Master of Arts, Miami University, 2015, Psychology

Very few researchers have used empirical data to fit Multialternative decision field theory (MDFT). The current research designed an apartment choice task to fit experimental data into MDFT to test the theory's choice predicted accuracy. The same data was also used to fit the expected utility theory. Three different measures of attribute weighting, calculated from self-report and eye tracking data, were used to test which measure can predict people's choice better. The results showed that MDFT's predicted accuracy was higher than the expected utility theory, and the three attribute weightings performed relatively well at predicting choice accuracy.

Committee: Joseph Johnson (Advisor); Christopher Wolfe (Committee Member); Amy Summerville (Committee Member) Subjects: Psychology

Master of Arts (M.A.), University of Dayton, 2013, Psychology, General

Previous research has found that performance is sometimes affected by transitions in workload. For some tasks and occupations, this type of change in demand can severely impact performance, which makes this a topic of interest for further research. The previous research conducted used a variety of tasks and methods, but few of the results obtained have been consistent. This study sought to determine the effect of workload transitions in a multi-tasking environment, which is an under-represented area in research on this topic. The use of subjective questionnaires to assess perceived workload and task-related stress has also been limited in previous research. Therefore, this study used the Air Force Multi-Attribute Task Battery (AF-MATB), which is a multi-tasking environment, the NASA Task Load Index, which is a measure of subjective workload, and the shortened Dundee Stress State Questionnaire, which a subjective measure of task-related stress. During testing, all participants completed AF-MATB trials that transitioned from an easy level to a difficult level or from a difficult level to an easy level. Also, they all completed easy and difficult control trials. Analyses of the performance data principally supported the success of the task difficulty manipulation, with significant differences only occurring between the easy and difficult portions of trials. However, the results of several AF-MATB subtasks indicated that the transition in task difficulty from difficult to easy had a negative impact on performance compared to performance in the easy control condition. The significant differences in two of these performance measures, however, may reflect trends in the data of the easy control condition as opposed to transition-related decrements in the difficult-easy condition, thereby making conclusions about the presence of transition effects in these instances somewhat difficult. The analysis of both the NASA Task Load Index and of the shortened Dundee State Questionna (open full item for complete abstract)

Committee: F. Thomas Eggemeier Ph.D. (Advisor); James Christensen Ph.D. (Committee Member); Susan Davis Ph.D. (Committee Member) Subjects: Experimental Psychology; Psychology

Master of Science (MS), Wright State University, 2012, Biomedical Engineering

The Multiple-Attribute Task Battery (MATB) is composed of four simultaneously running components to which a human operator responds. A prior report has quantified information content as a machine input baud rate using the Hick-Hyman and Fitt's Laws for three of the four components and defines a strategy function. This report covers methods to quantify information content of the fourth component, creating a single metric which describes overall task complexity and evaluates human performance and strategy. Six MATB task-scenarios (combinations of two, three, or all four MATB components) each at two input baud rates are evaluated. Subjects were also provided with a chart that shows information weighting of each MATB component. Results show a change in strategy paradigm between medium input baud rate and high input baud rate for the six task-scenarios collectively. This likely occurs because subjects only refer to the component weighting chart for strategy formulation when performing more challenging task-scenarios. Advancements made with this thesis give a better understanding of how humans process information during multitasking, provide a simpler and more effective metric for analyzing MATB human performance, and create a foundation for further model development.

Committee: Chandler Phillips MD (Advisor); David Reynolds PhD (Committee Member); Richard A. McKinley PhD (Committee Member) Subjects: Information Systems

Doctor of Philosophy (PhD), Ohio University, 2022, Higher Education (Education)

This dissertation demonstrates the interdisciplinary integration of critical appreciative inquiry (a qualitative planning process focused on inclusion in decision-making) and multi-attribute utility theory (a quantitative evaluation process focused on rationality in decision-making). Principles of positive psychology and decision-making underly the resulting model used in this proposal to evaluate a sample of programmatic initiatives of Ohio University's LGBT Center. Results from this work reveal the usefulness of deriving evaluation criteria from an organization's mission statement and are expected to generalize to other such centers. Implications for diversity leaders in higher education are advanced.

