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- Member of: ASU Electronic Theses and Dissertations
Description
Energy management system (EMS) is at the heart of the operation and control of a modern electrical grid. Because of economic, safety, and security reasons, access to industrial grade EMS and real-world power system data is extremely limited. Therefore, the ability to simulate an EMS is invaluable in researching the EMS in normal and anomalous operating conditions.
I first lay the groundwork for a basic EMS loop simulation in modern power grids and review a class of cybersecurity threats called false data injection (FDI) attacks. Then I propose a software architecture as the basis of software simulation of the EMS loop and explain an actual software platform built using the proposed architecture. I also explain in detail the power analysis libraries used for building the platform with examples and illustrations from the implemented application. Finally, I will use the platform to simulate FDI attacks on two synthetic power system test cases and analyze and visualize the consequences using the capabilities built into the platform.
I first lay the groundwork for a basic EMS loop simulation in modern power grids and review a class of cybersecurity threats called false data injection (FDI) attacks. Then I propose a software architecture as the basis of software simulation of the EMS loop and explain an actual software platform built using the proposed architecture. I also explain in detail the power analysis libraries used for building the platform with examples and illustrations from the implemented application. Finally, I will use the platform to simulate FDI attacks on two synthetic power system test cases and analyze and visualize the consequences using the capabilities built into the platform.
ContributorsKhodadadeh, Roozbeh (Author) / Sankar, Lalitha (Thesis advisor) / Xue, Guoliang (Thesis advisor) / Kosut, Oliver (Committee member) / Arizona State University (Publisher)
Created2019
Description
This multi-phase dissertation explores how student placement management software can be evaluated, selected, adopted, and diffused within a university setting, considering multiple stakeholders with varying needs and differing levels of decision-making authority. Utilizing a case study design and Roger’s Diffusion of Innovation framework (2003), the articles are proposed to generate a guide modeled to improve practice, which is the primary goal of Action Research (Barnett & Muth, 2008). These articles will chronicle lessons learned, offer considerations, and provide helpful resources to strategically adopt a software platform within a university setting. The articles are proposed as follows: 1) Selection of Field Education Management Software in Social Work (v, published May 2020) focusing on the evaluation and selection phases for Social Work programs; and 2) Toward a Decision Support Tool for Selecting Third-Party Student Management Software in Field-based Education (target journal - Springer - Educational Technology Research and Development) which will expand on previous research to a broader audience of student-placing programs and diffusing the software innovation throughout the university setting. Each article will explore a different aspect of the Action Research, the findings which emerged from the study, and provide additional insights and implications to each journal audience.
ContributorsSamuels, Kristen Mitchell (Author) / Basile, Carole (Thesis advisor) / Wolf, Leigh G (Committee member) / Hitchcock, Laurel I (Committee member) / Arizona State University (Publisher)
Created2021
Description
Introduction: A diet high in fermented, oligio-, di-, monosaccharide, and polyols
(FODMAP) has been shown to exacerbate symptoms of irritable bowel syndrome
(IBS). Previous literature has shown significant improvement in IBS symptoms after
adherence to a low FODMAP diet (LFD). However, dietary adherence to the LFD is
difficult with patients stating that information provided by healthcare providers
(HCPs) is generalized and nonspecific requiring them to search for supplementary
information to fit their needs. Notably, studies that have used a combination of
online and in-person methods for treatment have shown improved adherence to the
LFD. Objective: To determine whether a novel artificial intelligence (AI) dietary
mobile application will improve adherence to the LFD compared to a standard online
dietary intervention (CON) in populations with IBS or IBS-like symptoms over a 4-
week period. Methods: Participants were randomized into two groups: APP or CON.
The intervention group was provided access to an AI mobile application, a dietary
resource verified by registered dietitians which uses artificial intelligence to
individualize dietary guidance in real-time with the ability to scan menus and
barcodes and provide individuals with food scores based on their dietary preferences.
Primary measures included mobile app engagement, dietary adherence, and
manifestation of IBS-like symptoms. Baseline Results: A total of 58 participants
were randomized to groups. This is an ongoing study and this thesis details the
methodology and baseline characteristics of the participants at baseline and
intervention start. Validation of the application could improve the range of offerings
for lifestyle diseases treatable through dietary modification.
(FODMAP) has been shown to exacerbate symptoms of irritable bowel syndrome
(IBS). Previous literature has shown significant improvement in IBS symptoms after
adherence to a low FODMAP diet (LFD). However, dietary adherence to the LFD is
difficult with patients stating that information provided by healthcare providers
(HCPs) is generalized and nonspecific requiring them to search for supplementary
information to fit their needs. Notably, studies that have used a combination of
online and in-person methods for treatment have shown improved adherence to the
LFD. Objective: To determine whether a novel artificial intelligence (AI) dietary
mobile application will improve adherence to the LFD compared to a standard online
dietary intervention (CON) in populations with IBS or IBS-like symptoms over a 4-
week period. Methods: Participants were randomized into two groups: APP or CON.
The intervention group was provided access to an AI mobile application, a dietary
resource verified by registered dietitians which uses artificial intelligence to
individualize dietary guidance in real-time with the ability to scan menus and
barcodes and provide individuals with food scores based on their dietary preferences.
Primary measures included mobile app engagement, dietary adherence, and
manifestation of IBS-like symptoms. Baseline Results: A total of 58 participants
were randomized to groups. This is an ongoing study and this thesis details the
methodology and baseline characteristics of the participants at baseline and
intervention start. Validation of the application could improve the range of offerings
for lifestyle diseases treatable through dietary modification.
ContributorsRafferty, Aaron (Author) / Johnston, Carol (Thesis advisor) / Hall, Richard (Committee member) / Fitton, Renee (Committee member) / Arizona State University (Publisher)
Created2020
Description
Embedded software is different in many aspects to traditional software; as such, a software developer may face issues when attempting to transition from traditional to embedded software development. This thesis explores providing feedback and applying optimizations at the source code level of embedded software. The aim is to measure the impact of these optimizations on teaching embedded software design principles, as well as assessing the relative success of each optimization in terms of a variety of metrics. There are many considerations when altering code and is a known limitation imposed by most software optimization schemes. By applying optimizations at the source level, the aim is to demonstrate what the optimizations do and how they provide value to the resulting software. In order to fulfill these goals, the Embedded C Source Optimizer has been developed, which is used to import and export code, select which optimizations are applied, and provide feedback to the end user. This utility abstracts away the lower level operations performed by each optimization, while conveying the resulting changes to the end user. Since embedded systems are generally quite limited compared to modern computers, someone transitioning from traditional software design to embedded software may find it challenging to understand how to overcome these limitations. Clearly conveying means to improve a naive implementation of an embedded program aids through demonstrating what changes need to be made to satisfy embedded design rules. The optimizations which the utility can apply range from simple replacement operations to more complex applications of implicit utilization of built-in hardware peripherals on supported microcontrollers. Each optimization comes with its own set of considerations, risks, and potential level of improvement to the resulting code. These optimization options are evaluated by comparing embedded software before and after each option is applied through a variety of metrics, allowing the relative success of each to be determined as effectively as possible. The end goal for this utility is to aid in crossing the hurdle from traditional software to embedded software in a comprehensive and educational manner, with the provided optimization options acting as an avenue for teaching embedded concepts.
ContributorsLisonbee, Tanner Boyd (Author) / Heinrichs, Robert (Thesis advisor) / Acuna, Ruben (Committee member) / Jordan, Shawn (Committee member) / Arizona State University (Publisher)
Created2021