PHD, Kent State University, 2023, College of Communication and Information

The purpose of this study is to investigate the relationship between intentional online information seeking, incidental online information seeking, eHealth literacy, and shared decision-making; the relationship between intentional online information seeking, incidental online information seeking, information overload, eHealth literacy, information anxiety, and information avoidance in the context of diabetes. The study is based on Wilson's models (1981, 1997, 1999) of information behavior, Williamson's (1998) ecological model of information seeking and use, and S-O-R (Stimulus, Organism, Response) framework (Mehrabian & Russell, 1974). It examines the survey data from diabetic patients aged 18 to 44 years old in the U.S. Linear regression and structural equation modeling approaches were utilized to analyze the data. Results indicated that intentional online information seeking and eHealth literacy have positive impacts on shared decision-making. Information overload is positively related to information anxiety and information anxiety is positively related to information avoidance. Additional analyses also indicated that incidental online information seeking is negatively related to information avoidance, and eHealth literacy is negatively related to information anxiety. Information anxiety positively mediates the relationship from information overload to information avoidance. Results extend existing theoretical frameworks and suggested that there is a necessity to develop information and communication strategies to distribute high quality online health information online and training programs to help decrease diabetes information seekers' information anxiety and information avoidance about diabetes and encourage shared decision-making for diabetic patients.

Doctor of Philosophy, The Ohio State University, 2023, Educational Studies

This dissertation consists of a theoretical review and two empirical studies investigating adolescents' access of sexual health information. The overarching objectives of this project were to increase understanding of middle school students' sexual health information-seeking behaviors in online settings, namely on social media platforms, and expand general knowledge of young adolescents' questions and concerns about the topic of human anatomy within human sexuality education. A comprehensive review of the theoretical and empirical literature was conducted on adolescent online health information-seeking behavior and health education teaching tools, specifically in relation to sexual health. This review presents ways in which motivational influences impact adolescent social media use to seek health information and offers insight into how Longo's comprehensive and integrated model for understanding health information, communication, and information-seeking (2005) and Self-Determination Theory (Ryan & Deci, 2000, 2020) may be used as frameworks for improved understanding in adolescent use of social media for seeking information related to sexual health. Additionally, an overview of developmental changes within adolescence, and well-established health education tools, is given, providing a lens through which adolescent questions related to human sexuality may best be viewed by those invested in improving sexual health education. In the first empirical study, survey responses from 1,327 participants in 19 middle schools were analyzed to investigate student sexual health attitudes and behavioral outcomes influenced by seeking sexual health information on social media and exposure to sexual health content on social media. It was found that young adolescents frequently use Google, YouTube, and TikTok when seeking sexual health information and that they are frequently exposed to human sexuality content on TikTok, Instagram, and YouTube. When considering sexual health (open full item for complete abstract)

Bachelor of Business Administration (BBA), Ohio University, 2021, Business Administration

This study looks into the human element of information security (IS) by testing changes in attitude and behavioral intention following personalized IS awareness and training. Some modern IS research has left out attitude despite its theoretical foundation and ability to predict behavior, which is why the present study emphasizes its inclusion alongside behavioral intention. Traditional IS awareness and training programs fail to motivate employees to behave more securely due to a lack of empathy in the design of the IS program. This lack of motivation has caused employees to be the most commonly reported IS vulnerability for organizations. Many programs lack a degree of personal relevance that is needed to motivate employees to change their attitude and behavior towards IS. We propose a personalized awareness and training initiative that relies on personal relevance to address this issue. We argue that personalized awareness and training initiatives that rely on personal relevance are capable of significantly and positively changing IS attitude and behavioral intention amongst participants. The results of this study indicate that the type of awareness and training initiative participants received (general versus personalized) significantly and positively changed participant attitude, with no significant difference found in behavioral intention.

