Recognition reliable

Lately, polymeric composite materials have found a wide recognition thanks to their unique qualities /1,2/. But use of the materials for construction, is limited, because lack of reliable diagnostic facilities. The non-destructive control method (NC), based on the acoustic emission phenomenon (AE), might offer a prospective solution to the situation. 

Tests were done on real data containing approx. 32(XX) nontrivial images. Of these approx. 25% were classified by the rule-based system and another 25% by the CBR system. The reliability was high - of 330 defects present in the data only two were classified as non-defects. We are currently working on further improving the recognition ratio and increasing the speed of the system. 

The recognition ratios achieved by CBR systems developed as part of this project could not be bettered by either neural-network classifiers or rule-based expert system classifiers. In addition, CBR systems should be mote reliable than simple classifiers as they are programmed to recognise unknown data. The knowledge acquisition necessary to build CBR systems is less expensive than for expert systems, because it is simpler to describe the knowledge how to distinguish between certain types of data than to describe the whole data contents. 

The method was applied for determination of the quality of the detection media on test pieces following the type testing of the European standard [4] in order to check the validity of the method. The other application was the determination of the visibility in dependance of the variations of the inspection parameters (application of the detection medium, magnetization, inclination, viewing conditions) in a range which may appear in the practical inspections. The results leads to conclusions on the visibility level which is a measure of the probability of recognition for the indication that means of the reliability of the method. 

Problems involving routine calculations are solved much faster and more reliably by computers than by humans. Nevertheless, there are tasks in which humans perform better, such as those in which the procedure is not strictly determined and problems which are not strictly algorithmic. One of these tasks is the recognition of patterns such as feces. For several decades people have been trying to develop methods which enable computers to achieve better results in these fields. One approach, artificial neural networks, which model the functionality of the brain, is explained in this section. 

DT Jones. Genthreader An efficient and reliable protein fold recognition method for genomic sequences. J Mol Biol 287 797-815, 1999. 

Check the toxicity of process materials, identify short and long term effects for various modes of entry into the body and different exposure tolerance Identify the relationship between odour and toxicity for all process materials Determine the means for industrial hygiene recognition, evaluation and control Determine relevant physical properties of process materials under all process conditions, check source and reliability of data... 

The reliability and fairly low demanding computational cost of DFT methods opens the way for in silico investigations of the QM generation catalyzed by DNA itself, starting from metastable precursors, which are capable of oligonucleotide recognition. 

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