Operations Research, Systems Engineering and Industrial Engineering Commons^™

Railroad Condition Monitoring Using Distributed Acoustic Sensing And Deep Learning Techniques, Md Arifur Rahman

Electronic Theses and Dissertations

Proper condition monitoring has been a major issue among railroad administrations since it might cause catastrophic dilemmas that lead to fatalities or damage to the infrastructure. Although various aspects of train safety have been conducted by scholars, in-motion monitoring detection of defect occurrence, cause, and severity is still a big concern. Hence extensive studies are still required to enhance the accuracy of inspection methods for railroad condition monitoring (CM). Distributed acoustic sensing (DAS) has been recognized as a promising method because of its sensing capabilities over long distances and for massive structures. As DAS produces large datasets, algorithms for precise …

Comparative Analysis Of Fullstack Development Technologies: Frontend, Backend And Database, Qozeem Odeniran

Electronic Theses and Dissertations

Accessing websites with various devices has brought changes in the field of application development. The choice of cross-platform, reusable frameworks is very crucial in this era. This thesis embarks in the evaluation of front-end, back-end, and database technologies to address the status quo. Study-a explores front-end development, focusing on angular.js and react.js. Using these frameworks, comparative web applications were created and evaluated locally. Important insights were obtained through benchmark tests, lighthouse metrics, and architectural evaluations. React.js proves to be a performance leader in spite of the possible influence of a virtual machine, opening the door for additional research. Study b …

Human-Machine Collaboration In Healthcare Innovation, Breeze Fenton

Electronic Theses and Dissertations

Almost every individual has visited a healthcare institute, whether for an annual checkup, surgery, or a nursing home. Ensuring healthcare institutes are using human-machine collaboration systems correctly can improve daily operations. A maturity assessment and an implementation plan have been developed to help healthcare institutes monitor the human-machine collaboration systems. A maturity model, the Smart Maturity Model for Health Care (SMMHC), is a tool designed for maturity assessment. A four-step implementation plan was also created in this research. The implementation plan views the maturity of the institute and develops a strategy on how to improve it. The research utilized Integrated …

Building Competent Teams Of Experts Based On Project Completion Time And Skill Levels, Yalda Yazdanpanah

Electronic Theses and Dissertations

With many companies quickly expanding their sizes, building the best team of experts from the applicants has evolved into an interesting subject for computer-aided decision-making tasks. In this regard, the Team Formation Problem (TFP) has been well-studied in Artificial Intelligence and operations research literature in recent years. We consider a Team Formation Problem of assigning qualified experts to a given set of positions in a given set of projects where each position is to be filled with an expert with a required skill. In our setting, an expert can be quantitatively characterized by one level per skill, and each expert …

High-Density Parking For Autonomous Vehicles., Parag J. Siddique

Electronic Theses and Dissertations

In a common parking lot, much of the space is devoted to lanes. Lanes must not be blocked for one simple reason: a blocked car might need to leave before the car that blocks it. However, the advent of autonomous vehicles gives us an opportunity to overcome this constraint, and to achieve a higher storage capacity of cars. Taking advantage of self-parking and intelligent communication systems of autonomous vehicles, we propose puzzle-based parking, a high-density design for a parking lot. We introduce a novel method of vehicle parking, which leads to maximum parking density. We then propose a heuristic method …

Work Order And Subassembly Identification And Tracking System, Israa El-Sabbagh

Electronic Theses and Dissertations

The research encompassed in this thesis includes the development of a work order and subassembly identification and tracking software system created in-house and tested at SPM Automation (Canada) Inc. The research is motivated by the significant losses the company is enduring and the recurring problems occurring at the facility (i.e., excess inventory, late ordering, reordering, misplaced components, etc.). These problems are critical in the progress and profits of the company.

An extensive literature review was completed, and the research gaps were presented. The optimal work order and subassembly process was created using Process Mapping Methodology, Cause-and-Effect Diagrams, and 5Why Analysis. …

A Study Of Perceptions On Incident Response Exercises, Information Sharing, Situational Awareness, And Incident Response Planning In Power Grid Utilities, Joseph Garmon

Electronic Theses and Dissertations

The power grid is facing increasing risks from a cybersecurity attack. Attacks that shut off electricity in Ukraine have already occurred, and successful compromises of the power grid that did not shut off electricity to customers have been privately disclosed in North America. The objective of this study is to identify how perceptions of various factors emphasized in the electric sector affect incident response planning. Methods used include a survey of 229 power grid personnel and the use of partial least squares structural equation modeling to identify causal relationships. This study reveals the relationships between perceptions by personnel responsible for …

Multi Self-Adapting Particle Swarm Optimization Algorithm (Msapso)., Gerhard Koch

Electronic Theses and Dissertations

The performance and stability of the Particle Swarm Optimization algorithm depends on parameters that are typically tuned manually or adapted based on knowledge from empirical parameter studies. Such parameter selection is ineffectual when faced with a broad range of problem types, which often hinders the adoption of PSO to real world problems. This dissertation develops a dynamic self-optimization approach for the respective parameters (inertia weight, social and cognition). The effects of self-adaption for the optimal balance between superior performance (convergence) and the robustness (divergence) of the algorithm with regard to both simple and complex benchmark functions is investigated. This work …