Doctor of Philosophy, The Ohio State University, 2003, Human Nutrition and Food Management

The strategic use of management information systems (MIS) can convey competitive value. For this reason, it is important to understand which antecedents are associated with system success. By utilizing theoretical assumptions from several fields: strategic management, MIS, and hospitality, this study develops a model of Restaurant Management Information System (RMIS) success for the foodservice industry. The purpose of this study was to identify current information technology (IT) trends in the foodservice industry, to identify the types and quality of IT training and support offered to managers, and to develop and test the RMIS model. This study uses survey research. A survey was administered to restaurant managers (n = 243) to gather data about their system features and effectiveness. This study demonstrated several important findings. First, many foodservice establishments are utilizing systems more than indicated in earlier foodservice literature. Food and labor cost analyses, sales forecasts, server performance evaluations, menu analysis, and e-mail are commonly utilized by today's restaurant manager. Second, this study provides support for contingency theory, that is, firms do not use systems equally. Full and quick service restaurants, chains and independents, and successful and unsuccessful restaurants all utilized systems differently. Third, this study provided partial support for systems implementation theory. This study found that training related to system success, but not support. The availability (hours) of support provided by the “help desk” did not relate to system success. Lastly, this study used regression analysis to test the RMIS research model. The first regression model of RMIS success, with decision-making support satisfaction as a dependent variable, exhibited a fit of .450. Four antecedents – system use, system quality, report quality, and training quality –were significant. Sensitivity analysis was conducted on the regression analysis, and (open full item for complete abstract)

Master of Arts (MA), Bowling Green State University, 2020, Mathematics

Data is categorical or numerical information that is collected and analyzed. Some examples of data are the company's financial data or environmental data that can inform us of the state of the environment over time. Circumstances often lead to change. For example, the temperature globally has risen dramatically over the years, which began a phenomenon referred to as global warming. As a result, glaciers are rapidly melting, causing sea levels to rise. Rising sea levels damaging coastal areas with increase flooding and more frequent hurricanes. Nevertheless, if we can discover when the change occurred and what caused it, we can put reg-ulations and procedures in place to help avoid future damages. Determining the number of changes in a data set and when it occurred, is called the change point problem. Akaike (1973) introduced the Akaike information criterion (AIC) to solve the change point problem. Additional information criterion was introduced to expand upon and improve AIC. We will discuss AIC further, and we will utilize the Schwarz Information Criterion (SIC) and the Modified information criterion (MIC) to perform simulations on random lognormal distributed data. Chapter 1 introduces AIC and the binary segmentation procedure. Binary segmentation detects multiple change points in a data set. Note, the hypothesis test is employed to perform both AIC and binary segmentation procedures. Chapter 2 introduces SIC, then a theoretical basis and mathematical formulas are derived. Next, we use the criterion to administrate multiple simulations such as power tests and multiple sample size comparisons. Then we utilize SIC and the binary segmentation procedure to analyze the annual net flux of carbon to the atmosphere from land-use. Chapter 3 introduces MIC. Again, theoretical basis and mathematical formulas are derived. Multiple simulations are conducted, such as power test, sample size comparison, and information approach comparison. Lastly, we analyze historical crypt (open full item for complete abstract)

Master of Science, The Ohio State University, 2018, Genetic Counseling

Information seeking and scanning have been studied in the context of health behaviors but there are very little data about impact of information behaviors on individuals presenting for genetic counseling. To investigate, we conducted a cross-sectional survey of patients scheduled for cancer genetic counseling appointments (N=111). The electronic survey instrument was built using constructions of the Planned Risk Information Seeking Model (PRISM), which states that intent to seek information is the result of one's perceptions of their own knowledge insufficiency, risk perceptions, and attitudes and beliefs toward information seeking. The survey collected information about primary topics of interest and sources of information seeking, sources of cancer and genetics information scanning, and relationships between information seeking behaviors and, risk perceptions, perceived knowledge, perceived control, cancer-related worry and understanding of the genetic counseling process. The majority of participants (84.7%) report information scanning. More than half (54.1%) report information seeking. Information seeking was found to be associated with higher perceived knowledge, higher personal control over cancer risk, and better understanding of the genetic counseling process (ps < .05). Understanding information seeking and scanning behaviors of genetic counseling clients is the first step in understanding client information needs in order to tailor genetic counseling information interventions. This study serves as a pilot for future projects about information behaviors in the context of genetic counseling.

