Ultrasonic Flaw Detection Using Neural Network Models and Statistical Analysis: Simulation Studies

Flaw detection problems in ultrasonic NDE can be considered as two-class classification problems, i.e., determining whether a flaw is present or not present. To be practical, a flaw classification method must be able to handle the uncertainties associated with interference from grain noise which leads to poor signal-to-noise ratios (SNR). In this work, the use of neural network models and statistical correlation is demonstrated for one such detection/classification problem. In particular, based on simulation studies, we wish to establish practical strategies in detecting weak volumetric flaw signals corrupted by high grain noise. An example of this type that is of recent interest is the detection of “hard-alpha” inclusions in aircraft titanium components [1]. Both the feasibility and reliability of using these classifiers are assessed. This effort was carried out in parallel with another study [2] where more traditional signal processing approaches were taken

Mathematical Analysis of Copy Number Variation in a DNA Sample Using Digital PCR on a Nanofluidic Device

Copy Number Variations (CNVs) of regions of the human genome have been associated with multiple diseases. We present an algorithm which is mathematically sound and computationally efficient to accurately analyze CNV in a DNA sample utilizing a nanofluidic device, known as the digital array. This numerical algorithm is utilized to compute copy number variation and the associated statistical confidence interval and is based on results from probability theory and statistics. We also provide formulas which can be used as close approximations

Clinical Trials, Hong Kong vs. China

In pulse-echo ultrasonic nondestructive testing, a transducer sends an ultrasonic wave into the test sample and receives the reflected wave from discontinuities in the sample. The received energy is converted into an electrical signal by the transducer, resulting in a one-dimensional time domain signal called an A-scan. An alternate method of representing an ultrasonic NDT signal is the C-scan image, which consists of peak values of the A-scan obtained at each position of a raster scan