Doctor of Philosophy, The Ohio State University, 2022, Horticulture and Crop Science

Breeders use genomic selection (GS) for rapid cycling of parents for crop improvement. GS increases efficiency of breeding by shortening the duration of breeding cycles. The effect of rapid cycling on the wheat genome is unknown. The first objective of this dissertation was to assess the effect of five rapid cycles on the wheat genome. The OSU wheat breeding program began GS with a training population (YTP) phenotyped for yield, quality, and fusarium head blight (FHB) resistance traits. This YTP was genotyped with 3972 single nucleotide polymorphism (SNP) markers. The phenotypes and genotypes were used to build a GS model to obtain genomic estimated breeding values (GEBV). The GEBVs of F2 plants were then used to advance plants through five cycles of GS (YC1, YC2, YC3, YC4, YC5). We assessed the impact of GS on allele frequencies, the forces driving these changes, genetic distance (GD), population differentiation (FST), and linkage disequilibrium (LD). Relative to the YTP, we found that 27% of SNP had a significant change in allele frequency, 18% SNPs were under selection, 13% changed due to genetic drift, 9.3% were undiscernible for drift or selection, and 18.5% were fixed by YC5. Genetic distance narrowed within cycle while the GD between cycles increased at a 0.02 units per cycle. The cycles differentiated from the YTP at a rate of 0.046 FST units per cycle. The YC5 was highly differentiated from the YTP with an FST value of 0.224. We found the correlation between LD matrices decreasing at -0.057 units per cycle. Overall, we found reduction in genetic diversity, increased genetic differentiation of cycles from the YTP, and changes in LD patterns over cycles. The change in the genome is not desired when implementing GS because the changes will lower the prediction accuracy as the number of cycles increases. The second objective of this dissertation was to estimate the accuracy of GS at predicting the phenotypes of lines derived from cycles of GS. Prediction accur (open full item for complete abstract)

Doctor of Philosophy, The Ohio State University, 2017, Business Administration

Forecasts are a critical input that drive actions within the firm and throughout the supply chain. For good reason, there is a tremendous focus on accuracy for this input. This dissertation addresses three areas regarding forecast accuracy in logistics and the supply chain relating to three questions posed by demand planners at a logistics provider firm that partnered with this research. In attempting to determine “What is causing our replenishment forecast error?”, “What predictive factors can help improve our demand forecast accuracy?”, and with regards to forecast accuracy “How good is good enough?”, we explore three interrelated topics that have a broader impact on the academic conception of forecast accuracy than the original questions posed. In three essays, we identify governance form factors that affect replenishment forecast deviation and bias, demonstrate accuracy improvement though the inclusion of uncertain weather forecast information in demand forecasts, and identify themes that serve to bound achievable and desirable demand forecast accuracy through a systematic literature review of logistics and supply chain journals. Our first study measures the deviation and bias related to franchise governance form, but also demonstrates a novel approach to contextualize the heterogeneity of effects across regionally, temporally and product category related conditions. Our second study expands on previous work linking the inclusion of uncertain weather forecast variables to improvements in demand forecast accuracy by examining a wider range of products and locations in a new industry, but also by demonstrating the limits to the value of uncertain information. Finally, our systematic literature review comprehensively presents the current state of research on the thematic drivers of forecast accuracy. Each essay expands theoretical understanding of management phenomena, and reframes the manner in which previous research can be applied in practice. In (open full item for complete abstract)

