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.

BACKGROUND: Late identification of deteriorating children undermines timely implementation of life-saving measures to prevent cardiopulmonary arrest (CPA) or death. The Pediatric Early Warning System (PEWS) has been validated for use in pediatric acute care settings for early identification of children at increased risk of physiologic deterioration, yet there is a dearth of evidence of the use of PEWS in primary care. Implementing the PEWS in primary care could guide rural primary care practitioners to early detection and prompt management of deteriorating children. This DNP project evaluated the attitudes and perceptions of rural practitioners towards the implementation of the PEWS scoring tool. METHODS: A cross-sectional descriptive design was conducted using an anonymous online survey via an email listserv. RESULTS: Seventeen practitioners responded to the survey, but only 14 participants met criteria for inclusion – 2 males and 11 females. The sex of one participant was not reported. Participants areas of specialization include 79% specialized in family practice, 79% pediatric specialists 14% and (7%) listed as "Other." Thirty-one percent of participants reported a travel distance of over 60 miles, while 39% reported a travel distance of over 60 miles lasting over 60 minutes via ground from a place of care to a hospital that specializes in the pediatric emergency care, and pediatric care respectively. Although 92% reported they have not heard of the PEWS tool prior to this survey, 54% strongly agree that the PEWS could help prevent cardiopulmonary arrest or death. Similarly, 54% of respondents reported they strongly agree that the PEWS can help identify deteriorating children, while 39% somewhat agree. Over 62% strongly agree that implementing the PEWS is appropriate in primary care, while 31% somewhat agree. Fifty-four percent of participants strongly agree they could use the PEWS tool in their practice. DISCUSSION: Participants have a positive view of the PEWS tool and perceive implementation of the PEWS to be a vital clinical decision support tool that could lead pediatric primary care providers to early detection of deteriorating children before the occurrence of an adverse event. Further study could determine the generalizability of implementing the PEWS in primary care.

The devastating southeast Asian tsunami of December 26, 2004 has brought home the destructive consequences of coastal hazards in an absence of effective warning systems. Since the 1946 tsunami that destroyed much of Hilo, Hawai'i, a network of pole mounted sirens has been used to provide an early public alert of future tsunamis. However, studies in the 1960s showed that understanding of the meaning of siren soundings was very low and that ambiguity in understanding had contributed to fatalities in the 1960 tsunami that again destroyed much of Hilo. The Hawaiian public has since been exposed to monthly tests of the sirens for more than 25 years and descriptions of the system have been widely published in telephone books for at least 45 years. However, currently there remains some uncertainty in the level of public understanding of the sirens and their implications for behavioral response. Here, we show from recent surveys of Hawai'i residents that awareness of the siren tests and test frequency is high, but these factors do not equate with increased understanding of the meaning of the siren, which remains disturbingly low (13%). Furthermore, the length of time people have lived in Hawai'i is not correlated systematically with understanding of the meaning of the sirens. An additional issue is that warning times for tsunamis gene rated locally in Hawai'i will be of the order of minutes to tens of minutes and limit the immediate utility of the sirens. Natural warning signs of such tsunamis may provide the earliest warning to residents. Analysis of a survey subgroup from Hilo suggests that awareness of natural signs is only moderate, and a majority may expect notification via alerts provided by official sources. We conclude that a major change is needed in tsunami education, even in Hawai'i, to increase public understanding of, and effective response to, both future official alerts and natural warning signs of future tsunamis.

Volcano early warning systems are used globally to communicate volcano-related information to diverse stakeholders ranging from specific user groups to the general public, or both. Within the framework of a volcano early warning system, Volcano Alert Level (VAL) systems are commonly used as a simple communication tool to inform society about the status of activity at a specific volcano. Establishing a VAL system that is effective for multiple volcanoes can be challenging, given that each volcano has specific behavioural characteristics. New Zealand has a wide range of volcano types and geological settings, including rhyolitic calderas capable of very large eruptions (>500 km 3 ) and frequent unrest episodes, explosive andesitic stratovolcanoes, and effusive basaltic eruptions at both caldera and volcanic field settings. There is also a range in eruption frequency, requiring the VAL system to be used for both frequently active ‘open-vent’ volcanoes, and reawakening ‘closed-vent’ volcanoes. Furthermore, New Zealand’s volcanoes are situated in a variety of risk settings ranging from the Auckland Volcanic Field, which lies beneath a city of 1.4 million people; to Mt. Ruapehu, the location of popular ski fields that are occasionally impacted by ballistics and lahars, and produces tephra that falls in distant cities. These wide-ranging characteristics and their impact on society provide opportunities to learn from New Zealand’s experience with VAL systems, and the adoption of a standardised single VAL system for all of New Zealand’s volcanoes following a review in 2014. This chapter outlines the results of qualitative research conducted in 2010–2014 with key stakeholders and scientists, including from the volcano observatory at GNS Science, to ensure that the resulting standardised VAL system is an effective communication tool. A number of difficulties were faced in revising the VAL system so that it remains effective for all of the volcanic settings that exist in New Zealand. If warning products are standardised too much, end-user decision making and action can be limited when unusual situations occur, e.g., there may be loss of specific relevance in the alert message. Specific decision-making should be based on more specific parameters than the VAL alone, however wider VAL system standardisation can increase credibility, a known requirement for effective warning, by ensuring that warning sources are clear, trusted and widely understood. With a credible source, user groups are less likely to look for alternatives or confirmation, leading to faster action. Here we consider volcanic warnings within the wider concept of end-to-end multi-hazard early warning systems including detection, evaluation, notification, decision-making and action elements (based on Carsell et al. 2004).

