In-ground slope monitoring is an essential part of landslide early warning systems. Precise movement data from borehole monitors can detect emerging hazards near critical infrastructure. Typically, monitoring is done with inclinometers, but lower-cost alternatives have emerged which have yet to be tested in Tennessee. Time domain reflectometry (TDR) records magnitudes and depths of movements along a buried coaxial cable. When paired with a remote data logger, TDR can wirelessly transmit high resolution movement data in real time, making it promising for landslide early warning systems. Tennessee Department of Transportation (TDOT) has proposed a one-year feasibility study to test TDR for use in unstable soil slopes near highways. The study area is a well-known landslide site along Interstate 40 in Roane County, TN. Careful siting of borehole instrumentation is crucial for accurate monitoring. The goal of this study is to optimize TDR installation, with three specific aims: (i) evaluate landslide morphology, (ii) pinpoint locations and depths with greatest movement, and (iii) assess spatiotemporal patterns across the site. Statistical analysis of prior data from 13 inclinometers showed ongoing slope movement over the 21-acre complex landslide. Spatial interpolation suggested an asymmetrical failure surface with both shallow and deep motion. Space-time cube analysis indicated varying movement rates and timing across the site, suggesting separate landslide bodies. Based on these results, three optimal borehole depths and locations were proposed for TDR instruments. This analysis will ensure accuracy in tests of TDR for early warning system feasibility in Tennessee.

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Failure to rescue (FTR) outcomes may be one consequence of the relationship be-tween healthcare provider behaviors and attitudes, organizational factors, and environ-mental factors that intersect to potentially threaten patient safety. Early warning systems (EWS) were designed as surveillance systems to reduce failure to rescue events and avoid morbidity and mortality. Challenges with EWS include lack of standardization, organiza-tional barriers, such as culture and supports, and human factor attributes such as intuition, expertise, and experience. The experience and perceptions of nurses using EWS technolo-gy as it relates to their clinical assessment, critical thinking, and decision-making skills has yet to be undertaken. This study adds to the body of EWS and FTR literature and the broader culture of safety literature in acute care environments. The purposes of this exploratory qualitative descriptive study was to explore the experiences of nurses using EWS in acute care practice settings and how they perceive it impacts on their critical thinking and clinical decision-making processes. The study identi-fied three informative findings: a) EWS has added value particularly with novice nurses or nurses new to practice settings, b) EWS provides benefits to nurses working in acute clinical environments that experience high volumes and high acuity of patients by alerting or reminding them about potential FTR situations, and c) Existing EWS may require mod-ification to improve adequacy, reduce redundancy, and reduce alarm fatigue. Based on the evidence reviewed, a qualitative study to increase our understanding of the experi-ence of nurses and their perception of the impact of EWS and related technology on their critical thinking and other nursing practice processes has the potential to contribute to a wider evaluation of EWS systems and to improve patient outcomes. / Thesis / Master of Science (MSc) / Before patients on general medical or surgical hospital units become so ill that they need to be transferred to an intensive care unit, they have abnormal vital signs and other physiological changes that can go unnoticed for 2448 hours. As these changes can be hard to detect and serious illness can begin very slowly at first, early warning systems have been developed to help health care professionals respond to patient’s conditions before they need to be in an intensive care unit. These early warning systems can be in the form of new technology and assist nurses with preventing a serious illness from becoming critical. It is not well research or understood how nurses experience such early warning systems technology and it is not well understood how nurses think this technology impacts their nursing practice. The overall aim of the study is to learn more about the experience and perception of nurses who use this technology, how they believe it informs their nursing practice and how it supports them in making clinical decisions about patient care.

