Master of Science, The Ohio State University, 2013, Computer Science and Engineering

Non-volatile memory devices or flash, even with many advantages, still have a few problems such as the inability to update data in place. This necessitates the need for a garbage collector (GC) that can collect active data and create space by erasing flash blocks. However this is a very costly operation that increases the write latency thereby lowering the efficiency of the flash device. The frequency at which the GC is invoked by the underlying file system depends on the data's traffic pattern as well as the fullness of the device. It is therefore important to study different GC algorithms for different traffic patterns and at varying fullness levels in order to find the most efficient one for a particular situation. In this report we study the efficiency of byte address non-volatile memory devices (such as NOR), under varying traffic patterns. We study the algorithms using simulations coded in Matlab. A simulator for the flash file system as well as the GC algorithms and various applications traffic was developed and used for the study. We compare and contrast the efficiency and the time taken for the GCs at utilization levels ranging from 2% to 98%. We also model some of the algorithms analytically and find that our analytical results match our simulations. The performance results for five different GC algorithms for flash devices for three traffic/access patterns are presented in this report. The access patterns include long-tailed, uniform and bimodal distributions. The algorithms studied are a round-robin style first in first out (FIFE), a greedy least active clean (LAC), 3-Generation (3-Gen) GC, N-Generation (N-Gen) GC (a generalized generation algorithm) and Eta-N-Generation (Eta-N-Gen) GC (a variation on N-Gen). The results indicate that round-robin style GC algorithm (FIFE) and greedy algorithm (LAC) perform better in most of the scenarios than generational algorithms. This is counter-intuitive to the existing norms. LAC slightly underperforms the FI (open full item for complete abstract)

MS, University of Cincinnati, 2020, Engineering and Applied Science: Mechanical Engineering

This thesis discusses the design and testing of a robot constructed to collect ticks from rugged terrain in remote areas, focusing on locating the ideal design, material, and center of gravity to ensure maximum tick collection without causing instability. The design was tested in the field and in a laboratory. The optimum design uses a mast system holding drag strips to collect ticks from short grass and flag strips in the air along the side of the robot to collect ticks from tall grass and shrubs. The mast design does not impact the robot's ability to traverse challenging terrain, cause the robot to lose traction, frequently become permanently entangled in brush, or have any other detrimental effect on mobility. The drag and flag mounts are separate fixtures, removable, and adjustable along the horizontal and vertical axes to accommodate various terrain types; the flag attachment points are also adjustable horizontally to allow the rearrangement of strips for optimum tick collection. The design uses rough sponge cloth to collect ticks. The roughness and fibrous nature of the material increase the number of ticks collected. Each strip is designed for independent removal to contain ticks easily and replaces strips quickly; they are also designed to tear away from the robot if they become tangled in brush to prevent the robot from being incapacitated. A robotic solution to tick flagging and dragging protects humans from potential illness from bugs and insects carrying disease pathogens, injury from traveling across rough ground, and harm due to exposure to the elements; productivity is also increased. The collection strips mounted to a mast capture ticks despite adverse conditions, are easily interchangeable, and do not hinder the tick collection and removal process.

MCP, University of Cincinnati, 2004, Design, Architecture, Art and Planning : Community Planning

This proposed thesis topic concerns the integrated water management techniques that can be used to provide water to small, arid islands. The problems of water shortages are experienced throughout the world's arid areas such as deserts and small islands. The islands of the Aegean are indeed very arid. This is particularly evident during the summer months, which are very hot and dry. For many years there have been different techniques that the locals would use in order to collect water. Some of these have been the construction of cisterns which collected rainwater, the use of wells and the collection of water from natural springs. The problem still exists however, due to the low rainfall, the salination of the ground water and the excessive use of water in general. This thesis identifies the technologies and strategies that can be used to supply such islands with adequate and affordable water. The alternative technologies that can be used to address the problem of limited water supply in small islands are examined. An effective way of dealing with the issue of the unsustainable and extensive exploitation of water in small islands is by using integrated water management practices. These practices work with the natural, social and economic factors and aim at linking them, in order to achieve a more effective and sustainable water management system.

