Operations Research, Systems Engineering and Industrial Engineering Commons^™

Spatiotemporal Sensing And Informatics For Complex Systems Monitoring, Fault Identification And Root Cause Diagnostics, Gang Liu

USF Tampa Graduate Theses and Dissertations

In order to cope with system complexity and dynamic environments, modern industries are investing in a variety of sensor networks and data acquisition systems to increase information visibility. Multi-sensor systems bring the proliferation of high-dimensional functional Big Data that capture rich information on the evolving dynamics of natural and engineered processes. With spatially and temporally dense data readily available, there is an urgent need to develop advanced methodologies and associated tools that will enable and assist (i) the handling of the big data communicated by the contemporary complex systems, (ii) the extraction and identification of pertinent knowledge about the environmental …

Meta-Raps Hybridization With Machine Learning Algorithms, Fatemah Al-Duoli

Engineering Management & Systems Engineering Theses & Dissertations

This dissertation focuses on advancing the Metaheuristic for Randomized Priority Search algorithm, known as Meta-RaPS, by integrating it with machine learning algorithms. Introducing a new metaheuristic algorithm starts with demonstrating its performance. This is accomplished by using the new algorithm to solve various combinatorial optimization problems in their basic form. The next stage focuses on advancing the new algorithm by strengthening its relatively weaker characteristics. In the third traditional stage, the algorithms are exercised in solving more complex optimization problems. In the case of effective algorithms, the second and third stages can occur in parallel as researchers are eager to …

Development Of A Tridimensional Measuring Application For Ipads, Michael Casebolt, Nicolas Kouatli, Jack Mullen

Computer Science and Software Engineering

In today’s fast-paced distribution centers workers and management alike are constantly searching for the quickest and most efficient way to package items for distribution. Even with the advancement of app-oriented solutions to a variety of problems across many industries there is a distinct unmet need in distribution environments for an application capable of increasing the efficiency and accuracy of packaging items. This senior project focused on the development and testing of an application utilizing the Structure Three Dimensional Sensor and a 4th generation iPad to scan an object or group of objects to be packaged and determine the overall dimensions …

Improving Product Design Phase For Engineer To Order (Eto) Product With Knowledge Base Engineering (Kbe), Hanhdung Thi Dinh

Open Access Theses

In industry currently Computer Aided Design (CAD) is an important tool for the modification, analysis, or optimization of the 3D virtual environment that replicates the physical product. CAD software is an efficient and reliable tool. However, as globalization increases customer demands, this process needs to be faster and more efficient to accommodate changing product design situations, especially for Engineer-to- Order (ETO) products. ^ The traditional method of product design process is to operate CAD software without argumentation. Design engineers create CAD prototypes and drawings based on available knowledge and information which comes from engineering experts, company standards, industrial practices as …

Toward A Theory Of Multi-Method Modeling And Simulation Approach, Mariusz A. Balaban

Computational Modeling & Simulation Engineering Theses & Dissertations

The representation via simulation models can easily lead to simulation models too simple for their intended purpose, or with too much detail, making them hard to understand. This problem is related to limitations of the modeling and simulation methods. A multi-method Modeling and Simulation (M&S) approach has the potential for improved representation by taking advantage of methods' strengths and mitigating their weaknesses. Despite a high appeal for using multiple M&S methods, several related problems should be addressed first. The current level of theoretical, methodological, and pragmatic knowledge related to a multi-method M&S approach is limited. It is problematic that there …

Proclivity Or Popularity? Exploring Agent Heterogeneity In Network Formation, Xiaotian Wang

Computational Modeling & Simulation Engineering Theses & Dissertations

The Barabasi-Albert model (BA model) is the standard algorithm used to describe the emergent mechanism of a scale-free network. This dissertation argues that the BA model, and its variants, rarely take agent heterogeneity into account in the analysis of network formation. In social networks, however, people's decisions to connect are strongly affected by the extent of similarity. In this dissertation, the author applies an agent-based modeling (ABM) approach to reassess the Barabasi-Albert model. This study proposes that, in forming social networks, agents are constantly balancing between instrumental and intrinsic preferences. After systematic simulation and subsequent analysis, this study finds that …

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. …

A Prediction Modeling Framework For Noisy Welding Quality Data, Junheung Park

Wayne State University Dissertations

Numerous and various research projects have been conducted to utilize historical manufacturing process data in product design. These manufacturing process data often contain data inconsistencies, and it causes challenges in extracting useful information from the data. In resistance spot welding (RSW), data inconsistency is a well-known issue. In general, such inconsistent data are treated as noise data and removed from the original dataset before conducting analyses or constructing prediction models. This may not be desirable for every design and manufacturing applications since every data can contain important information to further explain the process. In this research, we propose a prediction …

Predictive Analytics For Disease Condition Of Patients In Emergency Department, Azade Tabaie

Wayne State University Theses

Emergency Departments (EDs) in hospitals are experiencing severe crowding and prolonged patient waiting times. The reported crowding in hospitals shows patients in hospital hallways, long waiting times and full occupancy of ED beds. ED crowding has several potential unfavorable effects including patients and staff frustration, lower patient satisfaction and poor health outcomes. The primary motivations behind this study are shortening the patients’ waiting time and improving patient satisfaction and level of care.