Doctor of Philosophy, University of Toledo, 2015, Psychology - Clinical

Exner's (2003) Comprehensive System and Meyer et al.'s (2011) Rorschach Performance Assessment System use Form Quality scores as a method for assessing the accuracy of perceptions on the Rorschach. However, Form Quality is a rather coarse classification method as it is based on just three options along a continuum of perceptual accuracy. There is currently not a fully dimensional Rorschach score that can thoroughly and efficiently tap into both the frequency with which particular objects are reported while taking the test and the perceptual fit of those objects to the cards. This study is focused on exploring the structure of a fit variable, Form Accuracy, in combination with a frequency variable, Percept Frequency, to make progress on a new dimensional method of scoring perceptual accuracy that will improve the ability to identify distorted perceptual processes and impaired reality testing and thus improve validity coefficients in the Rorschach-based identification of psychosis. Percept Frequency tables were developed from six internationally collected samples from Argentina, Brazil, Italy, Japan, Spain, and the U.S. that quantified how often objects were reported while completing the Rorschach task. Form Accuracy ratings were obtained from a database of 13,031 objects that had been rated an average of 9.9 times by different judges from eleven countries who were asked to rate the extent to which the object fit the contours of the inkblot at the location where it was seen. A criterion database containing 159 protocols and 3,897 scorable responses was then scored for Form Accuracy and Percept Frequency. Hierarchical Linear Modeling was used to complete structural analyses of Form Accuracy and Percept Frequency scores at the response level, and correlations of these variables were computed at the protocol level with a criterion measure assessing severity of disturbance based on psychiatric diagnoses. Across different levels of aggregation, there was resounding evidenc (open full item for complete abstract)

Master of Arts, The Ohio State University, 2012, EDU Teaching and Learning

The purpose of this study was to investigate the effects of the frequency of syntactical and lexical errors on the assessment of compositions written by Turkish EFL college students. It attempted to examine a) the most frequent types of syntactical errors and lexical errors in EFL students' compositions; b) the relationship between the types of writing prompt and the frequency of syntactical and lexical errors; c) the relationship between the frequency of syntactical and lexical errors and the holistic score of the compositions. The data, 210 compositions, were gathered from 80 Turkish university freshmen enrolled in a Basic English course at Bozok University during the second semester of 2009. The results of randomly selected 150 compositions written by Bozok University freshmen majoring in Electrical and Electronics Engineering, Computer Programming and History revealed that the students had the greatest problem with prepositions in syntactical error category and formal mis-selection of words in lexical error category. The results showed that the type of writing prompt seemed to have an effect on the frequency of occurrence of errors, whether they be syntactical or lexical errors. A low negative correlation was found between the holistic scores and the frequency of syntactical errors. Similarly, a low negative correlation was found between the holistic scores and the frequency of lexical errors. When it comes to the relationship between the frequencies of syntactical and lexical errors, and the holistic scores, a moderate negative correlation was found. Overgeneralization, inadequate application of rules, incomplete mastery, ignorance of rule restrictions and particularly negative transfer were found to be possible factors contributing to the occurrences of errors. The results also provided evidence that as the frequency of syntactical and lexical errors decreases the quality of the compositions relatively seems to increase.

Doctor of Philosophy, The Ohio State University, 2007, Teaching and Learning

Training in spoken grammatical accuracy at professional levels in English teacher education programs to ensure teaching quality is a program component. However, English as a foreign language (EFL) teacher education programs typically do not focus on this area in Taiwan. The present research employed a pretest-posttest control group experimental design to investigate the effects of an explicit grammar teaching method on a group of English teacher candidates' spoken grammatical accuracy. The main purpose of the study was to investigate if the proposed teaching method would improve the teacher candidates' oral English proficiency with respect to grammaticality, and if so, to what extent? Moreover, in light of concerns that second language speakers' attention to accuracy may impaired their fluency, the research also studied if explicit grammar instruction would impair speaking fluency of the teacher candidates. The research site was the Children English Teacher Education Program housed within National Taipei University of Education. Thirty-six participants were randomly assigned to two levels of the treatment on English conditional structures for five sessions of grammar instruction. The instrument used to measure the participants' performance on the pretest and posttest was the one-on-one oral interview. The data was analyzed using the ANCOVA procedures, controlling for any initial difference between two study groups. The study findings suggested that grammar instruction could improve spoken grammatical accuracy of English teacher candidates in Taiwan, who are advanced English learners. In addition, the increased grammatical accuracy was not obtained at the expense of fluency.

Master of Science (MS), Ohio University, 2002, Civil Engineering (Engineering)

Effect of machine vision based traffic data collection accuracy on traffic noise.

