Operations Research, Systems Engineering and Industrial Engineering Commons^™

Automation Of Data Analysis In Formula 1, Adam Joseph Mourad, Prescott Jeanne Delzell, Patrick Conner Mccabe

Industrial and Manufacturing Engineering

This paper explores economic solutions for Formula 1 racing companies who are interested in data visualization tools. The research was conducted on the current development of data gathering, data visualization, and data interpretation in Formula 1 racing. It was found that a large chunk of racing companies within the league needs an affordable, effective, and automated visualization tool for data interpretation. As data collection in Formula 1 arises, the need for faster and more powerful software increases. Racing companies profit off-brand exposure and the more a racing team wins, the more exposure they receive. The goal of the paper focuses …

Simulation And Optimization Of A Multi-Agent System On Physical Internet Enabled Interconnected Urban Logistics., Long Zheng

Electronic Theses and Dissertations

An urban logistics system is composed of multiple agents, e.g., shippers, carriers, and distribution centers, etc., and multi-modal networks. The structure of Physical Internet (PI) transportation network is different from current logistics practices, and simulation can effectively model a series of PI-approach scenarios. In addition to the baseline model, three more scenarios are enacted based on different characteristics: shared trucks, shared hubs, and shared flows with other less-than-truckload shipments passing through the urban area. Five performance measures, i.e., truck distance per container, mean truck time per container, lead time, CO₂ emissions, and transport mean fill rate, are included in …

Extracting Patterns In Medical Claims Data For Predicting Opioid Overdose, Ryan Sanders

Graduate Theses and Dissertations

The goal of this project is to develop an efficient methodology for extracting features from time-dependent variables in transaction data. Transaction data is collected at varying time intervals making feature extraction more difficult. Unsupervised representational learning techniques are investigated, and the results compared with those from other feature engineering techniques. A successful methodology provides features that improve the accuracy of any machine learning technique. This methodology is then applied to insurance claims data in order to find features to predict whether a patient is at risk of overdosing on opioids. This data covers prescription, inpatient, and outpatient transactions. Features created …

Effects Of Resampled Data On Time Series Forecasting Accuracy, Jennifer Garland

Theses and Dissertations

This thesis will look at time series forecasting of the air pollutants in Beijing, China and the power consumption of an individual household located in Sceaux, France. The forecast will be taken from two classical methods, the Holt-Winters’ methods and the Seasonal Autoregressive Integrated Moving Average (SARIMA) method. The Holt-Winters’ method will be looked at from the additive, multiplicative and damped methods. The SARIMA model will be looked at as a uni-variate model. In this thesis, it will be shown that less complex algorithms, such as the Holt-Winters’ methods can process larger data sets without the need of resampling, and …

Correction To: Better Beware: Comparing Metacognition For Phishing And Legitimate Emails (Metacognition And Learning, (2019), 14, 3, (343-362), 10.1007/S11409-019-09197-5), Casey I. Canfield, Baruch Fischhoff, Alex Davis

Engineering Management and Systems Engineering Faculty Research & Creative Works

The article "Better beware: comparing metacognition for phishing and legitimate emails", written by Casey Inez Canfield, Baruch Fischhoff and Alex Davis, was originally published electronically on the publisher's internet portal (currently SpringerLink) on 20 July 2019 without open access.

Hedge Fund Replication Using Strategy Specific Factors, Sujit Subhash, David Lee Enke

Engineering Management and Systems Engineering Faculty Research & Creative Works

Hedge funds have traditionally served wealthy individuals and institutional investors with the promise of delivering protection of capital and uncorrelated positive returns irrespective of market direction, allowing them to better manage portfolio risk. However, the financial crisis of 2008 has heightened investor sensitivity to the high fees, illiquidity, lack of transparency, and lockup periods typically associated with hedge funds. Hedge fund replication products, or clones, seek to answer these challenges by providing daily liquidity, transparency, and immediate exposure to a desired hedge fund strategy. Nonetheless, although lowering cost and adding simplicity by using a common set of factors, traditional replication …

Predicting The Daily Return Direction Of The Stock Market Using Hybrid Machine Learning Algorithms, X. Zhong, David Lee Enke