The very initial interaction between clinicians and a patient is recorded on nurse triage notes which contain details of the reason for patient’s visit including specific symptoms and …

Calculus For Decision Systems, Jorge Antonio Samayoa Ranero

Open Access Dissertations

The conceptualization of the term "system" has become highly dependent on the application domain. What a physicist means by the term system might be different than what a sociologist means by the same term. In 1956, Bertalanffy [1] defined a system as " a set of units with relationships among them". This and many other definitions of system share the idea of a system as a black box that has parts or elements interacting between each other. This means that at some level of abstraction all systems are similar, what eventually differentiates one system from another is the set of …

Behavioral Operations Management In Federal Governance, Frederick Leonard Mobley

Walden Dissertations and Doctoral Studies

The environmental uncertainty of federal politics and acquisition outsourcing in competitive markets requires an adaptive decision-analysis structure. Practitioners oriented toward exclusively static methods face severe challenges in understanding qualitative aspects of organizational governance. The purpose of this grounded theory study was to examine and understand behavioral relationship attributes within intuitive, choice, judgment, or preference decision-making processes. The problem addressed in this study was the detrimental effects of organizational citizenship behavior (OCB), compulsory citizenship behavior (CCB), and social exchange theory (SET) on the acquisition management relationship The OCB, CCB, SET dictates that sound business development, relationship acumen, emotional intelligence and perceptiveness …

Quantum Inspired Algorithms For Learning And Control Of Stochastic Systems, Karthikeyan Rajagopal

Doctoral Dissertations

"Motivated by the limitations of the current reinforcement learning and optimal control techniques, this dissertation proposes quantum theory inspired algorithms for learning and control of both single-agent and multi-agent stochastic systems.

A common problem encountered in traditional reinforcement learning techniques is the exploration-exploitation trade-off. To address the above issue an action selection procedure inspired by a quantum search algorithm called Grover's iteration is developed. This procedure does not require an explicit design parameter to specify the relative frequency of explorative/exploitative actions.

The second part of this dissertation extends the powerful adaptive critic design methodology to solve finite horizon stochastic optimal …

Detection And Recognition Of R/F Devices Based On Their Unintended Electromagnetic Emissions Using Stochastic And Computational Intelligence Methods, Shikhar Prasad Acharya

Doctoral Dissertations

"Radio Frequency (RF) devices produce some amount of Unintended Electromagnetic Emissions (UEEs). UEEs are generally unique to a device and can be thought of as a signature of the device. This property of uniqueness of UEEs can be used to detect and identify the device producing the emission. The problem with UEEs is that they are very low in power and are often buried deep inside the noise band which makes them difficult to detect. There are two types of UEE detection methods. The first one is called stimulated detection method where the UEEs of a device are enhanced using …

Computational Intelligence Based Complex Adaptive System-Of-Systems Architecture Evolution Strategy, Siddharth Agarwal

Doctoral Dissertations

The dynamic planning for a system-of-systems (SoS) is a challenging endeavor. Large scale organizations and operations constantly face challenges to incorporate new systems and upgrade existing systems over a period of time under threats, constrained budget and uncertainty. It is therefore necessary for the program managers to be able to look at the future scenarios and critically assess the impact of technology and stakeholder changes. Managers and engineers are always looking for options that signify affordable acquisition selections and lessen the cycle time for early acquisition and new technology addition. This research helps in analyzing sequential decisions in an evolving …

Rote-Lcs Learning Classifier System For Classification And Prediction, Benjamin Daniels

Masters Theses

"Machine Learning (ML) involves the use of computer algorithms to solve for approximate solutions to problems with large, complex search spaces. Such problems have no known solution method, and search spaces too large to allow brute force search to be feasible. Evolutionary algorithms (EA) are a subset of machine learning algorithms which simulate fundamental concepts of evolution. EAs do not guarantee a perfect solution, but rather facilitate convergence to a solution of which the accuracy depends on a given EA's learning architecture and the dynamics of the problem.

Learning classifier systems (LCS) are algorithms comprising a subset of EAs. The …