Committee: Krisanna Machtmes (Committee Chair); Pete Mather (Committee Member); Claudia Gonzalez-Vallejo (Committee Member) Subjects: Higher Education Administration; Psychobiology

Doctor of Philosophy, The Ohio State University, 2021, Psychology

Eye-tracking has been a useful process-tracing measure to disclose attentional mechanisms in human decision making, such as in multi-attribute decision making. In recent years, the field of multi-attribute decision making has been greatly advanced by the development of formal computational models. However, most computational models of multi-attribute decision making only deal with choices and response times. To date, there has been no detailed investigation on combining eye-tracking measures with computational models in multi-attribute decision making. This dissertation aims to investigate possible approaches that integrate eye fixation data with computational models, and to provide new insights into decision dynamics underlying multi-attribute decision tasks. Specifically, I adopted and evaluated two different approaches to combine computational models with eye fixation data in intertemporal choice and simple risky choice. The first fixation-modulated approach feeds eye fixation data into sequential sampling models as exogenous inputs, and predicts behavioral responses based on combinations of feature values and eye fixations. The second generative modeling approach predicts both choices and eye fixation data simultaneously through a single model structure with three essential cognitive components - information sampling, feature representation, and preference formation. Different model configurations under the generative modeling approach were constructed for both intertemporal choice and simple risky choice, where different models hold different assumptions about feature representation in multi-attribute tasks. These models were quantitatively fitted to experimental data from Amasino et al. (2019) and Stewart et al. (2016), with the synthetic likelihood approximation method and a set of summary statistics, in a Bayesian framework. The models displayed good fits to the experimental summary statistics. The model comparison results suggested large individual variabil (open full item for complete abstract)

Committee: Brandon Turner (Advisor); Alexander Petrov (Committee Member); Ian Krajbich (Committee Member) Subjects: Psychology

Doctor of Education (Ed.D.), Bowling Green State University, 2019, Leadership Studies

Context: Research within athletic training has placed an emphasis on the importance of mentorship for the profession. Mentorship is cited as a key to professional socialization, a guide to student decision making in regard to continued education and career ambitions, and a motivator for clinical preceptors (Nottingham, Barrett, Mazerolle, & Eason, 2016; Mazerolle, & Benes, 2014; Klossner, 2008). Objective: To investigate attributes of mentorship within athletic training implementing a two-phase approach. Design: A two-phase approach. Phase I a modified Delphi technique. Phase II a national survey to novice athletic trainers'. Participants: Phase I included 16 experts of athletic training. Phase II included 107 novice athletic trainers. Results: The results of this study identify 86 attributes expert athletic trainers believe to be important to serving as an athletic training mentor. Phase II of the study identified how frequently novice athletic trainers' rate mentor attribute occurrence. Implications: This study presents an empirical list of mentor attributes important for athletic training mentors to practice. This study also identifies that the mentor attributes deemed important by exerts are rated to occur more frequently by the novice athletic trainer. This study supports the need for more intentional development of athletic training mentors and the mentoring relationships cultivated.

Committee: Paul Willis Ed.D (Advisor); Michael Decker Ph.D (Other); Amanda Jarriel Ph.D (Committee Member); Matthew Kutz Ph.D (Committee Member); Kristina LaVenia Ph.D (Committee Member); Patrick Pauken J.D, Ph.D (Committee Member) Subjects: Educational Leadership; Sports Medicine

MS, University of Cincinnati, 2017, Engineering and Applied Science: Civil Engineering

