A Fuzzy Decision Tree for Fault Classification

In plant accident management, the control room operators are required to identify the causes of the accident, based on the different patterns of evolution of the monitored process variables thereby developing. This task is often quite challenging, given the large number of process parameters monitored and the intense emotional states under which it is performed. To aid the operators, various techniques of fault classification have been engineered. An important requirement for their practical application is the physical interpretability of the relationships among the process variables underpinning the fault classification. In this view, the present work propounds a fuzzy approach to fault classification, which relies on fuzzy if-then rules inferred from the clustering of available preclassified signal data, which are then organized in a logical and transparent decision tree structure. The advantages offered by the proposed approach are precisely that a transparent fault classification model is mined out of the signal data and that the underlying physical relationships among the process variables are easily interpretable as linguistic if-then rules that can be explicitly visualized in the decision tree structure. The approach is applied to a case study regarding the classification of simulated faults in the feedwater system of a boiling water reactor.     

Survival Weibull regression model for mismeasured outcomes

In some survival studies, the exact time of the event of interest is unknown, but the event is known to have occurred during a particular period of time (interval-censored data). If the diagnostic tool used to detect the event of interest is not perfectly sensitive and specific, outcomes may be mismeasured; a healthy subject may be diagnosed as sick and a sick one may be diagnosed as healthy. In such cases, traditional survival analysis methods produce biased estimates for the time-to-failure distribution parameters (Paggiaro and Torelli 2004 Paggiaro, A., and N. Torelli. 2004. The effect of classification errors in survival data analysis. Statistical Methods and Applications 13:213–25.[Crossref] , [Google Scholar]). In this context, we developed a parametric model that incorporates sensitivity and specificity into a grouped survival data analysis (a case of interval-censored data in which all subjects are tested at the same predetermined time points). Inferential aspects and properties of the methodology, such as the likelihood function and identifiability, are discussed in this article. Assuming known and non differential misclassification, Monte Carlo simulations showed that the proposed model performed well in the case of mismeasured outcomes; the estimates of the relative bias of the model were lower than those provided by the naive method that assumes perfect sensitivity and specificity. The proposed methodology is illustrated by a study related to mango tree lifetimes.     

Managerial and professional beliefs influencing public health privatization: results of a national survey of local health department directors

This article describes managerial and professional beliefs underlying decisions to privatize public health services. We drew a stratified, nationally representative sample of local health departments and interviewed 347 department directors by telephone. We used logistic regression to establish the independent effects of various beliefs on the decision to privatize. Over half of directors did not believe that there was valid evidence that privatization results in more efficient performance, and those who believed there was such evidence were not more likely to privatize. However, directors held professional and managerial beliefs that influenced their decision to privatize. Directors most likely to privatize were those who believed that local health departments should exclusively focus on the core public health functions, those who asserted that public health should become involved in an increasingly diverse array of social problems, and those who believed that employees should be used on a temporary and contractual, rather than permanent, basis wherever possible.     

Modelling the quality of work in the Italian social co-operatives combining NPCA-RSM and SEM-GME approaches

The objective of this paper is to describe and analyse with appropriate statistical models the links between work quality latent factors. Due to the complexity of the task, the analysis is carried out through a two-step approach:

• In the first step, we construct some multidimensional measures of the subjective quality of work, using nonlinear principal component analysis (NPCA) and Rasch analysis with the Rating Scale Model (NPCA-RSM);

• In the second step, we adopt a Structural Equation Model based on generalized maximum entropy (SEM-GME) to integrate the measures achieved with the previous step and to evaluate the relationships between the subjective work quality latent factors.

Therefore, the novel aspects of this paper are the following: (i) The integration between the NPCA-RSM and SEM-GME, which allows reduction of the variables analysed and evaluation of the measurement errors; (ii) The formalization of a Job Satisfaction Model for the study of the relationships between the subjective work quality latent factors in the Italian social services sector.     

Development and Governance in the Ex-Soviet Union: An Empirical Inquiry

The widespread adoption of the concept of wellbeing in the social sciences literature has allowed researchers to move beyond a narrow economic focus on income and consumption as the primary measure of inequality and poverty. Although statistical measurement and analyses of wellbeing have become increasingly feasible due to the availability of rich datasets, the empirical literature on wellbeing remains deficient in a number of ways. In this paper we argue that it is necessary that empirical studies of wellbeing encompass multiple. Applying Sen’s capability approach as our theoretical model we subsequently develop a modelling framework that applies the polychoric principal component analysis (PCA) method for the calculation of objective wellbeing and wellbeing inequality using household asset, education, health and housing dimensions. Findings from our case study of Vietnam challenge previous single dimensional analyses and reveal a number of layers to our understanding of wellbeing inequality in Vietnam. We argue that our use of polychoric PCA is especially suited to the analysis of wellbeing by explicitly incorporating the analysis of both cardinal and ordinal variables and overcoming deficiencies established in the literature relating to the use of standard PCA.

