A novel paper using Canada's real traffic accident data to propose a cost-prediction-based decision-making framework incorporating different ethical foundations for AVs. / Autonomous Vehicles (AVs) hold out the promise of being safer than manually driven cars. However, it is impossible to guarantee the hundred percent avoidance of collisions in a real-life environment with unpredictable objects and events. When accidents become unavoidable, the different reactions of AVs and their outcome will have different consequences. Thus, AVs should incorporate the so-called ‘ethical decision-making algorithm’ when facing unavoidable collisions. This paper is introducing a novel cost-prediction-based decision-making framework incorporating two common ethical foundations human drivers use when facing unavoidable dilemma inducing collisions: Ethical Egoism and Utilitarianism. The cost-prediction algorithm consists of Collision Injury Severity Level Prediction (CISLP) and Cost Evaluation. The CISLP model was trained using both Multinominal Logistic Regression (MLR) and a Decision Tree Classifier (DTC). Both algorithms consider the combination of relationships among traffic collision explanatory features. Four different Cost Evaluation metrics were purposed and compared to suit different application needs. The data set used for training and testing the cost prediction algorithm is the 1999-2017 National Collision Data Base (NCDB) which ensures the realistic and reliability of the algorithm. This paper is a novel paper using Canada's real traffic accident data to propose a cost-prediction-based decision-making framework incorporating different ethical foundations for AVs. / Thesis / Master of Applied Science (MASc)

Wide-area disturbances are power outages occurring over large geographical regions that dramatically affect the power system reliability, causing interruptions of the electric supply to residential, commercial, and industrial users. Historically, wide-area disturbances have greatly affected societies. Virginia Tech directed a research project related to the causes of the major disturbances in electric power systems. Research results showed that the role of the power system's protection schemes in the wide-area disturbances is critical. Incorrect operations of power system's protection schemes have contributed to a spread of the disturbances. This research defined hidden failures of protection schemes and showed that these kinds of failures have contributed in the degradation of 70-80 percent of the wide-area disturbances. During a wide-area disturbance analysis, it was found that hidden failures in protection schemes caused the disconnection of power system elements in an incorrect and undesirable manner contributing to the disturbance degradation. This dissertation presents a methodology to assess and rank the effects of unwanted disconnections caused by hidden failures based on Regions of Vulnerability and index of severity in the protection schemes. The developed methodology for the evaluation of the Region of Vulnerability found that the indicator that most accurately reflects the relationship of the Region of Vulnerability with the single line diagram is kilometers. For the representation of the Region of Vulnerability in the power system, we found segments in the transmission line in which the occurrence of faults do make the relay to operate, producing the unwanted disconnection caused by hidden failure. The results in the test system show that the infeed currents restrain the Region of Vulnerability from spreading along power system elements. Finally the methodology to compute the index of severity is developed. The index of severity has the objective of ranking the protection schemes, considers the dynamics of the protection schemes, and evaluates the overall disturbance consequence under the static and dynamic perspectives. / Ph. D.

During an audit, management frequently serves as an information source for auditors gathering evidence. Reliance on management's expertise requires auditors to exercise an adequate level of professional skepticism, because management is not an objective information source. In this respect, professional guidance urges auditors to maintain a skeptical mind-set since management's financial reporting incentives may lead to instances when it attempts to persuade the auditor into accepting a preferred accounting treatment. This study investigates how auditors' behavior when providing input on planning decisions common to an audit can influence an auditor's mind-set, and how this mind-set then influences the persuasiveness of subsequently encountered management information. My predictions are motivated by psychology theory on behavioral mind-sets, which indicates that in the course of completing a task, a mind-set can be activated that carries over and influences an individual's behavior in a subsequent, unrelated situation. In a 2x2 experiment, 83 experienced auditors participated in an update meeting with the engagement partner and then made preliminary internal control evaluations. I manipulated the activation of different mind-sets (bolstering or counter-arguing) during the audit update meeting; I also manipulated the severity of the control deficiency (high or low) during the subsequent internal control evaluation task. I hypothesized that the behavior of providing arguments either supporting or opposing common scheduling arrangements during a planning meeting with the engagement partner can activate a mind-set that then influences the persuasiveness of information subsequently received from the client. The increased severity of the deficiency was expected to mitigate the role of mind-sets in the audit environment. The results support my expectations. Auditors who developed a bolstering mind-set during a planning meeting rated the adequacy of management's internal control explanation higher and made internal control assessments indicative of lower risk than auditors who developed a counter-arguing mind-set. I also find that the impact of an auditor's mind-set is attenuated when auditors evaluate a control problem potentially indicative of a material weakness (i.e., higher severity). These results indicate that routine audit planning tasks altered an auditors' skeptical mind-set, which impacted the persuasiveness of management information, even though the update meeting was unrelated to the internal control assessment. However, as the severity of the identified deficiency increased, risk sensitivity mitigated the auditors' mind-set effects, as their professional skepticism was naturally heightened. These results have important audit implications given the importance of maintaining appropriate levels of professional skepticism throughout an audit, especially amid recent concerns that auditors, at times, fail to do so. The findings also inform the psychology and behavioral mind-set literatures by extending the generalizability of prior studies while also establishing the boundaries of this stream of research by examining different levels of severity. / Ph. D.

