Engineering topics

Meador, J.

Publications and source records attributed to Meador, J..

4 records

NASA NTRS2005

In Vitro Experimental Model to Investigate the Biological Effects across the Bragg Curve of High-LET Radiation

The space environment consists of a varying field of radiation particles including high energy ions, with a spacecrafts shielding material providing the only major protection to astronauts from harmful exposure. Unlike lowLET gamma or Xrays, the presence of shielding does not always reduce the radiation risks for energetic charged particle exposure since the dose delivered by the charged particle increases sharply as the particle approaches the end of its range, a position known as the Bragg peak and the correlating spatial dose distribution identified as the Bragg curve. The Bragg curve does not necessarily represent the biological damage along the particle traversal since biological effects are influenced by the track structure of both primary and secondary particles. Therefore, the biological Bragg curve is dependent of the energy and the type of the primary particle, and may vary for different biological endpoints. Here we describe a unique irradiation geometry and experimental system to measure the biological response across the Bragg curve in one consistent biological sample. Polyethylene shielding was used to achieve a Bragg curve distribution with the beam geometry parallel to a monolayer of fibroblast cells. We present data that highlights the differential formation of DNA double strand breaks (DSBs) and chromosomal deletions across the Bragg curve in human fibroblasts irradiated with 600 MeV/nucleon iron ion beams. Qualitative analyses of gammaH2AX fluorescence, a known marker of DSBs, indicated potentially increased clustering of DNA damage before the Bragg peak, enhanced homogenous distribution at the peak, and provided visual evidence of high linear energy transfer (LET) particle traversal of cells beyond the Bragg peak in agreement with one-dimensional transport approximations. A biological response curve generated for micronuclei induction across the Bragg curve for 600 MeV/n Fe ions did not reveal an increase in the yield of micronuclei at the Bragg peak location. Assessment of such biological parameters employing the described in vitro experimental system may provide improved platforms to measure a number of biological consequences of shielding materials across the Bragg curve for high charge and energy (HZE) ions.

Desai, N.↗

NASA NTRS1991

Measurement selection for parametric IC fault diagnosis

Experimental results obtained with the use of measurement reduction for statistical IC fault diagnosis are described. The reduction method used involves data pre-processing in a fashion consistent with a specific definition of parametric faults. The effects of this preprocessing are examined.

Wu, A.↗

NASA NTRS1990

Neural net diagnostics for VLSI test

This paper discusses the application of neural network pattern analysis algorithms to the IC fault diagnosis problem. A fault diagnostic is a decision rule combining what is known about an ideal circuit test response with information about how it is distorted by fabrication variations and measurement noise. The rule is used to detect fault existence in fabricated circuits using real test equipment. Traditional statistical techniques may be used to achieve this goal, but they can employ unrealistic a priori assumptions about measurement data. Our approach to this problem employs an adaptive pattern analysis technique based on feedforward neural networks. During training, a feedforward network automatically captures unknown sample distributions. This is important because distributions arising from the nonlinear effects of process variation can be more complex than is typically assumed. A feedforward network is also able to extract measurement features which contribute significantly to making a correct decision. Traditional feature extraction techniques employ matrix manipulations which can be particularly costly for large measurement vectors. In this paper we discuss a software system which we are developing that uses this approach. We also provide a simple example illustrating the use of the technique for fault detection in an operational amplifier.

Lin, T.↗

NASA NTRS1990

Auto-programmable impulse neural circuits

Impulse neural networks use pulse trains to communicate neuron activation levels. Impulse neural circuits emulate natural neurons at a more detailed level than that typically employed by contemporary neural network implementation methods. An impulse neural circuit which realizes short term memory dynamics is presented. The operation of that circuit is then characterized in terms of pulse frequency modulated signals. Both fixed and programmable synapse circuits for realizing long term memory are also described. The implementation of a simple and useful unsupervised learning law is then presented. The implementation of a differential Hebbian learning rule for a specific mean-frequency signal interpretation is shown to have a straightforward implementation using digital combinational logic with a variation of a previously developed programmable synapse circuit. This circuit is expected to be exploited for simple and straightforward implementation of future auto-adaptive neural circuits.

Watula, D.↗