Master of Science, University of Akron, 2017, Applied Mathematics

The use of wireless technologies has grown significantly in the past decade. According to Cisco Global Mobile Data Traffic Forecast , global mobile data communication and usage will increase seven-times within 2016 and 2021. Over the last few years, innovative wireless communication paradigms have been introduced to overcome the spectrum crunch due to limited wireless spectrum resources. Examples include multi-antenna applications, where a large number of antennas can be used at the transmitter and/or the receiver. This thesis contributes towards the analysis and design of multi-antenna wire-less communication systems from an information-theoretical aspect. Specifically, this thesis investigates the information rate between the input and output of wireless channels having multiple transmit antennas and a single receive antenna under both per-antenna power constraints as well as channels under joint per-antenna and sum power constraints. We consider a dynamic wireless environment where neither the transmitter nor the receiver knows the channel state information (CSI). First, an expression of the information rate of the considered channel achieved by a given discrete input vector is established. The expression involves a single integral, which can be calculated via numerical integrations. For a more effective and accurate calculation of the information rate, a novel technique based on piece-wise linear curve fitting (PWLCF) is then proposed. Since a PWLCF-based method is only applicable to integrals having finite limits, our approach is divide the domain into two separate regions. In the finite-range region, we apply the PWLCF. For the other region, we establish a lower bound on the integrand in the information rate, and show that the information rate can be estimated to achieve any accuracy level. By combining the two regions, it is shown that the information rate can be estimated with a predetermined accuracy. The proposed method provides a simple way to calcu (open full item for complete abstract)

Doctor of Philosophy, Case Western Reserve University, 2016, Social Welfare

The first aim of this dissertation was to describe online health information seeking behavior (OHISB) and health information seeking experience (HISE) in elderly cancer survivors using the Internet. The second purpose was to investigate predictors of OHISB and HISE in elderly cancer survivors using the Internet. In this dissertation, OHISB is defined as the behaviors engaged in by individuals to acquire health information via the Internet, while HISE refers to individuals' perceptions and appraisals of not only the quality of information sources and contents, but also experiences and feelings during information seeking. As a theoretical framework, this dissertation adopts the comprehensive model of information seeking (CMIS). The CMIS posits that individuals' health information seeking is affected by various demographic characteristics, health-related experiences, beliefs, salience, and perceptions of information sources. To address these purposes, a sample of 235 elderly cancer survivors was drawn from the 2007 Health Information National Trends Survey (HINTS); data were collected from January 2008 through May 2008 (a cross-sectional cohort survey). For this dissertation, inclusion criteria were individuals who reported they had been diagnosed with cancer at some time in their lives (self-report, not medical records), who used the Internet, and who were aged 60 years or older. A Structural Equation Model (SEM) was used to test the hypothesized structural relationships between predictors and OHISB, and between predictors and HISE. In advance of conducting the structural model, confirmatory factor analysis was used to confirm that each of two multiple-item scales (i.e., unmet health information needs and HISE) adequately fit a single factor model. In this dissertation, the structural model fit the data well. Being male and having higher trust in Internet health information significantly predicted higher OHISB, while higher education, more years since cancer d (open full item for complete abstract)

MS, Kent State University, 2015, College of Education, Health and Human Services / School of Foundations, Leadership and Administration

The internet and social media has boosted information sharing and user-generated content (UGC). As a result, many restaurant goers rely on online reviews for dining recommendations. The goal of this study is to add to the sparse literature on the influence of review extremeness, source credibility, website quality, and information usefulness on information adoption. Most notably, a hypothesized information adoption model with the addition of website quality will be tested in the context of restaurant review websites. Data was collected through an online survey, the link for which was emailed to 10,000 students in a Midwestern university. Three hundred and two students completed the survey. Results showed that the more negative a review, the more useful it is perceived. Perceived source credibility of the review writer exerted a positive impact on the perceived information usefulness. The only component of website quality that played a significant role in determining information adoption tendency of the review readers was the quality of the information disseminated in the website. Lastly, information usefulness also exerted a positive influence on information adoption. Managerial implications are discussed.

Doctor of Philosophy, University of Toledo, 2005, Manufacturing Management

With advances in information technology (IT), information systems integration (ISI) and its role in an integrated supply chain have become important to executives and researchers. ISI represents the degree of cooperation in information system practices between business functions within a firm and between a firm and its trading partners. It has been documented that the introduction and utilization of ISI for supply chain management enhance the firms' competitiveness and growth. While many firms focus on achieving high levels of IT utilization, without high levels of ISI, supply chain members may not attain the full benefits of working within a supply chain. The concept of ISI can be captured using two main sub-constructs (e.g., internal ISI and external ISI) and can be conceptualized at three levels – (1) Strategic, (2) Operational, and (3) Infrastructural. Studying the effects of ISI in these levels can help researchers and executives understand how ISI practices at different levels contribute to overall supply chain effectiveness. The implications of such an understanding may bring significant benefits to both operations researchers and practitioners. Such benefits may include making better decisions about which IT to utilize, which information systems (IS) practices to emphasize, and what level of ISI to attain. From a practitioner's perspective, this research provides important guidelines so firms may better understand ISI issues and effectively implement IT. This study proposes three significant contributions to supply chain management research. First, this study applies an information system perspective to study both causes and effects of supply chain integration. It proposes a theoretical framework that considers the role of ISI as a mediator between IT utilization and supply chain integration. Second, this study provides the inferences made from an instrument that is valid and reliable for the current study's context, which are beneficial for both practitione (open full item for complete abstract)