Master of Science (M.S.), University of Dayton, 2024, Electrical Engineering

RGB imagery provides detail which is usually sufficient to perform computer vision tasks. However, images taken in low-light appear vastly different from well-lit imagery due to the diversity in light intensity. Polarimetric data provides additional detail which focuses on the orientation of the light rather than intensity. Scaling our classic RGB images using polarimetric data can maintain the RGB image type, while also enhancing image contrast. This allows transfer learning using pre-trained RGB models to appear more feasible. Our work focuses on developing a large dataset of paired polarimetric RGB images in a highly controlled laboratory environment. Then, we perform transfer learning on a pre-trained image segmentation model with each of our image product types. Finally, we compare these results in both well-lit and low-light scenarios to see how our polarimetrically enhanced RGB images stack up against regular RGB images.

Master of Science, The Ohio State University, 2005, Graduate School

Doctor of Philosophy in Urban Studies and Public Affairs, Cleveland State University, 2024, Levin College of Public Affairs and Education

When designing fare structures, transit agencies are primarily concerned with generating revenue. They must however adhere to social justice goals set by transit governing bodies. Considering that travel is a derived demand, equitable access to public transportation enhances accessibility to desired destinations, especially for transit-dependent households. This three-essay dissertation addresses selected research questions in current transit pricing literature. The first essay examines the potential implications of fare capping policies for low-income transit users. The findings indicate that the introduction of monthly fare caps reduces total monthly fare expenditure among Extremely-Low-Income (ELI) riders and increases the likelihood of ELI riders earning unlimited monthly rides. The second essay explores how distance-based fares (DBF), compared to flat fare, potentially alters the travel expenditure of transit riders. This research finds that ELI riders experience significantly lower fare spending under a DBF system compared to a flat fare structure. The third essay tests current methodologies of extracting geodemographic information from mobile fare payment data. The findings show that land use type and the concentration of employment and housing in a neighborhood are significantly associated with the accuracy with which the residential locations of transit users can be inferred from mobile fare payment data. The analyses conducted in this dissertation are based on transit user activity data and survey data from a three-year federal grant led by NEORide, in partnership with multiple agencies in Ohio and Northern Kentucky. The research findings offer valuable insights into the current landscape of transit pricing and mobile fare payment technology in the United States.

Master of Fine Arts, The Ohio State University, 2024, Art

This collection of short stories and poems, accompanied by a glossary, is an ongoing diary about love, intimacy, domesticity, emotional maturation, and maternal inheritance, and is largely inspired by my Great Aunt Marge—major matriarch of the family, avid gardener, and hoarder. She had no children, but she was a mother. Psychic Garden considers the gut microbiome as one kind of garden and the gut as home to intuition. This writing is in close dialogue with, and perhaps in narration to, a body of work installed at Urban Arts Space from February 13th to March 16th, 2024, as part of The Ohio State University's MFA Thesis Exhibition titled Sun Spell.

Master of Computing and Information Systems, Youngstown State University, 0, Department of Computer Science and Information Systems

Bootstrap sampling serves as a cornerstone in statistical analysis, providing a robust method to evaluate the precision of sample-based estimators. As the landscape of data processing expands to accommodate big data, approximate query processing (AQP) emerges as a promising avenue, albeit accompanied by challenges inaccurate assessment. By leveraging bootstrap sampling, the errors of sample-based estimators in AQP can be effectively evaluated. However, the implementation of bootstrap sampling encounters obstacles, particularly in the computation-intensive resampling procedure. This thesis embarks on an exploration of various resampling methods, scrutinizing five distinct approaches: On Demand Materialization (ODM) Method, Conditional Binomial Method (CBM), Naive Method, Two-Step Poisson Random (TSPR), and Two-Step Poisson Adaptive (TSPA). Through rigorous evaluation and comparison of the execution time for each method, this thesis elucidates their relative efficiencies and contributions to AQP analyses within the realm of big data processing. Furthermore, this research contributes to the broader understanding of resampling techniques in statistical analysis, offering insights into their computational complexities and implications for big data analytics. By addressing the challenges posed by AQP in the context of bootstrap sampling, this thesis seeks to advance methodologies for accurate assessment in the era of big data processing.

