An event-based approach to validating solar wind speed predictions: high-speed enhancements in the Wang-Sheeley-Arge model

One of the primary goals of the Center for Integrated Space Weather Modeling (CISM) effort is to assess and improve prediction of the solar wind conditions in near‐Earth space, arising from both quasi‐steady and transient structures. We compare 8 years of L1 in situ observations to predictions of the solar wind speed made by the Wang‐Sheeley‐Arge (WSA) empirical model. The mean‐square error (MSE) between the observed and model predictions is used to reach a number of useful conclusions: there is no systematic lag in the WSA predictions, the MSE is found to be highest at solar minimum and lowest during the rise to solar maximum, and the optimal lead time for 1 AU solar wind speed predictions is found to be 3 days. However, MSE is shown to frequently be an inadequate “figure of merit” for assessing solar wind speed predictions. A complementary, event‐based analysis technique is developed in which high‐speed enhancements (HSEs) are systematically selected and associated from observed and model time series. WSA model is validated using comparisons of the number of hit, missed, and false HSEs, along with the timing and speed magnitude errors between the forecasted and observed events. Morphological differences between the different HSE populations are investigated to aid interpretation of the results and improvements to the model. Finally, by defining discrete events in the time series, model predictions from above and below the ecliptic plane can be used to estimate an uncertainty in the predicted HSE arrival times.

The effect of guia exame's ratings on the brazilian fund industry: an analysis of net-worth flows

This paper infers the impact the publication Guia Exame (the guide) has on the Brazilian fund industry, more specifically on the ability the concerned funds develop on attracting new investment. The impact is measured using the event-study analysis based on the variation of net worth subsequently to the event of being rated, according to the methodology applied by the guide to rank the funds. We used five years of fund ratings according to Guia Exame (2000-2004) and analyzed the changes of these funds net worth. We also compared the event amongst different categories of funds. The results found confirm the expected effects according to star rankings and asset manager size in all years.

The effect of guia exame’s ratings on the brazilian fund industry: an analysis of net-worth flows

This paper infers the impact the publication “Guia Exame” (the guide) has on the Brazilian fund industry, more specifically on the ability the concerned funds develop on attracting new investment. The impact is measured using the event-study analysis based on the variation of net worth subsequently to the event of being rated, according to the methodology applied by the guide to rank the funds. We used five years of fund ratings according to Guia Exame (2000-2004) and analyzed the changes of these funds’ net worth. We also compared the event amongst different categories of funds. The results found confirm the expected effects according to star rankings and asset manager size in all years.

Genetic variations in the PI3K-AKT-mTOR pathway and bladder cancer susceptibility and clinical outcomes

Bladder cancer is the fourth most common cancer in men in the United States. There is compelling evidence supporting that genetic variations contribute to the risk and outcomes of bladder cancer. The PI3K-AKT-mTOR pathway is a major cellular pathway involved in proliferation, invasion, inflammation, tumorigenesis, and drug response. Somatic aberrations of PI3K-AKT-mTOR pathway are frequent events in several cancers including bladder cancer; however, no studies have investigated the role of germline genetic variations in this pathway in bladder cancer. In this project, we used a large case control study to evaluate the associations of a comprehensive catalogue of SNPs in this pathway with bladder cancer risk and outcomes. Three SNPs in RAPTOR were significantly associated with susceptibility: rs11653499 (OR: 1.79, 95%CI: 1.24–2.60), rs7211818 (OR: 2.13, 95%CI: 1.35–3.36), and rs7212142 (OR: 1.57, 95%CI: 1.19–2.07). Two haplotypes constructed from these 3 SNPs were also associated with bladder cancer risk. In combined analysis, a significant trend was observed for increased risk with an increase in the number of unfavorable genotypes (P for trend<0.001). Classification and regression tree analysis identified potential gene-environment interactions between RPS6KA5 rs11653499 and smoking. In superficial bladder cancer, we found that PTEN rs1234219 and rs11202600, TSC1 rs7040593, RAPTOR rs901065, and PIK3R1 rs251404 were significantly associated with recurrence in patients receiving BCG. In muscle invasive and metastatic bladder cancer, AKT2 rs3730050, PIK3R1 rs10515074, and RAPTOR rs9906827 were associated with survival. Survival tree analysis revealed potential gene-gene interactions: patients carrying the unfavorable genotypes of PTEN rs1234219 and TSC1 rs704059 exhibited a 5.24-fold (95% CI: 2.44–11.24) increased risk of recurrence. In combined analysis, with the increasing number of unfavorable genotypes, there was a significant trend of higher risk of recurrence and death (P for trend<0.001) in Cox proportional hazard regression analysis, and shorter event (recurrence and death) free survival in Kaplan-Meier estimates (P log rank<0.001). This study strongly suggests that genetic variations in PI3K-AKT-mTOR pathway play an important role in bladder cancer development. The identified SNPs, if validated in further studies, may become valuable biomarkers in assessing an individual's cancer risk, predicting prognosis and treatment response, and facilitating physicians to make individualized treatment decisions. ^