Today most structures are developed from huge number of materials, each with a particular function and complex assembly requirement (Crisman, 2017). All these materials which are used to create a building, are responsible for a large amount of global energy consumption, both in the form of embodied energy and operational energy. Until recently, it was believed that embodied energy formed a very small percentage of energy consumption as opposed to the operational energy over the life span of the building. But, Sartori et.al 2007 in their study presented that the embodied energy of a conventional building is up to 38% of the life cycle energy use. This implies that material selection plays a crucial role in reducing the overall environmental impact of the building. The material and resource (MR) category of Leadership in Energy and Environmental Design (LEED®) rating system aims at reducing the embodied energy of the building through a life cycle approach. But even after five years of the launch, v4.0 certified projects scored a lesser average point than v3.0 certified projects. This research aims at providing a roadmap and a compendium of resources to the architects and sustainability consultants to help achieve more points in the MR category of LEED. To do so, points scored by certified projects were analyzed. This revealed that construction and demolition waste management credit was the most popular credit. On the other hand, credit involving building and material reuse were rarely pursued. Secondly, a web questionnaire survey to understand the credit compliance pattern in v4.0 and those which lacks clarity towards achieving compliance. The survey revealed that the whole building life cycle assessment (WBLCA) compliance path is likely going to be the most popular compliance path under the MR credit building life cycle impact assessment for new construction projects but none of the certified new construction projects scored points by pursuing WBLCA. This lead to the (open full item for complete abstract)

Committee: Hazem Elzarka Ph.D. (Committee Chair); Anton Harfmann M.Arch. (Committee Member); Julian Wang Ph.D. (Committee Member) Subjects: Civil Engineering

MA, Kent State University, 2017, College of Communication and Information / School of Media and Journalism

This study analyzed how partisan elites' statements about climate change in tweets and press releases relate to liberal and conservative news media's descriptions of climate change. Drawing on the attribute agenda-setting theory, this study found that partisan news outlets' descriptions of climate change—including whether climate change is discussed as a legitimate problem and its potential policy remedies, etc.—corresponded to likeminded Congress members' descriptions of those aspects of climate change. Specifically, liberal and conservative media outlets—FOXNews.com and MSNBC.com—may display divergent attitudes toward climate change that more closely adhere to likeminded partisan (Republican or Democratic) Congress members' statements about climate change than those of ideologically disparate Congressional counterparts. This study analyzed attributes assigned to climate change issue in press releases and tweets by partisan Congress members and attributes of climate change assigned in FOX News and MSNBC news stories. The cross-tabulation results showed that press releases and tweets by MOCs focus on different climate change attributes; homogeneous association between policy agenda and media agenda is stronger when policy agenda and media agenda are likeminded; and news stories by FOXNews.com and MSNBC.com have stronger associations with their likeminded partisan tweets than with press releases. This study implies that political use of Twitter is not only more influential than other social media, but it can also be more influential than traditional political communication like Congressional press releases.

Committee: Chance York (Committee Member); Danielle Coombs (Committee Member); Diane Finch (Committee Member); Kristin Yeager (Committee Member) Subjects: Journalism; Political Science

Doctor of Philosophy, The Ohio State University, 1983, Graduate School

Committee: Not Provided (Other) Subjects: Philosophy

Master of Science (MS), Wright State University, 2014, Earth and Environmental Sciences

Wright State University acquired two vibroseis-sourced seismic reflection lines over the Dominion East Ohio Gabor Gas Storage field near Canton, Ohio. The data were gathered over a fully charged reservoir within the Clinton interval. Seismic attributes were applied to the seismic data for interpretation. The seismic response of nearby wells was modeled for comparison with the seismic lines. Within the seismic data a gas shadow was observed. The gas shadow coincides with an area of high initial production of wells targeting the Clinton interval for production. The gas shadow is also associated with broadening of the Packer Shell sidelobe. Modelling of the seismic response of well API# 3416925010000 shows a broadening effect of the Packer Shell sidelobe similar to that seen in the seismic data. This broadening is also associated with low porosity, implying that broadening of the Packer Shell sidelobe is indicative of a poor hydrocarbon reservoir.

Committee: Doyle Watts Ph.D. (Committee Chair); Ernest Hauser Ph.D. (Committee Member); David Dominic Ph.D. (Committee Member) Subjects: Earth; Energy; Geology; Geophysics; Petroleum Geology

