ADAPT pattern recognition analysis

ADAPT Pattern recognition Cluster analysis Uses QSAR descriptors of molecular structure Limited to congeneric series of chemicals... 

Pattern Recognition Analysis. A set of interactive pattern recognition programs have been interfaced to the ADAPT system. 

ADAPT Automated data analysis and pattern recognition toolkit AMI Austin model 1... 

Image analysis is an important aspect of many areas of science and engineering, and imaging will play an important role in characterizing self-assembled structures as well as in on-line process control. Development of effective noise identification and suppression, contrast enhancements, visualization, pattern recognition, and correlation algorithms should be co-opted where possible and adapted to the analysis of self-assembled structures. 

A biometric variant of EAP (BEAP developed by Telefonica I D, may serve as an example) can be enhanced with the Iris Module. This enables to adapt Iris Recognition Device with Radius client and consequently to setup a remote access scenario based on iris pattern analysis. The Iris Module has the following proposed functionality ... 

Tel. 814-865-3739, fax 814-865-3314, e-mail pcj psuvm.psu.edu Adapted Data Analysis using Pattern recognition Toolkit. Generates molecular descriptors and applies metric methods to find structure-property relationships. VAX and Sun. 

One of the software systems available for pattern recognition studies is ADAPT (automated data analysis using pattern recognition techniques). The structure of each member of the data set is represented by molecular descriptors. These numerical indices, which encode information about the molecule, fall into four classes topological, geometrical, electronic and physicochemical. The data are analysed using pattern recognition techniques to develop a classifier which can discriminate between the classes of data. 

ADAPT has a variety of pattern recognition and statistical methods available for use. The object of the analysis phase is to find discriminants that separate subsets of the data into the proper categories. That is, one is trying to find mathematical models that will classify compounds as belonging to the active or inactive subset based on the molecular structure descriptors available. This phase of SAR studies Is guided by the user in a highly interactive manner in order to search through the available descriptors for the best set. 

If gas selectivity cannot be achieved by improving the sensor setup itself, it is possible to use several nonselective sensors and predict the concentration by model based, such as multilinear regression (MLR), principle component analysis (PCA), principle component regression (PCR), partial least squares (PLS), and multivariate adaptive regression splines (MARS), or data-based algorithms, such as cluster analysis (CA) and artificial neural networks (ANN) (for details see Reference 10) (Figure 22.5). For common applications of pattern recognition and multi component analysis of gas mixtures, arrays of sensors are usually chosen... 

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