The nation has placed a spotlight on improving graduation rates for all students. The current study analyzed retrospective, longitudinal student data from the fifth largest school district in Oregon to create an Early Warning Indicator System (EWS) to identify students on track to graduate and those who are not. This study creates an EWS system using the student demographics and the ABC’s of (a) attendance, (b) behavior, and (c) coursework to identify students who are on track and those who are not. I employed logistic regression model to build a prediction model using middle school data (N = 2,041) that examined predictors established in sixth through eighth grade with high school graduation. The dependent variable, four-year graduation was coded as graduate or non-graduate. The independent variables were (a) gender, (b) race, (c) ELL status, (d) SPED Status (e) attendance rate, (f) ODR’s, and (g) number of F’s in English Language Arts and Mathematics. Attendance rate was the strongest predictor of high school graduation. Overall the model predicted graduates with 89.7% accuracy and non-graduates with 33.6% accuracy with the total model predicting 69.5% of graduates and non-graduates.

Purpose: The aim of this project was to evaluate data from a survey sent to nurses in regards to the current practices and workflow of the Early Warning System (EWS) currently in use at Banner Health. Methods: A descriptive cross-sectional design was used to collect feedback from Registered Nurses. The survey was open between February and March of 2016. Likert style and open-ended questions demonstrate evidence supporting the following study questions: 1) What are the barriers to documentation that triggers the EWS? 2) To what extent is the EWS useful and usable? 3) What were the features of the EWS implementation? Results: Findings demonstrated three barriers associated with EWS protocol compliance to include increased workload (78%), previous negative responses from providers (62%), and alert fatigue (48%). Provider responsiveness to notification of the Early Warning Score was shown to be effective "most of the time" and "about half of the time" at 71%, with 12% indicating "sometimes" and "never". Deployment of the Rapid Response Team (RRT) when indicated by EWS algorithm showed only 9 (14%) of nurses always call the RRT, 7 (11%) call about half the time, and 16% indicated they never use the RRT. "Real time" charting occurred 50-75% or less than 50% of the time for 96% of respondents. Open ended questions support recommendations for future practice to include: implementation of a pop up alert for easy recognition of changes in EWS, tailoring parameters based on individual patient characteristics, automatic direct paging to medical providers, and elimination of the level of consciousness parameter. A validated usability survey provided data with a mean response rate (n=58). Nurses (84%) agree the EWS is useful and usable. Ease of use, efficiency, and comfort with EWS software showed 90% agree. System interface responses demonstrate 23% dislike using the interface, and 21% felt the system interface was unpleasant.Conclusions: Findings demonstrate EWS system usability and usefulness. Recommendations for improvement include implementation of a "pop up" alert for easy recognition of changes in the Early Warning Score and/or automatic direct paging to medical providers and nursing will increase effective use. Barriers to EWS protocol documentation include increased workload, previous negative response from providers, and alert fatigue. "Real time" documentation of physiological parameters is essential to successful triggering of an Early Warning Score.

Nowadays, the trend towards globalization and internationalization of business has strong impact on companies’ strategy. When a company is thinking about strategy development, it needs to pay attention to variable aspects on micro- and macro-level. This study includes the overview of the factors which need to be considered while developing a strategy. Moreover, a significant emphasize is made on the contemporary deriving challenges at the market. The purpose of the study is to investigate a new approach to the strategic planning, named “Early warning system”. For that purpose, it was conducted qualitative research at the example of the Ukrainian telecommunication company – MTS Ukraine. I identified factors which influence the company and analyzed how company copes with deriving challenges. Moreover, it was found out the company’s strategic planning process is significantly influenced by specific market characteristics such as high level of bureaucracy, specific behavior of some competitors, growing market.

