Master of Science, The Ohio State University, 1970, Graduate School

Committee: Not Provided (Other) Subjects:

Master of Science, The Ohio State University, 1987, Graduate School

Committee: Not Provided (Other) Subjects:

Master of Science in Electrical Engineering, University of Dayton, 2024, Electrical Engineering

This thesis presents a novel method to control an industrial robotic arm using multiple sensors. This system consists of a hybrid brain activity and vision sensors that convey a human being's intention and visual perception. We fuse and analyze the data from those sensors using a machine learning-based approach to automatically guide the manipulator to a designated location. We believe that this Brain–Machine–Interface (BMI) can greatly alleviate the burdensome traditional method used to program a robot (greatly aids the end-user). We experiment with different modular configurations for the brain activity information, i.e., parallelized models and what we refer to as a global model for fusing the information. We explore various machine learning and pattern recognition techniques as well as existing feature selection methods. Our experimental results show that the subject can control the robot to a destination of interest using a machine—robot–interface. We attain accuracy in the order of 99.6% when it comes to the desired motion and 99.8% for the case of deducing the desired characteristic (color) of the targeted object. These results outperform any similar existing approaches that we have researched. Moreover, in comparison to those similar operational systems, we present a unique modular configuration for brain activity interpretation and object detection mechanism that yields an overall system that is highly computationally efficient. Although, in this work, we implemented and demoed our approach using a simple pick and place demo, our work presents the basic structure underlying a system that can be efficiently used to benefit people with restricted ability to function physically (tetraplegic patients), and allowing them to perform complex and robotics related duties in an industrial setting.

Committee: Temesguen Messay-Kebede (Advisor); Barath Narayanan (Committee Member); Russell Hardie (Committee Member) Subjects: Computer Engineering; Computer Science; Electrical Engineering; Engineering; Remote Sensing; Robotics

Doctor of Philosophy, The Ohio State University, 2023, Physics

Low-mass galaxies provide an exciting opportunity to learn about many open questions in astronomy, including topics as seemingly disparate as galaxy formation and evolution and the particle nature of dark matter. To take full advantage of these galaxies however, we must devote energy to understanding the basics about their mass and environment. Traditionally this requires distance measurements that use expensive space-based imaging or spectra. An alternative approach is to exploit the discrete nature of galaxy stellar populations to measure so called surface brightness fluctuations (SBF), which change as a function of distance. SBF can provide accurate distances to galaxies without the stringent observational requirements necessary for other distance techniques and often without the need for extensive follow-up data after discovery. Given the huge number of low-mass galaxies being discovered in recent surveys and the upcoming deep imaging observatories that will undoubtedly uncover even more such galaxies, SBF offers a promising solution to obtaining distances to a revolutionary sample of these fascinating systems. In this dissertation, I develop an image processing pipeline with the goal of measuring SBF distances to dwarf galaxies with the Large Binocular Telescope. First, I demonstrate the technique with a quenched galaxy called Blobby in the outskirts of the M81 group. I use the measured distance to argue that Blobby is part of an understudied population of galaxies called backsplash galaxies, and that its mass and stellar population have likely been significantly affected by a past interaction with the group. Next, I measure the SBF of several other Local Volume galaxies, some with widely respected tip of the red giant branch (TRGB) distance measurements. I demonstrate that SBF is competitive with other distance methods and confirm (or reject) associations of dwarfs in the sample with several host galaxies. I discuss challenges with the SBF method, particula (open full item for complete abstract)

Committee: Annika Peter (Advisor); Klaus Honscheid (Committee Member); Linda Carpenter (Committee Member); Todd Thompson (Committee Member) Subjects: Astronomy; Astrophysics; Physics

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

In what circumstances will we fall prey to the sunk cost fallacy? Based on construal level theory, the present research investigated psychological distances (proximal vs. distal) as moderators that influence people's decision making with sunk costs. I ran a series of studies to test the effects of different types of psychological distances (spatial, temporal, social, and hypothetical) on sunk cost fallacy using scenario-based questions. I found significant but weak evidence that psychological distance may impact decision-making processes when sunk cost is involved. However, participants' construal level was not measurably altered by psychological distance condition. Despite the weak behavioral evidence, I followed up on these studies to test whether psychological distances altered implicit decision-making processes. In this follow-up study, I manipulated sunk costs and spatial psychological distance. I then applied participants' reaction times and decisions to a Diffusion Decision Model (DDM). In this model, I decomposed the underlying processes of decision making with sunk cost by comparing proximal and distal psychological distance conditions. Though the behavioral results did not show explicit differences in sunk cost fallacy between these two conditions, participants tended to respond faster in distal conditions. Further, the DDM suggested that the narrow threshold for evidence accumulation can be predicted by the differences between proximal and distal conditions. This work advances our understanding of psychological distances and decision making with sunk cost.