Doctor of Philosophy, Case Western Reserve University, 2014, Management

The substantial resources being invested in biomedical research have generated revolutionary discoveries in medical science. However, only about 14% of research findings make their way into clinical practice to benefit patients. And this 14% takes on average 17 years to be utilized into practice. This gap between science and practice has been labeled as “the Valley of Death”. Improving scientist-physician partnership (SPP) has recently been identified as a mechanism that could improve the transfer of medical science to clinical practice. However, research on SPP is scarce, and the mechanisms of SPP are unclear. I report on an exploratory multi-phase mixed method study of the experience of SPP by both physicians and scientists. Specifically I ask: what is involved in SPP, and what relationships and factors influence SPP and its outcomes at personal, organizational and socio-cultural levels? I used a grounded theory approach in the first phase to identify the factors involved in SPP. My interviews with scientists and physicians revealed that the gap between medical knowledge and clinical practice is not only a language translation problem, but a wide cross-professional collaboration challenge, in which individual attributes, organizational structures and socio-cultural forces all affect the participation in and success of SPP. In order to confirm and validate the findings of the qualitative study, a theoretical model founded on phase 1 was formulated and empirically tested using a survey of 440 physicians and scientists who have had cross-professional collaboration experiences. Three studies compose the second phase. The first study focuses on the role of personal attributes influencing SPP. I find that professional identity, recognition motivation, challenge motivation, introversion and conscientiousness all affect SPP satisfaction and outcomes directly or indirectly. The second study investigates the influence of institutional forces and or (open full item for complete abstract)

Committee: Kalle Lyytinen PhD (Committee Chair); Richard Boland PhD (Committee Member); Antoinette Somers PhD (Committee Member); Daniel Simon MD (Committee Member) Subjects: Health Care; Health Care Management; Management; Organizational Behavior; Social Research

Doctor of Philosophy (PhD), Wright State University, 2010, Computer Science and Engineering PhD

A Grid community is composed of diverse stake holders, such as data resource providers, computing resource providers, service providers, and the users of the resources and services. In traditional security systems for Grids, most of the authentication and authorization mechanisms are based on the user's identity or the user's classification information. If the authorization mechanism is based on the user's identity, fine-grained access control policies can be implemented but the scalability of the security system would be limited. If the authorization mechanism is based on the user's classification, the scalability can be improved but the fine-grained access control policies may not be supported. We developed an enhanced version of the Community Authorization Service (CAS) which supports centralized, fine-grained access control by managing the memberships, service types, resource objects and security policies of a Virtual Organization (VO). The current CAS provides fundamental solutions regarding user privacy, authentication and authorization, but it has some limitations due to its centralized management of the security policies of a VO, in terms of scalability, flexibility and interoperability. We enhanced the CAS to support diverse security requirements within a dynamic Grid environment by enabling the CAS server to publish a proxy certificate embedding additional attributes of users. It allows the service providers to support customized services by analyzing the attributes of users and security policies. Previous researches on privacy-preserving in a Grid have focused on protecting the data stored in a data server and on securing the communication to protect exchanged data. The issue of preserving the privacy of users has not been a major issue in the security domain. However, as on-line transactions prevail and diverse user attributes are required for authorization decision, the privacy-preserving becomes an important issue. Attribute-Based Access Control (A (open full item for complete abstract)

Committee: Soon M. Chung PhD (Advisor); Nikolaos Bourbakis PhD (Committee Member); Yong Pei PhD (Committee Member); Xinhui Zhang PhD (Committee Member); Chansu Yu PhD (Committee Member) Subjects: Computer Science

Master of Science in Engineering (MSEgr), Wright State University, 2007, Mechanical Engineering

Over the last thirty years, there were tremendous advances in multidisciplinary design optimization in reducing computational cost, developing algorithms for efficient sensitivity analysis in reaching an optimum. Most of these efforts assumed a single objective (attribute) function and a multitude of constraints. Very little work has been done in including the designer's preferences as part of the optimization scheme and in addressing the ability to handle multiple attributes simultaneously. This need to develop a systematic method for including designer's preferences is the main focus of this research work. The concept of modeling preferences among multi-attribute alternatives is prevalent in consumer product marketing, and the current work adopts a widely used marketing method known as conjoint analysis. This method is often implemented to assess the individual part-worth of the attributes, which provides insightful knowledge of the products and is then further used to create new products in the market. Conjoint analysis can be integrated with optimization techniques for engineering applications. In this work, a novel method of combining advances from management science and engineering disciplines is implemented. Details about the conjoint analysis algorithm is discussed with an example of designing a pizza. Furthermore, the method is applied to structural engineering applications such as a cantilever beam, a fixed plate, and a composite lightweight torpedo demonstrating the advantages of the method.