Active traffic management is a hot topic for addressing issues of highway congestion. It is the use of intelligent transportation systems to provide real time traffic information on highway conditions. In Austin, the segment of Interstate 35 between Riverside Drive and State Highway 71 experiences both congestion and safety issues. This report provides an introduction into the application of active traffic management through the use of a proposed queue warning system in the area. First, select crash data on the region is highlighted to present the safety conditions, particularly the type of collision and crash severity involved. Next, a proposed queue warning system design is described. This includes a description of the equipment used, methodology for system deployment, and expected outcomes. Finally, a computer simulation testing the operational performance of the queue warning system is performed using VISSIM, and the results are reported. This report aims to demonstrate the role that queue warning system and active traffic management may play in addressing metropolitan traffic needs. / text

Översvämningar förekommer regelbundet på stora delar av jordklotet. Utgående från de klimatförändringar vi ser idag med, bland annat, kraftigare och intensivare nederbörd är det troligt att det blir fler och större översvämningar framöver. Områden som inte tidigare varit översvämmade kan komma att bli översvämmande.   Varje land eller område med regelbundna översvämningar har någon form av varningssystem. Översikter över olika typer av system för att varna för översvämningar är svåra att finna.   Syftet med denna uppsats är att: Undersöka viktiga principer för effektiva varningssystem för översvämningar som orsakas av kraftig nederbörd och/eller vårflöden. Skapa en systematisk och strukturerad sammanställning över nuvarande system för att varna för översvämningar orsakade av kraftig nederbörd och/eller vårflöden. Ge praktiska exempel på några svenska kommuners system för att varna för översvämningar.   Litteratur- och internetsökningar kring varningssystem för översvämningar samt intervjuer med ”översvämningsansvariga” i Ödeshög och Vetlanda kommuner utgör grunden för informationen i denna uppsats.   Exempel på olika typer av varningssystem för översvämningar presenteras. Saker att tänka på vid val av, och vid drift och underhåll av, automatiska varningssystem belyses.   En indelning (Grust, 2006) av varningssystem i manuella, enkla automatiska och sofistikerade automatiska utökas till en matris med i matrisens andra dimension lokala, avrinningsområdes, nationella, multinationella och globala varningssystem. De i uppsatsen beskrivna exemplen på varningssystem positioneras in i matrisen.   Varningssystem för översvämningar i två svenska kommuner, Ödeshög och Vetlanda, beskrivs och likheter och skillnader mellan kommunernas system presenteras. / Flooding occurs all over the world on a regular basis. Based on the climate change ongoing today with heavier and more intense precipitation we can expect more and larger floods than we have seen before. Areas which have not been flooded earlier may now become flooded.   Every country or area which is flooded on a regular basis has some kind of warning system. Overviews of various types of flood warning systems are difficult to find.   The purpose of this thesis is to: Investigate important principles of effective flood warning systems caused by heavy precipitation and/or spring flood. Create a structured and systematical overview of current flood warning system for floods caused by heavy precipitation and/or spring flood. Describe two local Swedish community´s flood warning systems.   Literature and Internet search covering flood warning systems combined with interviews on site at Ödeshög and Vetlanda forms the basis for the information in this thesis.   Examples of various types of flood warning systems are presented. Issues regarding the selection of, and the operation and maintenance of, automatic warning systems are described.   A grouping (Grust, 2006) of warning systems in manual, simple automatic and sophisticated automatic is expanded to a matrix with the second dimension of the matrix being local, drainage area, national, multinational and global warning systems. The examples of warning systems covered in this thesis are placed in the matrix.   The similarities and differences between the flood warning systems in two local Swedish communities Ödeshög and Vetlanda are described.

