Engineering Commons^™

Fixed-Wing Uav Detection Based On Simulated Data Transfer Learning, Yu Fu, Yao Zhang, Meng Zhao, Mianzhao Wang, Jiangpeng Zheng, Chen Jia, Shengyong Chen

Journal of System Simulation

Abstract: Data play an important role in visual inspection tasks, but it is difficult to obtain a sufficient amount of real fixed-wing UAV data. Therefore, a data set containing a large number of simulated fixed-wing UAV data and a small number of real fixed-wing UAV data is constructed, and the real fixed-wing UAV data are detected by training simulated fixed-wing UAV data based on the idea of weight transfer. On this basis, a two-stage learning strategy is proposed to further reduce the missed detection rate of UAVs by using multi-scale feature fusion.The simulation results show that …

Research On No-Wait Flow Shop Scheduling Based On Discrete State Transition Algorithm, Jiaying Yu, Hongli Zhang, Yingchao Dong

Journal of System Simulation

Abstract: In view of the no-wait flow shop problem (NWFSP) widely existing in the manufacturing industry, an improved discrete state transition algorithm (IDSTA) is proposed to solve the problem. The coding mode of the workpiece is designed based on the characteristics of the flow shop scheduling problem (FSSP). The initial solution is constructed by the Nawaz-Enscore-Ham (NEH) method with the standard deviation of the processing time of the workpiece as the priority, and a multi-neighborhood combinatorial search strategy based on insertion and exchange is designed to improve the quality of the initial solution. A discrete state transition algorithm ( …

Action Recognition Method Based On Projection Subspace Views Under Single Viewing Angle, Benyue Su, Manzhen Sun, Qing Ma, Min Sheng

Journal of System Simulation

Abstract: In view of the self-occlusion problem of joint action tracking by a depth camera under a single viewing angle, a new human action recognition method based on projection subspace views is proposed. Without adding data acquisition equipment, the method projects the three-dimensional(3D) action sequences obtained under a single viewing angle into multiple two-dimensional subspacesand then seeks the maximum distance between classes in the two-dimensional subspaces, so as to increase the distance between 3D actions based on the fusion of multiple subspace views as much as possible. The recognition rate in the self-built AQNU …

Experimental And Numerical Behavior Of Encased Pultruded Gfrp Beams Under Elevated And Ambient Temperatures, Enas M. Mahmood, Teghreed H. Ibrahim, Abbas A. Allawi, Ayman El-Zohairy

Faculty Publications

In this research, experimental and numerical studies were carried out to investigate the performance of encased glass-fiber-reinforced polymer (GFRP) beams under fire. The test specimens were divided into two peer groups to be tested under the effect of ambient and elevated temperatures. The first group was statically tested to investigate the monotonic behavior of the specimens. The second group was exposed to fire loading first and then statically tested to explore the residual behavior of the burned specimens. Adding shear connectors and web stiffeners to the GFRP beam was the main parameter in this investigation. Moreover, service loads were applied …

Data-Driven Platform And Digital Operations, Bing Bai

Olin Business School Graduate Student Theses and Dissertations

The objective of this dissertation is to study the emerging operations issues on data-driven platforms and digital operations. With the increasing availability of data and the development of information technologies, platforms process a large amount of data in order to efficiently make daily operational decisions. Understanding human behaviors and the human-algorithm connection is instrumental to the success of this process. In my research, I implement field experiments and use structural models to study in-warehouse worker behavior and out-of-warehouse customer behavior in the last mile of logistics.

