Doctor of Manufacturing Management, University of Toledo, 2007, Manufacturing Management

This research studies the impact of various supply chain management (SCM) practices - external to the organization - and modularity based manufacturing practices - within the organization - on supply chain responsiveness. The study, further investigates the dimensions of supply chain responsiveness through an extensive literature review. It develops a reliable and valid instrument for the supply chain responsiveness construct, which will be beneficial for both practitioners and academicians. The study also assesses the impact of supply chain responsiveness on the outcome variable - competitive advantage - of the firm. The large scale web-based survey yielded 294 responses from industry professionals in the manufacturing and supply chain area. The data collected was put through rigorous statistical analysis to test for content, construct, and criterion-related validity, as well as reliability analyses. Further a structural equation model was developed to test the relationships between SCM practices, modularity based manufacturing practices, supply chain responsiveness, and competitive advantage. In addition, rigorous regression analyses and MANOVA were performed to analyze the effects of various relationships at the sub-construct level as well as item level. The research findings supported the hypotheses that SCM practices positively impact supply chain responsiveness, modularity based manufacturing practices are positively associated with supply chain responsiveness, supply chain responsiveness positively impacts competitive advantage of a firm, and SCM practices are positively associated with competitive advantage of a firm. The research also uncovered the critical and specific practices (at the sub-construct and item level) that increase supply chain responsiveness. Furthermore, the study uncovered the specific SCM practices and supply chain responsiveness criteria that increase competitive advantage of a firm.

Committee: Subba Rao (Advisor) Subjects: Business Administration, Management

MARCH, University of Cincinnati, 2020, Design, Architecture, Art and Planning: Architecture

ReGen: Detroit will look to occupy a unique space between the delicate balance of old and new in the Motor City. American post-industrial cities, were once leveled and left vacant, act as the ideal design “tabula rasa” and architectural stage. The architect can project their own ideals to create a new city that is more efficient, vibrant and harmonious with its historical context. If correctly applied, the architecture will work with the nature that has grown from the urban decay. ReGen will encapsulate three aspects 1. Modularity In the US, the car has greatly shaped urban design and western civilization. Detroit has mass produced, lived and was eventually diminished by the automobile, one of the most prolific and successful modular spaces known to man. By embracing the modular ingenuity that embodied Detroit for many years during its prosperity the city can be made anew. Pre-constructed, architecturally designed pods or shipping container spaces are becoming increasingly popularized in contemporary but for their many benefits they are still being extremely under-utilized in the American architectural and urban design landscapes. Modern construction capabilities allow us to design spaces that can have the affect in lowering overall building costs and constructing in a more cost effective environmentally friendly and less invasive way. The existing Detroit infrastructure was originally created to be a large transportation hub for over 1.8 million people. Today, there is opportunity to effectively transport modular units via car or truck anywhere in the city. In the more near future, shipping containers throughout the world can be brought to Detroit by train or boat. These containers can be retrofitted for reuse and can be purchased cheaply by Detroiters (similarly to Henry Ford's assembly line) to utilize in a number of ways. Because of their adaptability the units can as be plugged into several newly designed frameworks in the city. 2. Urban Agriculture (open full item for complete abstract)

Committee: Michael McInturf M.Arch. (Committee Chair); Elizabeth Riorden M.Arch. (Committee Member) Subjects: Design

MS, University of Cincinnati, 2019, Engineering and Applied Science: Mechanical Engineering

The purpose of this thesis is to discuss the development of a novel method for the cleaning of trench drains. It deals with the design, conceptualization, analysis and testing of a device which fits into the drain and cleans it without needing to interfere with the surrounding traffic or the drain itself. The project was an effort to shift the cleaning process for the trench drains from manual to either semi-automated or automated methods. Due to the previous methods like manual cleaning and cleaning through water jets being slow and highly inefficient processes respectively, there was a need for an automated mechanism which was fast, reliable and did not waste resources. The transition was intended to ensure a safer process with lesser manpower required in addition to being easier to implement. Over the course of developing this mechanism, two complete prototypes were designed and implemented in the drains. The performance of both the models has been discussed in detail. The prototype developed has three main sections to implement these functionalities: 1. A drive system to make it move forwards and backwards in the drain. This system controls the overall feed of the robot and the suction hose inside the drain. 2. A suction hose with a hose attachment and a shovel. This is the main section involved with the cleaning inside the drain. 3. A cutting mechanism with rotating brushes due to which all the clogged and hardened dirt is loosened and falls to the drain bottom from where it can be sucked into the hose efficiently. This ensures easy removal of the dirt from the drain. Overall, the various tests were conducted on the prototypes at different stages of their development which proved the working concept of the design and their functions. The new cleaning mechanism was found to work and operate smoothly for a little more than four total sections (14.2 ft) of the drain with it being entirely inside the drain throughout the operation time. Ideally, the (open full item for complete abstract)