The nursing culture of an inpatient pediatric unit was resistant to activating pediatric rapid response team (PRRT) alerts despite guidelines for activation. Nurses routinely assessed patients and assigned a pediatric early warning score (PEWS); however, the level of illness severity was not interpreted consistently among nurses and a PEWS action algorithm did not exist to guide nurses' minimal actions based on the PEWS score. Guided by 3 adult learning theories (Knowles, Kolb, and Bandura) and 1 evaluation model (Kirkpatrick), this staff education project sought to educate pediatric nurses on a PEWS action algorithm and determine whether this project improved nurses' knowledge, situational awareness, and attitude toward activating PRRT alerts. A convenience sample of 30 pediatric nurses completed a preeducation knowledge survey (EKS), attended an interactive PEWS education class, and completed a postEKS. After participating in the class, correct responses on the EKS increased from 43% to 82% and, using the Wilcoxon-signed rank test, a significant increase was noted in nurses' responses to questions related to self-efficacy, factual knowledge, and application. The overall increase in the nurses' self-efficacy and knowledge about the PEWS might enhance critical-thinking skills, foster identification of patients at risk for clinical deterioration, and empower nurses to follow the PEWS action algorithm including activation of PRRT alerts when indicated. This project has the potential to effect positive social change by supporting nurses' actions designed to improve pediatric patient outcomes.

Over one million high school students drop out of school each year in this country. Dropping out of school is a serious problem for the student, community, and the nation. Often dropouts are unable to compete in an increasingly technological society and face numerous consequences from their decision to leave school early including higher levels of poverty, unemployment, public assistance, incarceration, and poor health. Dropping out is a gradual process of school disengagement and related to individual, family, and school factors. In the past, it has been difficult to track individual student's progress through school and to determine accurate dropout and graduation rates. In 2005, the National Governors Association made a commitment to implement a uniform method to calculate and report graduates and dropouts as well as better data collections systems.This study intended to replicate aspects of other major studies around the county to determine the best early predictors of dropping out of school in this large school district in southern Arizona and use this information to build an early warning system. Student data were obtained from the district's Research and Accountability office for a cohort of students (n=6751) who began the ninth grade in fall 2006 and graduated or should have graduated in 2010. Data collected included general demographic information, academic data, number of schools attended, and school withdrawal codes.The intent of this research was to determine if there were statistically significant differences between dropouts and graduates in the variables collected and which variables yielded the highest effect sizes and should be included in the district's early warning system.Two analyses were used to determine significance differences between dropouts and graduates. Then four analyses were performed to determine the highest-yield variables for this district. Consistent with recent research in the field, the variables of ninth grade attendance, ninth grade English and Math grades, and GPA were the strongest predictors of student dropouts.Local educators can use this early warning information to help identify potential high school dropouts as early as possible and intervene more efficiently and effectively with these students.

The aim of this study is to propose an alternative approach in prognostics for airborne avionics system in order to enhance maintenance process and aircraft availability. The objectives are to analyse the dependency of avionic systems for fault propagation behaviour degradation, research and develop methods to predict the remaining useful life of avionics Line Replaceable Units (LRU), research and develop methods to evaluate and predict the degradation performances of avionic systems, and lastly to develop software simulation systems to evaluate methods developed. One of the many stakeholders in the aircraft lifecycle includes the Maintenance, Repair and Overhaul (MRO) industry. The predictable logistics process to some degree as an outcome of IVHM gives benefit to the MRO industry. In this thesis, a new integrated numerical methodology called ‘System Level Airborne Avionic Prognostics’ or SLAAP is developed; looking at a top level solution in prognostics. Overall, this research consists of two main elements. One is to thoroughly understand and analyse data that could be utilised. Secondly, is to apply the developed methodology using the enhanced prognostic methodology. Readily available fault tree data is used to analyse the dependencies of each component within the LRUs, and performance were simulated using the linear Markov Model to estimate the time to failure. A hybrid approach prognostics model is then integrated with the prognostics measures that include environmental factors that contribute to the failure of a system, such as temperature. This research attempts to use data that is closest to the data available in the maintenance repair and overhaul industry. Based on a case study on Enhanced Ground Proximity Warning System (EGPWS), the prognostics methodology developed showed a sufficiently close approximation to the Mean Time Before Failure (MTBF) data supplied by the Original Equipment Manufacturer (OEM). This validation gives confidence that the proposed methodology will achieve its objectives and it should be further developed for use in the systems design process.

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.

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.