In Chapter 1, “The Impacts of Algorithmic Work Assignment on Fairness Perceptions and Productivity: …

Passive Vs. Active Wearable Technology Monitoring Trunk Flexion In Elementary Teachers, Bailey Jose

Theses and Dissertations

The objective of this study was to assess the biomechanical and subjective measures of elementary school teachers while wearing active and/or passive wearable devices during the average workday. Five elementary school teachers wore a harness that held an Upright GO 2 posture tracking device and a Vicon Blue Trident sensor on the participant's upper back for two school days. Haptic feedback was on for one day and off for the other. Data from the Vicon wearable was analyzed to determine participants’ trunk flexion severity, frequency, and duration. Surveys were used to determine perceived exertion and perception of wearable technology. This …

Adaptive Large Neighborhood Search Algorithm – Performance Evaluation Under Parallel Schemes & Applications, Sandip Kumar

Theses and Dissertations

Adaptive Large Neighborhood Search (ALNS) is a fairly recent yet popular single-solution heuristic for solving discrete optimization problems. Even though the heuristic has been a popular choice for researchers in recent times, the parallelization of this algorithm is not widely studied in the literature compared to the other classical metaheuristics. To extend the existing literature, this study proposes several different parallel schemes to parallelize the basic/sequential ALNS algorithm. More specifically, seven different parallel schemes are employed to target different characteristics of the ALNS algorithm and the capability of the local computers. The schemes of this study are implemented in a …

A Generalizable Method And Case Application For Development And Use Of The Aviation Systems – Trust Survey (As-Ts)., Jamison Hicks

Theses and Dissertations

Automated systems are integral in the development of modern aircraft, especially for complex military aircraft. Pilot Trust in Automation (TIA) in these systems is vital for optimizing the pilot-vehicle interface and ensuring pilots use the systems appropriately to complete required tasks.

The objective of this research was to develop and validate a TIA scale and survey methodology to identify and mitigate trust deficiencies with automated systems for use in Army Aviation testing. There is currently no standard TIA assessment methodology for U.S. Army aviation pilots that identifies trust deficiencies and potential mitigations.

A comprehensive literature review was conducted to identify …

Developing Systems Engineering And Machine Learning Frameworks For The Improvement Of Aviation Maintenance, Fatine Elakramine

Theses and Dissertations

This dissertation develops systems engineering and machine learning models for aviation maintenance support. With the constant increase in demand for air travel, aviation organizations compete to maintain airworthy aircraft to ensure the safety of passengers. Given the importance of aircraft safety, the aviation sector constantly needs technologies to enhance the maintenance experience, ensure system safety, and limit aircraft downtime. Based on the current literature, the aviation maintenance sector still relies on outdated technologies to maintain aircraft maintenance documentation, including paper-based technical orders. Aviation maintenance documentation contains a mixture of structured and unstructured technical text, mainly inputted by operators, making them …

An Online Adaptive Machine Learning Framework For Autonomous Fault Detection, Nolan Coulter

Doctoral Dissertations and Master's Theses

The increasing complexity and autonomy of modern systems, particularly in the aerospace industry, demand robust and adaptive fault detection and health management solutions. The development of a data-driven fault detection system that can adapt to varying conditions and system changes is critical to the performance, safety, and reliability of these systems. This dissertation presents a novel fault detection approach based on the integration of the artificial immune system (AIS) paradigm and Online Support Vector Machines (OSVM). Together, these algorithms create the Artificial Immune System augemented Online Support Vector Machine (AISOSVM).

The AISOSVM framework combines the strengths of the AIS and …

Routing Battery-Constrained Delivery Drones In A Depot Network: A Business Model And Its Optimization-Simulation Assessment, Yanchao Liu

Industrial and Systems Engineering Faculty Research Publications

This paper proposes a novel business model for on-demand package shipment services using drones, and evaluates different modeling and solution approaches for the drone routing problem that underpins the service operation. In the proposed service, customers’ shipment orders of arbitrary origins and destinations, payload weights and bid values are collected every five minutes, and available drones from multiple depots are then dispatched to fulfill a subset of these orders in a way to maximize profit. A drone path starts from a depot, serves one or more customer orders in sequence, and ends at a depot for battery recharging, which incurs …