PhD, University of Cincinnati, 2023, Education, Criminal Justice, and Human Services: Criminal Justice

For correctional programs and policies to enhance public safety, they must be implemented as designed and adhere to evidence-based practices. Effective implementation hinges on proper and systematic data collection on processes and outcomes. In recognition of this, there has been an increasing emphasis on formalized data collection in criminal justice systems across the U.S. Currently, little is known about how large-scale data collection initiatives are developed and implemented. In the spirit of more efficient spending, greater transparency, and improved outcomes within specialty dockets, the debut and subsequent adoption of the Ohio Supreme Court's (OSC) Data Collection and Reporting Initiative (DCRI) for Ohio specialty courts presents a unique opportunity to better understand the development and early implementation of a new statewide performance measurement initiative in near-real time. The purpose of this study is to evaluate the early development and implementation of the DCRI in Ohio using a mixed-method approach. This dissertation used a combination of interview, survey, and secondary reporting data to (1) describe the purpose of and process by which the DCRI was developed, initiated, and enacted by the OSC for Ohio specialty dockets; (2) quantify indices of DCRI implementation across all specialty dockets statewide, including the onset, consistency, timeliness, and accuracy of implementation; (3) assess docket-level contextual factors related to organizational infrastructure and climate that may impact specialty dockets' implementation of the DCRI; (4) describe the processes by which specialized dockets approach implementation of the DCRI; and (5) quantitatively analyze the relationship between organizational infrastructure and climate contextual factors and DCRI implementation indices across specialized dockets. This dissertation found that the DCRI was developed as a response to growing calls for more systematic approaches to collectin (open full item for complete abstract)

Doctor of Philosophy (Ph.D.), Bowling Green State University, 2023, Data Science

The COVID-19 pandemic has changed the world forever. A massive amount of data collected from digital platforms provides opportunities to assess public opinion to the pandemic. We are in the era of digital data, and it is of our interest to harness these digital sources to investigate on how COVID-19 is perceived in multiple geographic areas. The motive for focusing on the data from digital platforms is that the traditional survey approaches have increased costs and low response rates and that the face-to-face survey was less likely to occur during the pandemic because of social distancing and stay-at-home orders. Twitter is a major social media platform where internet users express their opinion, which positions the platform an excellent place to mine data and gauge public opinion towards the pandemic. However, due to the API and other constraints on accessing the entire tweet corpus, collecting tweet samples is generally indispensable for analyzing the activities on the platform. Besides Twitter, Google is another popular digital platform where the pandemic-related searches are entered frequently. We believe that combining, visualizing, comparing, and analyzing data collected from both sources provide a research arch that helps shed light on the pandemic. Additionally, when working in tandem with the digital data, we process and incorporate the official COVID-19 case counts data, treating it as the benchmark for some analysis. In this dissertation, we are tackling the pandemic-related data from three different perspectives, and each perspective results in a deliverable. These deliverables are in the aspects of tweet sampling, digital trace data visualization, and analysis of combined data from Google and Twitter. For tweet sampling, the goal is to propose a sampling method in a way that the samples collected by using the method via Twitter Search API are better representation for the tweet corpus population. Regarding data visualization, we propose three new (open full item for complete abstract)

PhD, University of Cincinnati, 2022, Engineering and Applied Science: Environmental Engineering