Master of Arts, Miami University, 2005, Speech Pathology and Audiology

Motor learning literature demonstrates that training in a specific motor movement can improve performance for that movement and other similar tasks. Vocalises are exercises used in vocal training to improve quality and precision in singing performance. It was hypothesized that a short-term training program using a specific vocalise would improve singing performance on the practiced vocalise and vocalises of similar and greater complexity. Twelve female sopranos were divided into two groups, only one of which completed the short-term vocalises training program. Performance was assessed for pitch and rhythm accuracy. Results indicated that the group that completed the short-term training program did not significantly improve their pitch and rhythm accuracy on the three vocalises compared to the group that did not complete the training. Also, no carryover effect was seen after a 1-week rest-period for either group. This study demonstrates that short-term training in vocalises may not improve motor performance.

Master of Science, Miami University, 2024, Mechanical and Manufacturing Engineering

Wire electrical discharge machining (WEDM) enables production of complex parts with tight tolerances, although maintaining dimensional accuracy in corners and tapers remains challenging due to wire deflection and vibration. This study optimizes WEDM parameters for achieving high-accuracy in machining complex geometrical parts and taper cuts in 6061 Aluminum alloy using Excetek W350G WEDM machine with a copper wire electrode. Parameters including Wire Tension, Pulse On-Time, Pulse Off-Time, Wire Feed Rate, Open Circuit Voltage, and Flashing Pressure were varied using L18 Taguchi Orthogonal Array and response graph method to identify optimal cutting conditions. Results indicated feature-specific optimization is crucial, as different geometrical features (rectangular fins, triangular fins, gears) exhibited varying critical parameters. Key findings highlighted the importance of Wire Tension and Pulse On-Time in maintaining cutting accuracy, although at varying levels for specific features. Response graphs demonstrated effects of major WEDM parameters on corner and profile accuracies, whereas Taguchi analysis provided optimum settings of parameters for each feature and taper cutting. Validation experiments for rectangular fins showed significant improvement in the dimensional error for the fin length and taper angle. These advancements will enhance precision, efficiency, and versatility of WEDM processes in machining complex profiles, and corners, contributing to precision manufacturing.

MS, University of Cincinnati, 2024, Engineering and Applied Science: Computer Science

The continuous threat of deepfakes, cleverly crafted deceptions masquerading as reality, necessitates cutting-edge detection methods. While there are many methods available, this project dives into the realm of fine-tuning the VGG16 convolutional neural network (CNN) and synergistically integrating Natural Language Processing (NLP) to unveil deepfake images effectively. By using the Keras API and machine learning principles, we empower the model to discern authentic images from their manipulated counterparts, drawing inspiration from real-world cases like the notorious Jennifer Aniston deepfake scam. Firstly, we establish a robust foundation for feature extraction by pre-training the VGG16 architecture on vast image datasets. Subsequently, we meticulously curate a comprehensive deepfake image dataset encompassing diverse manipulation techniques and real-world scenarios. This tailor-made dataset fuels the fine-tuning of specific VGG16 layers, accurately crafting a model with exceptional generalizability. Intriguingly. The project rigorously evaluates the fine-tuned VGG16 model's performance on unseen deepfakes through a battery of meticulous metrics, including accuracy, and loss while detecting the deepfakes. We delve into a comprehensive comparison, carefully analyzing these results not only against the baseline performance of a model I created from scratch, the untrained VGG16, the VGG16 after I applied transfer learning. This project aspires to make a significant contribution to the ongoing battle against deepfakes by showcasing the remarkable potential of fine-tuning the VGG16 that helps us in achieving superior detection accuracy. By thoroughly incorporating real-world examples and harnessing the synergistic power of CNNs, we strive to develop a robust and adaptable solution capable of combating the ever-evolving landscape of deepfakes. Ultimately, this endeavor aims to safeguard online safety and trust, mitigating the detrimental effects of deepfakes on (open full item for complete abstract)