Committee: Janet Jiaxiang Dong Ph.D. (Committee Chair); Hazem Elzarka Ph.D. (Committee Member); Jing Shi Ph.D. (Committee Member) Subjects: Mechanical Engineering

Doctor of Philosophy, The Ohio State University, 2018, Computer Science and Engineering

Worldwide the amount of data generated by the medical community is staggering, and increasing dramatically. Using this data to improve patient care using analytics and machine learning is a huge and largely untapped opportunity. The most important medical data captured exist in patients' electronic health records (EHRs) which are maintained and utilized by health care providers. EHRs consist of rich and comprehensive patient-specific information from a large number of sources in different formats with heterogeneous data types. There are numerous challenges in attempting to apply existing analytic tools and methodologies to this data. Many features extracted from EHRs have dependent relationships - for example, “flu” and “high body temperature”. Bayesian networks, as one of the few modeling methodologies which capture feature dependence rather than assuming independence, provide a flexible foundation for modeling EHRs. However, existing Bayesian network learning methodologies produce models whose complexity makes them difficult for clinicians to utilize or even interpret. Therefore, better model visualization methodologies, as well as learning methods which produce models more amenable to simplification and summarization, are critical to making them interpretable and useful to clinicians, and therefore to improving patient care. In this dissertation, I present a framework for predictive analysis of patient clinical data, from feature extraction to model analysis. I first study straightforward machine learning approaches on extracted EHR features and find that incorporating diagnosis features improves area under ROC curve (AUC) by 10% compared to a baseline. Because of the many dependencies between features extracted from EHRs, I next investigate Bayesian network models, in which my clinician collaborators have identified known and suspected high pressure ulcer risk factors. The models also substantially increase sensitivity of the prediction - nearly three times (open full item for complete abstract)

Committee: Raghu Machiraju (Advisor); Sookyung Hyun (Committee Co-Chair); Srinivasan Parthasarathy (Committee Member); Guy Brock (Committee Member); Lynda Hardy (Committee Member) Subjects: Computer Science; Nursing

Doctor of Philosophy, University of Akron, 2014, Integrated Bioscience

A longstanding question in biology is why phenotypic diversity is unevenly distributed across the tree of life. Such differences can be caused by both extrinsic (e.g., natural selection) and intrinsic factors (e.g., how a trait functions). Despite numerous examples of diversification in form and function of complex biomechanical traits, we know relatively little about these processes in ornamental traits. Diverse ornamental feather colors in birds can be produced either by absorption (pigment-based colors) or scattering of light by feather nanostructures (structural colors). Because structural colors are deterministically related to the nanostructures that produce them, they are excellent systems to study form-function relationships and diversity of ornamental traits. In my dissertation I combine methods from physics and evolutionary biology to understand how proximate mechanisms explaining color (coherent light scattering) explain patterns of color diversity using iridescent feathers as a model system. Specifically, I ask two fundamental questions, one proximate and one ultimate, about iridescent colors: i) How are iridescent colors produced? and ii) What are the implications of how iridescent traits function for how they evolve? To tackle these questions, I sampled a nanostructurally diverse range of species, quantified their nanostructures with TEM and optical microscopy, experimentally tested the roles of different nanostructural traits in producing color by modifying them at the nanometer scale with FIB milling or humidity changes, and linked form and function with optical modeling. I then used simulation-based approaches and large-scale comparative analysis of color diversity to explore evolutionary consequences of functionally modular nanostructures in feathers. Together, my results suggest that morphological novelties in birds have, at least in part, allowed birds to achieve their vast morphological and colour diversity, and the way a color is produced has i (open full item for complete abstract)

Committee: Matthew Shawkey Dr. (Advisor); Blackledge Todd Dr. (Committee Member); Luettmer-Strathmann Jutta Dr. (Committee Member); Dhinojwala Ali Dr. (Committee Member); Doucet Stephanie Dr. (Committee Member) Subjects: Biology; Physics

