Freight transportation networks are an important component of everyday life in modern society. Disruption to these networks can make peoples’ daily lives extremely difficult as well as seriously cripple economic productivity. This dissertation develops a quantitative framework for assessing vulnerability and redundancy of freight transportation networks. The framework consists of three major contributions: (1) a two- stage approach for estimating a statewide truck origin-destination (O-D) trip table, (2) a decision support tool for assessing vulnerability of freight transportation networks, and (3) a quantitative approach for measuring redundancy of freight transportation networks.The dissertation first proposes a two-stage approach to estimate a statewide truck O-D trip table. The proposed approach is supported by two sequential stages: the first stage estimates a commodity-based truck O-D trip table using the commodity flows derived from the Freight Analysis Framework (FAF) database, and the second stage uses the path flow estimator (PFE) concept to refine the truck trip table obtained from the first stage using the truck counts from the statewide truck count program. The model allows great flexibility of incorporating data at different spatial levels for estimating the truck O- D trip table. The results from the second stage provide us a better understanding of truck flows on the statewide truck routes and corridors, and allow us to better manage the anticipated impacts caused by network disruptions.A decision support tool is developed to facilitate the decision making system through the application of its database management capabilities, graphical user interface, GIS-based visualization, and transportation network vulnerability analysis. The vulnerability assessment focuses on evaluating the statewide truck-freight bottlenecks/chokepoints. This dissertation proposes two quantitative measures: O-D connectivity (or detour route) in terms of distance and freight flow pattern change in terms of vehicle miles traveled (VMT). The case study adopts a “what-if” analysis approach by generating the disruption scenarios of the structurally deficient bridges in Utah due to earthquakes. In addition, the potential impacts of disruptions to multiple bridges in both rural and urban areas are evaluated and compared to the single bridge failure scenarios.This dissertation also proposes an approach to measure the redundancy of freight transportation networks based on two main dimensions: route diversity and network spare capacity. The route diversity dimension is used to evaluate the existence of multiple efficient routes available for users or the degree of connections between a specific O-D pair. The network spare capacity dimension is used to quantify the network- wide spare capacity with an explicit consideration of congestion effect. These two dimensions can complement each other by providing a two-dimensional characterization of freight transportation network redundancy. Case studies of the Utah statewide transportation network and coal multimodal network are conducted to demonstrate the features of the vulnerability and redundancy measures and the applicability of the quantitative assessment methodology.

Studying long-term ecological studies allows for a better understanding of processes driving populations and communities, and this understanding can be used to improve conservation eorts. These studies can describe how changes in the environment have led to current states of populations and communities, and indicate if the current state or trend falls within expectations based on past dynamics. Studies of long-term datasets also help ecologists predict how populations may shift with climate, water, or land-use change and determine necessary management action to maintain sustainable populations and community interactions. Serving as a \test of time," long-term monitoring can provide insight into the in uence of predation, intra- or interspecic competition, and other interactions on system dynamics. Studies need to explicitly include these drivers and sources of autocorrelation in data (e.g., spatial autocorrelation) to obtain unbiased estimates of ecological processes for guiding management. Fortunately, new statistical analyses for ecological applications are available that help ecologists make full use of the information present in long-term studies while properly accounting for sampling error and autocorrelation. In this study, I use advanced statistical methods to analyze a long-term dataset, the Waterfowl Breeding Population and Habitat Survey, and address questions about waterfowl population and community dynamics. In Chapter 2, I use multi-state occupancy models to determine how the presence of lesser and greater scaup (Aythya anis and A. marila) has changed on their breeding grounds in North America since 1955. In Chapter 3, I use a Bayesian hierarchical model to determine the drivers of the breeding scaup population in the Northwest Territories of Canada. Lastly, in Chapter 4 I incorporate more waterfowl species into the hierarchical model from Chapter 3 to determine the drivers of the pochard duck community, along with the role of species interactions. My results indicate that the occupancy of scaup has decreased in the boreal forest of Canada and increased in the prairie parklands. Additionally, scaup in the Northwest Territories are largely in uenced by density dependence and snow cover extent. Finally, the pochard community in the Northwest Territories is regulated more by environmental drivers than intra- or interspecic interactions. These results indicate that management of the species through hunting regulations likely deserves further study, as scaup likely exhibit some sort of compensation in response to hunting.