Genetic analysis of Pitx2 in left -right asymmetry and cardiovascular development

Pitx2, a paired-related homeobox gene that is mutated in human Rieger Syndrome, plays a key role in transferring the early asymmetric signals to individual organs. Pitx2 encodes three isoforms, Pitx2a, Pitx2b and Pitx2c. I found that Pitx2c was the Pitx2 isoform for regulating left-right asymmetry in heart, lung and the predominant isoform in guts. Previous studies suggested that the generation of left-right asymmetry within individual organs is an all or none, random event. Phenotypic analysis of various Pitx2 allelic combinations, that encode graded levels of Pitx2c, reveals an organ-intrinsic mechanism for regulating left-right asymmetric morphogenesis based on differential response to Pitx2c levels. The heart needs low Pitx2c levels, while the lungs and duodenum require higher doses of Pitx2c. In addition, the duodenal rotation is under strict control of Pitx2c activity. Left-right asymmetry development for aortic arch arteries involves complex vascular remodeling. Left-sided expression of Pitx2c in these developing vessels implied its potential function in this process. In order to determine if Pitx2c also can regulate the left-right asymmetry of the aortic arch arteries, a Pitx2c-specific loss of function mutation is generated. Although in wild type mice, the direction of the aortic arch is always oriented toward the left side, the directions of the aortic arches in the mutants were randomized, showing that Pitx2c also determined the left-right asymmetry of these vessels. I have further showed that the cardiac neural crest wasn't involved in this vascular remodeling process. In addition, all mutant embryos had Double Outlet Right Ventricle (DORV), a common congenital heart disease. This study provided insight into the mechanism of Pitx2c-mediated late stages of left-right asymmetry development and identified the roles of Pitx2c in regulation of aortic arch remodeling and heart development. ^

Geospatial analysis of groundwater depth for manual well drilling suitability in the Zinder Region, Niger

Manual and low-tech well drilling techniques have potential to assist in reaching the United Nations' millennium development goal for water in sub-Saharan Africa. This study used publicly available geospatial data in a regression tree analysis to predict groundwater depth in the Zinder region of Niger to identify suitable areas for manual well drilling. Regression trees were developed and tested on a database for 3681 wells in the Zinder region. A tree with 17 terminal leaves provided a range of ground water depth estimates that were appropriate for manual drilling, though much of the tree's complexity was associated with depths that were beyond manual methods. A natural log transformation of groundwater depth was tested to see if rescaling dataset variance would result in finer distinctions for regions of shallow groundwater. The RMSE for a log-transformed tree with only 10 terminal leaves was almost half that of the untransformed 17 leaf tree for groundwater depths less than 10 m. This analysis indicated important groundwater relationships for commonly available maps of geology, soils, elevation, and enhanced vegetation index from the MODIS satellite imaging system.

A simplified Probabilistic Safety Assesment of a Steam-Methane Reforming Hydrogen Production Plant coupled to a High-Temperature Gas Cooled Nuclear Reactor

A Probabilistic Safety Assessment (PSA) is being developed for a steam-methane reforming hydrogen production plant linked to a High-Temperature Gas Cooled Nuclear Reactor (HTGR). This work is based on the Japan Atomic Energy Research Institute’s (JAERI) High Temperature Test Reactor (HTTR) prototype in Japan. This study has two major objectives: calculate the risk to onsite and offsite individuals, and calculate the frequency of different types of damage to the complex. A simplified HAZOP study was performed to identify initiating events, based on existing studies. The initiating events presented here are methane pipe break, helium pipe break, and PPWC heat exchanger pipe break. Generic data was used for the fault tree analysis and the initiating event frequency. Saphire was used for the PSA analysis. The results show that the average frequency of an accident at this complex is 2.5E-06, which is divided into the various end states. The dominant sequences result in graphite oxidation which does not pose a health risk to the population. The dominant sequences that could affect the population are those that result in a methane explosion and occur 6.6E-8/year, while the other sequences are much less frequent. The health risk presents itself if there are people in the vicinity who could be affected by the explosion. This analysis also demonstrates that an accident in one of the plants has little effect on the other. This is true given the design base distance between the plants, the fact that the reactor is underground, as well as other safety characteristics of the HTGR. Sensitivity studies are being performed in order to determine where additional and improved data is needed.

