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Intelligent Feature Selection for Machine Learning using the Dynamic Wavelet Fingerprint


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Table of Contents

Background and history.- Intelligent structural health monitoring with ultrasonic lamb waves.- Automatic detection of flaws in recorded music.- Pocket depth determination with an ultrasonographic periodontal probe.- Spectral intermezzo: Spirit security systems.- Lamb wave tomographic rays in pipes.- Classification of RFID tags with wavelet fingerprinting.- Pattern classification for interpreting sensor data from a walking-speed robot.- Cranks and charlatans and deepfakes.

About the Author

Professor Mark K. Hinders holds BS, MS and PhD degrees in Aerospace and Mechanical Engineering from Boston University, and is currently a Professor of Applied Science at the College of William & Mary in Virginia. Before coming to Williamsburg in 1993, Professor Hinders served as a Senior Scientist at Massachusetts Technological Laboratory, Inc., and as a Research Assistant Professor at Boston University. Before that he was an Electromagnetics Research Engineer at USAF Rome Laboratory located at Hanscom AFB, MA. Professor Hinders is currently conducting research in wave propagation and scattering phenomena as applied to medical imaging, intelligent robotics, security screening, remote sensing and nondestructive evaluation. He and his students are studying the interactions of acoustic, ultrasonic, elastic, thermal, electromagnetic and optical waves with various materials, tissues and structures. He is a founding member of the Applied Science Department and former Graduate Director and Department Chair.

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