control charts were being used in a healthcare setting for clinical decision making and operational decision-making purposes. The findings showed that the application of control charts was almost equal for the clinical decision-making sector and the operational decision-making sector. On further analysis, the ability of control charts to function as a standalone tool was affirmed by the vast majority …

Comparison Of Classification Algorithms And Undersampling Methods On Employee Churn Prediction: A Case Study Of A Tech Company, Heather Cooper

Master's Theses

Churn prediction is a common data mining problem that many companies face across industries. More commonly, customer churn has been studied extensively within the telecommunications industry where there is low customer retention due to high market competition. Similar to customer churn, employee churn is very costly to a company and by not deploying proper risk mitigation strategies, profits cannot be maximized, and valuable employees may leave the company. The cost to replace an employee is exponentially higher than finding a replacement, so it is in any company’s best interest to prioritize employee retention.

This research combines machine learning techniques with …

Combining Machine Learning And Empirical Engineering Methods Towards Improving Oil Production Forecasting, Andrew J. Allen

Master's Theses

Current methods of production forecasting such as decline curve analysis (DCA) or numerical simulation require years of historical production data, and their accuracy is limited by the choice of model parameters. Unconventional resources have proven challenging to apply traditional methods of production forecasting because they lack long production histories and have extremely variable model parameters. This research proposes a data-driven alternative to reservoir simulation and production forecasting techniques. We create a proxy-well model for predicting cumulative oil production by selecting statistically significant well completion parameters and reservoir information as independent predictor variables in regression-based models. Then, principal component analysis (PCA) …

Design Of A Printed Circuit Board For A Sensorless Three-Phase Brushless Dc Motor Control System, Joshua Castle

Master's Theses

The use of brushless motors has increased in recent years due to superior performance characteristics compared with alternatives. The operation of a brushless motor is dependent upon a separate controller which is often in the form of a printed circuit board. As such, the size and performance capability of the controller can restrict the performance of the overall motor control system so advancements of these controllers further the potential use of BLDC motors. This project outlines the design of a PCB based, sensorless motor controller for operation of a three-phase BLDC motor powered by a 24 V, high current external …

Machine Learning Applications To Predict Road Crash And Soccer Game Outcomes, Lu Bai

Master's Theses

Machine learning has become a cutting-edge and widely studied data science field of study in recent years across many industries and disciplines. In this thesis, two problems (1- crash severity prediction, 2- soccer game outcome prediction.) were investigated by using a set of machine learning approaches, namely: Ridge regression, Lasso Regression, Support Vector Machine (SVM), Neural Network (NN), Random Forest (RF).

The first study is focused on investigating the critical factors affecting crash severity on a comprehensive time-series state-wide traffic crash data. The dataset covers crashes occurred in the state of Connecticut between 1995 and 2014. Traffic crashes are an …

Resource-Constrained Project Scheduling With Autonomous Learning Effects, Jordan M. Ticktin

Master's Theses

It's commonly assumed that experience leads to efficiency, yet this is largely unaccounted for in resource-constrained project scheduling. This thesis considers the idea that learning effects could allow selected activities to be completed within reduced time, if they're scheduled after activities where workers learn relevant skills. This paper computationally explores the effect of this autonomous, intra-project learning on optimal makespan and problem difficulty. A learning extension is proposed to the standard RCPSP scheduling problem. Multiple parameters are considered, including project size, learning frequency, and learning intensity. A test instance generator is developed to adapt the popular PSPLIB library of scheduling …

Direct Assessment Of Entrepreneurial Minded Learning Through Integrated E-Learning Modules, Aadtiyasinh Rana

Master's Theses

Entrepreneurial Minded Learning (EML) has a significant emphasis in engineering education

today. Several approaches have been used to assess the impact of various EML approaches. Many indirect assessment techniques have been used and a few direct assessment techniques have been developed. The work presented in this thesis investigates the effectiveness of two specific measurement methods to quantify entrepreneurial minded learning in students.

The University of New Haven has adopted the approach of integrating e-learning modules on entrepreneurial topics and related contextual activities into courses as the primary approach of developing an entrepreneurial mindset (EM) in students. This study focuses on …

Application Of Big Data Analytics In Agriculture Supply Chain Management, Sankara Narayanan Mangalam Ananthapadmanabhan

Master's Theses

The increasing trend in frequency of natural disasters in tandem with globalization of business makes the agricultural supply chain significantly vulnerable to disruption. This thesis presents a pragmatic approach for creating a Business Continuity Model that can notify supply chain planners when there is an increase in risk of agriculture supply chain disruption due to natural disasters. The methodology presented in this thesis applied big data analytics and machine learning algorithms along with agriculture product related exponential decay function to create a regionalized composite risk score, that incorporated both direct and indirect risk associated with the Agriculture Fresh Supply Chain. …

Characterization Of Resistance Change In Stretchable Silver Ink Screen Printed On Tpu-Laminated Fabrics Under Cyclic Tensile Loading, Corey R. Sutton

Master's Theses

A stretchable silver ink was screen printed to TPU sheets, then tensile coupons of the TPU, both bare and laminated to cotton, Denim and spandex fabric, were subjected to 1000 cycles of 20% uniaxial strain. In-situ resistance measurements of printed traces were processed to generate datasets of maximum and minimum resistance per cycle. A mechanistic fit model was used to predict the resistance behavior of the ink across TPU/fabric levels. The results show that traces strained on TPU laminated to spandex (polyester) fibers had an average rate of increase in resistance significantly lower than that of traces strained on bare …

Benchmarking Oecd Countries’ Sustainable Development Performance: A Goal-Specific Pca Approach, Shyam Lamichhane

Master's Theses

In this thesis, the current status of the Organisation for Economic Co-operation and Development (OECD) countries’ sustainable development performance towards reaching the recently announced 2030 Agenda (17 UN Sustainable Development Goals (SDGs)) was investigated. Over 90 social, economic and environmental sustainability indicators were considered for the performance assessment of OECD countries towards reaching the targeted SDGs. The current weighted averaging approach used in the recent SDG Index and Dashboards Report was used as the benchmark and its limitations were discussed. To overcome the limitations, a novel Goal Specific Principal Component Analysis (GS-PCA) approach was proposed to create composite sustainability index …