The Alford method is a modern tool for estimating anisotropy from cross-dipole acoustic logging records. The azimuthal angle of the acoustic anisotropy direction is estimated by the minimum cross energy of the converted records. The interval times (speeds) of the fast and slow bending wave pfast, pslow in the forward and reverse directions of anisotropy are estimated using the corresponding transfor-mations. Practical implementation of the method is considered, using the analytical solution of the min-imization problem.
The problem regarding the use of machine learning in cybersecurity is difficult to solve because the advances in the field offer many opportunities that it is challenging to find exceptional and beneficial use cases for implementation and decision making. Moreover, such technologies can be used by intruders to attack computer systems. The goal of this paper to explore machine learning usage in cybersecurity and cyberattack and provide a model of machine learning-powered attack.
Semblance or slowness time coherence is a measure of the coherence of energy distribution be-tween recorded signals at antenna array receivers of acoustic wave logging probe in the coordinates "the reduced time of the wave path from the middle of the antenna array” — “interval time". Several semblance filtering methods are proposed to allow for elimination of the effect of aliasing and to separate the wave packet components.