When there is information overload on the visual modality, another system of warnings must be adopted to prevent potential risks—tactile warning systems present a viable alternative. Building on work on design approaches for auditory warning systems that match appropriate warnings to the severity of risk, this thesis presents an approach to design tactile warnings based on perceived urgency. To do this, I use a subjective rating technique. I performed three experiments to demonstrate this approach. Our research approach uses subjective rating technique to evaluate perceived urgency. Three experiments were conducted to design tactile warnings with a tactile interface developed by attaching a grid of tactors on a vest. In Experiment 1 and 2, I evaluated perceived urgency of several warning designs with three important parameters of tactile warnings with subjective rating. In Experiment 3 I examined one warning design in the context of flight simulation. The results of Experiment 1 and 2 showed that participants can discriminate between all levels of perceived urgency from most warning parameters. In Experiment 3, the results showed that selected warning design was correctly mapped with the severity of most events. The findings suggest that tactile warnings based on perceived urgency can be a possible approach, but further studies will be required to evaluate different parameters of tactile warnings.

This thesis involves the design of an early warning source water monitoring station for a riverine source of drinking water. These stations provide downstream water utilities with advanced notification of contamination events so they have time in which to implement a response. Many threats facing riverine water supplies, such as accidental spills, are uncertain in nature. Therefore, designing a monitoring station for the detection of these events requires a probabilistic modelling approach. Sources of uncertainty considered in this research include the location, mass and duration of a spill event as well as the flow at the time of the spill and the water quality model parameters. Probability distributions for each of these uncertainties were defined and a Monte Carlo experiment was conducted. The design objectives include maximizing the probability of detection and maximizing the probability of having a threshold amount of warning time. These objectives are in conflict with each other because the probability of detection improves as the station moves closer to the intake and the amount of warning time increases as the station is located further upstream. Values for the competing objectives were calculated for a number of potential monitoring station locations at multiple sample intervals and the tradeoff solutions were analyzed. This methodology was applied to the Hidden Valley Intake which services the Regional Municipality of Waterloo’s Mannheim Water Treatment Plant. The Hidden Valley Intake is located in Kitchener, Ontario and withdraws up to 72 ML of water per day from the Grand River. Based on an analysis of the Monte Carlo simulation results for the case study application, it was found that locating the monitoring station near the Victoria Street Bridge, approximately 11 km upstream of the intake, represents the best tradeoff in the design objectives. Sampling at least once per hour is recommended to increase the amount of warning time. The impact of various sources of uncertainty was also explored in this thesis. It was found that the flow at the time of a spill and the spill location are the only sources of uncertainty that significantly impact the probability distributions of relevant model results.

As shisha smoking is increasing globally, the need for a critical action to control shisha smoking consumption becomes crucial. Despite the success of cigarette warning labels in increasing smokers' awareness of the negative health effects of smoking and in motivating smokers to quit, nothing is known about the potential impact health warning labels may have on shisha users. The current study investigated the perception of effectiveness of text-only versus graphic warning among shisha smokers. This study sought to examine the impact of viewing health warning labels on perceived susceptibility and severity of shisha smoking health hazards, on motivating intentions to quit, and on changing the pattern of shisha smoking. Eligible participants first completed an online baseline questionnaire, and were then randomly assigned to one of three conditions:a control condition, in which they viewed nutrition labels (n=100) , or one of two experimental groups in which they viewed Text- only warning labels (n=117), or they viewed Graphic warning labels (n=125). In each of these three conditions, participants viewed six health warning labels and rated them using likert scale questions immediately following each label. Two weeks later, participants were invited to complete an online follow-up questionnaire. The findings indicate that Graphic tobacco warnings grab participants' attention and elicit unfavourable emotional reactions. Although there was a relatively little impact of viewing health warnings on subsequent shisha use, Graphic warnings significantly improved some of the participants' health knowledge .In addition, Graphic warnings significantly increased smokers' beliefs that shisha is harmful to health and dangerous to non-smokers. Patterns of the findings revealed that quit intentions were relatively higher among those who viewed Graphic warning labels. To our knowledge, this study is the first to examine the effect of health warnings on shisha smokers. Overall, findings provide modest support for the efficcacy of shisha warnings on establised users. Findings imply that packaging and labelling policies for shisha and shisha products require additional development. Further examination of specific themes and contents of health warnings directed specifically to shisha smokers in different cultural settings will be critical to ensure the relevance of health warnings in distinct cultural settings.