<p> One of the important objectives of a Radar Warning Receiver (RWR) aboard a tactical aircraft is to evaluate the level of threat posed by hostile radars in an extremely complex Electronic Warfare (EW) environment in reliable, robust and timely manner. For the RWR objective to be achieved, it passively collects electromagnetic signals emitted from potentially hostile radars. One class of such radar systems is the Multi-Function Radar (MFR) which presents a serious threat from the stand point of a RWR. MFRs perform multiple functions simultaneously employing complex hierarchical signal architecture. The purpose of this paper is to uncover the evolution of the operational mode (radar function) from the view point of a target carrying the RWR when provided with noisy observations and some prior knowledge about how the observed radar functions. The RWR estimates the radar's threat which is directly dependant on its current mode of operation. This paper presents a grid filter approach to estimate operational mode probabilities accurately with the aid of pre-trained Observable Operator Models (OOMs) and Hidden Markov Models (HMMs). Subsequently, the current mode of operation of a radar is estimated in the maximum a posteriori (MAP) sense. Practicality of this novel approach is tested for an EW scenario in this paper by means of a hypothetical MFR example. Finally, we conclude that the OOM-based grid filter tracks the mode of operation of a MFR more accurately than the corresponding HMM-based grid filter. </p> / Thesis / Master of Applied Science (MASc)

An average of 42,000 fatalities occur on the United States of America's roads each year as a result of motor-vehicle crashes (National Highway Traffic Safety Administration, 2003). The dangers with respect to curves exist, from late notification of direction and speed, varying methods for determining advisory speeds, as well as driver unfamiliarity and/or over confidence. A curve-warning device, a device that notifies the driver of an upcoming curve and, possibly, conveys its vehicle-specific advisory speed and even direction, has the potential to drastically reduce the dangers of curve navigation. This study was performed as a proof of concept with regard to appropriate modalities and respective stimuli for a curve warning application. For this study, objective and subjective measurements were collected in a simulator environment to compare conditions comprised of multiple stimuli from the auditory (icon, tone, and speech), visual (Heads Down Display and Heads Up Display), and haptic (throttle push-back) modalities. The results of the study show that the speech stimulus was the most appropriate of the auditory stimuli for both objective and subjective measurements. Objectively, the HDD and HUD were comparable with respect to performance, although the participants tended to favor the HDD in their subjective ratings. The throttle push-back did little to positively impact the performance measurements, and based on participant comments and ratings, it is not recommended for a curve-warning application. Of the stimulus conditions (combinations of two and three modalities), the Speech and HDD condition provided performance gains and subjective acceptability above the rest of the conditions. / Master of Science

Risk indicators are metrics that are widely used in risk management to indicate how risky an activity is. Among different types of risk indicators, early warning systems are designed to help decision makers predict and be prepared for catastrophic events. Especially, in complex systems where outcomes are often difficult to predict, early warnings can help decision makers manage possible risks and take a proactive approach. Early prediction of catastrophic events and outcomes are at the heart of risk management, and help decision makers take appropriate actions in order to mitigate possible effects of such events. For example, physicians would like to prevent any adverse events for their patients and like to use all pieces of information that help accurate early diagnosis and interventions. In this research, first we study risk assessment for occupational injuries using accident severity grade as an early warning indicator. We develop a new severity scoring system which considers multiple injury severity factors, and can be used as a part of a novel three-dimensional risk assessment matrix which includes an incident's severity, frequency, and preventability. Then we study the predictability of health outcome based on early risk indicators. A systems model of patient health outcomes and hospital length of stay is presented based on initial health risk and physician assessment of risk. The model elaborates on the interdependent effects of hospital service and a physician's subjective risk assessment on length of stay and mortality. Finally, we extend our research to study the predictive power of early warning systems and prognostic risk indicators in predicting different outcomes in health such as mortality, disease diagnosis, adverse outcomes, care intensity, and survival. This study provides a theoretical framework on why risk indicators can or cannot predict healthcare outcomes, and how better predictors can be designed. Overall, these three essays shed light on complexities of risk assessments, especially in health domain, and in the contexts where individuals continuously observe and react to the risk indicators. Furthermore, our multi-method research approach provides new insights into improving the design and use of the risk measures. / Ph. D.