In this dissertation, new, compact, hand-held, portable aerosol collectors were developed and evaluated for sample collection and analysis by optical spectroscopies or microscopy with high sensitivity and low detection limits. Firstly, the design and evaluation of a multi-stage focusing nozzle was performed for collection of spot samples for subsequent chemical analysis via optical spectroscopies. The new, multi-stage focusing nozzle consisted of a succession of smooth converging stages for the concentration of a broad range of particle sizes into a narrow particle beam to obtain minute particulate deposits. A numerical computation method was employed along with the experiments, for comparison. Aerosol collection through the multi-stage focusing nozzle was the only method that could ensure high analytical measurement sensitivity at high Reynolds numbers, when compared with other conventional techniques. Moreover, a new, compact, high-flowrate, water-based, Mixing-flow type, Condensation Aerosol Concentrator (MCAC) prototype was presented and evaluated for concentration of submicrometric particles that are challenging to collect. The droplet growth characteristics promoted in the MCAC were calculated theoretically and were compared with the experimental results. The MCAC allows direct collection of particles either as a minute spot sample for onsite direct-reading spectroscopic analysis or as a liquid suspension for offline chemical analysis. Nanoparticles with an initial aerodynamic diameter down to 25 nm are enlarged into easily collectable droplets with an activation efficiency greater than 90%. Finally, the performance evaluation of a prototype, triple-tube, laminar-flow type, condensation aerosol collector, the NanoSpotTM Collector was described. The NanoSpotTM Collector was developed for direct aerosol sample collection on a miniscule sample deposition area, onto an electron microscopy stub or grid for direct electron or optical microscopy and laser spectroscop (open full item for complete abstract)

Doctor of Philosophy (PhD), Ohio University, 2022, Industrial and Systems Engineering (Engineering and Technology)

In this study, I aim to solve the problem of locating mobile parcel lockers considering traffic and customer preferred modes of transportation on urban road networks. The considered road network is a real road network of Rockford, Illinois. I used the publicly available real traffic data for a subset of the considered network to estimate the traffic for the entire road network, and then used the estimated traffic data to estimate travel time for the entire road network. Travel time data, customer preferred modes of transportation, and parcel weights were incorporated in the total cost in the objective function. To solve the problem of locating mobile parcel lockers, I used a heuristic clustering algorithm and multi-threaded Dijkstra's algorithm. In addition, I compared the results of the heuristic algorithm to the exact solution of a mathematical model. Next, I compared the performance of the mobile parcel lockers to stationary parcel lockers based on a set of customer-convenience metrics in four scenarios. The results show a promising improvement in customer convenience when mobile parcel lockers are used for last-mile delivery. In addition, the considered scenarios were also compared in different controlled settings, namely, traffic, and density of demand points. Finally, the effect of the number of stops on mobile parcel lockers convenience was studied.

Master of Science, The Ohio State University, 2022, Genetic Counseling

Background: Race, ethnicity, and ancestry (REA) are distinct terms that are often used interchangeably to refer to ascribed social identities. Within the medical setting, REA is commonly collected as demographic information with race and ethnicity being frequently used as surrogates for ancestral background. Currently, patient- or provider-reported REA is being used in biomedical and healthcare research instead of genetic ancestry, which is scientifically interpreted. The utilization of patient- or provider-reported REA in the clinical interpretation of potentially disease-associated variants may result in inaccurate risk assessment. Genetic counselors (GCs) often collect patient-reported REA as part of the pedigree construction process. Methods for obtaining patient-reported REA are currently not well characterized. This study aims to do the following: determine the proportion of genetic counselors who currently collect patient-reported REA during routine genetic counseling encounters, characterize how genetic counselors ask their patients about REA, and describe the characteristics of genetic counselors that do collect REA information as well as those that do not. An additional exploratory aim of investigating whether or not genetic counselors can determine race, ethnicity, and ancestry emerged during survey construction. Methods: 239 board-certified genetic counselors were recruited by electronic means to complete a 20-question online survey assessing GCs' perception of race, ethnicity, and ancestry, the current practices of GCs, and the demographics of GCs. Data regarding GCs' REA perception, current practices, and demographics were analyzed using descriptive statistics and chi-squared tests. Statistical analysis was not significant. Results: More participants ask patients for ancestry data (93%) in comparison to ethnicity (65%) or race data (40%). 75% of participants collect REA data from patients directly. Phrases and/or terms associated with “ethnicity”, “cou (open full item for complete abstract)