Two efficient representations for set-sharing analysis in logic programs

Set-Sharing analysis, the classic Jacobs and Langen's domain, has been widely used to infer several interesting properties of programs at compile-time such as occurs-check reduction, automatic parallelization, flnite-tree analysis, etc. However, performing abstract uniflcation over this domain implies the use of a closure operation which makes the number of sharing groups grow exponentially. Much attention has been given in the literature to mitígate this key inefficiency in this otherwise very useful domain. In this paper we present two novel alternative representations for the traditional set-sharing domain, tSH and tNSH. which compress efficiently the number of elements into fewer elements enabling more efficient abstract operations, including abstract uniflcation, without any loss of accuracy. Our experimental evaluation supports that both representations can reduce dramatically the number of sharing groups showing they can be more practical solutions towards scalable set-sharing.

Análisis Integrado de Seguridad de un accidente de SGTR en un reactor nuclear tipo PWR

El accidente de rotura de tubos de un generador de vapor (Steam Generator Tube Rupture, SGTR) en los reactores de agua a presión es uno de los transitorios más exigentes desde el punto de vista de operación. Los transitorios de SGTR son especiales, ya que podría dar lugar a emisiones radiológicas al exterior sin necesidad de daño en el núcleo previo o sin que falle la contención, ya que los SG pueden constituir una vía directa desde el reactor al medio ambiente en este transitorio. En los análisis de seguridad, el SGTR se analiza desde un punto determinista y probabilista, con distintos enfoques con respecto a las acciones del operador y las consecuencias analizadas. Cuando comenzaron los Análisis Deterministas de Seguridad (DSA), la forma de analizar el SGTR fue sin dar crédito a la acción del operador durante los primeros 30 min del transitorio, lo que suponía que el grupo de operación era capaz de detener la fuga por el tubo roto dentro de ese tiempo. Sin embargo, los diferentes casos reales de accidentes de SGTR sucedidos en los EE.UU. y alrededor del mundo demostraron que los operadores pueden emplear más de 30 minutos para detener la fuga en la vida real. Algunas metodologías fueron desarrolladas en los EEUU y en Europa para abordar esa cuestión. En el Análisis Probabilista de Seguridad (PSA), las acciones del operador se tienen en cuenta para diseñar los cabeceros en el árbol de sucesos. Los tiempos disponibles se utilizan para establecer los criterios de éxito para dichos cabeceros. Sin embargo, en una secuencia dinámica como el SGTR, las acciones de un operador son muy dependientes del tiempo disponible por las acciones humanas anteriores. Además, algunas de las secuencias de SGTR puede conducir a la liberación de actividad radiológica al exterior sin daño previo en el núcleo y que no se tienen en cuenta en el APS, ya que desde el punto de vista de la integridad de núcleo son de éxito. Para ello, para analizar todos estos factores, la forma adecuada de analizar este tipo de secuencias pueden ser a través de una metodología que contemple Árboles de Sucesos Dinámicos (Dynamic Event Trees, DET). En esta Tesis Doctoral se compara el impacto en la evolución temporal y la dosis al exterior de la hipótesis más relevantes encontradas en los Análisis Deterministas a nivel mundial. La comparación se realiza con un modelo PWR Westinghouse de tres lazos (CN Almaraz) con el código termohidráulico TRACE, con hipótesis de estimación óptima, pero con hipótesis deterministas como criterio de fallo único o pérdida de energía eléctrica exterior. Las dosis al exterior se calculan con RADTRAD, ya que es uno de los códigos utilizados normalmente para los cálculos de dosis del SGTR. El comportamiento del reactor y las dosis al exterior son muy diversas, según las diferentes hipótesis en cada metodología. Por otra parte, los resultados están bastante lejos de los límites de regulación, pese a los conservadurismos introducidos. En el siguiente paso de la Tesis Doctoral, se ha realizado un análisis de seguridad integrado del SGTR según la metodología ISA, desarrollada por el Consejo de Seguridad Nuclear español (CSN). Para ello, se ha realizado un análisis termo-hidráulico con un modelo de PWR Westinghouse de 3 lazos con el código MAAP. La metodología ISA permite la obtención del árbol de