Detecting Pathobiomes Using Machine Learning, Valerie Jackson, Valerie Jackson

Industrial Engineering Undergraduate Honors Theses

Machine learning is a field with high growth potential due to the overall continuous progressions, developments, advancements, and improvements caused by the way it is used to help interpret and use large amounts of data [1]. One type of data that can be collected and analyzed by these machine learning models is data that is associated with DNA and information that the DNA gives. The research will be focusing specifically on using machine learning technology to detect pathobiomes indicative of salmonella pork. The pathobiome associated with salmonella is very similar to others, and this causes a problem for classification/detection with …

Optimizing Wedding Venue Selection Process Using Integer Programming, Luis Rodriguez

Theses/Capstones/Creative Projects

Choosing the right wedding venue can be extremely difficult for the unsuspecting engaged couple. There is a myriad of variables that must be taken into account prior to the illustrious wedding date; these variables include the option for a reception, the location, and food requirements, to name a few. Consequently, the typical couple seems to spend multiple months researching and visiting many wedding spaces. However, even though months go into planning, it still is not a guarantee that all variables are accounted for. Furthermore, without a wedding planner, these couples may second-guess their chosen site due to seemingly arduous issues …

Automated Visualization Pipeline For Near Real-Time Risk Management System, Paris Joslin

Industrial Engineering Undergraduate Honors Theses

In modern society, technological capabilities and the amount of data readily available to users continue to grow exponentially. Many have adopted these new capabilities but lack the infrastructure needed to efficiently utilize high-powered software and programs. Without a method to collect, store, and process large datasets in real-time, individuals and businesses can quickly become overwhelmed, inhibiting effective decision-making processes. There is potential to improve decision-making abilities by enhancing the computing infrastructure. To accomplish this task, we will explore the ideas surrounding High Performance Computing (HPC) and data visualization software. High Performance Computing is the ability to process data and perform …

Machine Learning For Ultraviolet Spectral Prediction, Linh Ho Manh

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

Machine Learning has found wide applications in material science, including dielectric polymers, superconducting materials, and drug property prediction. The use of data analytics and machine learning methods to predict Vacuum Ultraviolet (VUV) spectra by encoding molecular structure is gaining interest because high-quality VUV spectral prediction capability would enable the study of new molecules without costly wet-lab measurements. This dissertation aims to study feature representations for molecular structures that enhance the prediction of VUV spectra via machine learning models. Both interpretable machine learning and deep learning are studied. Chapter 1 provides an overview of VUV/UV spectra retrieval, and Chapter 2 reviews …

Testing The Effects Of Different Designs On The Physical Properties Of 3d-Printed Watch Bands, Ross Harper

Industrial Engineering Undergraduate Honors Theses

Technological innovation progresses at an ever-increasing rate, and this is especially true in the field of 3D-printing. 3D-printing has become popular in manufacturing settings and among amateur hobbyists alike, largely because 3D-printers can fabricate an enormous number of designs from an array of materials and allow for fine-tuning through several setting options. Individuals with proficient 3D-printing abilities can produce a nearly infinite number of components for diverse applications in manufacturing, recreation, ergonomics, and many more. Some individuals use their skills to create functional substitutes for name-brand items, including bands to fit and be worn with a smart watch. However, little …

Lead Distribution Modeling For Supply Chains With A Large Number Of Items, Wesley Tate

Industrial Engineering Undergraduate Honors Theses

Adding randomness into a simulation model allows for a better understanding of the variation that can occur in a real-life setting. This paper documents the methodology used to recommend a set of distribution models to cover administrative and production lead times for the simulation program involving hundreds of thousands of items. The problem of distribution fitting for large datasets is addressed, with histograms, Q-Q, and P-P plots being used to verify models in addition to goodness-of-fit test statistics. Variable level reduction using frequency and distribution matching approaches are outlined followed by the use of random forest modeling to identify key …

Network Effects Of Emergency Department Clinician Strain And Patient Congestion, Aisha Nelson