PhD, University of Cincinnati, 2007, Engineering : Biomedical Engineering

An important goal for biomedical research is to elucidate causal and modifier networks of human disease. While integrative functional genomics approaches have shown success in the identification of biological modules associated with normal and disease states, a critical bottleneck is representing knowledge capable of encompassing asserted or derivable causality mechanisms. Both single gene and more complex multifactorial diseases often exhibit several phenotypes and a variety of approaches suggest that phenotypic similarity between diseases can be a reflection of shared activities of common biological modules composed of interacting or functionally related genes. Thus, analyzing the overlaps and interrelationships of clinical manifestations of a series of related diseases may provide a window into the complex biological modules that lead to a disease phenotype. In order to evaluate our hypothesis, we are developing a systematic and formal approach to extract phenotypic information present in textual form within Online Mendelian Inheritance in Man (OMIM) and Syndrome DB databases to construct a disease - clinical phenotypic feature matrix to be used by various clustering procedures to find similarity between diseases. Our objective is to demonstrate relationships detectable across a range of disease concept types modeled in UMLS to analyze the detectable clinical overlaps of several Cardiovascular Syndromes (CVS) in OMIM in order to find the associations between phenotypic clusters and the functions of underlying genes and pathways. Most of the current biomedical knowledge is spread across different databases in different formats and mining these datasets leads to large and unmanageable results. Semantic Web principles and standards provide an ideal platform to integrate such heterogeneous information and could allow the detection of implicit relations and the formulation of interesting hypotheses. We implemented a page-ranking algorithm onto Semantic Web to prioriti (open full item for complete abstract)

Committee: Dr. Bruce Aronow (Advisor) Subjects:

PhD, University of Cincinnati, 2003, Arts and Sciences : Philosophy

In this dissertation I argue for a wider and more robust notion of the modularity of mind thesis. The developmental disorder of autism is the prime analytic tool for developing this approach. I argue that a variety of other approaches are deeply flawed in that they cannot account for the autistic spectrum disorder. I mean by this the autistic profile of deficits such as the lack of social interaction and the avoidance of social contact. I begin with Fodorian modularity. I argue that autism presents us with a case that threatens the division Fodor has between modules and central systems. The autistic disorder exemplifies an area of higher cognition (theory of mind) that has many of the properties commonly associated with modular processing. Since Fodor cannot opt for a modular account of theory of mind it must be that his account of central systems is incorrect. I next argue that Baron-Cohen's amended modular architecture cannot explain autism since the autistic deficit cannot be due to a defective module for processing intentional action. Furthermore, his use of modularity threatens to make his view of cognition incoherent. Finally I take up Gopnik and Meltzoff's approach that eschews any type of modularity and instead posits a general learning mechanism. If autism, as they claim, were a general theorybuilding problem, then one should expect to see other behavioral deficits in other areas of autistic cognition. We do not. I then offer an alternative version of modularity inspired by Karmiloff-Smith (1992). It gives us advantages. On Karmiloff-Smith's account we would expect the autistic deficit to have more perceptually basic components and recent research is bearing this out. Progressive modularity also provides us with a framework in which to understand the ways autistic persons understand the social world. This approach also seeks to unify the cognitive work being done on development with burgeoning work on development in neuroscience.

Committee: Dr. Robert C. Richardson (Advisor) Subjects: Philosophy

Doctor of Manufacturing Management, University of Toledo, 2008, Manufacturing Management

Build-to-order Supply Chain (BOSC) is viewed by many researchers as an effective way to achieve high customer value because BOSC can fulfill an individual or a group of customers' orders while maintaining low cost, cutting inventory cost, eliminating waste, and achieving short response time through flexible manufacturing and integrated logistics. BOSC is needed to support mass customization, which is the ability to make high variety and low cost products and deliver them quickly to meet the diverging needs of customers. Mass customization can be achieved by implementing modularity-based manufacturing practices, postponing production steps that determine product features and performances, and applying IT to coordinate actions and speed up final production and delivery. BOSC also emphasizes the importance of partnership with suppliers and customers, web-based technologies, and rapid transport and delivery. This research proposes that BOSC capability (i.e., cost effectiveness, volume effectiveness, and timely delivery) can be achieved through three dimensions of supply chain practices: modularity, postponement, and partnership. This study applies social dilemma theory and resource dependency theory to build a model to explore the mechanism of inducing these three dimensions of supply chain practices. Social dilemma theory states that members in an alliance have a higher tendency to defect (e.g., withhold information or not fully participate) rather than to cooperate because members may achieve higher short-term profits through defecting (Dawes, 1980). These defects will cause long-term failure of an alliance, and members will loose their profits in the long run. Resource dependency theory indicates that members in a supply chain should depend and cooperate to move out of the dilemma of defecting to gain higher profits in the long-run instead of competing with one another. The literature suggests two types of solutions to change the views of members in an alliance from (open full item for complete abstract)

Committee: Mark Vonderembse (Committee Co-Chair); T. S. Ragu-Nathan (Committee Co-Chair); Thomas Sharkey (Committee Member); Hongyan Zhang (Committee Member) Subjects: Management

