The Naval Civil Engineering Laboratory has conducted a study of the potential applications of isotopic devices and techniques within the Naval Shore Establishment. Radiation characteristics, general applications of isotopic devices, and specific problem areas are discussed. Recommendations are included for the use of surface density and moisture gages in the inspection of compacted earth, and f...

Ceramic Matrix Composites (CMC) are promising future materials for jet aircraft engines. CMC parts are produced by piling fabric layers made of silicon carbide yarn. To detect defects in the parts, this study proposes a computational method in which each piece of yarn is recognized from volumetric models obtained by X-ray CT scanning. The method produces a set of curves, each of which represent...

High Dimension Low Sample Size statistical analysis is becoming increasingly important in a wide range of applied contexts. In such situations, it is seen that the appealing discrimination method called the Support Vector Machine can be improved. The revealing concept is “data piling” at the margin. This leads naturally to the development of “Distance Weighted Discrimination,” which also is bas...

We study the influence of solid friction on the structure of the force network sustaining a regular bidimensional granular piling. We show how the mechanical equations describing local equilibrium may couple naturally with a stochastic variable. A Monte Carlo method is designed to extract the force networks satisfying static equilibrium conditions. A statistical ensemble is constructed and we s...

The Nara Bladder Tumor No. 2 cell line, established from a urinary bladder carcinoma in the Wistar rat, formed keratinizing cells and multicellular pearls in meniscus gradient culture when fed with a medium of 15 or 30% fetal calf serum in Eagle's minimal essential medium. Confluent monolayer cultures were first prepared with the tubes in conventional horizontal position. When cultures were the...

Optimization algorithms are iterative procedures that evolve from guessed starting points (SP) to the desired global minimum. Their performance can be greatly improved [1], if a neural network (NN) is created to select suitable SP. Here, we have trained NN’s to select possible groundstate geometries for silicon clusters. A genetic algorithm uses these candidates as initial population and perfor...