     

Postural analysis of workers in a typical meat processing company in Brazil

Companies have increasingly sought strategies that will ensure a more competitive position in the marketplace. Among these strategies adopted by companies include the health and welfare of the worker, factors currently valued by consumers, especially those of most demanding market. Thus, the postural analysis is of great importance and interest because it is the study of positioning related to body parts like head, torso and limbs, capable of producing loads that may be excessive or insufficient causing disturbances in the muscle skeletal system worker. The aim of this study was to perform a postural analysis of the main sectors of workers (slaughter, cutting room, special cuts, packaging and dispatch) of a typical refrigerator pig industry in Brazil during the execution of their daily activities as well as developing proposals to minimize and/or eliminate the diseases and accidents. The study followed the safety norms of Brazilian Ministry of Labor and Employment. The posture analysis used the OWAS (Ovako Working Posture Analyzing System) methodology. The postures assumed by workers in the sector of packaging were as the most in need of emergency and quick action.     

Hazard identification and pre-map with a simple specific tool: synthesis of application experience in handicrafts in various productive sectors

In August 2009, an international group was founded with the task of developing a "toolkit for MSD prevention" under the IEA and in collaboration with the World Health Organization.According to the ISO standard 11228 series and the new Draft ISO TR 12259 "Application document guides for the potential user", our group developed a preliminary "mapping" methodology of occupational hazards in the craft industry, supported by software (Excel?, free download on: www.epmresearch.org).The possible users of toolkits are: members of health and safety committees; health and safety representatives; line supervisors; foremen; workers; government representatives; health workers providing basic occupational health services; occupational health and safety specialists.The proposed methodology, using specific key enters and quick assessment criteria, allows a simple ergonomics hazards identification and risk estimation to be made. It is thus possible to decide for which occupational hazards a more exhaustive risk assessment will be necessary and which occupational consultant should be involved (occupational physician, safety engineer, industrial hygienist, etc.).The methodology has been applied in different situations of small and medium craftsmanship Italian enterprises: leather goods, food, technical dental work, production of artistic ceramics and stained glass, beekeeping activities. The results are synthetically reported and discussed in this paper.     

A RETROSPECTIVE STUDY ON THE INFLUENCE OF A STATE PARK-LAKE ON LAND VALUE,FROM THE TIME OF LAND ACQUISITION TO RESERVOIR FILLING

A new multiple purpose park-lake facility is being developed in the sub urbanrural fringe of the Philadelphia, Pennsylvania metropolitan region. This study assesses the impact of the new park-lake upon surrounding land values in order to provide information for improved planning and decision making in such a context. The investigation covers the period from the time of land acquisition to that of near-completion of dam construction. The results of the study provide a “baseline” from which it will later be possible to assess changes in land values as the park-lake becomes fully operational as a major public recreational facility. Two geographic zones of impact on surrounding land value are identified by the analysis, and variations in the impact of the park-lake over time are identified. The importance of these new findings to public organizations involved in recreational decision making is discussed and areas for future research are suggested.     

Measuring Change Over Time in Socio-economic Deprivation and Health in an Urban Context: The Case Study of Genoa

Poverty and disability are interrelated, but data that can disentangle to what extent one causes the other and vice versa is not available. However, data from Vietnam allows us to examine this interrelationship in a way not done previously. Using small area estimation techniques, we uncover three findings not yet found in the literature. First, disability prevalence rates vary significantly within a country even at the district level. Second, the poverty gap between people with and without disabilities also varies at the district level. And most importantly, the size of that gap lessens based on district characteristics that can be affected by policy. Districts with better health care and infrastructure, such as road and health services, show less of a link between disability and poverty, supporting the hypothesis that improvements in infrastructure and rehabilitation service can lessen the impact of disability on families with disabled members.     

Optimal Maintenance Time for Repairable Systems Under Two Types of Failures

Determination of preventive maintenance is an important issue for systems under degradation. A typical maintenance policy calls for complete preventive repair actions at pre-scheduled times and minimal repair actions whenever a failure occurs. Under minimal repair, failures are modeled according to a non homogeneous Poisson process. A perfect preventive maintenance restores the system to the as good as new condition. The motivation for this article was a maintenance data set related to power switch disconnectors. Two different types of failures could be observed for these systems according to their causes. The major difference between these types of failures is their costs. Assuming that the system will be in operation for an infinite time, we find the expected cost per unit of time for each preventive maintenance policy and hence obtain the optimal strategy as a function of the processes intensities. Assuming a parametrical form for the intensity function, large sample estimates for the optimal maintenance check points are obtained and discussed.