MS, University of Cincinnati, 2021, Engineering and Applied Science: Aerospace Engineering

This thesis describes the design and development work of a marine debris cleanup system - Piranha. It is an autonomous water surface vehicle that can collect different types of garbage such as plastic bottles and bags. To begin with, Piranha is simple, with minimum moving parts including only two thrusters and a lever system. Necessary sensors like IMUs and GPS on Piranha enable positioning and navigation functions. Besides sensors, a LoRa wireless module allows the human worker to control Piranha from a distance. The simulation software for Piranha is discussed in chapter four with the theoretical equations and numerical methods. In the end, some control algorithms, including a 13 state EKF, a heading controller, and a trajectory tracking controller, are brought up to achieve autonomy at a certain level. This report reveals the development cycle of Piranha, from the very simple low-level mechanical parts to the high-level robotics system design.

Honors Theses, Ohio Dominican University, 2021, Honors Theses

As technology advances, the number of Internet users and the amount of data created by them grow immensely each day. Much of this data may be collected without users' knowledge by use of various online technologies that make transparency to consumers a low priority. This report studies various technologies that are capable of capturing and analyzing data, and uses a survey to determine how much the average consumer uses these technologies, knows about these technologies, and is concerned by these technologies. Results of the survey show that participants trend toward having low levels of technology literacy, while showing moderate levels of giving out data to technologies that they use. Coupled with participants showing high levels of concern over their data and these technologies, the difference between the knowledge and given data levels are a cause for concern for the future of data privacy.

MA, Kent State University, 2021, College of Arts and Sciences / Department of Anthropology

Researchers have examined the potential physical and behavioral effects in individuals diagnosed with alcoholism, a chronic disease in which an individual experiences intense cravings for alcohol, an inability to limit consumption, and a continuation of consumption despite negative legal, professional, interpersonal, or physical consequences (Michael and Bengston, 2018). This study aims to determine whether there are common indicators of pathology and associated morbidity in individuals with a cause of death reported as alcoholism verses those with a cause of death reported as pneumonia, by the presence of fractures, their states of healing, and also dental disease. We use this comparison of samples to assess whether there exists a difference between chronic stressors that affect morbidity verses the swift, fast-acting effects of infectious disease in a skeletal collection predating the advent of antibiotics and vitamin supplementation. This study was conducted using the Hamann-Todd Human Osteological Collection housed at the Cleveland Museum of Natural History, the largest historical aggregation of modern human skeletons, comprised of individuals who likely lived through the 1918 Influenza pandemic, national Prohibition, rapid industrialization, and the start of the Great Depression. The results of this study have predominantly corresponded to previous research that examined the association between chronic alcohol consumption and fracture incidence: That chronic alcoholics are more likely to exhibit fractures than the control group, and these fractures are observed most often in the craniofacial region, ribs, upper limb, and vertebrae. There was a statistically significant association between cause of death and fracture incidence (individuals in the alcoholism group were over twice as likely to exhibit a fracture than individuals in the pneumonia group) and the association between ancestry and fracture incidence was also statistically significant (European-derived (open full item for complete abstract)

Master of Fine Arts (MFA), Bowling Green State University, 2021, Creative Writing/Fiction

In this short story collection, Welcome Home, I explore what it means to be lonely, an outsider, and someone searching for their place in the world. My characters are complex men and women who struggle with grief, heartbreak, and a disconnection from their own mind and body. These characters consider themselves the NPCs in the lives of main characters, who shape, affect, or harm them. We see them grow over the course of these stories and learn to find their voices. They are not in the in-group, but outsiders in more ways than one. In many of these stories, I allow my characters to be angry. They feel like real people because they are real people. Despite run-ins with an alien, a virtual reality device that allows you to explore your literal memories, or a cult to Neil Armstrong, theses stories are grounded in the fact that they are centered around human beings with real struggles.

