ENBIS-8 in Athens

21 – 25 September 2008 Abstract submission: 14 March – 11 August 2008

My abstracts

 

The following abstracts have been accepted for this event:

  • On t and EWMA t Charts for Monitoring Changes in the Process Mean

    Authors: Philippe CASTAGLIOLA (1), Gemai CHEN (2), Lingyun ZHANG (2)
    Affiliation: (1) Université de Nantes & IRCCyN UMR CNRS 6597, Carquefou, France, (2) University of Calgary, Calgary, Alberta, T2N 1N4, Canada
    Primary area of focus / application:
    Submitted at 26-Apr-2008 20:55 by Philippe CASTAGLIOLA
    Accepted (view paper)
    23-Sep-2008 09:20 On t and EWMA t Charts for Monitoring Changes in the Process Mean
    The performance of X-bar chart is usually and naturally studied under the assumption that the process variance is well estimated and does not change. This is, of course, not always the case in practice. We find that in the No case, X-bar charts are not robust against errors in variance estimation or changing variance. In this paper we discuss the use of a t-chart and an Exponentially Weighted Moving Average (EWMA) t-chart to monitor the process mean. We show that the EWMA t-chart has the desired robustness property. We also propose new control limits for both the t-chart and the EWMA t-chart.
  • Common terminology as a pre-requisite for a common use in international standardisation of basic concepts for expressing measurement uncertainty in metrology and testing

    Authors: Franco Pavese
    Affiliation: INRIM, Torino, Italy
    Primary area of focus / application:
    Keywords: Meteorology, Measurement Uncertainty
    Submitted at 28-Apr-2008 09:30 by Franco Pavese
    Accepted
    23-Sep-2008 12:00 Common terminology as a pre-requisite for a common use in international standardisation of basic concepts for expressing measurement uncertainty in metrology and testing
    This presentation is an advancement with respect to the published paper F.Pavese "Replicated observations in metrology and testing: modelling repeated and non-repeated measurements" Accred Qual Assur (2007) 12:525-534.
    It is supposed to address especially the users in laboratories at the field level in either industry or services (food, health, biology, pharmaceutical labs, environment, calibration, etc.), to help in understanding some of the differences occurring between written standards and also, when the case, to warn about possible misunderstandings.
  • Latent Class Models for Marketing Strategies: an Application to Promotion in the Pharmaceutical Sector

    Authors: Francesca Bassi
    Affiliation: University of Padova, Italy
    Primary area of focus / application:
    Submitted at 28-Apr-2008 12:21 by Francesca Bassi
    Accepted
    22-Sep-2008 10:35 Latent Class Models for Marketing Strategies: an Application to Promotion in the Pharmaceutical Sector
    Some extensions of the latent class (LC) approach are applied to analyze the Italian pharmaceutical market. Available data were collected in a survey on Italian general practitioners. All doctors were asked to express a judgment on various aspects regarding promotional activity – on a seven-point scale - organized by the pharmaceutical industries with which they were in contact and to declare the percentage of drugs produced by each firm which they usually prescribe.
    LC models for multilevel data were applied in order to identify market segments, i.e., groups of doctors with similar attitudes toward pharmaceutical representatives’ activities. A second aim of the paper is to verify which aspects of firms’ promotional activity may be determinant in influencing doctors’ prescriptions. LC regression models were estimated for this purpose.
    Traditional LC models assume that observations are independent. However, in our case this assumption was violated since doctors judged more than one pharmaceutical industry; multilevel LC models make it possible to modify the above assumption. A multilevel LC model consists of a mixture model equation for level-1 and level-2 units, in which a group-level discrete variable is introduced so that parameters are allowed to differ across latent classes or groups. Our level-1 units were judgments expressed by doctors on the seven aspects of the promotional activity; our level-2 units were doctors. We were interested in defining clusters of doctors (classes).
    LC regression models estimate a linear relation between a dependent variable and a set of explanatory variables, accounting for the fact that observations may arise from a number of unknown heterogeneous groups in which regression coefficients differ. LC regression models can be viewed as random-coefficient models that, like multilevel or hierarchical models, can take into account dependencies between observations. This extends the application of LC regression models to situations with repeated measurements. In our case, the dependent variable was the percentage of drugs produced by a certain pharmaceutical industry prescribed by practitioners, and predictors were the judgments expressed by doctors on the seven aspects of promotional activity.
  • The application of the Taguchi method to optimize the glycosaminoglycan extraction protocol from nails