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

The field of online language education is experiencing rapid growth, emphasizing the need to understand factors that influence students' communication behaviors in online learning environments. This research study examines the relationships between need satisfaction, willingness to communicate (WTC), quantity of communication(i.e., frequency of communication), and quality of communication (i.e., language performance) in asynchronous and synchronous learning modes. Using Experience Sampling Methodology, data was collected from high school students enrolled in an online language course. Weekly surveys were used to capture participants' situational need satisfaction, WTC, and quantity of communication. Quality of communication was assessed through weekly writing assignments and synchronous speaking performance. Findings from multiple group path analyses revealed that students' need satisfaction for competence, and relatedness were significantly related to their WTC in both asynchronous and synchronous learning modes. The study identified differences in relationship patterns in asynchronous and synchronous learning modes, highlighting the influence of specific contextual factors on communication behaviors. Additionally, the study employed cross-lagged analyses to explore the temporal effects between need satisfaction and WTC, and between WTC and communication behaviors. The findings revealed the associations between students' prior learning experiences, students' perceptions, and subsequent engagements over time. The study explored the specificity of relationships within and across learning modes and content units, providing insights into contextual factors that are associated with students' communication behaviors. By examining the differences in relationships across various modes and considering temporal dynamics within specific contexts, this research enhances our understanding of factors contributing to supportive online environments and positive communication (open full item for complete abstract)

Doctor of Philosophy, The Ohio State University, 2023, Slavic, East European and Eurasian Studies

“How can teachers help students improve their second language (L2) speaking accuracy?” This is a question that most L2 educators ask themselves every day. Although L2 writing is a popular topic among Second Language Acquisition (SLA) researchers, the consideration that L2 writing has the potential to act as a scaffold for L2 speaking accuracy has often been overlooked. This research attempts to draw SLA researchers' attention to the untapped potential that L2 writing has on improving L2 speaking accuracy. This research provides empirical evidence that L2 writing have a great potential to improve accuracy of L2 oral discourse. Twenty-three Novice, twenty-one Intermediate, and twenty Advanced university students of Russian participated in the study. They completed a text reconstruction task by working with the original text to 'notice the gap' using both written and spoken modes of recall. Both written and spoken forms of recall provided sufficient opportunity for improving semantic accuracy and produced textual complexity, and for acquiring new vocabulary with all three levels of learners. However, only the Novice, Intermediate, and Advanced learners working with the texts in writing showed improvement in their speaking accuracy. These findings can be considered the first step in drawing scholars' attention to the benefits of utilizing L2 writing to improve L2 speaking accuracy that have often been overlooked. This research also bridges the gap in our understanding of written and spoken recall of texts written in L2. The relationship between written and spoken recall has primarily been analyzed with English-speaking monolinguals. It has been reported that written recall provides semantically more accurate responses than spoken recall due to the higher cognitive load and attention required to produce a text. The pilot study described in this dissertation examined the written and spoken text recall relationship in L2 learners of Russian, and analyzed how individual w (open full item for complete abstract)

Master of Science (MS), Bowling Green State University, 2022, Forensic Science

908 Devices has created a handheld High-Pressure Mass Spectrometer™ (HP-MS), called the MX908®, for field analysis of unknown substances. According to the manufacturer, the MX908® has a theoretical limit of detection in the low to mid parts per billion (ppb) range, but because the device provides qualitative rather than quantitative data, the actual limits of detection are unknown. The purpose of this experiment was to determine a limit of detection and sensitivity of the MX908® for methamphetamine, fentanyl, heroin, and cocaine by comparing known standards for each drug processed on the MX908® and a Shimadzu 8050 triple quadrupole Liquid Chromatograph Mass Spectrometer (LC-MS). Samples were spotted directly on the MX908® swabs and spotted on a table and swabbed off. This was to compare a controlled setting to a simulation of a practical use of the swabs and instrument. Cocaine and methamphetamine were the only two drugs reliably detected by the instrument. More testing is necessary to validate the MX908® for future use