The purpose of this study was to measure the competency of problem solving skills of fourth-year veterinary students. The study identified two primary objectives, (a) define clinical competency for fourth-year veterinary medical students, and (b) construct an instrument to assess the student’s level of clinical competency. A faculty advisory panel identified three themes in the development of a definition of clinical competency, (a) competency was situational, (b) competency was described by ability, and (c) the definition of fourth-year student competence was descriptive within the context of primary patient care. The description of competency contributed to the establishment of parameters applied to the rubric. Student self-assessments were taken twice; initially at the beginning of the clinical rotation, and again at the end of the rotation as a post-clinical assessment. The faculty instructor provided a comparison post-clinical assessment to serve as an authentication of the reliability of the instrument. Overall, students qualified themselves to be “Fully Competent Students” at the beginning of the clinical rotation, and also at the end of the rotation. However, in the disaggregated quantified scores, the student self-assessment peaked at the highest competence level, “Among The Most Competent Students,” for five descriptors of values and beliefs listed under Responsibility, Professionalism, and Interpersonal Skills. The faculty comparison assessment was in agreement with the student’s qualified description as “Fully Competent Students” but did not agree with the higher quantified scores posted for values and beliefs. The descriptive statistics of the data reflect that the mean increased between the pre-clinical (M = 8.43, SD = 1.36) and the post-clinical (M = 9.10, SD = 1.32) assessments. The comparison mean for the faculty assessment (M = 9.01, SD = 1.52) was slightly lower than the student post-assessment. The assessment provided evidence supporting a confidence statement that the instrument has the sensitivity to detect changes in skills, and is consistent with research validated measures of problem-solving skills. Faculty authentication provided evidence of intra-rater reliability, while statistical analysis provided evidence that a relationship appears to be present between live-patient animal instruction and the increase in problem-solving competence of fourth-year veterinary students.

Dissertation (LLM)--University of Pretoria, 2013. / gm2015 / Centre for Human Rights / LLM / Unrestricted

As a result of its capacity for material discrimination, hyperspectral imaging has been utilized for applications ranging from mining to agriculture to planetary exploration. One of the most common methods of exploiting hyperspectral images is spectral unmixing, which is used to discriminate and locate the various types of materials that are present in the scene. When this processing is done without the aid of a reference library of material spectra, the problem is called blind or unsupervised spectral unmixing. Independent component analysis (ICA) is a blind source separation approach that operates by finding outputs, called independent components, that are statistically independent. ICA has been applied to the unsupervised spectral unmixing problem, producing intriguing, if somewhat unsatisfying results. This dissatisfaction stems from the fact that independent components are subject to a scale ambiguity which must be resolved before they can be used effectively in the context of the spectral unmixing problem. In this dissertation, ICA is explored as a spectral unmixing approach. Various processing steps that are common in many ICA algorithms are examined to assess their impact on spectral unmixing results. Synthetically-generated but physically-realistic data are used to allow the assessment to be quantitative rather than qualitative only. Additionally, two algorithms, class-based abundance rescaling (CBAR) and extended class-based abundance rescaling (CBAR-X), are introduced to enable accurate rescaling of independent components. Experimental results demonstrate the improved rescaling accuracy provided by the CBAR and CBAR-X algorithms, as well as the general viability of ICA as a spectral unmixing approach.

The purpose of this study was to compare depressive symptoms reported by boys who were either pre- or postpubescent and who were legally designated delinquent or had no legal histories. A self-report puberty scale and a semi-structured interview (the Child Assessment Schedule-CAS) were administered to 48 boys. Results were analyzed using analysis of variance (ANOVA). Significance levels between groups were examined with Duncan's range test. No significant differences were found between pre- and postpubescent boys for reporting depressive symptoms, but delinquent youths were found to report significantly more depressive symptoms than nondelinquent youths. The implications of these results are discussed in relation to the measures used and recommendations for future research.

Book Summary: This book is really a reflection of the past more than 20 years of work with teens and suicide prevention in the state of Kentucky. The work to establish the “Stop Youth Suicide Campaign (SYS)” has resulted in contact with many young adults, and we have found that the most important thing for all of them was finding a caring person they trust and can talk to. Because of the constant need, the SYS went from a goal of being a one year awareness campaign to becoming a major community resource, working with the state and local governments and state legislators to add as many resources as possible. We have witnessed for the first time a drop of youth suicide rates below the national average, according to the 2013 Youth Risk Behavior Surveillance done biannually by the Center for Disease Control. In this book, we will tackle various topics and specific populations in relation to suicide written by people who work with teens and care about them.