Ph.D., Antioch University, 2024, Leadership and Change

Fighting false information, propaganda, open lies, rumors, misinformation, and disinformation by attacking it directly and challenging it is the dominant strategy for dealing with false beliefs (Lazer et al., 2018; Maseri et al., 2020; Van Bavel et al., 2021), and it is an important one. Refuting falsity is crucial. At the same time, there are instances when fighting false information does not work (Ardevol-Abreu et al., 2020; McIntyre, 2018; Van Bavel et al., 2021). One of the reasons is that it denies another's worldview, belief systems, and, as a result, their identity and even right to exist. Searching for alternative strategies for dealing with falsity, this study used qualitative research methodology and conducted three focus group discussions. My research findings show that identifying and framing a narrative behind falsity shifts the dynamic from facts to interaction, from fighting to beginning relationships to that narrative, and potentially people who stand for it, consciously or unconsciously. It allows one to find a belief system and a worldview of the other, and to engage and interact with it. Thus, there is a shift from finding who is telling the truth or lies to providing space for various belief systems and worldviews to interact with each other. Making this shift changes the power dynamic and empowers human beings to stop being simply victims of falsity and gain agency. My research also shows that there is a high need for talent and skills to hold polarities and different narratives, allowing them to co-exist and not deny each other, facilitating unpredictable and unimaginable ways to interact with each other, and bring more flow into communication instead of distancing even further. Finding narratives behind falsity and holding the opposite stories allow one to see falsity as not just an absolute evil, but potentially meaningful, transforming it into an opportunity for community-building processes and for people to work on differe (open full item for complete abstract)

Doctor of Business Administration (D.B.A.), Franklin University, 2023, Business Administration

As technology changes constantly, so does the need for organizations to adapt by promptly and effectively implementing technological improvements to gain a competitive edge. Information systems in the information technology (IT) industry are continually seeing new innovations, and business leaders must be prepared to adopt these technological options to strengthen their organizations' information system infrastructure. This dissertation study aims to define the variables that contribute to organizational readiness for change (ORC) to determine information system implementation decisions for companies in the IT industry using a quantitative methodology and an existing decision model as the theory. Behavioral intention is the construct that measures and helps ascertain whether employees are prepared for change. Based on the Pare model, this dissertation study theorized that 10 independent variables are positively related to ORC. Following completion of the survey-based process, the analysis process used partial least squares structural equation modeling (PLS-SEM). This study should benefit the IT industry, which struggles with change management activities within its departments and organizations.

Doctor of Philosophy, The Ohio State University, 2023, Educational Studies

As mobile learning (m-learning) becomes increasingly prevalent in education, it is recognized for its potential to enhance the overall quality of teaching and learning. Despite the many benefits, m-learning apps often experience low retention rates, which directly impede learners' benefit from using them and cause a waste of resources in app design, development, and maintenance. To investigate the critical factors influencing learners' acceptance of m-learning outside the classroom, this study introduced a novel model, the Mobile Learning Acceptance Determination (mLAD) Model, based on the Technology Acceptance Model and the updated DeLone and McLean Information System Success Model. Through the mLAD model, the study identified the critical app quality factors that influence learners' acceptance of m-learning. The moderating effects of the type of m-learning apps on learners' acceptance of m-learning were also revealed. An online questionnaire named the m-Learning Acceptance Questionnaire (mLAQ) was developed and disseminated through Amazon Mechanical Turk. A total of seven hundred forty-seven adult learners in the U.S. participated in the study. The descriptive statistical results of the examined factors revealed that m-learning apps available in the market demonstrate high mobility and content quality. Still, their interactivity and service quality could be improved. Furthermore, the results of the structural equation modeling analysis indicated that learners' two beliefs, perceived usefulness, and perceived ease of use, are the two essential determinants of learners' intention to use m-learning apps outside the classroom. Quality factors, such as content quality, interface design, mobility, and service quality, are the antecedents of learners' m-learning acceptance, given that they significantly and directly influence perceived usefulness and ease of use and indirectly impact learners' intention to use m-learning apps through learners' two beliefs. Through (open full item for complete abstract)

