Methodological issues in developing a multi-dimensional coding procedure for small group chat communication

In CSCL research, collaboration through chat has primarily been studied in dyadic settings. This article discusses three issues that emerged during the development of a multi-dimensional coding procedure for small group chat communication: a) the unit of analysis and unit fragmentation, b) the reconstruction of the response structure and c) determining reliability without overestimation. Threading, i.e. connections between analysis units, proved essential to handle unit fragmentation, to reconstruct the response structure and for reliability of coding. In addition, a risk for reliability overestimation was illustrated. Implications for analysis methodology in CSCL are discussed

Accounting for multivariate probabilities of failure in vertical seawall reliability assessments

The aim of this paper is to appraise the current knowledge on seawall performance and reliability, and to make the case for improved reliability assessments of vertical seawalls, which are used here as a representative for coastal flood defences. In order to achieve this aim, a brief introduction to flood risk management is first given. Then, vertical seawalls are introduced, and their most prominent failure modes are discussed. Reliability analysis is introduced within the context of flood risk management. More specifically, the fragility curve approach that is currently in use in industry is described, and its limitations are discussed. Finally, it is argued that recent advances in multivariate extreme value models would enable improvements to the approaches currently applied in practice. It is stressed that future risk assessment models of coastal flood defences ought to include multiple failure modes and their interactions, a thorough analysis of the model uncertainties, and potential computational costs, in view of providing practitioners with an improved and functional risk assessment tool. Carter, Magar, Simm, Gouldby & Walli

Reliability and risk assessment of structures

Development of reliability and risk assessment of structural components and structures is a major activity at Lewis Research Center. It consists of five program elements: (1) probabilistic loads; (2) probabilistic finite element analysis; (3) probabilistic material behavior; (4) assessment of reliability and risk; and (5) probabilistic structural performance evaluation. Recent progress includes: (1) the evaluation of the various uncertainties in terms of cumulative distribution functions for various structural response variables based on known or assumed uncertainties in primitive structural variables; (2) evaluation of the failure probability; (3) reliability and risk-cost assessment; and (4) an outline of an emerging approach for eventual certification of man-rated structures by computational methods. Collectively, the results demonstrate that the structural durability/reliability of man-rated structural components and structures can be effectively evaluated by using formal probabilistic methods

Development and evaluation of ergonomics and psycosocial assessment method for assessing work-related upper limb disorders

The observational methods have been considered as the most widely used for assessing work-related upper limb disorders (WULDs) because it is inexpensive, practical to use, and flexible to use in a wide range of workplaces. However, the existing methods have a specific purposes and do not universally ideal for all risk factors. Most of the existing methods only focus on assessing physical risk factors of WULDs especially in body postures and do not considered other factors of WULDs such as psychosocial, work organizational, and individual risk factors. Nowadays, psychosocial work characteristics are recognized as important risk factors. Besides that, during the tool development process, it was found that some of the existing observational methods have limited work perform the reliability, usability, and validity analysis. In order to improve these limitations, this study aims to develop a new observational method known as Upper Limb Risk Assessment (UPLIRA) tool and to determine the reliability and validity of the UPLIRA tool. The initial development of UPLIRA tool was conducted in three stages including the development of the UPLIRA system components, development of the UPLIRA checklist (prototype), and psychometric properties evaluation (reliability and validity). In reliability trials, the results of inter and intra rater reliability shows good (K = 0.802 - 0.806) to very good (K = 0.811 - 0.833) agreement among the observers. Meanwhile, the usability trials shows that the UPLIRA tool was applicable to wide range of jobs/tasks, valuable at works, and action level is easy to understand (mean 4.17 ± 0.753). Whereas, in validity trials the highest risk scores were obtained by cashier workers contrast to office workers according to the UPLIRA assessment. Based on the results so far, it can be concluded that the UPLIRA tool was found to be practically reliable and applicable to a wide range of workplaces

