Potential applications of discrete-event simulation and fuzzy rule-based systems to structural reliability and availability

This chapter discusses and illustrates some potential applications of discrete-event simulation (DES) techniques in structural reliability and availability analysis, emphasizing the convenience of using probabilistic approaches in modern building and civil engineering practices. After reviewing existing literature on the topic, some advantages of probabilistic techniques over analytical ones are highlighted. Then, we introduce a general framework for performing structural reliability and availability analysis through DES. Our methodology proposes the use of statistical distributions and techniques – such as survival analysis – to model component-level reliability. Then, using failure- and repair-time distributions and information about the structural logical topology (which allows determination of the structural state from their components’ state), structural reliability, and availability information can be inferred. Two numerical examples illustrate some potential applications of the proposed methodology to achieving more reliable and structural designs. Finally, an alternative approach to model uncertainty at component level is also introduced as ongoing work. This new approach is based on the use of fuzzy rule-based systems and it allows the introduction of experts’ opinions and evaluations in our methodology.

Corporate codes of ethics in Australia, Canada and USA : measurement and structural properties of a cross-cultural model

The objective is to test the consistency of measurement and structural properties in a model of corporate codes of ethics (CCE) on an aggregated level and across multiple samples derived from three countries, namely Australia, Canada and the USA. The properties of four constructs of CCE are described and tested, these being: surveillance/training, internal communication, external communication, and guidance. The conclusion is that the measurement and structural models on an aggregated level have a satisfactory fit, validity and reliability. Furthermore, they are consistent when tested on each of the three samples (i.e. cross-validated). The cross-cultural model makes a contribution in addition to previous mostly descriptive studies and theory in the field using confirmatory factor analysis and structural equation modeling.

Measurement and structural properties of organizational codes of ethics in private and public Sweden

Purpose – The purpose of this paper is to test the measurement and structural properties in a model of organizational codes of ethics (OCE) in Sweden.

Design/methodology/approach – The measurement and structural properties of four OCE constructs (i.e. surveillance/training, internal communication, external communication, and guidance) were described and tested in a dual sample based upon private and public sectors of Sweden.

Findings – Results show that the measurement and structural models of OCE in part have a satisfactory fit, validity, and reliability.

Research limitations/implications – The paper makes a contribution to theory as it outlines a set of OCE constructs and it presents an empirical test of and OCE model in respect to measurement and structural properties. A number of research limitations are provided.

Practical implications – It provides a model to be considered in the implementation and monitoring of OCE. The present research provides opportunities for further research in refining, extending, and testing the proposed OCE model in other cultural and organizational settings.

Originality/value – The OCE model extends previous studies that have been predominately descriptive, by using confirmatory factor analysis and structural equation modeling.

Towards automated detection of depression from brain structural magnetic resonance images

Introduction : Depression is a major issue worldwide and is seen as a significant health problem. Stigma and patient denial, clinical experience, time limitations, and reliability of psychometrics are barriers to the clinical diagnoses of depression. Thus, the establishment of an automated system that could detect such abnormalities would assist medical experts in their decision-making process. This paper reviews existing methods for the automated detection of depression from brain structural magnetic resonance images (sMRI).Methods : Relevant sources were identified from various databases and online sites using a combination of keywords and terms including depression, major depressive disorder, detection, classification, and MRI databases. Reference lists of chosen articles were further reviewed for associated publications.Results : The paper introduces a generic structure for representing and describing the methods developed for the detection of depression from sMRI of the brain. It consists of a number of components including acquisition and preprocessing, feature extraction, feature selection, and classification.Conclusion : Automated sMRI-based detection methods have the potential to provide an objective measure of depression, hence improving the confidence level in the diagnosis and prognosis of depression.

Construct validity and reliability of the single checking administration of medications scale

Research indicates that single checking of medications is as safe as double checking; however, many nurses are averse to independently checking medications. To assist with the introduction and use of single checking, a measure of nurses' attitudes, the thirteen-item Single Checking Administration of Medications Scale (SCAMS) was developed. We examined the psychometric properties of the SCAMS. Secondary analyses were conducted on data collected from 503 nurses across a large Australian health-care service. Analyses using exploratory and confirmatory factor analyses supported by structural equation modelling resulted in a valid twelve-item SCAMS containing two reliable subscales, the nine-item Attitudes towards single checking and three-item Advantages of single checking subscales. The SCAMS is recommended as a valid and reliable measure for monitoring nurses' attitudes to single checking prior to introducing single checking medications and after its implementation.

Structural damage identification based on self-fitting ARMAX model and multi-sensor data fusion

Statistical time series methods have proven to be a promising technique in structural health monitoring, since it provides a direct form of data analysis and eliminates the requirement for domain transformation. Latest research in structural health monitoring presents a number of statistical models that have been successfully used to construct quantified models of vibration response signals. Although a majority of these studies present viable results, the aspects of practical implementation, statistical model construction and decision-making procedures are often vaguely defined or omitted from presented work. In this article, a comprehensive methodology is developed, which essentially utilizes an auto-regressive moving average with exogenous input model to create quantified model estimates of experimentally acquired response signals. An iterative self-fitting algorithm is proposed to construct and fit the auto-regressive moving average with exogenous input model, which is capable of integrally finding an optimum set of auto-regressive moving average with exogenous input model parameters. After creating a dataset of quantified response signals, an unlabelled response signal can be identified according to a 'closest-fit' available in the dataset. A unique averaging method is proposed and implemented for multi-sensor data fusion to decrease the margin of error with sensors, thus increasing the reliability of global damage identification. To demonstrate the effectiveness of the developed methodology, a steel frame structure subjected to various bolt-connection damage scenarios is tested. Damage identification results from the experimental study suggest that the proposed methodology can be employed as an efficient and functional damage identification tool. © The Author(s) 2014.

Validity and reliability of a pictorial instrument for assessing perceived motor competence in Portuguese children

BACKGROUND: It is important to assess young children's perceived Fundamental Movement Skill (FMS) competence in order to examine the role of perceived FMS competence in motivation toward physical activity. Children's perceptions of motor competence may vary according to the culture/country of origin; therefore, it is also important to measure perceptions in different cultural contexts. The purpose was to assess the face validity, internal consistency, test-retest reliability and construct validity of the 12 FMS items in the Pictorial Scale for Perceived Movement Skill Competence for Young Children (PMSC) in a Portuguese sample.

METHODS: Two hundred one Portuguese children (girls, n = 112), 5 to 10 years of age (7.6 ± 1.4), participated. All children completed the PMSC once. Ordinal alpha assessed internal consistency. A random subsamples (n = 47) were reassessed one week later to determine test-retest reliability with Bland-Altman method. Children were asked questions after the second administration to determine face validity. Construct validity was assessed on the whole sample with a Bayesian Structural Equation Modelling (BSEM) approach. The hypothesized theoretical model used the 12 items and two hypothesized factors: object control and locomotor skills.

RESULTS: The majority of children correctly identified the skills and could understand most of the pictures. Test-retest reliability analysis was good, with an agreement ration between 0.99 and 1.02. Ordinal alpha values ranged from acceptable (object control 0.73, locomotor 0.68) to good (all FMS 0.81). The hypothesized BSEM model had an adequate fit.

CONCLUSIONS: The PMSC can be used to investigate perceptions of children's FMS competence. This instrument can also be satisfactorily used among Portuguese children.