Abstract: A signal processing technique which correlates eddy current inspection data from a tube having a critical tubing defect with a range of predicted burst pressures for the tube is provided. The method can directly correlate the raw eddy current inspection data representing the critical tubing defect with the range of burst pressures using a regression technique, preferably an artificial neural network. Alternatively, the technique deconvolves the raw eddy current inspection data into a set of undistorted signals, each of which represents a separate defect of the tube. The undistorted defect signal which represents the critical tubing defect is related to a range of burst pressures utilizing a regression technique.

Abstract: Method for displaying an available time according to battery capacity in a mobile station, including the steps of (1) forming relations between current consumption(mA) of the mobile station both in a standby mode and a call mode and a strength of a received signal into tables, and storing the tables in a memory respectively, (2) measuring a battery voltage for calculating a remained amount of battery capacity(mAh), (3) measuring a strength of a received signal, and reading current consumption(mA) both in the standby mode and in the call mode corresponding to the measured strength of the received signal, (4) dividing the remained amount of the battery capacity(Mah) by respective current consumption to calculate an available standby time and an available call time, and (5) displaying the available standby time and/or the available call time, whereby enhancing an efficiency of use of the mobile station because available time of use of the mobile station can be known with easy, and a time when the battery should