Cost-benefit modelling for reliability growth

Decisions during the reliability growth development process of engineering equipment involve trade-offs between cost and risk. However slight, there exists a chance an item of equipment will not function as planned during its specified life. Consequently the producer can incur a financial penalty. To date, reliability growth research has focussed on the development of models to estimate the rate of failure from test data. Such models are used to support decisions about the effectiveness of options to improve reliability. The extension of reliability growth models to incorporate financial costs associated with 'unreliability' is much neglected. In this paper, we extend a Bayesian reliability growth model to include cost analysis. The rationale of the stochastic process underpinning the growth model and the cost structures are described. The ways in which this model can be used to support cost-benefit analysis during product development are discussed and illustrated through a simple case

Risk analysis and reliability of the GERDA Experiment extraction and ventilation plant at Gran Sasso mountain underground laboratory of Italian National Institute for Nuclear Physics

The aim of this study is the risk analysis evaluation about argon release from the GERDA experiment in the Gran Sasso underground National Laboratories (LNGS) of the Italian National Institute for Nuclear Physics (INFN). The GERDA apparatus, located in Hall A of the LNGS, is a facility with germanium detectors located in a wide tank filled with about 70 m3 of cold liquefied argon. This cryo-tank sits in another water-filled tank (700 m3) at atmospheric pressure. In such cryogenic processes, the main cause of an accidental scenario is lacking insulation of the cryo-tank. A preliminary HazOp analysis has been carried out on the whole system. The risk assessment identified two possible top-events: explosion due to a Rapid Phase Transition - RPT and argon runaway evaporation. Risk analysis highlighted a higher probability of occurrence of the latter top event. To avoid emission in Hall A, the HazOp, Fault Tree and Event tree analyses of the cryogenic gas extraction and ventilation plant have been made. The failures related to the ventilation system are the main cause responsible for the occurrence. To improve the system reliability some corrective actions were proposed: the use of UPS and the upgrade of damper opening devices. Furthermore, the Human Reliability Analysis identified some operating and management improvements: action procedure optimization, alert warnings and staff training. The proposed model integrates the existing analysis techniques by applying the results to an atypical work environment and there are useful suggestions for improving the system reliability

Value-at-Risk and expected shortfall for rare events

We show that the use of correlations for modeling dependencies may lead to counterintuitive behavior of risk measures, such as Value-at-Risk (VaR) and Expected Short- fall (ES), when the risk of very rare events is assessed via Monte-Carlo techniques. The phenomenon is demonstrated for mixture models adapted from credit risk analysis as well as for common Poisson-shock models used in reliability theory. An obvious implication of this finding pertains to the analysis of operational risk. The alleged incentive suggested by the New Basel Capital Accord (Basel II), amely decreasing minimum capital requirements by allowing for less than perfect correlation, may not necessarily be attainable

Prediction of depression in European general practice attendees: the PREDICT study

Background Prevention of depression must address multiple risk factors. Estimating overall risk across a range of putative risk factors is fundamental to prevention of depression. However, we lack reliable and valid methods of risk estimation. This protocol paper introduces PREDICT, an international research study to address this risk estimation. Methods/design This is a prospective study in which consecutive general practice attendees in six European countries are recruited and followed up after six and 12 months. Prevalence of depression is assessed at baseline and each follow-up point. Consecutive attendees between April 2003 and September 2004 who were aged 18 to 75 were asked to take part. The possibility of a depressive episode was assessed using the Depression Section of the Composite International Diagnostic Interview. A selection of presumed risk factors was based on our previous work and a systematic review of the literature. It was necessary to evaluate the test-retest reliability of a number of risk factor questions that were developed specifically, or adapted, for the PREDICT study. In a separate reliability study conducted between January and November 2003, consecutive general practice attendees in the six participating European countries completed the risk factor items on two occasions, two weeks apart. The overall response rate at entry to the study was 69%. We exceeded our expected recruitment rate, achieving a total of 10,048 people in all. Reliability coefficients were generally good to excellent. Discussion Response rate to follow-up in all countries was uniformly high, which suggests that prediction will be based on almost a full cohort. The results of our reliability analysis are encouraging and suggest that data collected during the course of PREDICT will have a satisfactory level of stability. The development of a multi-factor risk score for depression will lay the foundation for future research on risk reduction in primary care. Our data will also provide the necessary evidence base on which to develop and evaluate interventions to reduce the prevalence of depression