eventos dinámico del SGTR, teniendo en cuenta las incertidumbres en los tiempos de actuación del operador. Las simulaciones se realizaron con SCAIS (sistema de simulación de códigos para la evaluación de la seguridad integrada), que incluye un acoplamiento dinámico con MAAP. Las dosis al exterior se calcularon también con RADTRAD. En los resultados, se han tenido en cuenta, por primera vez en la literatura, las consecuencias de las secuencias en términos no sólo de daños en el núcleo sino de dosis al exterior. Esta tesis doctoral demuestra la necesidad de analizar todas las consecuencias que contribuyen al riesgo en un accidente como el SGTR. Para ello se ha hecho uso de una metodología integrada como ISA-CSN. Con este enfoque, la visión del DSA del SGTR (consecuencias radiológicas) se une con la visión del PSA del SGTR (consecuencias de daño al núcleo) para evaluar el riesgo total del accidente. Abstract Steam Generator Tube Rupture accidents in Pressurized Water Reactors are known to be one of the most demanding transients for the operating crew. SGTR are special transient as they could lead to radiological releases without core damage or containment failure, as they can constitute a direct path to the environment. The SGTR is analyzed from a Deterministic and Probabilistic point of view in the Safety Analysis, although the assumptions of the different approaches regarding the operator actions are quite different. In the beginning of Deterministic Safety Analysis, the way of analyzing the SGTR was not crediting the operator action for the first 30 min of the transient, assuming that the operating crew was able to stop the primary to secondary leakage within that time. However, the different real SGTR accident cases happened in the USA and over the world demonstrated that operators can took more than 30 min to stop the leakage in actual sequences. Some methodologies were raised in the USA and in Europe to cover that issue. In the Probabilistic Safety Analysis, the operator actions are taken into account to set the headers in the event tree. The available times are used to establish the success criteria for the headers. However, in such a dynamic sequence as SGTR, the operator actions are very dependent on the time available left by the other human actions. Moreover, some of the SGTR sequences can lead to offsite doses without previous core damage and they are not taken into account in PSA as from the point of view of core integrity are successful. Therefore, to analyze all this factors, the appropriate way of analyzing that kind of sequences could be through a Dynamic Event Tree methodology. This Thesis compares the impact on transient evolution and the offsite dose of the most relevant hypothesis of the different SGTR analysis included in the Deterministic Safety Analysis. The comparison is done with a PWR Westinghouse three loop model in TRACE code (Almaraz NPP), with best estimate assumptions but including deterministic hypothesis such as single failure criteria or loss of offsite power. The offsite doses are calculated with RADTRAD code, as it is one of the codes normally used for SGTR offsite dose calculations. The behaviour of the reactor and the offsite doses are quite diverse depending on the different assumptions made in each methodology. On the other hand, although the high conservatism, such as the single failure criteria, the results are quite far from the regulatory limits. In the next stage of the Thesis, the Integrated Safety Assessment (ISA) methodology, developed by the Spanish Nuclear Safety Council (CSN), has been applied to a thermohydraulical analysis of a Westinghouse 3-loop PWR plant with the MAAP code. The ISA methodology allows obtaining the SGTR Dynamic Event Tree taking into account the uncertainties on the operator actuation times. Simulations are performed with SCAIS (Simulation Code system for Integrated Safety Assessment), which includes a dynamic coupling with MAAP thermal hydraulic code. The offsite doses are calculated also with RADTRAD. The results shows the consequences of the sequences in terms not only of core damage but of offsite doses. This Thesis shows the need of analyzing all the consequences in an accident such as SGTR. For that, an it has been used an integral methodology like ISA-CSN. With this approach, the DSA vision of the SGTR (radiological consequences) is joined with the PSA vision of the SGTR (core damage consequences) to measure the total risk of the accident.