This thesis involves the design of an early warning source water monitoring station for a riverine source of drinking water. These stations provide downstream water utilities with advanced notification of contamination events so they have time in which to implement a response. Many threats facing riverine water supplies, such as accidental spills, are uncertain in nature. Therefore, designing a monitoring station for the detection of these events requires a probabilistic modelling approach. Sources of uncertainty considered in this research include the location, mass and duration of a spill event as well as the flow at the time of the spill and the water quality model parameters. Probability distributions for each of these uncertainties were defined and a Monte Carlo experiment was conducted. The design objectives include maximizing the probability of detection and maximizing the probability of having a threshold amount of warning time. These objectives are in conflict with each other because the probability of detection improves as the station moves closer to the intake and the amount of warning time increases as the station is located further upstream. Values for the competing objectives were calculated for a number of potential monitoring station locations at multiple sample intervals and the tradeoff solutions were analyzed. This methodology was applied to the Hidden Valley Intake which services the Regional Municipality of Waterloo’s Mannheim Water Treatment Plant. The Hidden Valley Intake is located in Kitchener, Ontario and withdraws up to 72 ML of water per day from the Grand River. Based on an analysis of the Monte Carlo simulation results for the case study application, it was found that locating the monitoring station near the Victoria Street Bridge, approximately 11 km upstream of the intake, represents the best tradeoff in the design objectives. Sampling at least once per hour is recommended to increase the amount of warning time. The impact of various sources of uncertainty was also explored in this thesis. It was found that the flow at the time of a spill and the spill location are the only sources of uncertainty that significantly impact the probability distributions of relevant model results.

There are several methods to predict financial crises. There are also several types of indicators used by financial institutions. These indicators, which are estimated in different ways, often show various developments, although it is not possible to directly assess which is the most suitable. Here, we still try to find what characteristics that industry group has and forecast financial crises In this paper, our data started from monthly of 1977 January to 2008 December in S&P100. We consider Fama-French and Cluster Analysis to process data to make data with same characteristic within a group. Then, we use GARCH type models and apply it to VaR predicting stock turmoil. In conclusion, we found that the group which has high kurtosis value is the key factor for predicting stock crises instead of volatility. Moreover, the characteristics of this industry which can predict stock crises is a great scale. On the other hand, we can through this model to double check the reaction for anticipating. Therefore, people can do some actions to control risk to reduce the loss.

Due to the financial turmoil in recent years, risk management has become an important issue, investors would like to be fully-prepared to cope with financial crisis before it happen. This research uses the Fama and French three-factor and the U.S. Dollar Index (USDX) as an exchange rate variations indicator to capture the international relations. It constitutes a four-factor model to analyze the S&P100 stock returns changes, and we introduce the skewed-t distribution to simulate the distribution of stock returns and capture the characteristics of skewness and kurtosis. We use cluster analysis to cluster the sample companies by their risk characteristics. And then we observe the explanatory power of each risk factor. The study shows that the S&P100 stocks are subjected to the market premium, and the scale effect is smaller than others. ¡@¡@ At last, in accordance with the GARCH-Skewed-t model to simulate the average, variance, skewness and kurtosis of each cluster. We track the long-term performance of each parameter which are used to observe the unusual changes before financial crisis. The empirical results show that the skewness parameter has perfect warning for financial turmoil. The cluster with warning ability is affected by B/M ratio effect and exchange rate changes. Among the case, the cluster has the best early warning effect when it's influenced by the exchange rate indicator. It displays that by adding an exchange rate risk indicator into the multi-factor model, we will have a better clustering result. It means that the skewness parameter of cluster with influence of exchange rate indicator can be used to observe financial turmoil, which can in turns, be used as an early warning system to determine the occurrence of extreme events.

In recent year, the securities firms had suffered form the turmoil of the financial crisis in Taiwan. Although the Taiwan Stock Exchange Corporation and the Securities and Futures Commission have their own early warning systems (EWS), the EWS based on financial statements and the "capital adequacy ratio", respectively for the risks that the brokers and dealers assume, still have some defects: (1) EWS based on financial statements are static and time-lagged in the rapid-moving market, and (2) the calculation rules in the capital adequacy ratio are inelastic and inefficient. This research emphasizes on the stock positions of the dealers, and calculate the "Value at Risk" (VaR) for these positions. In this way, we hope to know whether the EWS based on VaR can detect the risks of the dealers in time, and improve the drawbacks of the EWS based on financial statements and capital adequacy ratio. We found that: (1) the EWS based on VaR can effectively reflect the market risk of the dealers, and (2) the "historical simulation" method might distort the real portfolio risk, thus we suggest that "delta-normal" is a better method, and (3) the EWS based on VaR can discriminate the risk level of different securities dealers. In conclusion, we have the suggestion of the EWS for securities firms in the future. For firm-wide operation, the EWS based on financial statements is suitable; for the credit risks the securities firms may assume, the capital adequacy ratio is better; as for the market risk of the positions, VaR, undoubtedly, is a good alternative.

