Abstract: A method and system are provided for model-based analysis of samples of interest and management of sample classification. Predetermined modeled data is provided including data indicative of K models for respective K measurement schemes based on a predetermined function having a spectral line shape, data indicative of M characteristic vectors of M predetermined group to which different samples relate, and data indicative of a common vector of weights for the M groups. A data processor utilizes the data and operates to apply model-based processing to measured spectral data of a sample of interest using the predetermined modeled data, and generate classification data indicative of relation of the specific sample of interest to one of the M predetermined groups.

Abstract: A computer implemented method of monitoring data output by a server over a network is provided, in which the server is arranged to store data. The method includes analysing, by a computing device, outgoing data from the server sent over the network; filtering, by the computing device, a portion of the outgoing data to determine a remaining portion of the outgoing data; analysing, by the computing device, the remaining portion of the outgoing data to determine the amount of information in the remaining portion of the outgoing data; and performing, by the computing device, a predetermined action if the amount of information in the remaining portion of the outgoing data is over a threshold.