Doctor of Philosophy, The Ohio State University, 1997, Business Administration

Mass customization has quickly entered the lexicon of popular business. Many companies are striving to provide customized products and services to their customers at low costs. However, the concept of mass customization represents an apparent paradox for manufacturing by combining customization and mass production, offering unique products in a mass produced, low cost, high volume production environment. Historically, production lines were designed to manufacture either customized, crafted products or mass produced, standardized products. Customized products are made using low volume processes that cope well with a high variety of products. Similarly, a mass production process is chosen for making standardized products in a high volume, low cost environment. In contrast to this traditional dichotomy, mass customization provides a one-of-a-kind product manufactured on a large scale allowing customers to purchase a customized product near the cost of a mass produced item. The manufacturing systems required to support mass customization has not been adequately discussed in extent research. This study explores the multi-faceted nature of mass customization by developing a typology of mass customization approaches and the operational parameters required to support each approach. Notions of customer involvement and modularity coupled with modularity types in a conceptual model to provide a basis for identifying mass customizers. The conceptual model suggests a set of configurations of process and infrastructure which work in concert to support the various types of mass customization. This conceptual model is tested through empirical investigation of 194 companies producing both consumer and industrial products. In addition to developing new scales to capture the concept of mass customization, the survey instrument includes scales relating to the environment, performance, business and operations strategy as well as choices made with respect to process, organization and inf (open full item for complete abstract)

Committee: Peter Ward (Advisor) Subjects:

Doctor of Philosophy (PhD), Ohio University, 2009, Biological Sciences (Arts and Sciences)

The research presented here is an examination of the morphology and histology of several broad categories of skin structures in living amniotes, together with analyses of the osteological correlates associated with each skin category. The epidermal horn and armor-like dermis of extant rhinoceros are examined in detail, and the evolution of both of these skin structures is reconstructed in phylogenetic context from fossil evidence. The evolution of rhinoceros dermal armor is strongly associated with the evolution of shearing tusks used in fighting behaviors, and precedes the evolution of epidermal horns by ~20 Ma. The distribution and morphology of cephalic scales, rhamphothecal plates,and feathers in Sauropsida is then examined in an analysis of evolutionary modularity.Two distinct regions of skin, one around the mouth and another on the skull roof, show independent patterns of morphological evolution, suggesting that skin features in these regions are interconnected as modules. Rhamphotheca in neornithine birds are one possible expression of this modularity. In a separate analysis, plates of compound rhamphotheca (e.g., in albatross) are shown to be homologous with regions of simple rhamphotheca. Rhamphotheca occupy a topographically similar area of skin in nearly all neornithine birds, and the variable expression of softer grooves leads to several homoplastic occurrences of compound rhamphotheca. Several adaptive scenarios have been proposed for novel skin structures in non-avian dinosaurs, but the lack of direct fossil evidence for skin in these animals and the ambiguity in available reconstructions has made it difficult to evaluate these scenarios. Detailed reconstructions for cephalic skin structures drawing on gross morphology and paleohistology are presented for the lineage of centrosaurine dinosaurs leading to Pachyrhinosaurus and for the abelisaurid theropod Majungasaurus. The transition from tall horn cores to gnarled pachyostotic bosses in centrosaurine d (open full item for complete abstract)

Committee: Lawrence M. Witmer PhD (Advisor) Subjects: Biology; Paleontology; Zoology

Master of Arts, University of Toledo, 2013, Philosophy

A productive relationship between the philosophy of mind and the empirical cognitive sciences not only is possible, but also is pursued productively by practitioners from both sides. In the first two chapters, I consider two examples of sets of concepts (“folk psychology” and the “architecture of the mind”) which are shared between the philosophy of mind and the empirical cognitive sciences and analyze them from both perspectives. I introduce a historical-analytical apparatus called “inherited ontologies” to track these sets of concepts and how they emerge, mutate, and replicate over time in order to show that what can begin as semantic opacity can end as ontological confusion. I argue that the important question is not whether we inherit our implicit ideas about the mind from our genes or our culture, but how shared inheritance manifests in different ways in different individuals. In the third chapter, I argue that the plurality of kinds of minds should inform how we research our minds. Instead of supposing that a plurality of approaches to study a plurality of minds is a problem to be solved, we should embrace cognitive and methodological diversity as not only possible but desirable in a shared problem space. The cognitive sciences should develop a unity of purpose without collapsing into a presumed uniformity of subject matter.

Committee: Madeline Muntersbjorn Ph.D (Committee Chair); John Sarnecki Ph.D (Committee Member); Stephen Christman Ph.D (Committee Member) Subjects: Artificial Intelligence; Behavioral Sciences; Cognitive Psychology; Education; Linguistics; Metaphysics; Neurosciences; Philosophy; Philosophy of Science; Psychology; Science History