ENBIS: European Network for Business and Industrial Statistics
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ENBIS-14 in Linz
21 – 25 September 2014; Johannes Kepler University, Linz, Austria Abstract submission: 23 January – 22 June 2014The following abstracts have been accepted for this event:
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Failure Diagnostics and Prognostics based on Hidden Markov Models
Authors: Tingting Liu (Vrije Universiteit Brussel), Lemeire Jan (Vrije Universiteit Brussel)
Primary area of focus / application: Modelling
Secondary area of focus / application: Reliability
Keywords: Condition-based maintenance (CBM), Hidden Markov models (HMM), Diagnostics, Prognostics
Submitted at 29-Apr-2014 16:20 by Tingting Liu
Accepted
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Reducting Cost of Monte Carlo Experiments in Power Production Safety Contexts: Some Benefits of Monotonicity
Authors: Nicolas Bousquet (EDF R&D), Vincent Moutoussamy (EDF R&D), Thierry Klein (IMT Toulouse), Fabrice Gamboa (IMT Toulouse)
Primary area of focus / application: Reliability
Secondary area of focus / application: Reliability
Keywords: Monte Carlo, Monotonicity, Computer codes, Metamodelling, Deterministic bounds, Design of Experiments
Submitted at 29-Apr-2014 16:57 by Nicolas Bousquet
Accepted
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Spatial Outlier Detection in the Air Quality Monitoring Network of Normandy (France)
Authors: Jean-Michel Poggi (Univ. Paris Descartes & Univ. Paris-Sud Orsay), Michel Bobbia (Air Normand), Michel Misiti (Univ. Paris-Sud Orsay), Yves Misiti (Univ. Paris-Sud Orsay), Bruno Portier (Normandie Université, INSA Rouen)
Primary area of focus / application: Mining
Secondary area of focus / application: Metrology & measurement systems analysis
Keywords: Air quality, Kriging, Nearest neighbors, Particulate matter, Spatial outlier detection
The general strategy uses a jackknife type approach and is based on the comparison of the actual measure with some robust prediction. Two ways to handle spatial prediction are considered: the first one is based on the nearest neighbors weighted median which directly consider concentrations while the second one is based on kriging increments, instead of more traditional pseudo-innovations.
The two methods are applied to the PM10 monitoring network in Normandy and are fully implemented by Air Normand (the official association for air quality monitoring in Haute-Normandie) in the Measurements Quality Control process. Some numerical results are provided on recent data from January 1, 2013 to May 31, 2013 to illustrate and compare the two methods. -
Robust Multivariate Process Control of Multi-Way Data in Semiconductor Fabrication
Authors: Peter Scheibelhofer (Institute of Statistics, Graz University of Technology), Günter Hayderer (ams AG), Ernst Stadlober (Institute of Statistics, Graz University of Technology)
Primary area of focus / application: Process
Keywords: Fault detection, Multivariate process control, Multi-way PCA, Robust statistics, Kernel methods
Submitted at 30-Apr-2014 10:16 by Peter Scheibelhofer
Accepted
In a case study with data from the Austrian semiconductor manufacturer ams AG an observed production fault can be detected and its root cause can be tracked down successfully. -
On the Practical Interest of Some Discrete Lifetime Models in Industrial Reliability Studies in the Context of Power Production
Authors: Alberto Pasanisi (EDF R&D), Come Roero (INRIA Paris Sud), Nicolas Bousquet (EDF R&D), Emmanuel Remy (EDF R&D)
Primary area of focus / application: Reliability
Secondary area of focus / application: Modelling
Keywords: Discrete survival data, Inverse Polya model, Discrete Weibull model, Ageing
Submitted at 30-Apr-2014 10:22 by Alberto Pasanisi
Accepted
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Identifying Patient Communication Needs: An Empirical Test on Rare Cancer in Italy
Authors: Rosa Falotico (Università degli Studi di Milano Bicocca), Caterina Liberati (Università degli Studi di Milano Bicocca), Paola Zappa (University of Italian Switzerland, Lugano)
Primary area of focus / application: Quality
Secondary area of focus / application: Mining
Keywords: Patient communication needs, Online communication, Qualitative interviews, Text mining
Submitted at 30-Apr-2014 10:49 by Rosa Falotico
Accepted
This work aims to address the extent of these limitations, examining patient propensity toward using web communication and identifying the patient needs that it could contribute to satisfy.
For this purpose, we run an exploratory empirical study on a sample of rare cancer patients treated in a highly specialized research center in Northern Italy. We conduct semi-structured interviews on patient propensity and needs and analyze their transcriptions by means of text mining techniques. We clean and normalize the texts with automatic techniques for lexical- grammatical analysis and, finally, we synthesize the text contents with correspondence analysis (shortly, CA). CA allows us to identify the main concepts expressed by patients and to represent geometrically, in a reduced factorial space, the patients and the concepts. This simultaneous graphic representation of concepts and individuals allows visual representation of the association between patients and their information needs.