All Theses

We develop a discrete-event simulation model to study how staffing strain affects patient outcomes across a network of Emergency Departments (EDs). The aim is to observe how clinician staffing and transfers throughout the system affect the system’s behavior. We will study the network of the seven EDs in the Prisma Health-Upstate system. Patient acuity and resource need are stratified using the five-level Emergency Severity Index (ESI). Patient flow data within and between EDs are collected from EPIC, staffing data from ShiftAdmin, and environmental COVID-19 prevalence data from the Department of Health and Environmental Control. Time periods include the Omicron wave …

The Impact Of A Carbon Tax On Emissions, Jessica Creech

Industrial Engineering Undergraduate Honors Theses

A carbon tax is an economic policy that aims to reduce various emissions to serve the protection of the environment. Versions of this policy have been implemented in multiple countries across the world to introduce a cost for contributing to environmental damage. Since climate change is prevalent in today’s world, finding an effective method to reduce emissions is essential. However, many countries hesitate to utilize a carbon tax for two reasons. First, they are unsure if the carbon tax is effective at reducing emissions. Second, there is a concern that the implementation of such a tax will be detrimental to …

Design And Development Of A Virtual Reality Training Platform For Fiber-Reinforced Composite Manufacturing, Taufiq Rahman

Industrial, Manufacturing, and Systems Theses - Archive

This study presents the design and development of a virtual reality (VR) training platform for manufacturing fiber-reinforced composites, a sophisticated and high-demand material in various industries. Due to the high costs and safety concerns associated with compression molding machines - essential equipment for this manufacturing process, the VR platform offers a promising alternative for training to educational institutions and manufacturing industries. The platform provides an immersive, interactive training and cost-efficient learning environment, allowing users to gain practical experience without the risks and expenses of physical training. The VR training module was developed using the Unity game engine and deployed on …

Evaluating The Impact Of Broadband Access And Internet Use In A Small Underserved Rural Community, Javier Valentín-Sívico, Casey I. Canfield, Sarah A. Low, Christel Gollnick

Engineering Management and Systems Engineering Faculty Research & Creative Works

Having adequate access to the internet at home enhances quality-of-life for households and facilitates economic and social opportunities. Despite increased investment in response to the COVID-19 pandemic, millions of households in the rural United States still lack adequate access to high-speed internet. In this study, we evaluate a wireless broadband network deployed in Turney, a small, underserved rural community in northwest Missouri. In addition to collecting survey data before and after this internet intervention, we collected pre-treatment and post-treatment survey data from comparison communities to serve as a control group. Due to technical constraints, some of Turney's interested participants could …

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 …

Sealion Cubesat Mission Architecture Using Model Based Systems Engineering With A Docs As Code Approach, Kevin Yi-Tzu Chiu

Mechanical & Aerospace Engineering Theses & Dissertations

CubeSats are a growing population within the space industry. Every year, universities launch numerous amounts of CubeSats due to their inexpensive cost of development, launch, and deployment. However, this comes with numerous challenges. As the number of university-CubeSats grow, so too do the numbers that fail. With development teams consisting mainly of students with little to no training, proper and yet easy to use tools or methods should be implemented to help ensure mission success. Especially in the critical stages of planning before and during development, a technical approach to quickly track life cycle development of a CubeSat is needed. …

Human Psychology Factors Influencing Agile Team Autonomy In Post-Pandemic Remote Software Organizations, Ravikiran Kalluri

Engineering Management & Systems Engineering Theses & Dissertations

Agile project management methods are gaining in popularity in the software industry as software development teams are being asked to be adaptive to market needs and resilient to change and uncertainty. With increasing market uncertainty, global competition, and time-to-market pressure, it is becoming a challenge to develop an innovative product and deliver it on-time without the opportunity that comes from team autonomy to experiment and learn from failures in a remote workplace. To resolve this challenge, it is critical to understand the myriad human psychological factors in play that influence Agile team autonomy in a remote work environment.