Doctor of Philosophy, The Ohio State University, 2023, Civil Engineering

Global Navigation Satellite System (GNSS) positioning performance degrades greatly when satellite signals are blocked or reflected multiple times before reaching the receiver, especially under forest canopies and in urban canyons. In these challenging environments, the accuracy of GNSS range measurements can only attain to tens meters or even worse. The integration of GNSS and Inertial Measurement Unit (IMU) has become a standard practice and core component of various navigation systems to operate under short GNSS gaps. Nevertheless, it cannot provide continuously accurate navigation solution without a high end IMU on board during prolonged GNSS outages. This dissertation investigates alternative navigation methods in GNSS challenged environments. Research is mainly focused on three aspects, (1) integration of laser scanners to improve the navigation accuracy of a single platform, (2) collaborative navigation to improve the navigation accuracy of the whole network of platforms, and (3) multiple outlier detection to ensure the integrity of collaborative navigation. Robust and efficient algorithms were developed to register laser point clouds to support high precision positioning. The algorithms include center determination of spherical targets, which are designed to be deployed in the area and used as anchors, and sphere center matching. The sphere center determination algorithms include laser point indexing, sphere point classification, least-squares fitting, and sphere center refinement. The sphere center matching algorithm exploits the topology of the sphere centers to determine the correspondence between sphere centers. The developed algorithms were tested to be more than four times faster than an implementation of unoptimized Iterative Closest Point (ICP) algorithm on point cloud registration of two real data sets. A framework was established to integrate sensors deployed on different platforms, called as nodes, and internodal range measurements t (open full item for complete abstract)

Master of Arts, The Ohio State University, 2022, Communication

This study serves as the first test of the Planned Risk Information Avoidance (PRIA) model proposed by Deline & Kahlor (2019). Information avoidance is an often overlooked subject of information management, and it must be studied in order to inform our understanding and allow health communicators to apply the knowledge gained in the study of information avoidance to reduce the prevalence of avoidance of health promotion messaging. The context of this study concerned parents of children age 5-11 (N=508), and their interactions with COVID-19 vaccination information for their children. Results showed that the PRIA model was largely supported by our findings, with the exception of closure and perceived behavioral control. Implications for this study are the expansion of a model dedicated to understanding avoidance, and some suggestions for how to apply these findings. This includes considering vaccination risk as separate from disease risk (in trying to combat avoidance of vaccination messaging), and using norms to influence attitudes toward avoidance, in efforts to minimize avoidance intentions.

Doctor of Philosophy, Case Western Reserve University, 2022, Physics

In the last two decades, advances in experimental techniques have opened up new vistas for understanding bio-molecules and their complex networks of interactions in the cell. In this thesis, we use theoretical modeling and machine learning to explore two surprising aspects that have been revealed by recent experiments: (i) the discovery that many different types of cellular signaling networks, in both prokaryotes and eukaryotes, can transmit at most 1 to 3 bits of information; (ii) the observation that single bio-molecules can exhibit multiple, stable conformational states with extremely heterogeneous functional properties. The first part of the thesis investigates how the energetic costs of signaling in biological networks constrain the amount of information that can be transferred through them. The focus is specifically on the kinase-phosphatase enzymatic network, one of the basic elements of cellular signaling pathways. We find a remarkably simple analytical relationship for the minimum rate of ATP consumption necessary to achieve a certain signal fidelity across a range of frequencies. This defines a fundamental performance limit for such enzymatic systems, and we find evidence that a component of the yeast osmotic shock pathway may be close to this optimality line. By quantifying the evolutionary pressures that operate on these networks, we argue that this is not a coincidence: natural selection is capable of pushing signaling systems toward optimality, particularly in unicellular organisms. Our theoretical framework is directly verifiable using existing experimental techniques, and predicts that many more examples of such optimality should exist in nature. In the second part of the thesis, we develop two machine learning methods to analyze data from single-molecule AFM pulling experiments: a supervised (deep learning) and an unsupervised (non-parametric Bayesian) algorithm. These experiments involve applying an increasing force on a bio-molecul (open full item for complete abstract)

PHD, Kent State University, 2021, College of Arts and Sciences / Department of Geography