Doctor of Education (Ed.D.), Bowling Green State University, 2021, Leadership Studies

Research shows that the variance in lifetime earnings of Americans can often be forecast by their level of education. Americans with a bachelor's degree are more likely to live an economically sound life, as their lifetime earnings total US$1 million more than high school graduates (Blagg & Blom, 2018). However, earning a degree in higher education can be challenging for students attending college for the first time. Studies indicate that a substantial number of first-time-in-college (FTIC) students are underprepared to meet the demands of a college education (Carnevale, Smith, & Strohl, 2013; Conley, 2016). This issue is significant, as projections reflect a shortage of 16 to 23 million college-educated adults by 2025 (Carnevale & Rose, 2011). The purpose of the study was to assess the effects of the PK-16 Pathways of Promise (P³) Project—a high school intervention program—on the post-secondary outcomes of full-time, FTIC students. In total, 1,574 full-time, FTIC students from 20 local education agencies (LEAs) in institutes of higher education (IHEs) in Northwest Ohio were compared for significant differences on several variables, including grade point average (GPA), proportion of credits lost in early-level courses, cumulative number of credit-bearing hours earned by the end of the academic year, and persistence and retention rates. The quasi-experimental research design included an intervention group and a comparison group. Students in both groups attended one of the three IHEs in the study. However, the intervention group resided within a 20- to 25-mile radius of the IHEs in the study, whereas students in the comparison group resided in different regional areas within Ohio. Based on their home districts' geographical locations, students in the comparison group were assumed to be more likely to attend one of the IHEs as a residential student. Controlling for sex, ethnicity, high school GPA, and school typology, the analysis used multilevel modeling (MLM). MLM (open full item for complete abstract)

PHD, Kent State University, 2020, College of Arts and Sciences / Department of Computer Science

Traditionally, the multi-party telepresence system is supported by one or more servers called Multipoint Control Unit(MCU). These servers are expensive, involve the third party in the system, and also bottleneck for large scale implementation. So, this dissertation presents protocols for autonomous Peer-to-Peer(P2P) implementation of Crowd-scale Telepresence System. The protocols use multiple features from widely adopted P2P network, Gnutella. The proposed protocols and strategies are designed based on the Principle of Distributed Computing (PDC) and the Principle of Priority-based Resource Allocation(PPRA). These principles are considered to address three of the four identified challenges of CMTS implementation, (1) Computational Challenge, (2) Temporal Challenge, and (3) Overcrowding Challenge. The fourth one is the visual challenge which is left for future work. The PDC is used to address the first two challenges by distributing of MCU's workloads among participating peers. The MCU consists of a Multipoint Controller(MC) and one or more Multipoint Processors(MP). For distributed MCU, the optimal placement of MC and MPs in the P2P overlay network is necessary, which is time-consuming because of exponential search space. So, a phase-based design approach is considered. For optimal placement of MC, three incremental protocols, such as GAncestor, ZePoP, and ZePoP-ε are presented. Then, multiple methods are discussed to place the MPs around the optimal MC. For supporting the desired frame rate, two versions of progressive timer management schemes are used at MPs. The protocol ZePoP-ε is designed based on PPRA that emphasis to properly utilize the limited resources of the P2P network. Thus, PPRA is used to address the overcrowding challenge as well as the temporal challenge. It is used to design a profit-based stream collection mechanism of ZePoP-ε for maximizing a Dynamic Role and Demand based Index (DRDI) in bounded waiting time. The proposed protocols and methods co (open full item for complete abstract)

Doctor of Philosophy (PhD), Ohio University, 2020, Mechanical and Systems Engineering (Engineering and Technology)

The development of the self-evolving data collection engine through analytics and business intelligence (SEDCABI) research engine along with plug-in prediction module (PPM) is demonstrated for the prediction of cryptocurrency (specifically, Bitcoin). Leveraging all data proves increase the accuracy of the prediction when compared to using only structured data, or only using unstructured data alone.