Drought conditions and wildfires can induce soil water repellency. Precipitation shifts are expected to exacerbate drought and wildfire in regions such as the southeastern United States, making it critical to understand how repellency affects water exchange processes in soil. The objectives of this dissertation were to 1) quantify the water vapor sorption dynamics of two clay minerals in which water repellency was induced; 2) identify if and for how long wildfires in humid hardwood forests induce water repellency, 3) evaluate if organic carbon content and hydrophobic functional groups explain actual and potential soil water repellency; and 4) understand how vertical position (i.e., depth) of water repellent layers affect infiltration processes. To meet these objectives, a laboratory test was first conducted examining water vapor sorption processes in water-repellent clay minerals. Next, a field study occurred in two forests that experienced wildfires in late 2016: Mount Pleasant Wildfire Refuge, Virginia, and Chimney Rock State Park, North Carolina, United States. Measurements include water drop penetration time, soil water content, and tension infiltration. Complimentary laboratory tests quantified potential soil water repellency, soil organic carbon content and hydrophobic functional groups. Results showed that water repellency inhibited water vapor condensation because of altered mineral surface potentials and decreased surface areas. Burned hardwood forest soils presented water repellency for > 1 year, though laboratory measurements presented different trends than in situ measurements. Total organic carbon content and hydrophobic functional groups correlated with soil water repellency measured in the laboratory but not the field. Soil water content was lower in burned than unburned soils, and negatively correlated with water repellency. Water repellency in the surface layers significantly reduced relative water infiltration rates, whereas subsurface water repellency did not, and water repellency persisted longer in sites with surface compared to subsurface water repellency. Finally, while the wildfires increased the occurrence of water repellency, they did not alter the underlying relationship between relative infiltration and surface water repellency. Altogether, this study provided new insight into water repellency effects on water partitioning at soil-atmosphere interfaces, and presented evidence of soil and hydrological changes induced by wildfires in humid hardwood forests. / PHD / Rising temperatures and shifting precipitation patterns that result from global climate change have the potential to induce long-term droughts, which may induce soil water repellency, as can wildfires that become more prevalent and damaging. Water repellency can alter the physical, chemical, and hydraulic properties of soil. These alterations may drive soil erosional processes and increase the mobility of surface-bound pollutants with the potential to reduce water quality and degrade down-gradient aquatic ecosystems. Thus, it is critical to understand how water repellency affects water movement in and through soils. Despite several decades of research towards this topic, some critical questions still remain. For example, how does water repellent soil influence water characteristics in the vapor phase (which is increasingly important under drought conditions)? Do wildfires in humid hardwood forests cause soil water repellency? If so, how long does water repellency persist? Do water repellency measurements using field and laboratory techniques correspond to one another? How does the depth of water repellent soil layer(s) affect water movement? In order to solve this questions, several tests were conducted in both field and laboratory. The field experiments occurred within forested hillslopes that underwent varying degrees of burning during widespread wildfires that affected the Southeastern United States in late 2016. Choosing two forested locations, we measured actual water repellency, soil moisture, and infiltration in burned and unburned sites after wildfire, and took loose samples for laboratory tests. In the lab, we tested potential water repellency on air-dried soil samples, soil organic carbon content and hydrophobic substance percentage. We also conducted water vapor sorption experiments to quantify water vapor exchange in two types of water repellent minerals: kaolinite and montmorillonite. The results showed that water repellency can affect water exchange between the subsurface and the atmosphere, by both limiting water vapor sorption and reducing liquid water infiltration. Soil organic matter and composition correlate well with potential water repellency measured in the laboratory, though less so with actual water repellency measured in the field. Instead, soil water content provided a high and inverse correlation with actual water repellency. Finally, water infiltration rates were influenced by the vertical position (depth) of water repellent layers, with water repellency at the soil surface causing much reduced initial infiltration rates compared to water-repellent layers in the subsurface.