The role …

Editorial: Innovative Shared Transportation, Marco Nie, Hai Wang, Wai Yuen Szeto

Research Collection School Of Computing and Information Systems

Recent technological developments—mobile computing, autonomous driving, alternative fuel vehicles, and blockchain, to name a few—have enabled numerous innovations in mobility, transportation, and logistics services. They offer unprecedented opportunities to transform conventional transportation systems, for both personal travel and freight logistics, with novel solutions. Of these solutions, those built on the emerging concept of shared economy, such as Uber, Didi, and Cargostream, have received much attention recently. The rapidly expanding scope of shared transportation services now includes ride-sourcing, ridesharing, car sharing, hitch service, flexible paratransit, shared freight delivery, shared logistics, bike sharing, shared last-mile service, parking space sharing, and so on.

Interaction Effects And Selecting Regression Models Of Taylor Swift Song Popularity, Halle Schneidewind

Industrial Engineering Undergraduate Honors Theses

Understanding music popularity and what drives it is important not only for artists but for other individuals who are financially tied to music sales including producers, writers, and record labels. Studies have been done to define how a song’s popularity can be measured, what attributes or features are drivers for popularity, and to what extent can a song’s popularity even be predicted. This paper takes two linear regression approaches to predicting the popularity of a Taylor Swift song on Spotify based on auditory features the Spotify API estimates and historic popularity of songs on Spotify. One model takes into consideration …

Mapping Information Flows That Support Adaptive Capacity In The Sterile Processing Department (Spd), Jacob Hionis

All Theses

The Sterile Processing Department (SPD) is the part of the hospital that is responsible for decontaminating, assembling, and sterilizing surgical trays for use in the Operating Rooms (ORs). Errors in the SPD can lead to delayed surgeries or patient harm. The SPD is a complex system, with multiple interconnected subdepartments and roles. Complex systems require coordination between stakeholders. This study aims to discover how an organization can adapt to scale, and how information flows support these adaptations. In this study, observations, semi-structured interviews, and on-the-job interviews were conducted with members across the SPD and OR to elicit pressures, adaptations, and …

Demand Prediction And Inventory Management Of Surgical Supplies, Rajon Paul Pantha

Graduate Theses and Dissertations

Effective supply chain management is critical to operations in various industries, including healthcare. Demand prediction and inventory management are essential parts of healthcare supply chain management for ensuring optimal patient outcomes, controlling costs, and minimizing waste. The advances in data analytics and technology have enabled many sophisticated approaches to demand forecasting and inventory control. This study aims to leverage these advancements to accurately predict demand and manage the inventory of surgical supplies to reduce costs and provide better services to patients. In order to achieve this objective, a Long Short-Term Memory (LSTM) model is developed to predict the demand for …

Challenges, Limitations, And Strengths For An Optimal Predictive Maintenance Application, Erick Armando Rosales

Open Access Theses & Dissertations

Industry 4.0, the fourth industrial revolution, has emerged as the most recent digital transformation worldwide, expanding and reshaping the manufacturing industry by introducing novel technologies. In Industry 4.0, Smart Manufacturing (SM) and the Internet of Things (IoT) have collaborated to bring the best of both worlds and make the new manufacturing era more cost-effective, automated, and digitized. As a result, many businesses are putting sensors, intricate networks of integrated systems, big data analytics, cloud computing, and storage in place to use predictive maintenance (PdM) best. PdM uses IoT to convert physical activities into digital activities, also known as digitization. Predictive …

Cyber-Physical Production Systems And Their Practical Integration And Application With Simio Software, Jose Carlos Garcia Marquez Basaldua

Open Access Theses & Dissertations

Industry 4.0 comprises a diverse array of technologies and components that are revolutionizing the manufacturing industry, from Digital Twins, Cyber-Physical Systems and Augmented Reality. The elements that englobe Industry 4.0 vary from framework to framework. Nevertheless, there are similarities in the available literature on what constitutes Industry 4.0. Some of the most critical components specified by the available literature include Digital Twins and Cyber-Physical Systems. A Factory Digital Twin is a virtual representation of a production system that can mimic the behavior of the physical asset. Moreover, a digital twin must have synchronization with its physical twin (i.e., production floor), …