Master of Science, The Ohio State University, 2022, Dentistry

Objectives: The purpose of this in vitro study was to evaluate the fabrication and seating accuracy of surgical guides fabricated by using 3 different types of 3D printing technologies. Methods: Twenty-one identical polyurethane models were divided into 3 groups and used to plan implants and design surgical guides using digital software. Twenty-one surgical guides were fabricated using 3 different 3D printing technologies: digital light processing (DLP), stereolithography (SLA), and continuous liquid interface printing (CLIP)(n=7). A digital scan of the printed surgical guide was made with an intraoral scanner and the scan file was compared to the CAD file to analyze the fabrication accuracy. Accuracy was evaluated on the internal cameo seating surface as well as the overall external surface of the surgical guide. Then, the triple scan protocol was used to evaluate the seating accuracy of the guides on their respective models. A metrology grade superimposition software was used to calculate accuracy. Results: Overall there was a statistically significant interaction between the 3D printer and the accuracy of the guide compared to the CAD file (p<.001). The trueness of the surgical guides was significantly different for the internal cameo surface but not for the overall external surface of the surgical guide. SLA had the lowest mean RMS deviation (59.04μm) for internal surface of the guide while CLIP had the highest mean RMS (117.14μm). CLIP had the lowest mean RMS (82.25μm) for the overall external surface of the guide while DLP had the highest mean RMS (91.00μm). SLA and DLP seating accuracy was not significantly different (p=1.000) but, both had significantly lower mean RMS values than CLIP (p=0.003, p=0.014). All 3D printing technologies had low variability amongst measured deviations and therefore were similarly precise. Conclusions: Overall, the 3D printers tested produced precise surgical guides. However, 3D printing technology effected (open full item for complete abstract)

PHD, Kent State University, 2022, College of Arts and Sciences / Department of Psychological Sciences

Given the broad negative effects of stress on people's daily lives, health, and relationships (Black & Garbutt, 2002; Bodenmann, 2000; Neff & Karney, 2004; Sin et al., 2015), knowing the degree to which romantic partners perceive each other's stress accurately and/or with biases can be critical to understanding how couples interpret stress, communicate about stress, help each other cope with stress, and ultimately mitigate the negative effects of stress to maintain a successful relationship. Using intake and daily diary data collected online from cohabiting couples (N = 170 people; 85 couples) across the United States, I used multi-level path models to examine the level of tracking accuracy and bias (projection and mean-level) in people's judgments of their romantic partner's overall and daily external and internal stress and the degree of similarity between partners' stress. I also examined whether individual differences (i.e., stress communication; responsiveness; dyadic coping style; parental status, parental stress, pandemic stress) were associated with levels of accuracy and bias in partner stress perceptions and whether biased perceptions of partner stress (i.e., overperception and underperception), compared to accurate perceptions, were associated with conflict, relationship satisfaction, satisfaction with stress support, perceived positive dyadic coping, and perceived negative dyadic coping. Results showed that for overall stress and daily external stress, people were generally accurate in their perceptions—demonstrating both tracking accuracy and mean-level accuracy, but they also tended to be biased such that they projected their own stress experience onto their partner. In contrast, people did not demonstrate tracking accuracy in their perceptions of daily internal stress, but instead relied heavily on projection and tended to overperceive their partner's daily internal stress. Greater responsiveness and greater negative dyadic coping were associated with (open full item for complete abstract)

PHD, Kent State University, 2022, College of Arts and Sciences / Department of Modern and Classical Language Studies

Post-editing of machine translation (MT) is a workflow that is being used for an increasing number of text types and domains (Koponen, 2016; Hu, 2020; Zouhar et al., 2021),but the sections of text that post-editors need to fix have become harder to detect due to the increased human-like fluency that neural machine translation (NMT) affords (Comparin & Mendes, 2017; Yamada, 2019). This dissertation seeks to address this problem by developing a word-level machine translation quality estimation (MTQE) system to highlight words in raw MT output that need editing in order to aid post-editors. Subsequently, this MTQE system is tested in a large-scale post-editing experiment to determine if it increases productivity and decreases cognitive effort and error rate. This MTQE system is based on two automatically generated features: word translation entropy, generated from the output of multiple MT systems (a feature that has never been used in MTQE), and word class (based on part-of-speech tags). For the post-editing experiment, a within-subjects design assigns raw MT output to participants under three different conditions. Two experimental conditions consist of MT output that has been enhanced with highlighting surrounding the stretches of text that likely need to be edited. In the first experimental condition, this highlighting is supplied automatically by the MTQE system, and in the second experimental condition, this highlighting is supplied by an experienced translator, indicating what text needs editing. The control condition constitutes MT output without highlighting. Participants post-edit three experimental texts in Trados Studio while time-stamped keystroke logs are gathered (which are later integrated into the CRITT Translation Process Research Database (TPR-DB)), and various measures of temporal, technical, cognitive, perceived effort, and group editing activity are used to assess the efficacy and usefulness of highlighting potential errors in the post-editing user (open full item for complete abstract)