Committee: Ramana Grandhi (Advisor) Subjects: Engineering, Mechanical

PhD, University of Cincinnati, 2012, Business: Business Administration

Consumers often face a choice among options described by differing amounts of information. In such situations, consumers may defer choice to avoid the uncertainty induced by missing information. In our study, we investigated the boundary conditions under which the tendency to defer choice can be reduced. In particular, we identified depletion, need for cognitive closure, and attribute accessibility as key situational factors related to the role of missing attribute information on choice deferral. We conducted three experiments that show that when the need for cognitive closure is high, depleted (vs. non-depleted) individuals are more likely to defer choice when attribute-accessibility is high. However, when the need for cognitive closure is low, depleted (vs. non-depleted) individuals are more likely to defer choice when attribute-accessibility is low. Furthermore, spontaneous inference and perceived uncertainty mediate the depletion effect, such that spontaneous inference reduces perceived uncertainty and this decreases the likelihood of choice deferral. Finally, depleted individuals are more sensitive to the status quo when the need for cognitive closure is low, while non-depleted individuals are more sensitive to the status quo when the need for cognitive closure is high. Implications of the results for understanding choice deferral are discussed.

Committee: Frank Kardes PhD (Committee Chair); Inigo Arroniz PhD (Committee Member); Chung-Yiu Chiu PhD (Committee Member) Subjects: Marketing

PhD, University of Cincinnati, 2008, Engineering : Mechanical Engineering

The severity of combined aerodynamics and power transmission response in high-speed, high power density systems such as a rotorcraft is still a major cause of annoyance in spite of recent advancement in passive, semi-active and active control. With further increase in the capacity and power of this class of machinery systems, the acoustic noise levels are expected to increase even more. To achieve further improvements in sound quality, a more refined understanding of the factors and attributes controlling human perception is needed. In the case of rotorcraft systems, the perceived quality of the interior sound field is a major determining factor of passenger comfort. Traditionally, this sound quality factor is determined by measuring the response of a chosen set of juries who are asked to compare their qualitative reactions to two or more sounds based on their subjective impressions. This type of testing is very time-consuming, costly, often inconsistent, and not useful for practical design purposes. Furthermore, there is no known universal model for sound quality. The primary aim of this research is to achieve significant improvements in quantifying the sound quality of combined aerodynamic and power transmission response in high-speed, high power density machinery systems such as a rotorcraft by applying relevant objective measures related to the spectral characteristics of the sound field. Two models have been proposed in this dissertation research. First, a classical multivariate regression analysis model based on currently known sound quality metrics as well some new metrics derived in this study is presented. Even though the analysis resulted in the best possible multivariate model as a measure of the acoustic noise quality, it lacks incorporation of human judgment mechanism. The regression model can change depending on specific application, nature of the sounds and types of juries used in the study. Also, it predicts only the averaged preference scores and do (open full item for complete abstract)

Committee: Teik C. Lim PhD (Committee Chair); Jay H. Kim PhD (Committee Member); Mark J. Schulz PhD (Committee Member) Subjects: Acoustics; Mechanical Engineering

PhD, University of Cincinnati, 2007, Engineering : Computer Science

The internet era and high speed networks have ushered in the capabilities to have ready access to large amounts of geographically distributed data. Individuals, businesses, and governments recognize the value of this available resource to those who can transform the data into information. These databases, though valuable as individual entities, become significantly more valuable when they function as parts of a federated database and their data can be aggregated for collective mining or computations. This requires data mining algorithms to shift their focus from working with single databases to efficiently working with federated databases. Any such methodology must address issues relating to the security and privacy of data, cost of communication among the database nodes and the overlap of attributes among the databases. Most of the algorithms designed for mining single databases are not easily adaptable for federated databases. We present a new perspective for mining vertically partitioned databases that balances the information loss of perturbation methods and those of secure multi-party or encryption methods. We achieve scalable and secure computation on a general vertical partitioning of an implicit global database among the explicit federated components. We use an implicit aggregation to efficiently compute first and second order statistical quantities, and inter-tuple distance based clustering for data in the federated databases. We demonstrate these by computing the covariance matrix and the k-nearest neighbor and other clustering for databases. Our computation of the covariance matrix has worst case message complexity of n(2σ)k−1 divided by k, where n is the number of tuples on the learner and each of the participating databases finds on average tuples per local query. The k-nearest neighbors can be computed with message complexity in the worst case of σk−1. The information exchanged between the nodes is minimized and consists of summaries derived from multi (open full item for complete abstract)