Committee: Brooke Macnamara (Committee Chair); Mark Turner (Committee Member); Anastasia Dimitropoulos (Committee Member); Heath Demaree (Committee Member) Subjects: Cognitive Psychology

Doctor of Philosophy, The Ohio State University, 2022, City and Regional Planning

The lack of access to affordable and healthy food is cited as a significant reason for health disparities in society and threatens public health. For decades, trends in the urbanization and food retail sector have left a considerable part of the society deprived of affordable and healthy food outlets in their neighborhoods. This is especially the case for low-income groups and people of color. In addition to the uneven spatial distribution of healthy and affordable food outlets, defining food access in itself is a very complex task. This complexity makes developing strategies to solve food access issues in society challenging. People's or households' decisions regarding where to shop, how far to travel, and what to purchase, as well as different individual and household attributes, ranging from where they live to how much they value diet, are all important. Hence, the following dissertation aims to examine the different characteristics that impact where households shop, how far they travel, and what they purchase. The goal is to broaden our understanding of food access. The dissertation includes three different studies using information from the USDA's National Household Food Acquisition and Purchase Survey (FoodAPS) dataset. Specifically, the first study addresses food store choice of shoppers, including their ability to access the nearest healthy store (supermarket/superstore), unhealthy stores (gas station, convenience store, dollar store), and other healthy stores (specialty stores, farmers' markets, medium to large grocery stores). The first study highlights how price and distance matter for selecting the nearest healthy store. When the nearest healthy store is a far distance, shoppers are driven to purchase at nearby stores, which may be unhealthy or small healthy stores, such as a grocery store. The second study examines factors that affect the distances household travel for food. The surrounding food environment is associated with total real traveled miles (open full item for complete abstract)

Committee: Bernadette Hanlon (Advisor) Subjects: Urban Planning

Doctor of Philosophy, The Ohio State University, 2017, City and Regional Planning

Research on travel behavior continues to be one of the most prominent areas in the transportation area. Planners and policymakers try to understand and manage travel behavior. Making and implementation of travel demand management (TDM) policies greatly rely on the understanding of the determinants of activity-travel patterns and travel demand. Among the activity-travel patterns, trip chaining and joint travel have received much research interest. Trip chaining is typically viewed as a home-based tour that connects multiple out-of-home activities. Joint travel is commonly defined as traveling with others. Travel demand is generally measured by trip generation and travel distances. Investigating different aspects of travel behavior helps us better understand the links between activity participation and mobility, and improves the evaluation of the transportation infrastructure investments and policies such as high occupancy vehicle (HOV) lanes and vehicle miles traveled (VMT) reduction programs. Several studies have regarded trip chaining, joint travel, trip generation, and travel distances as different dimensions of travel behavior to be examined in terms of various socio-demographics and urban form factors. However, limited work has been done to use activity-travel patterns as mediating variables and analyze how trip chaining and joint travel shape the resulting travel demand. Furthermore, relationships between travel behavior and urban form factors at out-of-home activity locations remain unclear. Based on the 2012 travel survey data from the Cleveland Metropolitan Area, this study first investigates the relationships among trip chaining, joint travel, home-based tour generation, and travel distances at three different levels: tour, individual, and household levels. Second, the influences of socio-demographics and urban form factors at tour origins and destinations on travel behavior are examined simultaneously. Lastly, while using trip chaining and joint travel a (open full item for complete abstract)

Committee: Gulsah Akar (Advisor); Zhenhua Chen (Committee Member); Jean-Michel Guldmann (Committee Member) Subjects: Land Use Planning; Transportation; Transportation Planning

Doctor of Philosophy, The Ohio State University, 1955, Graduate School

Committee: Not Provided (Other) Subjects: Psychology

MS, Kent State University, 2009, College of Arts and Sciences / Department of Computer Science

There is still much research in the areas of routing and location updates in cellular communication networks. Given the limited amount of memory and power of these network devices it is desirable to find the most effective and resource conscious method for solving routing and location update problems. Recently, these problems have been addressed for simply connected cellular networks and significant results were achieved.  An effective method for addressing, location update and routing has been offered using a method of isometric embeddings into a set of three trees.  This method however does not fully work when a hole is present in the network.  To handle networks containing holes, a variation of the above method is required, where the cellular network will be decomposed into few sub-graphs that encompass the properties of the original network graph.  Proposed here is a method that will handle the above mentioned problems on cellular networks with holes, namely holes with disc structures and other shapes that have the convex property.  Also presented are two distinct methods for handling networks with multiple disc-structured holes.  These methods will also use sub-graphs to reduce the number of holes while preserving all shortest paths.

Committee: Feodor F. Dragan PhD (Advisor); Ruoming Jin PhD (Committee Member); Hassan Peyravi PhD (Committee Member) Subjects: Computer Science