Engineering Management and Systems Engineering Faculty Research & Creative Works

Big data analytic techniques associated with machine learning algorithms are playing an increasingly important role in various application fields, including stock market investment. However, few studies have focused on forecasting daily stock market returns, especially when using powerful machine learning techniques, such as deep neural networks (DNNs), to perform the analyses. DNNs employ various deep learning algorithms based on the combination of network structure, activation function, and model parameters, with their performance depending on the format of the data representation. This paper presents a comprehensive big data analytics process to predict the daily return direction of the SPDR S&P 500 …

A Case Study: The First Coastal Nuclear Decommissioning Project In California, Willie Aaron Quiros

Construction Management

San Onofre Nuclear Generating System (SONGS) is one of two nuclear power plants in California. Since the shut down in 2012, there is only one actively remaining, Diablo Canyon Nuclear Power Plant, which is set to shut down in 2024. This paper will examine the decommissioning of SONGS thus far; the first coastal nuclear decommissioning project in California’s stringent permitting process. This project was awarded as a joint venture to AECOM and Energy Solutions, both having experiencing in the field of nuclear decommissioning. This paper will outline what nuclear decommissioning challenges have been in the past; general steps of decommissioning …

Aisle Design For Order Picking Operations With Unit-Load Replenishment., Dominic Ian Sleigh

Electronic Theses and Dissertations

The warehouse design problem has been addressed in the last decade with fewer constraints than ever before. Between optimization for unit load and order picking warehouses, the former has had extensively more research performed. Unit load optimization efforts have promised labor savings of 20-22%. Of the existing research for order-picking warehouses, only small improvements of less than 4% have been claimed. We propose the design optimization for order-picking warehouses requires consideration for inherently incurred unit load operations from pallet inbound activities, as well as forward-pick area replenishment. We perform experiments comparing optimization of aisle design using order picking data with …

A Systematic Approach For Automatically Answering General-Purpose Objective And Subjective Questions, Lok Prasad Acharya

Theses and Dissertations

In this era of information explosion, people generally rely on the Internet, and more precisely, the search engines to get answers to their questions. However, what a search engine can do is just retrieve documents. Given some keywords, it only returns the relevant ranked documents that contain the keywords. Although users often want a precise answer to a question, they are left to extract answers from the documents themselves. This is where Automatic Question Answering (AQA) systems come into play. An AQA system takes questions in natural language as input and searches related answers in the set of documents and …

Uncertainty And Error In Combat Modeling, Simulation, And Analysis, Jason A. Blake

Theses and Dissertations

Due to the infrequent and competitive nature of combat, several challenges present themselves when developing a predictive simulation. First, there is limited data with which to validate such analysis tools. Secondly, there are many aspects of combat modeling that are highly uncertain and not knowable. This research develops a comprehensive set of techniques for the treatment of uncertainty and error in combat modeling and simulation analysis. First, Evidence Theory is demonstrated as a framework for representing epistemic uncertainty in combat modeling output. Next, a novel method for sensitivity analysis of uncertainty in Evidence Theory is developed. This sensitivity analysis method …

Better Beware: Comparing Metacognition For Phishing And Legitimate Emails, Casey I. Canfield, Baruch Fischhoff, Alex Davis

Engineering Management and Systems Engineering Faculty Research & Creative Works

Every electronic message poses some threat of being a phishing attack. If recipients underestimate that threat, they expose themselves, and those connected to them, to identity theft, ransom, malware, or worse. If recipients overestimate that threat, then they incur needless costs, perhaps reducing their willingness and ability to respond over time. In two experiments, we examined the appropriateness of individuals' confidence in their judgments of whether email messages were legitimate or phishing, using calibration and resolution as metacognition metrics. Both experiments found that participants had reasonable calibration but poor resolution, reflecting a weak correlation between their confidence and knowledge. These …

Effects Of Musical Ability On Flight Planning, Situational Awareness, And Flight Path Deviations, Andrew P. Henry

Doctoral Dissertations and Master's Theses

Numerous studies have been conducted on music education and the benefits that learning an instrument has on the brain. However, there is little research that connects a pilot’s ability to play an instrument to a pilot’s ability to fly an airplane. When learning an instrument, students learn non-musical abilities, such as executive functions, which may correspond with the skills necessary to be a good pilot. The purpose of this study was to find a relationship between learning a musical instrument and pilot performance, specifically related to flight planning, situational awareness, and flight path deviations. This study was a quasi-experimental design …

Assessing The Repeatability Of Clinical Tests In People With And Without Flexion-Induced Neck Pain, Ashton Human