Cancer epidemiology has a long history of applying geographic thinking to address long-standing place-based disparities. This dissertation adds new knowledge to geospatial approaches to social determinants of cancer outcomes. It establishes a framework consisting of three dimensions in evaluating, identifying, and prioritizing spatially heterogeneous risk factors of cancer outcomes. The first dimension is protection. Using a space-time statistic, the first study evaluated whether a non-spatial healthcare policy, Medicaid expansion, has offered protection targeting spatially vulnerable populations against adverse cancer outcomes such as breast cancer late-stage diagnosis. The second dimension is phenotype. Using a classification and regression tree, the study disentangled how risk factors of late-stage breast cancer diagnosis were conceptualized and capsulized as phenotypes that labeled groups of homogenous geographic areas. It provides a novel angle to uncover cancer disparities and to provide insights for cancer surveillance, prevention, and control. The third dimension is priority. Using a geographic random forest along with several validation methods, the study emphasized the importance of the competing effect among risk factors of cancer mortality that are specific to geographic areas. The findings from this study can be used directly for priority settings in addressing the most urgent issues associated with cancer mortality. This dissertation demonstrated that geographic methodologies and frameworks are useful and are imperative to cancer epidemiology.

Doctor of Philosophy, Case Western Reserve University, 2021, Management

Information technology (IT) projects are getting more complex by the day. From piloting to deployment, through different project phases and cycles, the IT field is still experiencing catastrophic failure. Seventy-one percent (71%) of IT projects are either outright failures or remain significantly challenged during the project execution, and most are related to soft-skills inadequacies. The three studies in this dissertation provide empirical evidence through various theoretical lenses that help explain how to avoid such failures. In particular, I focus on IT project managers' influence in forming critical project alignment toward actualizing project benefits and shaping consequent project success. Study 1 researched factors that lead IT projects to fail. I intended to better understand what shapes project outcomes, that is, causes that contribute to failure. Findings revealed, the use/lack of power, authority, and influence shapes project outcome. Study 2 investigated the role of the IT project manager's influence toward actualizing project benefits realization. I developed a model of benefits realization at the project level and analyzed to what extent it is driven by the stakeholders' and business alignment induced by three types of influence (dimensions); behavioral, and informational, and power-based held associated with the project manager's role. Findings revealed information and behavioral-based influence are significant means of impacting stakeholder alignment to realize benefits. Also, my research suggested that power and behavioral-based influence are significant means of impacting business alignment to realize benefits. Study 3 aimed to uncover the influence tactics (success elements) IT project managers enact while creating stakeholders and business alignment. Results revealed that IT project managers use different tactics to achieve the desired results and/or actualize benefits while engaging with business and stakeholders. Nonetheless, this behavior i (open full item for complete abstract)

Master of Arts, The Ohio State University, 2021, East Asian Studies

Productivity growth drives long-term economic growth and rising living standards in a modern economy. Information and communications technology (ICT) has been a key driver of both total factor productivity (TFP) and labor productivity growth since the 1990s. Japan, which has consistently had the lowest labor productivity in the G7, has not seen significant levels of ICT-driven productivity growth in its non-manufacturing sectors despite investing heavily in ICT hardware. This paper explores the reasons for Japan's failure to reap productivity gains from its ICT investments. I claim Japanese firms have failed to invest in organizational capital and new business practices to maximize the potential of ICT. A preponderance of very small firms with elderly managers have left large swaths of the economy with minimal ICT investment. Part of the failure to update business practices stems from labor market rigidity which reduces the labor input savings from ICT systems and inefficient capital markets which protect inefficient incumbent firms. Furthermore, the low rate of firm entry and exit, coupled with a lack of foreign direct investment, hinders the adoption of new ideas and the reallocation of capital and labor.

Master of Science (MS), Ohio University, 2020, Electrical Engineering (Engineering and Technology)

This thesis discusses the continued development of a Predictive Alerting of Energy (PAE) algorithm that has been integrated into an Information Management and Decision Support Tool (IMDS). The tool was designed to increase Aircraft State Awareness (ASA) by reducing pilot workload through a set of visual alerts on the Vertical Situation Display (VSD) and the Engine Indicating and Crew Alerting System (EICAS) display along with aural alerts. This work relies heavily on past work in which the fundamental principles of the core Fast Time Simulations (FTS) functionality were created. A new method of detecting High and Fast (HF) and Low and Slow (LS) conditions during runway side-steps on approach is discussed. Lastly, the feasibility of a machine learning energy prediction method is explored using a Long Short-Term Memory (LSTM) network, a type of Recurrent Neural Network (RNN).