Aplicación de la metodología ISA al análisis de la secuencia de pérdida del sistema de agua de refrigeración de componentes en una central nuclear con reactor de agua a presión

La metodología Integrated Safety Analysis (ISA), desarrollada en el área de Modelación y Simulación (MOSI) del Consejo de Seguridad Nuclear (CSN), es un método de Análisis Integrado de Seguridad que está siendo evaluado y analizado mediante diversas aplicaciones impulsadas por el CSN; el análisis integrado de seguridad, combina las técnicas evolucionadas de los análisis de seguridad al uso: deterministas y probabilistas. Se considera adecuado para sustentar la Regulación Informada por el Riesgo (RIR), actual enfoque dado a la seguridad nuclear y que está siendo desarrollado y aplicado en todo el mundo. En este contexto se enmarcan, los proyectos Safety Margin Action Plan (SMAP) y Safety Margin Assessment Application (SM2A), impulsados por el Comité para la Seguridad de las Instalaciones Nucleares (CSNI) de la Agencia de la Energía Nuclear (NEA) de la Organización para la Cooperación y el Desarrollo Económicos (OCDE) en el desarrollo del enfoque adecuado para el uso de las metodologías integradas en la evaluación del cambio en los márgenes de seguridad debidos a cambios en las condiciones de las centrales nucleares. El comité constituye un foro para el intercambio de información técnica y de colaboración entre las organizaciones miembro, que aportan sus propias ideas en investigación, desarrollo e ingeniería. La propuesta del CSN es la aplicación de la metodología ISA, especialmente adecuada para el análisis según el enfoque desarrollado en el proyecto SMAP que pretende obtener los valores best-estimate con incertidumbre de las variables de seguridad que son comparadas con los límites de seguridad, para obtener la frecuencia con la que éstos límites son superados. La ventaja que ofrece la ISA es que permite el análisis selectivo y discreto de los rangos de los parámetros inciertos que tienen mayor influencia en la superación de los límites de seguridad, o frecuencia de excedencia del límite, permitiendo así evaluar los cambios producidos por variaciones en el diseño u operación de la central que serían imperceptibles o complicados de cuantificar con otro tipo de metodologías. La ISA se engloba dentro de las metodologías de APS dinámico discreto que utilizan la generación de árboles de sucesos dinámicos (DET) y se basa en la Theory of Stimulated Dynamics (TSD), teoría de fiabilidad dinámica simplificada que permite la cuantificación del riesgo de cada una de las secuencias. Con la ISA se modelan y simulan todas las interacciones relevantes en una central: diseño, condiciones de operación, mantenimiento, actuaciones de los operadores, eventos estocásticos, etc. Por ello requiere la integración de códigos de: simulación termohidráulica y procedimientos de operación; delineación de árboles de sucesos; cuantificación de árboles de fallos y sucesos; tratamiento de incertidumbres e integración del riesgo. La tesis contiene la aplicación de la metodología ISA al análisis integrado del suceso iniciador de la pérdida del sistema de refrigeración de componentes (CCWS) que genera secuencias de pérdida de refrigerante del reactor a través de los sellos de las bombas principales del circuito de refrigerante del reactor (SLOCA). Se utiliza para probar el cambio en los márgenes, con respecto al límite de la máxima temperatura de pico de vaina (1477 K), que sería posible en virtud de un potencial aumento de potencia del 10 % en el reactor de agua a presión de la C.N. Zion. El trabajo realizado para la consecución de la tesis, fruto de la colaboración de la Escuela Técnica Superior de Ingenieros de Minas y Energía y la empresa de soluciones tecnológicas Ekergy Software S.L. (NFQ Solutions) con el área MOSI del CSN, ha sido la base para la contribución del CSN en el ejercicio SM2A. Este ejercicio ha sido utilizado como evaluación del desarrollo de algunas de las ideas, sugerencias, y los algoritmos detrás de la metodología ISA. Como resultado se ha obtenido un ligero aumento de la frecuencia de excedencia del daño (DEF) provocado por el aumento de potencia. Este resultado demuestra la viabilidad de la metodología ISA para obtener medidas de las variaciones en los márgenes de seguridad que han sido provocadas por modificaciones en la planta. También se ha mostrado que es especialmente adecuada en escenarios donde los eventos estocásticos o las actuaciones de recuperación o mitigación de los operadores pueden tener un papel relevante en el riesgo. Los resultados obtenidos no tienen validez más allá de la de mostrar la viabilidad de la metodología ISA. La central nuclear en la que se aplica el estudio está clausurada y la información relativa a sus análisis de seguridad es deficiente, por lo que han sido necesarias asunciones sin comprobación o aproximaciones basadas en estudios genéricos o de otras plantas. Se han establecido tres