Master of Science in Engineering, University of Akron, 2021, Mechanical Engineering

The viscoelastic properties of rubber have allowed compounds to be utilized across many different industries. Rubber is a very unique material, and the chosen manufacturing process can result in numerous variations of the polymer. With many potential outcomes, it is crucial to accurately determine the physical attributes of the polymer. For many applications, but specifically for the tire industry, one of the standard methods for determining viscoelastic properties is through dynamic mechanical analysis (DMA). The raw data from DMA is adjusted through the Williams, Landel, and Ferry (WLF) shift equation to create a master curve for the rubber specimen. This study investigates methods for the calculation of friction coefficient, and suggests a new code to predict the friction coefficient. Several discussions in the paper will be for validation of the code and its range of applications. We then implement a parametric analysis to determine which factors critically affect the friction factor results. By finding the sensitivity of the inputs to the new code for friction coefficient, the critical inputs can be identified. The parameters that are studied are the storage modulus, loss modulus, surface asperities heights, the surface asperities wavelength, and the adhesive contribution to friction. The adhesion and hysteresis contributions to the friction coefficient are also discussed in this paper. It is shown that the adhesive contribution plays a large role in determining the friction coefficient. The data from the study will determine the effect that direct DMA testing has on the friction coefficient as well as tire performance indicators. The indicators that the direct testing affects the most are the wet traction indicator, the snow traction indicator, and the ice traction indicator.

Doctor of Education (Ed.D.), Bowling Green State University, 2020, Leadership Studies

No country can afford mass access and high quality-it will never happen (Altbatch, 2012). Massification has characterized global higher education since the mid-1940s starting in the United States, spreading to Europe and East Asia in the 20th Century, before expanding to Sub-Sahara Africa. Various scholars have linked massification, and the transformation of higher education to the dilution of quality university education, leading to Juakalization. The term Juakalization is a metaphor derived from the word `Jua kali' is used in this study to denote low-quality education standards witnessed in universities, by relating institutions of higher education in Kenya with the country's informal, economic artisan sector known as Jua Kali. The expansion of higher education in Kenya after the year 2010, resulted in confusion, frustration, lack of employee loyalty, and clashes in corporate culture, posing leadership challenges. This mixed methods, sequential, and explanatory study, sought to gain new insights into leadership behavior at seven public universities operating in Kenya before 2010. The research explored the relationship between leaders self-perception and the perception of their followers with regard to leadership effectiveness in managing the performance of universities during the Juakalization phenomenon. The findings indicated that university vice-chancellors frequently utilized effective leadership practices and that their followers were aware of effective leadership behavior. However, all indications point to the dilution of quality higher education. Three conclusions arise from the study findings: first, leaders and followers must produce change; second, the desired change ought to be transformational; and third, the leader follower relationship must produce quality products, because leading is about practice and transformation.

