Alistair Duffy

Feature selective validation (FSV) for validation of computational electromagnetics (CEM). part I-the FSV method

A goal for the validation of computational electromagnetics (CEM) is to provide the community with a simple computational method that can be used to predict the assessment of electromagnetic compatibility (EMC) data as it would be undertaken by individuals or teams of engineers. The benefits of being able to do this include quantifying the comparison of data that has hitherto only been assessed qualitatively, to provide the ability to track differences between model iterations, and to provide a means of capturing the variability and range of opinions of groups and teams of workers. The feature selective validation (FSV) technique shows great promise for achieving this goal. This paper presents a detailed analysis of the FSV method, setting it firmly in the context of previous comparison techniques; it suggests the relationship between validation of graphically presented data and the psychology of visual perception. A set of applicability tests to judge the effectiveness of computer-based CEM validation techniques is also proposed. This paper is followed by a detailed comparison with visual assessment, which is presented in Part II

The feature selective validation (FSV) method

The feature selective validation (FSV) method is one of the candidate techniques for the quantitative validation of computational electromagnetics (CEM), particularly within electromagnetic compatibility (EMC) and signal integrity (SI). In applications so far, it has demonstrated significant promise and is likely to be a central feature of the growing research interest in CEM validation. This paper presents a detailed review of the FSV method and implementation. It concludes with a discussion of some of the current research topics.

Dielectric Analysis of Phosphorylcholine Head Group Mobility in Egg Lecithin Liposomes

AbstractPurpose. A knowledge of the interfacial properties of lecithin underpins our understanding of many of the physicochemical characteristics of drug delivery systems such as liposomes and lecithin stabilized microemulsions. In order to further this understanding, a high frequency dielectric study of the interfacial properties of egg lecithin liposomes was undertaken. Methods. The effect of temperature, lecithin concentration and probe sonication on the interfacial dielectric properties of liposomal suspensions was investigated by high frequency dielectric relaxation spectroscopy between 0.2–6 GHz. Results. The frequency dependent permittivity of each suspension exhibited a dielectric dispersion centred around 100 MHz, corresponding to the relaxation of zwitterionic head groups. The activation energy for head group reorientation was estimated as ΔH = 6.3 kJ mol−1. There was an increase in extent of inter-head group interactions on increasing the liposome volume fraction, whereas the effect of probe sonication showed that: (i) head groups in both the outer and inner lamellae contribute to the dielectric response; (ii) the head groups may be less restricted in liposomes of high surface curvature with few lamellae; (iii) the high frequency permittivity of the suspension increased on sonication, as a result of a reduction in the amount of (depolarized) interlamellar water following a reduction in the number of lamellae per liposome. Conclusions. Dielectric analysis of the zwitterionic head groups of lecithin therefore provides a means for investigating the surface of lecithin liposomes, and may be used to investigate the effect of drugs and other solutes on membranes.

Applications of FSV to EMC and SI data

This paper is concerned with the usability of the feature selective validation (FSV) method for comparing validation data. It addresses how it can help in the validation process and how the resulting validation data can be interpreted. It does this by considering two different case studies. The first considers two approaches to modeling electric fields in an equipment rack, and the second compares a Spice model for coupled circuit boards with a reference full wave model. The paper concludes that while the single value summary metrics are helpful to give an overall level of agreement, the detailed point-by-point information is very helpful when considering how to improve the models or measurements involved.

Applying a behavioural and operational diagnostic typology of competitive intelligence practice: empirical evidence from the SME sector in Turkey

This paper reports on an empirical study conducted within the SME sector in the city of Istanbul, Turkey. The findings from this study enabled the creation of a behavioural and operational typology of competitive intelligence practice, one developed from the work of S. Wright, D.W. Pickton and J. Callow (2002. Competitive intelligence in UK firms: A typology. Marketing Intelligence & Planning, 20, 349–360). Using responses to questions which indicated a type of behaviour or operational stance towards the various strands of CI practice under review it has been possible to identify areas where improvements could be made to reach an ideal situation which could garner significant competitive advantage for the SMEs surveyed.

A simple formula for calculating the frequency‐dependent resistance of a round wire

At high frequencies, the current distribution across a circular wire is modified by the skin effect, causing the greatest current density to be near the surface of the wire. One common method of calculating the wire resistance inoles determining complex Bessel func- tions, the solution of which is prone to approximations as the skin depth becomes less than about one tenth the wire radius. An alternatie method of determining this resistance is presented which is significantly simpler than the Bessel function approach, easier toisualize, and not reliant on approximations when determining the solution. This approach is based on determining the width of an annulus which carriers the equialent current to the full wire. Results are presented which confirm the accuracy of the equialent annulus method. Q 1998 John Wiley & Sons, Inc. Microwave Opt Technol Lett 19: 84)87, 1998.

Factors influencing the successful validation of transient phenomenon modelling

An increased requirement for validation of computational electromagnetic simulation and modelling through the publication of IEEE Standard 1597.1 brings to light some interesting issues surrounding the validation of transients. The structure of a transient event has three particular regions of interest that can have an influence on the results, of which only two are generally well defined. These are the initial quiescent phase from t = 0 to the transient event; the transient event itself up to the point where the energy has fallen to a predefined limit, and the post-transient phase where residual energy is still present in the system. This latter region is generally ill-defined and changes the way that a validation comparison should be made, from, for example a frequency domain coupling study where the region of interest is usually well defined. This study looks at the influence of the three regions on the validation results and suggests how the Feature Selective Validation (FSV) method can be applied in transient studies.

Offset Difference Measure Enhancement for the Feature-Selective Validation Method

The feature-selective validation (FSV) method is proving itself to be a robust and helpful technique to quantify visually complex measurement sets, such as those resulting from computational electromagnetic validation exercises or experimental repeatability studies. This paper reports on an enhancement to this technique that includes data related to the level of dc difference (i.e., offset) between two sets of results, hitherto disregarded within the method. This offset difference measure (ODM) contributes to the amplitude difference measure (ADM) and ensures that the ADM and global difference measure values reflect the level of disagreement between the two traces even if this is the only difference between the two. The paper describes the background to this development and provides details of the selection and implementation of the ODM measure.

Analysis of techniques to compare complex data sets.

This paper analyses a number of techniques that can be used to compare complex data sets, such as those arising from electromagnetic simulation and experimentation. The techniques assessed are: correlation, several reliability factors and feature selective validation. The study examines the performance of each technique for data comparison. The paper provides a comprehensive summary of the techniques and compares their performance and comments on their use in the validation of numerical modelling codes and model designs.

Comparing FSV and human responses to data comparisons

The feature selective validation (FSV) method was developed with the specific goal to mirror the approach taken by engineers when assessing data presented visually during the validation of computational electromagnetics. The FSV (feature selective validation) technique has been demonstrated to have good agreement with the human survey results for a number of different data sets. Survey results for data sets in good agreement show a very small standard deviation, however, data sets with fair agreement have a significantly higher standard deviation.