By increasing fruit exposure to sunlight and influencing fruit development, leaf thinning in the fruit zone can improve grape quality and lower disease incidence; however, further investigations on the timing, varietal response and intensity are needed to optimize results and to better understand underlying physiologic responses. Fruit zone leaf thinning was applied at different timing and intensities to evaluate its effect on cluster health and fruit composition in Cabernet Sauvignon and Chardonnay. Treatments consisted of control (C), pre-bloom leaf thinning (PB) and two levels of fruit-set leaf thinning (three leaves, PF3 and six leaves, PF6). In an additional project on Cabernet Sauvignon, two levels of hedging (17th node, NH and 12th node, H) were integrated with no leaf thinning (L) and fruit set leaf thinning (LR, three leaves). All leaf thinning treatments consistently reduced disease incidence compared to control vines in both varieties, with the reduction extent varying between 2017 and 2018. Yield was not negatively affected by leaf thinning treatments, even though PB reduced cluster compactness by decreasing the number of berries per cluster of Chardonnay in 2017. Control vines tended to have greater titratable acidity than defoliated vines, while Brix and pH responses varied between seasons. No direct positive correlation was found between sunlight exposure and norisoprenoids concentration. Post fruit set leaf thinning PF6 consistently increase free norisoprenoids at harvest, while pre-bloom defoliation never did. Heterogeneous responses were observed for bound and total norisoprenoids. In Cabernet Sauvignon free, bound and total 1,1,6-trimethyl-1,2-dihydronaphtalene (TDN) was consistently increased by PF3. Hedging negatively influenced Brix and anthocyanins accumulation in 2017, and increased free norisoprenoids while decreasing the bound and total fraction. Results revealed that a high level of stress possiblt caused by excess sunlight and/or reduced photosynthesis might negatively affect norisoprenoids glycosylation. / Master of Science in Life Science / This project evaluates the effect of a grapevine canopy management practice on grape quality. The objective was to find a suitable technique to expose the fruits to sunlight in order to increase grape aroma concentration and improve grape sanitary status of Virginia vineyards. Leaves were removed from the fruit zone with different intensities at two grape developmental stages, in two varieties (Chardonnay and Cabernet Sauvignon). Treatments consisted of control, three leaves removed before blooming (PB) and three or six leaves removed after fruit set (PF3 and PF6 respectively) In an additional project with Cabernet Sauvignon, the effect of canopy height was integrated with the fruit zone defoliation. Results showed that the removal of leaves from the fruit zone is effective in improving grape sanitary status at harvest, with the improvement extent depending on the season climatic conditions and on the amount of leaves removed. Crop yield was not negatively affected by treatments. Non defoliated grapes tended to have greater acidity at harvest, while sugar responses were inconsistent. Aroma compounds responded heterogeneously to fruit zone defoliation, but volatile odorants were consistently greatest in the most exposed grapes (PF6) compared to all other treatments at harvest. Pre-bloom defoliation instead, never increased volatile aroma compounds compared to control at harvest. Generally, non-volatile odorants were greater in less severely defoliated vines or control. An overall positive effect was observed with PF3. Canopy height was demonstrated to be able to indirectly affect grape quality and composition, with the short canopy reducing grape’s sugar and color content and increasing grape’s volatile aroma compounds concentration at harvest in 2017. The removal of three or six leaves from the fruit zone in post fruit set could be a suitable practice to improve grape quality in the Virginia environment.

Much of the biodiversity in a forest comes from the understory vegetation. However, centuries of fire suppression in the western United States have made human-implemented disturbance necessary for reinstating natural disturbance cycles. However, the mechanical thinning and prescribed burning treatments used by land managers may differentially affect the response of the understory community. This study aimed to compare how prescribed fire and mechanical thinning treatments, with the size and severity of those treatments, affect understory plant communities in aspen-conifer forests over time. We sampled the understory community in burned, mechanically thinned, and untreated forest stands one, three, or five years post-treatment. Within these treatment areas, we measured understory cover, species richness, and leaf area index in belt transects, and we calculated species diversity and non-native cover for each transect. Understory cover increased in burn and mechanical treatments over time and was significantly higher in burned treatments than in untreated stands five years after treatments. Additionally, understory cover was highest in large, low-severity fires. Species richness also increased in burned areas as time since treatment increased. Species richness and species diversity positively correlated with canopy openness in untreated plots, while the cover of non-native species positively correlated with fire severity. Large, lower-severity burns had the most significant positive impact on understory plant communities, but these impacts may take time to become apparent.

