Engineering Commons^™

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 …

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 …

A Valuation Model For Two-Stage Contract Negotiations Over Multiple Interdependent Issues, Nnaemeka U. Amaeshi

Masters Theses

"Most real-world negotiation scenarios involve multiple interdependent issues over which the negotiating parties will seek an agreement. Simultaneous negotiation over multiple interdependent issues is an especially challenging problem because utility functions of negotiating agents are typically nonlinear and difficult to analyze. Also, negotiations often happen under circumstances of incomplete information, where either party has either little or inaccurate information about the preferences or utilities of the other party. Consequently, negotiations may go over multiple rounds until a mutually acceptable agreement is reached. The objective of this research is to create a quantitative model of decision-making that helps one negotiating party …

Utilizing Learning Style Preferences And Quality Function Deployment For Curriculum Development, Julie M. Ezzell

Masters Theses

"Workplace requirements continually evolve to keep pace with the developing global market. To meet ever increasing standards, educational institutions have been investigating methods to prepare students for their future employment. Course modifications should be carefully considered to meet the requirements of all stakeholders, including those of the students. The objective of this research was to provide students with an overall better learning experience that tailors the teaching methods to his/her individual learning preferences. To meet this objective, a comprehensive survey was provided to an undergraduate course in quality. The survey documented the student's individuality when learning and made note of …

Modeling Supply Chain Interdependent Critical Infrastructure Systems, Varun Ramachandran

Doctoral Dissertations

"While strategies for emergency response to large-scale disasters have been extensively studied, little has been done to map medium- to long-term strategies capable of restoring supply chain infrastructure systems and reconnecting such systems from a local urban area to national supply chain systems. This is, in part, because no comprehensive, data-driven model of supply chain networks exists. Without such models communities cannot re-establish the level of connectivity required for timely restoration of goods and services. This dissertation builds a model of supply chain interdependent critical infrastructure (SCICI) as a complex adaptive systems problem. It defines model elements, data needs/element, the …

The Engagement Of Expert Opinions In The Modeling Of Multi-Attribute Decision Making For The Selection Of Project Delivery Methods In Building Construction, Issam H. Algraiw

Doctoral Dissertations

"Choosing the most appropriate project delivery method (PDM) available is acknowledged as a crucial issue in the construction industry. Both the choice and application of an unsuitable PDM can result in project failure. Likewise, the selection of a suitable PDM can increase the chance for project success. A method of selecting from among the seven PDMs recognized by the Construction Specifications Institute (CSI) was created in an attempt to address this issue.

This research was comprised of three objectives. The first objective was to determine the influential factors needed to select the appropriate PDMs available to the US construction industry. …

A Decision Support Simulation Model For Bed Management In Healthcare, Raja A. Baru

Masters Theses

"In order to provide access to care in a timely manner, it is necessary to effectively manage the allocation of limited resources such as beds. Bed management is key to the effective delivery of high-quality and low-cost healthcare. An efficient utilization of beds requires a detailed understanding of the hospital's operational behavior. It is necessary to understand the behavior of a hospital in order to make necessary adjustments to its resources, and policies, which can improve patient's access to care. The aim of this research was to develop a discrete event simulation to assist in planning and staff scheduling decisions. …

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 …

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 …