Verification and validation of Bayesian knowledge-bases

Knowledge-base V&V primarily addresses the question: “Does my knowledge-base contain the right answer and can I arrive at it?” One of the main goals of our work is to properly encapsulate the knowledge representation and allow the expert to work with manageable-sized chunks of the knowledge-base. This work develops a new methodology for the verification and validation of Bayesian knowledge-bases that assists in constructing and testing such knowledge-bases. Assistance takes the form of ensuring that the knowledge is syntactically correct, correcting “imperfect” knowledge, and also identifying when the current knowledge-base is insufficient as well as suggesting ways to resolve this insufficiency. The basis of our approach is the use of probabilistic network models of knowledge. This provides a framework for formally defining and working on the problems of uncertainty in the knowledge-base.

In this paper, we examine the project which is concerned with assisting a human expert to build knowledge-based systems under uncertainty. We focus on how verification and validation are currently achieved in .     

Self-Organising Maps: A new way to screen the level of satisfaction of dialysis patients

Evaluation of patient satisfaction has become an important indicator for assessing health care quality. Fresenius Medical Care (FME) as a global provider of dialysis services through its NephroCare network has a strong interest in monitoring patient satisfaction.The aim of the paper is to test and validate a methodology for detecting a residual area of low satisfaction in dialysis patients.The FME Patient Satisfaction Programme questionnaire was distributed to haemodialysis (HD) patients treated in 335 centers of its network. It contained 79 questions covering various satisfaction aspects regarding Dialysis Unit, Dialysis Arrangement, Nurses, Doctors, etc.To analyse the data provided by the questionnaire, the Self-Organising Map (SOM) method was used. SOM is a neural network model for clustering and projecting high-dimensional data into a low-dimensional space, preserving topological relationships of original high-dimensional data spaces.10,632 HD patients completed the questionnaire. Mean age was 63.05 ± 14.93 years with 56.69% males. Response rate was 66%. Overall level of satisfaction was 1.99 (range from ?3 to +3). On average patients were very satisfied with all issues. Nevertheless, a group of patients, around 60 years old, balanced gender ratio, whose level of satisfaction was lower than 1, were highlighted.In the NephroCare clinics patient satisfaction with service is rather high. While traditional analysis usually stops here, the SOM method allows identification of areas of potential improvement for specific patient groups.     

Multivariate Modeling of Age and Retest in Longitudinal Studies of Cognitive Abilities.

Longitudinal multivariate mixed models were used to examine the correlates of change between memory and processing speed and the contribution of age and retest to such change correlates. Various age- and occasion-mixed models were fitted to 2 longitudinal data sets of adult individuals (N > 1,200). For both data sets, the results indicated that the correlation between the age slopes of memory and processing speed decreased when retest effects were included in the model. If retest effects existed in the data but were not modeled, the correlation between the age slopes was positively biased. The authors suggest that although the changes in memory and processing speed may be correlated over time, age alone does not capture such a covariation. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Modelling and Validating a multiple-configuration railway signalling system using SDL

This paper discusses some issues about the usage of SDL and related commercial SDL support tools for the validation of a railway signalling system: in particular, the issue of the multiple configurations presented by this system is addressed, discussing the possible strategies to validate the system regardless to the actual configuration.     

Maximum and Minimum Likelihood Hebbian Learning for Exploratory Projection Pursuit

In this paper, we review an extension of the learning rules in a Principal Component Analysis network which has been derived to be optimal for a specific probability density function. We note that this probability density function is one of a family of pdfs and investigate the learning rules formed in order to be optimal for several members of this family. We show that, whereas we have previously (Lai et al., 2000; Fyfe and MacDonald, 2002) viewed the single member of the family as an extension of PCA, it is more appropriate to view the whole family of learning rules as methods of performing Exploratory Projection Pursuit. We illustrate this on both artificial and real data sets.     

Influence of the gasket materials on the clamping pressure distribution in a PEM water electrolyzer: Bolt torques and operation mode in pre-conditioning

To keep optimally connected, all electrolysis cell elements is one of the most important design criteria. The optimal distribution of the clamping points is crucial to increasing cell performance. In this work, the compression pressure distribution inside of a 25 cm² PEM electrolysis cell was evaluated, using different materials: Teflon®, Viton®, ethylene propylene diene monomer rubber (EPDM), and nitrile rubber. Sealing material evaluation was performed taking as performance indicators: total compressed area (%) and compression pressure, for different torques applied. Pressure distribution was obtained by using pressure-sensitive films, analyzing the distribution of pressure points from three-dimensional plots (3D), and quantifying intensities of the images obtained. Results showed that pressure points distribution depends on the stiffness and thickness of the gasket materials. For a tightening torque of 3.70 N m, a pressure of 2.23 MPa is obtained with 85% of the membrane area compressed using nitrile rubber-EPDM gaskets.     

Transitions in Presence of Short Laser Pulses

Abstract

Accurate numerical calculations are carried out to investigate the validity of the two-state approximation in the case of resonant interactions between electromagnetic radiation and atoms. Short pulses are considered and the presence of the atomic spectrum is modelled by introducing a third, non-resonant, state. We show that the harmonics of the pulse profile may play a significant role in the dynamics of the process and may cause energy non-conserving transitions between the atomic states.     

Damage detection and artificial healing of asphalt concrete after trafficking with a load simulator

Artificial healing of asphalt concrete by induction heating requires the addition of electrically conductive and/or magnetic materials into the asphalt mixture. Hence, bitumen can be heated up by an alternating electromagnetic field, decreasing therefore its viscosity and allowing it to flow for closing cracks and recover bonding among the mineral aggregates.In this work, a recent performance oriented study of this innovative approach to prove the feasibility of the healing concept at large scale is presented. This work was focused on the analysis of 1.8 m long test slabs damaged by the Model Mobile Load Simulator MMLS3. It is known that visible cracks cannot be completely healed by this technique and therefore, recovery of the mechanical performance is not significant. For this reason, inductive heating must be applied not later than the initiation of micro-cracks to allow them to be promptly closed avoiding their propagation.In order to monitor the damage level of a number of the test slabs during the loading phase, a digital image correlation system was used in this work. This optical method allowed us to see the accumulated damage as well as to select the right moment to accomplish the healing process. In addition, this method was useful to confirm that the strength was recovered after a healing process and hence, an increase of life of the asphalt pavement might be obtained. Finally, it was demonstrated that healing by induction heating can be a feasible alternative for maintenance purposes when used before irreversible damage of the pavement.     

Google Scholar Metrics evolution: an analysis according to languages

In November 2012 the Google Scholar Metrics (GSM) journal rankings were updated, making it possible to compare bibliometric indicators in the ten languages indexed—and their stability—with the April 2012 version. The h-index and h-5 median of 1,000 journals were analysed, comparing their averages, maximum and minimum values and the correlation coefficient within rankings. The bibliometric figures grew significantly. In just seven and a half months the h-index of the journals increased by 15 % and the median h-index by 17 %. This growth was observed for all the bibliometric indicators analysed and for practically every journal. However, we found significant differences in growth rates depending on the language in which the journal is published. Moreover, the journal rankings seem to be stable between April and November, reinforcing the credibility of the data held by Google Scholar and the reliability of the GSM journal rankings, despite the uncontrolled growth of Google Scholar. Based on the findings of this study we suggest, firstly, that Google should upgrade its rankings at least semi-annually and, secondly, that the results should be displayed in each ranking proportionally to the number of journals indexed by language.