Graduate Theses and Dissertations

The accessibility of mobile technology has improved productivity but can contribute to musculoskeletal disorders due to the posture associated with using such devices. Neck flexion, a posture assumed by smartphone users, has been shown as a risk factor for the development of clinical neck pain if sustained for prolonged periods. Determining the individuals who are naturally more predisposed to develop flexion-induced neck pain can aid in the prevention and treatment of musculoskeletal disorders. The purpose of this thesis is to assess the repeatability of clinical tests between trials over the course of two days in young adults who do and …

Optimizing Block-Stacking Operations With Relocation, Hueon Lee

Graduate Theses and Dissertations

The focus of the dissertation is developing the optimization problem of finding the minimum-cost operational plan of block stacking with relocation as well as devising a solution procedure to solve practical-sized instances of the problem. Assuming changeable row depth instead of permanent row depth, this research is distinguished from conventional block stacking studies.

The first contribution of the dissertation is the development of the optimization problem under the assumption of deterministic demand. The problem is modeled using integer programming as a variation of the unsplittable multi-commodity flow problem. To find a good feasible solution of practical-sized instances in reasonable time, …

Contributions Of Role-Playing Games: Advantages Of Incorporating Social Media In Disaster Response, Erin Mullin

Graduate Theses and Dissertations

After a disaster, emergency managers need to know who needs help, what type of help they need, and how soon they need it. Traditionally, they have relied on 911 calls and ground assessments to collect this information. Because the needs of a population are not able to be identified in a timely manner by ground assessments and because individuals are often unable to get through to 911, many civilians in distress turn to social media outlets as a last-ditch effort to obtain the services they need. Due to the uncertainty concerning the accuracy of social media posts, responding to disaster …

A Mathematical Programming Model For The Green Mixed Fleet Vehicle Routing Problem With Realistic Energy Consumption And Partial Recharges, Vincent F. Yu, Panca Jodiwan, Aldy Gunawan, Audrey Tedja Widjaja

Research Collection School Of Computing and Information Systems

A green mixed fleet vehicle routing with realistic energy consumption and partial recharges problem (GMFVRP-REC-PR) is addressed in this paper. This problem involves a fixed number of electric vehicles and internal combustion vehicles to serve a set of customers. The realistic energy consumption which depends on several variables is utilized to calculate the electricity consumption of an electric vehicle and fuel consumption of an internal combustion vehicle. Partial recharging policy is included into the problem to represent the real life scenario. The objective of this problem is to minimize the total travelled distance and the total emission produced by internal …

An Agent Based Model Of Passenger Boarding For Examining Commercial Aircraft Boarding Strategies, Frank W. Ciarallo, Raymond R. Hill, Kerry K. Ward

Faculty Publications

We use an agent-based simulation methodology to study airline passenger boarding using measures that reflect both the customer experience and airline efficiency perspective. This approach supports exploration of models of actual aircraft used in practice and detailed modeling of passenger dynamics. This paper discusses the modeling approach and a set of experiments comparing several boarding strategies from practical settings as well as the literature.

Improving Grapheme-To-Phoneme Translation With The Use Of Nalu Attention Mechanisms, Brian Sheldon Smith

Theses and Dissertations

In recent years, Natural Language Processing in the field of machine learning has seen some major improvements. Data scientists have shown that neural networks are capable of breaking down semantics of sentences, translating languages, and answering complex questions with fast recall. While impressive, these feats all hinge on having access to a massive amount of clean text, or data sets with almost perfect grammar and spelling. Without this, neural networks will usually fail to converge on a meaningful result. To partially this dependency, Grapheme-to-Phoneme conversion can be employed. This is the conversion of words from their spellings to a form …

Deep Brain Stimulation: Prediction Model For Volume Of Tissue Stimulated, Melissa Jones, Tarun Goswami

Biomedical, Industrial & Human Factors Engineering Faculty Publications

An attempt has been made to understand deep brain stimulation in humans via marketable devices that are approved by the US Food and Drug Administration. The electrode characteristics were presented to influence the volume of tissue stimulated. Experimental data were digitized and VTS data were presented a function of electrode diameter, aspect ratio, applied current, pulse duration, voltage and frequency. Amongst other trends voltage and VTS were found to exhibit a three-stage relation, where Stage II characteristics were represented by a linear equation. It is in this stage, the VTS was found to be stable and where the most effective …