    Authors: Rozina Vavetsi Department of Experimental Pharmacology, School of Medicine, University of Athens and T.E.I Piraeus/University of Paisley, Scotland 75 M.Asias St., Goudi 15669 Athens, Greece E-mail: rvavetsi@med.uoa.gr Chrysanthi Papanastasopoulou Department of Experimental Pharmacology, School of Medicine, University of Athens 75 M.Asias St., Goudi 15669 Athens, Greece E-mail: chpapan@med.uoa.gr Georgia Dougekou Department of Experimental Pharmacology, School of Medicine, University of Athens 75 M.Asias St., Goudi 15669 Athens, Greece E-mail: ssapounas@gmail.com George J. Besseris T.E.I Piraeus/University of Paisley, Scotland, Argirokastrou 30 St., Drosia 14572 Athens, Greece E-mail: besseris@teipir.gr Nikolaos M. Sitaras Department of Experimental Pharmacology, School of Medicine, University of Athens 75 M.Asias St., Goudi 15669 Athens, Greece E-mail: nsitar@med.uoa.gr
    Primary area of focus / application:
    Submitted at 28-Apr-2008 21:18 by Rozina Vavetsi
    Accepted
    23-Sep-2008 11:35
    Glycosaminoglycans (GAGs), a class of complex polysaccharides of the extracellular environment have been recognized to participate in numerous physiological and pathological processes. Dermatan sulphate, the predominant glycan in skin, is particularly attractive because it is expressed in many mammalian tissues and has been implicated in tumorigenesis, would repair, infections and fibrosis. Human nails – a special epithelial structure with continuously produced cells that become keratinized and eventually desquamated- have not yet been studied for their glycosaminoglycan content.
    The aim of the present study was a) to investigate the content of glycosaminoglycans in human nails and optimize the extraction laboratory protocol so the maximum of them is liberated, and b) study the presence of dermatan sulphate in this material.
    Unpolished human nails were obtained from 30 healthy individuals and GAGs were sequentially extracted with guanidinium chloride (Gu-HCl). To optimize the extraction protocol the Taguchi method was applied. Cellulose acetate electrophoresis was performed for the qualitative identification of GAGs. Enzymatic treatment with specific lyases followed, to study the presence of dermatan sulphate in this material.
    The results indicated the best combination of the extraction parameters that liberated the maximum concentration of GAGs from nails, being 116 ± 15.8 μg/g of tissue. Cellulose acetate electrophoresis after treatment with specific enzymes revealed a metachromatic band with mobility identical to dermtan’ s sulfate
  • Factors affecting the near-miss reporting

    Authors: Yousif Rahim and Prof. Ron Kenett
    Affiliation: University of Torino, Italy
    Primary area of focus / application:
    Submitted at 28-Apr-2008 21:36 by Yousif Rahim
    Accepted (view paper)
    23-Sep-2008 16:30 Factors affecting the near-miss reporting
    Factors affecting the near miss reporting

    Yousif Rahim
    University of Torino, Italy
    Det Norske Veritas, Norway
    yousif.rahim@unito.it

    Prof. Ron Kenett
    University of Torino, Italy
    KPA, Israel
    ron@kpa.co.il

    An effective safety improvement system needs an effective system for reporting all types of incidents including near miss. Reactive safety strategies incorporate various monitoring techniques for accidents, cases of ill-health and near misses as near miss is an opportunity to improve safety practice based on a condition, or an incident with the potential for more serious consequences.

    Under-reporting is a problem in many sectors of industry, and this is significant since; if reporting levels are low, the accident data will not provide the full picture of accidents that have occurred and analysis of such data may be of limited use in determining the real problem areas.

    The problem of under-reporting and especially of near-miss reporting can only be solved by having an organisation-wide culture for solution oriented and not the penalisation of the party responsible. To achieve this goal, there must be a continuous commitment on the part of top management to the issue of reporting all incidents and follow up the implementation of corrective measures and actions.

    Objectives:
    1. To find out and ensure that near-misses are reported
    2. To find an appropriate method for reporting near miss
    3. Find factors encouraging employees to report near miss
    4. Utilising near miss information, in order to take action to prevent serious accidents occurring
    5. To describe how reporting leading to improvement in safety performance.

    Methods.
    Conducting relevant literature review on state of art in the field of safety management systems, includes review of both white papers and grey literature. Review the Safety management system documents for the major oil and gas companies. Relevant databases will be interrogated with main focus on usability and quality of the accident data.

    Discussion
    Design a process for containing and explaining all near miss consecutive stages:
    - Identification
    - Disclosure
    - Distribution
    - Direct and Root Cause Analysis
    - Solution identification
    - Dissemination to implementers
    - Resolution

    The importance of near miss data for operations and corporate level effectiveness will be highlighted through the effect of near-miss reporting in improvement of corporate health, safety and environment performance.

    The study will focus on how the near-misses reporting system and data can provide essential data and information to find and discover the potential broken safety barriers and weaknesses in the management system of companies.
  • Method for VaR-based Portfolio Selection

    Authors: Xu, Chunhui and Ng, Peggy
    Primary area of focus / application:
    Submitted at 28-Apr-2008 23:46 by Peggy Ng
    Accepted
    22-Sep-2008 11:43 Method for VaR-based Portfolio Selection
    Value-at-Risk (VaR) is taken as a measure of risk in portfolio selection. Since VaR is generally a non-convex and non-smooth function, conventional optimization methods fail to solve portfolio selection models that incorporate VaR. In this paper, we propose a soft optimization method for solving VaR-based portfolio selection models. In theory, the soft method does not necessarily produce an optimal portfolio, but identifies a good enough portfolio with a high probability. In return for this compromise, the soft method is simpler to use than linear programming algorithms.
    An investment experiment is performed using data from the New York stock market. Portfolios suggested by the soft method are compared to two commonly used investment strategies. The results show that the portfolio selected by the soft method may produce a higher return at lower risk than the two investment strategies, which demonstrates the effectiveness of the proposed method. The results also suggest that VaR could be applied as a measure of risk in portfolio selection from a computational point of view.