The I-81 Corridor in Virginia traverses the western part of the state, connecting Bristol in the south to Winchester in the north. A study carried out at the Virginia Tech Center for Transportation Research identified traffic safety, work zone safety and traffic control, trucking issues, and intercity traveler information needs as important issues that deserve attention on the I-81 Corridor in Virginia. Analysis of work zone accident statistics showed a need for real-time systems to enhance work zone safety. Real-time advanced warning and traffic control systems provide a means of dynamic information dissemination and advanced warning, thereby enhancing work zone safety and facilitating traffic control. The focus of this research was on the development of functional and system requirements for a real-time advanced warning and traffic control system for work zones. This task was based on the examination of work zone accidents and their causes. The functional requirements include advanced warning, surveillance, advisory, and control functions. Each of these functions consists of several sub-functions. The needs with respect to each of these functions have also been identified. System requirements such as real-time operation, credibility, portability, ease of installation, and adaptability were also identified. Evaluation criteria and potential Measures Of Effectiveness (MOEs) for the evaluation of the system were also identified. Additionally, issues related to the evaluation of the system, such as time duration for evaluation and data collection techniques were identified and examined. / Master of Science

Yes / The National Early Warning Score (NEWS) is being replaced with NEWS2 which adds 3 points for new confusion or delirium. We estimated the impact of adding delirium on the number of medium/high level alerts that are triggers to escalate care. Methods Analysis of emergency medical admissions in two acute hospitals (York Hospital (YH) and Northern Lincolnshire and Goole NHS Foundation Trust hospitals (NH)) in England. Twenty per cent were randomly assigned to have delirium. Results The number of emergency admissions (YH: 35584; NH: 35795), mortality (YH: 5.7%; NH: 5.5%), index NEWS (YH: 2.5; NH: 2.1) and numbers of NEWS recorded (YH: 879193; NH: 884072) were similar in each hospital. The mean number of patients with medium level alerts per day increased from 55.3 (NEWS) to 69.5 (NEWS2), a 25.7% increase in YH and 64.1 (NEWS) to 77.4 (NEWS2), a 20.7% increase in NH. The mean number of patients with high level alerts per day increased from 27.3 (NEWS) to 34.4 (NEWS2), a 26.0% increase in YH and 29.9 (NEWS) to 37.7 (NEWS2), a 26.1% increase in NH. Conclusions The addition of delirium in NEWS2 will have a substantial increase in medium and high level alerts in hospitalised emergency medical patients. Rigorous evaluation of NEWS2 is required before widespread implementation because the extent to which staff can cope with this increase without adverse consequences remains unknown.

To date, there are no evidence-based peer bystander intervention trainings (BIT) aimed at educating peers in school shooting warning behaviors. The purpose of this study was to examine an interactive BIT where peers were taught warning behaviors related to someone planning a school shooting and how to report this information. This training was evaluated against a currently available training method (i.e., PowerPoint presentation based) and a control group to determine the best training approach. College students between 18 and 19 years old (N = 57) completed pre, post, and one-month follow-up assessments. At each timepoint accuracy in detection of warning behaviors, overall willingness to report, attitudes toward reporting, perceived behavioral control (PBC), and intent to report was assessed. A linear regression mixed effects model was performed for each variable of interest. Results indicate that all groups increased in accuracy from preassessment to post assessment, and from preassessment to one-month follow-up for the first accuracy assessment, but not the second. Participants’ willingness to report, attitudes toward reporting, PBC, and intent to report increased between preassessment and post assessment, and preassessment and one-month follow-up. The was a significant interaction effect between time and group for willingness to report and PBC between preassessment and post assessment for the interactive BIT group compared to the control group. The interactive BIT group demonstrated the highest positive attitudes toward reporting compared to the control group between pre and post assessment. For intent to report, the PowerPoint presentation group demonstrated the highest increase in intent to report compared to the interactive BIT group at one-month follow-up. Results indicate the intervention training has potential for educating peers in warning behaviors with modifications. Future research should focus on these modifications.