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The purpose of this study consisted of three main components: 1) to identify effective counselor characteristics in the literature; 2) to describe existing admission requirements of counseling programs; and, if a need was determined, 3) to develop a framework for a standard set of admission requirements, balanced between cognitive-behavioral characteristics and personal-emotional characteristics, to more thoroughly assess prospective master’s level counseling students. This study discusses the typical admission requirements of master's level CACREP (The Council for Accreditation of Counseling and Related Educational Programs) counseling programs and what the research indicates are characteristics of effective counselors. A literature review of effective counselor characteristics and graduate admission requirements was conducted, CACREP guidelines were examined, and admission requirements and procedures for all 129 CACREP counselor education programs were analyzed. The findings from the literature review were then compared with the data collected and analyzed from existing master’s level CACREP counseling programs to determine gaps between the literature-identified characteristics of effective counselors and current admission criteria of CACREP programs. Follow-up telephone interviews with a faculty of leadership stature from a sample of 20 CACREP counseling programs were conducted. After determining a need, information collected was used to develop a framework for a standard set of admission requirements. Results indicated that currently, a) there is no framework for a standard set of admission requirements for assessing prospective students for master’s level counseling programs that identify personal-emotional characteristics, b) there are gaps between what the literature identifies as effective counselor characteristics and what is typically assessed during admission, c) an agreement exists that the counseling profession must do a better job of gate-keeping, and d) that a framework of admission requirements is needed by counselor educators to assist in a more thorough screening and examination of personal characteristics of prospective students. Finally, e) this research established a foundation for this framework of a standard set of admission requirements that could be used by faculty to more exhaustively assess prospective master’ s level counseling students. / Ph. D.

To assess fraud risk, auditors collect evidence in a sequential manner by reviewing workpaper documentation, and by collecting corroborating and clarifying information from financial (management) personnel and nonfinancial (operating) personnel. SAS 99 (AICPA, 2002) noted that audit evidence gathered from financial personnel may be susceptible to deception. In addition, prior researchers have found auditors to be poor at detecting deception immediately following deceptive communication. Though the audit process is sequential and iterative, these studies measured auditors– ability to detect deception at a single point and did not provide corroborating evidence after the deceptive communication for auditors to revise their judgments. In this study, I examined auditors’ fraud risk assessments and truthfulness judgments throughout the audit process when there was an attempt at deception by management (financial) personnel. The belief adjustment model provided a framework to examine auditors’ initial judgments, their judgments directly following a deception attempt by financial personnel, and their judgments after receiving corroborating evidence from nonfinancial personnel. Sixty-four experienced auditors electronically completed one of four randomly assigned cases and, within each case, assessed the fraud risk, truthfulness, trustworthiness, and reliability of financial personnel at multiple points for a fictitious client. I manipulated the presence (absence) of fraud and the level of experience of the source of corroborating evidence (operating personnel). I hypothesized that auditors would not be able to differentially evaluate fraud risk and truthfulness judgments of financial personnel between the fraud and no fraud conditions when exposed to workpaper documentation and deceptive client inquiry evidence by management (financial personnel). However, I expected to find that auditors– would update their fraud risk and truthfulness judgments as they reviewed audit evidence from nonfinancial (operating) personnel. The results indicate that auditors in this study are not able to appropriately assess fraud risk and the truthfulness of financial personnel following the review of workpaper and client inquiry evidence. While the client was deceptive in the fraud condition only, auditors did not differentially assess the fraud risk and truthfulness of financial personnel between the fraud and no fraud conditions. After auditors reviewed evidence from nonfinancial personnel, in the presence of fraud, auditors increased their fraud risk and decreased their truthfulness judgments of financial personnel as inconsistent evidence was presented from a corroborating source. Therefore, in the presence of fraud, auditors improved the effectiveness of the audit process by appropriately increasing their fraud risk assessments in light of inconsistent audit evidence from nonfinancial (operating) personnel. Of equal importance, in the absence of fraud, auditors decreased their fraud risk assessments as consistent evidence was presented from a corroborating source. Therefore, auditors increased the efficiency of the audit process by appropriately decreasing their fraud risk assessments after integrating consistent audit evidence from nonfinancial personnel into their judgments. Further, I observed that these auditors revised their fraud risk assessments to a greater extent when audit evidence was provided by a source with a higher level of experience. Though prior research has found auditors to be poor at detecting deception, the results of this study indicate that auditors will increase or decrease their fraud risk assessments and truthfulness judgments based on the consistency of audit evidence gathered from a corroborating source. Therefore, in practice, auditors may be able to detect deception as the audit progresses. / Ph. D.