fases en el proceso de análisis: primero, obtención del árbol de sucesos dinámico de referencia; segundo, análisis de incertidumbres y obtención de los dominios de daño; y tercero, cuantificación del riesgo. Se han mostrado diversas aplicaciones de la metodología y ventajas que presenta frente al APS clásico. También se ha contribuido al desarrollo del prototipo de herramienta para la aplicación de la metodología ISA (SCAIS). ABSTRACT The Integrated Safety Analysis methodology (ISA), developed by the Consejo de Seguridad Nuclear (CSN), is being assessed in various applications encouraged by CSN. An Integrated Safety Analysis merges the evolved techniques of the usually applied safety analysis methodologies; deterministic and probabilistic. It is considered as a suitable tool for assessing risk in a Risk Informed Regulation framework, the approach under development that is being adopted on Nuclear Safety around the world. In this policy framework, the projects Safety Margin Action Plan (SMAP) and Safety Margin Assessment Application (SM2A), set up by the Committee on the Safety of Nuclear Installations (CSNI) of the Nuclear Energy Agency within the Organization for Economic Co-operation and Development (OECD), were aimed to obtain a methodology and its application for the integration of risk and safety margins in the assessment of the changes to the overall safety as a result of changes in the nuclear plant condition. The committee provides a forum for the exchange of technical information and cooperation among member organizations which contribute their respective approaches in research, development and engineering. The ISA methodology, proposed by CSN, specially fits with the SMAP approach that aims at obtaining Best Estimate Plus Uncertainty values of the safety variables to be compared with the safety limits. This makes it possible to obtain the exceedance frequencies of the safety limit. The ISA has the advantage over other methods of allowing the specific and discrete evaluation of the most influential uncertain parameters in the limit exceedance frequency. In this way the changes due to design or operation variation, imperceptibles or complicated to by quantified by other methods, are correctly evaluated. The ISA methodology is one of the discrete methodologies of the Dynamic PSA framework that uses the generation of dynamic event trees (DET). It is based on the Theory of Stimulated Dynamics (TSD), a simplified version of the theory of Probabilistic Dynamics that allows the risk quantification. The ISA models and simulates all the important interactions in a Nuclear Power Plant; design, operating conditions, maintenance, human actuations, stochastic events, etc. In order to that, it requires the integration of codes to obtain: Thermohydraulic and human actuations; Even trees delineation; Fault Trees and Event Trees quantification; Uncertainty analysis and risk assessment. This written dissertation narrates the application of the ISA methodology to the initiating event of the Loss of the Component Cooling System (CCWS) generating sequences of loss of reactor coolant through the seals of the reactor coolant pump (SLOCA). It is used to test the change in margins with respect to the maximum clad temperature limit (1477 K) that would be possible under a potential 10 % power up-rate effected in the pressurized water reactor of Zion NPP. The work done to achieve the thesis, fruit of the collaborative agreement of the School of Mining and Energy Engineering and the company of technological solutions Ekergy Software S.L. (NFQ Solutions) with de specialized modeling and simulation branch of the CSN, has been the basis for the contribution of the CSN in the exercise SM2A. This exercise has been used as an assessment of the development of some of the ideas, suggestions, and algorithms behind the ISA methodology. It has been obtained a slight increase in the Damage Exceedance Frequency (DEF) caused by the power up-rate. This result shows that ISA methodology allows quantifying the safety margin change when design modifications are performed in a NPP and is specially suitable for scenarios where stochastic events or human responses have an important role to prevent or mitigate the accidental consequences and the total risk. The results do not have any validity out of showing the viability of the methodology ISA. Zion NPP was retired and information of its safety analysis is scarce, so assumptions without verification or approximations based on generic studies have been required. Three phases are established in the analysis process: first, obtaining the reference dynamic event tree; second, uncertainty analysis and obtaining the damage domains; third, risk quantification. There have been shown various applications of the methodology and advantages over the classical PSA. It has also contributed to the development of the prototype tool for the implementation of the ISA methodology (SCAIS).