Committee: Dr. Raj Bhatnagar (Advisor) Subjects: Computer Science

MS, University of Cincinnati, 2003, Engineering : Industrial Engineering

Process planning has been imposed by the Computer Integrated Manufacturing (CIM) ideology a post-design nature, and researches in Computer Aided Process Planning (CAPP) have been mistakenly directed to automatic process planning. However, the nature of process planning dictates a successful CAPP system should be a decision support system rather than a decision generation system. Setup planning is an intermediate phase of process planning, and automatic setup planning constitutes a critical component of CAPP. The contradiction between the seemly productive research in the automatic setup planning literature and the reality of a near zero commercial application has to be ascribed to the same misconceived goal of freeing human being from every decision making process. In this thesis, a quantitative setup plan evaluation system driven by multiple attributes utility analysis coupling with manufacturing error simulation is proposed to serve three purposes, 1) to answer what is optimality of setup plans, 2) to build a framework of comparison for setup plans in practice and 3) to incorporate in existing automatic setup planning systems a human interface to fulfill their potential values.

Committee: Dr. Samuel H. Huang (Advisor) Subjects: Engineering, Industrial

Master of Science (MS), Ohio University, 1997, Industrial and Manufacturing Systems Engineering (Engineering)

The purposes of this thesis are to apply data mining methodologies to explore the regularity of data generated by a genetic algorithm performing a scheduling operation and develop a rule set scheduler to approximate the genetic algorithms scheduler. Genetic algorithms are stochastic search algorithms based on the mechanics of genetics and natural selection. After evolution of each generation, the survivors are those best adapted to their environment. Because of genetic inheritance, these survivors are, to a certain degree, similar. For genetic algorithms in job shop scheduling problems, a solution presents an operation sequence for resource allocation. Among these optimal or near optimal solutions, similar relationships may exist between operations and sequential order, as well as characteristics of operations and sequential order. These relationships may be generalized to dispatching rules. Data mining, developed for extracting knowledge from data, employs machine learning and database management systems to extract useful information from data. This thesis uses an attribute-oriented induction methodology to explore the relationship between an operations' sequence and its attributes - operation order, processing time, remain processing time and machine load, and develop a rule set schedule with the discovered knowledge.

Committee: David Koonce (Advisor) Subjects: Engineering, Industrial

Master of Science (MS), Ohio University, 2005, Industrial and Manufacturing Systems Engineering (Engineering)

This paper looks at a current method of generating geometric forging models for jet engine components, specifically jet engine disks and aims to find geometric models that require less information and retain the existing model's level of accuracy. In order to create models that require less information Attribute Estimating Relationships (AERs) are generated to estimate attribute dimensions, these estimated attribute dimensions are used to generate the forging model of the disk. AERs are generated using two different methods the Standard Deviation (SD) method and the Sum of Squares (SS) method. These two methods are analyzed and the SS method is determined to be superior in this case. Using the SS method to generate AERs it is possible to develop a geometric forging model that requires less information and also retains a high level of accuracy.

Committee: Dale Masel (Advisor) Subjects:

PHD, Kent State University, 2006, College of Business and Entrepreneurship, Ambassador Crawford / Department of Management and Information Systems

This dissertation explores the effect of information disclosure interventions on the performance of Reverse Multi-attribute Auctions. A conceptual model that integrates information asymmetry theory, signaling theory and decision process theory is developed. Computer-based experiments are then employed to compare the performance of multi-attribute auctions that make use of different information disclosure policies. Results indicate that having preference and public information leads to better performing auctions than having private or no information. Public information appears to trigger more aggressive bidding than all other information types assessed. Finally, preference, public and private information all play an important role in building bidder confidence.

Committee: Murali Shanker (Advisor) Subjects: Business Administration, General