The problem of dilemma zone protection and red-light-running is especially important in certain rural intersections due to the higher speeds at these intersections and their isolated nature. In addition, the presence of a larger percentage of trucks mean that adequate warning and help need to be given to these truck drivers in order to enable them to stop safely, or proceed through the intersection before the onset of red. To curb any potential danger at such intersections, a Texas Department of Transportation (TxDOT) research project on Advanced Warning for End of Green Phase (AWEGS) at high speed intersections deployed AWEGS at two rural intersection sites ?? Tx 6 @ FM 185 near Waco and US 290 @ FM 577 in Brenham. The deployment of AWEGS involved a Level 1 and a later upgrade to a more efficient Level 2 in Waco. Initial results on red-light-running, even though promising, were expressed as observed red-light-running events per day. These resulting rates did not reflect exposure, and the results also raised some concerns with regards to some increase in red-light-running from Level 1 to Level 2. A more detailed analysis of the red-light-running issue at these two sites is provided in this thesis. The main areas of red-light-running analyses presented here are with respect to the reductions in red-light-running rates for the exposure factors of number of cycles and vehicular volumes, the comparison of day and night RLR rates and the nature of speeds of vehicles running the red light at the intersection in Waco. AWEGS was found to reduce the total red-light-running per exposure factor after its deployment. Both Level 1 and Level 2 AWEGS operations were found to reduce red-light-running by up to 60%. Generally, total red-light-running per exposure factor between Level 1 and Level 2 was found to be about the same. Level 2 had lower daytime red-light-running rates and higher nighttime rates than Level 1. Generally, day rates were found to be higher than night rates for all levels of AWEGS deployment. It is recommended that, to better understand the operational aspects of AWEGS and to improve its operations, more implementation of AWEGS and further tests be done. An automated method to collect and analyze data needs to be developed as well as a means of automatically recording video data for calibration and verification It is also recommended that Level 1 technology be implemented in areas where the Level 2 technology may be either too complex or too expensive.

It is important to identify students at-risk for school non-completion as early as possible. Research has demonstrated that data sources such as teacher nomination and individual demographic characteristics are less accurate identification methods of students who are at-risk for not graduating on-time. Instead, the use of early warning systems (EWS) based upon research validated indicators that reliably identify students who are Off-track, or at-risk for not graduating on-time, has been a promising approach. Questions remain though about the relationship of Off-track Status at an earlier time point to Off-track Status at a later time point as well as the relationship between a variety of individual and school-level predictors and Off-track Status. The purpose of this study was to examine student patterns of Off-track (for graduation) Status at two time points each year from sixth grade through the end of 10th grade as determined by a district-implemented EWS. In addition, this study examined factors that were hypothesized to contribute to students becoming off-track for high school graduation and the earliest time that those factors demonstrated influence on an Off-track Status. Individual (e.g., SES Level, Third-Grade Reading scores, etc.) and school-level predictors (e.g., School Rates of Discipline, School Promoting Power, etc.) of Off-track Status were collected through archival data on a cohort of 4,268 sixth-grade students across 15 middle schools and 13 high schools from the 2007/2008 school-year through the 2011/2012 school-year. Significant relationships between individual-level variables (SES Level, Hispanic racial/ethnic designation, Grade Point Average, Office Discipline Referrals and Previous Off-track Status) were found. Implications for research to practice include a focus on early intervention of Off-track Status students and the inclusion of additional variables in a middle and high school EWS. An additional implication for practice is the local customization of EWS through further analyses of predictor sensitivity and specificity as well as examination of specific school-level contributions to increased numbers of Off-track Status students which would allow for refinement of EWS specific to a given population and provide information on schools that may need additional resources to support students.

Intrastate conflicts in Sub-Saharan Africa are a development tragedy and a security dilemma that requires more prevention and better intervention from the international community. Such engagement necessitates a robust early warning system, which can determine, with a sufficient degree of accuracy, the countries most at risk of experiencing intrastate conflict. This research summarizes and critiques current efforts to conceptualize intrastate conflict in Sub-Saharan Africa and determine what factors best explain the likelihood of intrastate conflict onset. The research examines the challenges of empirically modelling the human behaviour that underlies intrastate conflict, as well as some promising avenues for overcoming challenges posed by data issues and existing methodological shortcomings. The research concludes that with improved data and research design, and more attention being paid to how statistical significance reflects pathway(s) to violence, the development of an intrastate conflict early warning system is possible.