Airborne particulate contamination effect on high voltage breakdowns during tube conditioning

In this research we examine high voltage breakdowns (HVBs) during neutron tube conditioning which has been a problem for decades. In the recent past there has been much debate on whether or not to procure a real-time airborne monitoring system for the commercial production of neutron tubes in order to determine the effect and calculate the impact of airborne particles. The main problem is, such monitoring system is costly, and with the exact causes of HVBs not being fully known, the expense must be justified. The goal of this thesis was to analyze the instrumentation used in airborne particle monitoring in order to assert that the instruments were reliable in obtaining the data needed to make improvements. General reliability studies on the instruments were conducted followed by a quasi-experiment which led to the finding that airborne particulates have a measureable effect on external HVBs. This finding led to an observational study on the production floor which examines internal HVBs. An exploratory analysis of the data obtained was conducted and preliminary results showed that the particles may influence the occurrence of internal HVBs in the tubes. As a result of this research the data justified the need to have a real-time airborne monitoring system in order to conduct further research and funding for the system was granted

Defects control charts for high-quality processes

The traditional C-chart by Shewhart has been widely applied for monitoring count data in industrial and nonindustrial processes. However, using C-chart always experiences an excessive amount of false alarms, since control limits of traditional C-chart are defined by impractical normal assumption. Specially, when we monitor two or more correlated characteristics of defects, C-chart becomes unsuitable. Thus, monitoring a process by traditional C-chart leads to the increase of unnecessary costs of inspection. There are many works that have attempted to improve C-charts. In this thesis, 11 selected improved versions of C-chart are presented. The performances of improved C-charts are evaluated in term of numerical results to demonstrate the sensitivity of the charts and costs of inspections. We also propose an optimal bivariate Poisson field chart to monitor two correlated characteristics of defects. Our chart is based on the optimization of bivariate Poisson confidence interval and projection of bivariate Poisson data in Poisson field. The detailed description of our proposed algorithm is presented by numerical data. The experimental results demonstrate improved performances regarding user-friendly visualization and false alarm rate Furthermore, we propose an optimal diagonal inflated bivariate Poisson field chart to monitor two over/under dispersed correlated count data. The detailed description of our chart will be presented. The experimental results demonstrate improved performances according to loss function and false alarm rate compared to other methods

Health, Nutrition and Academic Achievement: New Evidence from India

Using new and unique panel data, we investigate the role of long-term health and childhood malnutrition in schooling outcomes for children in rural India, many of whom lack basic numeracy and literacy skills. Using data on students’ performance on mathematics and Hindi tests, we examine the role of the endogeneity of health caused by omitted variables bias and measurement error and correct for these problems using a household fixed effects estimator on a sub-sample of siblings observed in the data. We also present several extensions and robustness checks using instrumental variables and alternative estimators. We find evidence of a positive causal effect of long-term health measured as height-for-age z-score (HAZ) on test scores, and the results are consistent across several different specifications. The results imply that improving childhood nutrition will have benefits that extend beyond health into education.Health, Nutrition, Schooling, India

Time Series Modelling

The analysis and modeling of time series is of the utmost importance in various fields of application. This Special Issue is a collection of articles on a wide range of topics, covering stochastic models for time series as well as methods for their analysis, univariate and multivariate time series, real-valued and discrete-valued time series, applications of time series methods to forecasting and statistical process control, and software implementations of methods and models for time series. The proposed approaches and concepts are thoroughly discussed and illustrated with several real-world data examples

Advanced Modelling Strategies: Challenges and pitfalls in robust causal inference with observational data

Advanced Modelling Strategies: Challenges and pitfalls in robust causal inference with observational data summarises the lecture notes prepared for a four-day workshop sponsored by the Society for Social Medicine and hosted by the Leeds Institute for Data Analytics (LIDA) at the University of Leeds on 17th-20th July 2017

International Society for Disease Surveillance Conference 2011: Building the Future of Public Health Surveillance: Building the Future of Public Health Surveillance

Daniel Reidpath - ORCID: 0000-0002-8796-0420 https://orcid.org/0000-0002-8796-04204pubpub1117

Pressure transients in water distribution networks: understanding their contribution to pipe repairs

Drinking water infrastructure functions to provide a service to meet customer demands and health requirements. Pipe repairs are one of the biggest challenges of ageing water infrastructure in the UK and world wide. Pressure transients resulting from sudden interruptions of the movement of the water can be caused by routine value operations. In a single pipeline one extreme event can burst a pipe. However the occurrences and impact of pressure transients in operational water distribution systems were not currently fully understood. This research developed new insights and understanding of pressure transient occurrences and their contribution to observed pipe repair rates. A large scale field monitoring program, including deploying and managing high-speed (100 Hz) instrumentation for 11 months, was designed and implemented to cover 67 district metered areas (DMA) subdivided into 79 pressure zones. In total 144 locations were monitored. The data was analysed using a novel method, termed transient fingerprint. This allowed the identification of discrete pressure transients and their three fundamental components (magnitude, duration and numbers of occurrences) leading to a quantitative interpretation of pressure transients. Evolutionary polynomial regression modelling was used to assess the impact of directly measured pressure transient data in context with static pressure, age, diameter and soil variables on 64 cast iron pipes. The analysis suggested that high magnitude, short duration repeatedly occurring pressure transients can have an adverse effect on the pipes. The extrapolation of pressure transient analysis into 7978 cast iron pipes showed inconclusive results suggesting that more accurate pressure transient data is required for each pipe in the network. Additional analysis carried out on 25 asbestos cement pipes, with actual measurements of pressure transients for each pipe, confirmed an adverse effect of pressure transient on water network observed in cast iron pipes. This research has provided an understanding of the occurrence of pressure transients that has implications on pipe management strategies. Mitigation techniques to locate pressure transient sources based on the project outcomes could be utilised to better manage distribution systems and ultimately reduce future pipe replacements and associated costs