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.

No description available.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Intrusion Detection Systems (IDS) are designed to monitor the computer network infrastructure against possible attacks by generating security alerts. With the increase of components connected to computer networks, traditional IDS are not capable of effectively detecting malicious attacks. This occurs either by the distributed amount of data that traverses the network or the complexity of the attacks launched against the network. Therefore, the design of Internet Early Warning Systems (IEWS) enables the early detection of threats in the network, possibly avoiding eventual damages to the network resources. The IEWS works as a sink that collects alerts from different sources (for example, from different IDS), centralizing and correlating information in order to provide a holistic view of the network. This way, the current dissertation describes an IEWS architecture for correlating alerts from (geographically) spread out IDS using the Case-Based Reasoning (CBR) technique together with IP Georeferencing. The results obtained during experiments, which were executed over the implementation of the developed technique, showed the viability of the technique in reducing false-positives. This demonstrates the applicability of the proposal as the basis for developing advanced techniques inside the extended IEWS architecture. / Sistemas de Detecção de Instrução (Intrusion Detection Systems IDS) são projetados para monitorar possíveis ataques à infraestruturas da rede através da geração de alertas. Com a crescente quantidade de componentes conectados na rede, os IDS tradicionais não estão sendo suficientes para a efetiva detecção de ataques maliciosos, tanto pelo volume de dados como pela crescente complexidade de novos ataques. Nesse sentido, a construção de uma arquitetura Internet Early Warning Systems (IEWS) possibilita detectar precocemente as ameaças, antes de causar algum perigo para os recursos da rede. O IEWS funciona como um coletor de diferentes geradores de alertas, possivelmente IDS, centralizando e correlacionado informações afim de gerar uma visão holística da rede. Sendo assim, o trabalho tem como objetivo descrever uma arquitetura IEWS para a correlação de alertas gerados por IDS dispersos geograficamente utilizando a técnica Case-Based Reasoning (CBR) em conjunto com Georreferenciamento de endereços IP. Os resultados obtidos nos experimentos, realizados sobre a implementação da técnica desenvolvida, mostraram a viabilidade da técnica na redução de alertas classificados como falsos-positivos. Isso demonstra a aplicabilidade da proposta como base para o desenvolvimento de técnicas mais apuradas de detecção dentro da arquitetura de IEWS estendida.

Published Article / Early indication of possible drought can help in developing suitable drought mitigation strategies and measures in advance. Therefore, drought forecasting plays an important role in the planning and management of water resource in such circumstances. In this study, a non-linear streamflow forecasting model was developed using Artificial Neural Network (ANN) modeling technique at the Melka Sedi stream gauging station, Ethiopia, with adequate lead times. The available data was divided into two independent sets using a split sampling tool of the neural network software. The first data set was used for training and the second data set, which is normally about one fourth of the total available data, was used for testing the model. A one year data was set aside for validating the ANN model. The streamflow predicted using the model on weekly time step compared favorably with the measured streamflow data (R2 = 75%) during the validation period. Application of the model in assessing appropriate agricultural water management strategies for a large-scale irrigation scheme in the Awash River Basin, Ethiopia, has already been considered for publication in a referred journal.

Freqüentemente, a população das áreas metropolitanas é surpreendida pela ocorrência de inundações muito rápidas que causam danos diversos. O sistema de alerta antecipado contra inundações é uma ferramenta que visa minimizar tais impactos. O componente de previsão do sistema será abordado neste trabalho. Tal previsão é feita através de um modelo conceitual de previsão hidrometeorológica de precipitação baseado em equações termodinâmicas e modelo simplificado de física das nuvens seguido de um modelo chuva-vazão. A antecedência proporcionada pelo modelo hidrometeorológico aplicado é de 30 minutos para variáveis de entrada observadas. Este tempo pode ser estendido com a inclusão de estimativas futuras das variáveis de entrada. A calibração do modelo foi feita manualmente com o uso de duas medidas de desempenho, esta etapa pode ser aprimorada em pesquisas futuras. Apesar da simplicidade do modelo hidrometeorológico apresentou-se satisfatório em algumas simulações, conseguindo prever o início das precipitações. / Urban population are often surprised by flash floods which cause several kinds of damages. An early warning system is a tool which aims to minimize such impacts. This work will approach the forecast component of this system. A conceptual hydrometeorological precipitation forecasting model, based on thermodynamics equations and simplified cloud physics, will be used to perform the forecast. Model lead time is 30 minutes for measured inputs, this time can be extended by the use of estimated inputs instead of the measured ones. Calibration was performed manually based on conservation of precipitation volume and its distribution in time. This step can be improved on future researches. In spite of model’s simplicity, some simulations presented satisfactory results, being able to forecast precipitation’s beginning.

The study aims to empirically study the Early warning system and how national parliaments in the EU vary regarding the issuing of reasoned opinions. In recent years the subject of subsidiarity within the EU has become an increasingly debated and controversial topic. The Early warning system aims to alleviate the democratic deficiency of the EU, but the scientific community is divided on how efficient it is. Using data from the European parliament this study examines reasoned opinions and factors that influences why national parliaments issue them and why there is such a variation amongst the national parliaments issuing them. The study finds that being a member of the Eurozone and the EU15 has important implications for parliaments issuing reasoned opinions.