Neural Computation of the MoM Matrix Elements for Planar Configurations

In this paper a new artificial neural network (ANN) based model for the calculation of the method of moments (MoM) matrix elements is presented. Training sets that characterize the matrix elements are first constructed. These sets are then utilized to effectively train two radial basis function (RBF) neural networks to accurately estimate all the elements of the MoM matrix for any mesh used. The potential of the proposed approach is demonstrated in the case of a narrow microstrip line. The current distribution on the microstrip line produced by the trained RBF networks agrees very well with the exact distribution. In addition, the proposed ANN model is much faster than the conventional MoM procedure.     

Reliability and scale effect in toughness of concrete structures

In the present work, the distribution of the random toughness characteristics (i.e. critical energy release rate, G_1c) has been evaluated on the basis of experimental observations. Fracture test results from three groups of geometrically similar concrete specimens of size (width×total depth×thickness), 420×420×50–1680×1680×200 mm³, made with different maximum aggregate size of 9.5, 19, 38, and 76 mm were analyzed using a recently proposed distribution of extremes. In applications of probability, it is important to use an appropriate distribution type and adequate techniques for estimating the parameters of distribution. In this study, a new type distribution of minima is employed for probability computations. It was noticed that the entropy of distribution increases with the crack length, i.e. the uncertainty of toughness, G_1c, value increases with crack length. A non-linear reduction of the maximum allowable splitting force with the defect size, a, was noticed. For large specimens, the maximum allowable splitting load is more sensitive to the required reliability level than that for small specimens. Reliability increases with aggregate size when all other conditions were constant.     

An innovative semianalytical technique for ceramic evaluation at microwave frequencies

We have developed an innovative semianalytical technique for various substrate material characterization. The developed technique is a measurement procedure and data-reduction formulation that takes into consideration the radiation loss in a resonant structure, allowing for a more effective means of dielectric- and conductor-loss determination for a microstrip ring resonator and its substrate material. We separate dielectric and conductor loss precisely, evaluate the contribution of each term in the overall loss performance, and analytically predict the error in their respective predicted value.     

Sequential tripping strategy for a transmission network back-upprotection expert system

This paper describes a sequential tripping strategy used in a wide area back-up protection expert system (BPES) to combat situations in which protection relays have maloperated or information is missing. The BPES is an innovative back-up protection scheme designed to prevent the occurrence of widespread blackouts. The BPES evaluates the certainty that transmission lines are likely to be affected by the fault and uses a sequential tripping strategy to isolate the fault if a firm decision is not available due to maloperated relays and/or missing information. The mode of analysis and the sequential tripping strategy ensures that the BPES will clear a fault at minimum risk to the network. An example is included to demonstrate how the certainty factor based sequential tripping strategy is employed by the BPES to clear a fault which occurred on the South Western part of the UK National Grid System     

INHIBITION OF BOTULINUM TOXIN PRODUCTION BY PEDIOCOCCUS ACIDILACTICI IN TEMPERATURE ABUSED REFRIGERATED FOODS

The "Wisconsin process'(a combination of lactic acid starter culture and sucrose) has previously been shown to be effective in preventing botulinum toxigenesis in reduced nitrite bacon. This technology has been applied to other low-acid refrigerated foods which receive less than a 12D thermal process. A combination of Pediococcus acidilactici and dextrose was effective in preventing botulinum toxigenesis in chicken salad. When the chicken salad was temperature abused, the P. acidilactici catabolized available dextrose to lactic acid. Extracellular accumulation of the lactic acid caused a decrease in the pH of the product. Pathogen challenge tests verified that the rate and extent of lactic acid accumulation in the chicken salad during temperature abuse was sufficient to preclude botulinum toxigenesis. This technology has the potential to be of use in a variety of low-acid refrigerated foods.