Yes / Background: This study proposes a decision support system created in collaboration with machine learning experts and ophthalmologists for detecting keratoconus (KC) severity. The system employs an ensemble machine model and minimal corneal measurements. Methods: A clinical dataset is initially obtained from Pentacam corneal tomography imaging devices, which undergoes pre-processing and addresses imbalanced sampling through the application of an oversampling technique for minority classes. Subsequently, a combination of statistical methods, visual analysis, and expert input is employed to identify Pentacam indices most correlated with severity class labels. These selected features are then utilized to develop and validate three distinct machine learning models. The model exhibiting the most effective classification performance is integrated into a real-world web-based application and deployed on a web application server. This deployment facilitates evaluation of the proposed system, incorporating new data and considering relevant human factors related to the user experience. Results: The performance of the developed system is experimentally evaluated, and the results revealed an overall accuracy of 98.62%, precision of 98.70%, recall of 98.62%, F1-score of 98.66%, and F2-score of 98.64%. The application's deployment also demonstrated precise and smooth end-to-end functionality. Conclusion: The developed decision support system establishes a robust basis for subsequent assessment by ophthalmologists before potential deployment as a screening tool for keratoconus severity detection in a clinical setting.

This research clarified existing inconsistencies in self-assessment literature, and added to the body of knowledge for rating effectiveness of organizational assessments by defining relationships among rating effectiveness criteria (ratee, rater, rating scale, rating process) and measures (interrater reliability, halo error, leniency and severity, range restriction) based on extensive literature review. A research framework was developed from this review, and was employed in computing rating effectiveness measures at the individual (i.e., examiner or eight rating scale dimensions) and sector (e.g., Private Manufacturing Sector, Private Service Sector, Public Local Sector, Public State & Federal Sector) levels for a State Quality Award (SQA) using data from the 1998 applications. Interrater reliability (measured by intraclass correlations for each rating scale dimension) was low to moderate, and differed by dimension. Halo error (measured by the determinant of the dimension intercorrelation matrices for each examiner) was present for all examiners. Leniency and severity (measured by presence of statistically significant Rater main effect for each dimension) was present for 11 of 32 cases, and differed by dimension. Range restriction (measured by variance analysis for each dimension) was present for 22 of 32 cases, and differed by dimension. A post-hoc principle component analysis indicated poor internal reliability for the rating scale. To improve, the SQA should replace the existing rating scale and provide in-depth training on all elements of the rating process. The importance of the SQA using boxplots, histograms, and rating effectiveness measures to make fully informed decisions was discussed. / Master of Science

Yes / This paper proposes a framework to cope with the lack of data at the time of a disaster by em-ploying predictive models. The framework can be used for disaster human impact assessment based on the socio-economic characteristics of the affected countries. A panel data of 4252 natural onset disasters between 1980 to 2020 is processed through concept drift phenomenon and rule-based classifiers, namely Moving Average (MA). A Predictive model for Estimating Data (PRED) is developed as a decision-making platform based on the Disaster Severity Analysis (DSA) Technique. A comparison with the real data shows that the platform can predict the human impact of a disaster (fatality, injured, homeless) up to 3% errors; thus, it is able to inform the selection of disaster relief partners for various disaster scenarios.

The nightmare prevalence literature to date has largely focused on nightmare episode severity (i.e. frequency), with 8%-87% of individuals reporting these events in the past week to year. While this has helped to determine the prevalence of these events, focus on the episode severity alone is problematic because it means little is known about the actual prevalence of nightmare disorder. Moreover, focus on episode severity likely overestimates the actual prevalence of clinically significant nightmares while also obscuring clinically significant consequences of the disorder. Understanding the prevalence of nightmare disorder can help guide treatment planning and interventions. The present study recruited UNT undergraduates (N = 372; 351 analyzed) and managed all participant data using Research Electronic Data Capture (REDCap). The present study aimed to determine the prevalence of nightmare disorder, as stated in the DSM-5, to facilitate accurate characterization of the disorder. Additionally, as part of the secondary aim the influence of gender on nightmare disorder status and psychological wellbeing as measured by psychological and sleep outcome variables was examined. Finally, comparisons of individuals with DSM-5-defined nightmare disorder to those without the disorder were conducted on previously examined correlates (e.g., trauma symptoms, depression).