Master of Science, The Ohio State University, 2020, Dentistry

Statement of problem. Additively manufactured (AM) digital implant models (DIM) fabricated with 3D-printing technology have become more popular in the recent years, combining the advantages of both digital and analog workflows. They are a physical model on which dentists and laboratory technicians can evaluate and work on restorations for layering and adjustments. Even though 3D-printed DIMs have provided a solution between digital and analog workflows, limited evidence exists regarding the accuracy of the implant analog position on these models. Multiple factors related to the fabrication and accuracy of 3D-printed DIMs have been studied. However, the influence of the digital implant analog design on the accuracy of implant analog positions on 3D-printed models is still unclear and only one study related to this topic has been published. Purpose. To compare the implant analog position trueness between AM DIMs with 3 different digital implant analog designs and conventional implant analog stone casts. The study aimed to evaluate and compare the effect of digital implant analog design and insertion on the trueness of analog position of DIMs compared to a conventional implant stone cast. Materials and Methods. A modified partially edentulous maxillary implant model with a conventional implant replica (Nobel Biocare Implant Replica CC RP) on site #13 was used as the master reference model (MRM). Conventional implant-level vinylpolysiloxane (VPS) impressions of the MRM were made using custom trays with the closed tray impression technique and poured in type IV stone to obtain 12 conventional implant casts (Group A, n=12). A complete-arch implant-level digital scan of the MRM with an implant intraoral scan body (ISB) was made using an intraoral scanner (IOS). The digital scan file was exported to a dental CAD software and used to create 3 different DIM designs for different 3 different DIM analogs: NobelProcera (Group B), Elos Medtech (Group C) and Nt-trading (Gro (open full item for complete abstract)

Doctor of Philosophy, The Ohio State University, 2020, Electrical and Computer Engineering

Passive radar systems often exploit multiple transmitters, so even if there is just one receiver site there can still be many bistatic geometries. While this configuration can dramatically improve the coverage of the radar, it can also exacerbate the spatial variation of the performance already inherent in a bistatic radar geometry. Computation of the bistatic Cramer-Rao lower bound (CRLB) for the range and velocity measurement accuracy provides a quantitative method for evaluating the performance variation. In turn, this understanding can enhance the “illuminator selection”, a methodology used to determine the illuminator that provides the best estimation accuracy for the target parameters, which is then used to minimize the estimation error and therefore improve the detection and tracking performance of the passive radar system. The monostatic and bistatic CRLB is calculated for the advanced television systems committee (ATSC) signal that is a pervasive waveform to exploit for North American passive radar systems. A relationship between the ambiguity function of the signal and the CRLB will be used to estimate the bounds of the range and velocity measurements. The effect of the 3D geometry in the CRLB is addressed by taking into account the receiver, transmitter, and target altitudes. The 3D range and velocity modified CRLB (MCRLB) are analyzed for different bistatic geometries available in the Columbus, Ohio area for a single receiver located at The Ohio State University ElectroScience Laboratory (OSU-ESL). The performance of multiple digital TV illuminators is evaluated to select the optimal illuminator that exhibits the lowest MCRLB. The use of multiple transmitters simultaneously in a multistatic radar configuration improves the radar performance, and increase the resolution. The MCRLB for passive multistatic radar systems using the ATSC signal as a signal of opportunity is analyzed for the localization and bistatic parameters. Closed-form expressions (open full item for complete abstract)

Master of Science, The Ohio State University, 2020, Environmental Science

Agricultural nutrient loss has a variety of environmental consequences. In the Maumee River watershed, the region of focus for the studies presented here, these consequences include the formation of harmful algal blooms in western Lake Erie. These algal blooms threaten use of water for drinking, recreation, and tourism, and have public health impacts. While adoption of agricultural best management practices is widely encouraged in this region to minimize nutrient loss, these practices are not universally adopted. Numerous previous studies have investigated factors contributing to farmers' adoption of best management practices, but less is known about farmers' risk perceptions associated with nutrient loss. This project involves two analyses of nutrient loss risk perceptions. First, a conceptual model is presented that attempts to explain one possible mechanism through which farmer risk perceptions associated with nutrient loss are formed. Then, the second analysis seeks to characterize relative “accuracy” of perceptions using nutrient loss data obtained through simulation of specific suites of management practices in a Soil and Water Assessment Tool (SWAT) model of the watershed. Both analyses use farmer survey data, collected in the Maumee River watershed in 2014, to address the research questions of interest. The conceptual model presented in Chapter 1 investigates the roles that farmer identity, perceived sufficiency of nutrient management practices, and land vulnerability to nutrient loss play in explaining farmer risk perceptions. We found that many of the relationships hypothesized to exist between these variables were not statistically significant, and that risk perception associated with nutrient loss was primarily driven by farmers' conservation identities, with some role of perceived sufficiency of nutrient management practices. However, we did not observe the hypothesized influence of land vulnerability to nutrient loss on perceived sufficiency of n (open full item for complete abstract)