Project risk management:a combined analytic hierarchy process and decision tree approach

Time, cost and quality achievements on large-scale construction projects are uncertain because of technological constraints, involvement of many stakeholders, long durations, large capital requirements and improper scope definitions. Projects that are exposed to such an uncertain environment can effectively be managed with the application of risk management throughout the project life cycle. Risk is by nature subjective. However, managing risk subjectively poses the danger of non-achievement of project goals. Moreover, risk analysis of the overall project also poses the danger of developing inappropriate responses. This article demonstrates a quantitative approach to construction risk management through an analytic hierarchy process (AHP) and decision tree analysis. The entire project is classified to form a few work packages. With the involvement of project stakeholders, risky work packages are identified. As all the risk factors are identified, their effects are quantified by determining probability (using AHP) and severity (guess estimate). Various alternative responses are generated, listing the cost implications of mitigating the quantified risks. The expected monetary values are derived for each alternative in a decision tree framework and subsequent probability analysis helps to make the right decision in managing risks. In this article, the entire methodology is explained by using a case application of a cross-country petroleum pipeline project in India. The case study demonstrates the project management effectiveness of using AHP and DTA.

Expert systems for fault analysis

The initial aim of this research was to investigate the application of expert Systems, or Knowledge Base Systems technology to the automated synthesis of Hazard and Operability Studies. Due to the generic nature of Fault Analysis problems and the way in which Knowledge Base Systems work, this goal has evolved into a consideration of automated support for Fault Analysis in general, covering HAZOP, Fault Tree Analysis, FMEA and Fault Diagnosis in the Process Industries. This thesis described a proposed architecture for such an Expert System. The purpose of the System is to produce a descriptive model of faults and fault propagation from a description of the physical structure of the plant. From these descriptive models, the desired Fault Analysis may be produced. The way in which this is done reflects the complexity of the problem which, in principle, encompasses the whole of the discipline of Process Engineering. An attempt is made to incorporate the perceived method that an expert uses to solve the problem; keywords, heuristics and guidelines from techniques such as HAZOP and Fault Tree Synthesis are used. In a truly Expert System, the performance of the system is strongly dependent on the high quality of the knowledge that is incorporated. This expert knowledge takes the form of heuristics or rules of thumb which are used in problem solving. This research has shown that, for the application of fault analysis heuristics, it is necessary to have a representation of the details of fault propagation within a process. This helps to ensure the robustness of the system - a gradual rather than abrupt degradation at the boundaries of the domain knowledge.

Application of Naïve Bayesian sequential analysis to primary care optometry

The objective of this study was to investigate the effects of circularity, comorbidity, prevalence and presentation variation on the accuracy of differential diagnoses made in optometric primary care using a modified form of naïve Bayesian sequential analysis. No such investigation has ever been reported before. Data were collected for 1422 cases seen over one year. Positive test outcomes were recorded for case history (ethnicity, age, symptoms and ocular and medical history) and clinical signs in relation to each diagnosis. For this reason only positive likelihood ratios were used for this modified form of Bayesian analysis that was carried out with Laplacian correction and Chi-square filtration. Accuracy was expressed as the percentage of cases for which the diagnoses made by the clinician appeared at the top of a list generated by Bayesian analysis. Preliminary analyses were carried out on 10 diagnoses and 15 test outcomes. Accuracy of 100% was achieved in the absence of presentation variation but dropped by 6% when variation existed. Circularity artificially elevated accuracy by 0.5%. Surprisingly, removal of Chi-square filtering increased accuracy by 0.4%. Decision tree analysis showed that accuracy was influenced primarily by prevalence followed by presentation variation and comorbidity. Analysis of 35 diagnoses and 105 test outcomes followed. This explored the use of positive likelihood ratios, derived from the case history, to recommend signs to look for. Accuracy of 72% was achieved when all clinical signs were entered. The drop in accuracy, compared to the preliminary analysis, was attributed to the fact that some diagnoses lacked strong diagnostic signs; the accuracy increased by 1% when only recommended signs were entered. Chi-square filtering improved recommended test selection. Decision tree analysis showed that accuracy again influenced primarily by prevalence, followed by comorbidity and presentation variation. Future work will explore the use of likelihood ratios based on positive and negative test findings prior to considering naïve Bayesian analysis as a form of artificial intelligence in optometric practice.

Application of data mining techniques in the prediction of coronary artery disease : use of anaesthesia time-series and patient risk factor data

