Abstract: The present disclosure relates to a method for carrying out dose delivery quality assurance for high-precision radiation treatment, in which parameters affecting a pass rate of dose delivery quality assurance can be derived through regression analysis, which is a known statistical analysis method, and a pass rate prediction model capable of predicting each parameter and the pass rate of dose delivery quality assurance can be derived, and accordingly, it can be predicted in advance whether dose delivery quality assurance will be passed according to the parameters through the above prediction model, without repeatedly carrying out dose delivery quality assurance according to a patient's treatment plan, and as a result, the efficiency of dose delivery quality assurance can be enhanced, and the time or capacity required for such quality assurance is reduced, such that radiation treatment for an actual patient can be quickly and precisely carried out.

Abstract: A method of transforming minutiae using the Taylor series for interoperable fingerprint recognition between disparate fingerprint sensors, which parses the fields of a Standard Interchange Format (SIF) template having the level of minutiae proposed in SC37, extract information fields corresponding to resolution, image size, and minutiae, corrects the locations of minutiae constituting the template, and standardizes the minutiae, thus increasing a recognition rate for fingerprint matching, and which applies transformation parameters using the Taylor series to a golden template that is generated using a plurality of samples for the same fingerprint which are input from a plurality of disparate fingerprint recognition sensors, thus improving recognition performance and reliability of matching between the disparate sensors that use the transformation of minutiae merely by correcting the locations of the minutiae, without correcting resolution or distortion characteristics.