The high morbidity and mortality associated with atherosclerotic coronary vascular disease (CVD) and its complications are being lessened by the increased knowledge of risk factors, effective preventative measures and proven therapeutic interventions. However, significant CVD morbidity remains and sudden cardiac death continues to be a presenting feature for some subsequently diagnosed with CVD. Coronary vascular disease is also the leading cause of anaesthesia related complications. Stress electrocardiography/exercise testing is predictive of 10 year risk of CVD events and the cardiovascular variables used to score this test are monitored peri-operatively. Similar physiological time-series datasets are being subjected to data mining methods for the prediction of medical diagnoses and outcomes. This study aims to find predictors of CVD using anaesthesia time-series data and patient risk factor data. Several pre-processing and predictive data mining methods are applied to this data. Physiological time-series data related to anaesthetic procedures are subjected to pre-processing methods for removal of outliers, calculation of moving averages as well as data summarisation and data abstraction methods. Feature selection methods of both wrapper and filter types are applied to derived physiological time-series variable sets alone and to the same variables combined with risk factor variables. The ability of these methods to identify subsets of highly correlated but non-redundant variables is assessed. The major dataset is derived from the entire anaesthesia population and subsets of this population are considered to be at increased anaesthesia risk based on their need for more intensive monitoring (invasive haemodynamic monitoring and additional ECG leads). Because of the unbalanced class distribution in the data, majority class under-sampling and Kappa statistic together with misclassification rate and area under the ROC curve (AUC) are used for evaluation of models generated using different prediction algorithms. The performance based on models derived from feature reduced datasets reveal the filter method, Cfs subset evaluation, to be most consistently effective although Consistency derived subsets tended to slightly increased accuracy but markedly increased complexity. The use of misclassification rate (MR) for model performance evaluation is influenced by class distribution. This could be eliminated by consideration of the AUC or Kappa statistic as well by evaluation of subsets with under-sampled majority class. The noise and outlier removal pre-processing methods produced models with MR ranging from 10.69 to 12.62 with the lowest value being for data from which both outliers and noise were removed (MR 10.69). For the raw time-series dataset, MR is 12.34. Feature selection results in reduction in MR to 9.8 to 10.16 with time segmented summary data (dataset F) MR being 9.8 and raw time-series summary data (dataset A) being 9.92. However, for all time-series only based datasets, the complexity is high. For most pre-processing methods, Cfs could identify a subset of correlated and non-redundant variables from the time-series alone datasets but models derived from these subsets are of one leaf only. MR values are consistent with class distribution in the subset folds evaluated in the n-cross validation method. For models based on Cfs selected time-series derived and risk factor (RF) variables, the MR ranges from 8.83 to 10.36 with dataset RF_A (raw time-series data and RF) being 8.85 and dataset RF_F (time segmented time-series variables and RF) being 9.09. The models based on counts of outliers and counts of data points outside normal range (Dataset RF_E) and derived variables based on time series transformed using Symbolic Aggregate Approximation (SAX) with associated time-series pattern cluster membership (Dataset RF_ G) perform the least well with MR of 10.25 and 10.36 respectively. For coronary vascular disease prediction, nearest neighbour (NNge) and the support vector machine based method, SMO, have the highest MR of 10.1 and 10.28 while logistic regression (LR) and the decision tree (DT) method, J48, have MR of 8.85 and 9.0 respectively. DT rules are most comprehensible and clinically relevant. The predictive accuracy increase achieved by addition of risk factor variables to time-series variable based models is significant. The addition of time-series derived variables to models based on risk factor variables alone is associated with a trend to improved performance. Data mining of feature reduced, anaesthesia time-series variables together with risk factor variables can produce compact and moderately accurate models able to predict coronary vascular disease. Decision tree analysis of time-series data combined with risk factor variables yields rules which are more accurate than models based on time-series data alone. The limited additional value provided by electrocardiographic variables when compared to use of risk factors alone is similar to recent suggestions that exercise electrocardiography (exECG) under standardised conditions has limited additional diagnostic value over risk factor analysis and symptom pattern. The effect of the pre-processing used in this study had limited effect when time-series variables and risk factor variables are used as model input. In the absence of risk factor input, the use of time-series variables after outlier removal and time series variables based on physiological variable values’ being outside the accepted normal range is associated with some improvement in model performance.

Performance characterisation of a constructed wetland

Performance of a constructed wetland is commonly reported as variable due to the site specific nature of influential factors. This paper discusses outcomes from an in-depth study which characterised treatment performance of a wetland based on the variation in runoff regime. The study included a comprehensive field monitoring of a well established constructed wetland in Gold Coast, Australia. Samples collected at the inlet and outlet was tested for Total Suspended Solids (TSS), Total Nitrogen (TN) and Total Phosphorus (TP). Pollutant concentrations in the outflow were found to be consistent irrespective of the variation in inflow water quality. The analysis revealed two different treatment characteristics for events with different rainfall depths. TSS and TN load reduction is strongly influenced by hydraulic retention time where performance is higher for rainfall events below the design event. For small events, treatment performance is higher at the beginning of the event and gradually decreased during the course of the event. For large events, the treatment performance is comparatively poor at the beginning and improved during the course of the event. The analysis also confirmed the variable treatment trends for different pollutant types.