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Tree Grammar를 이용한 한글 인식 Algorithm과 Simulation에 관한 연구
李敎鎬,鄭燦義 건국대학교 1985 論文集 Vol.20 No.1
Syntactic pattern recognition is concerned with the application of formal language and automata theory to the modeling and description of structural relationship in pattern classes. In this paper, the recognition of Korean characters is tried with the tree grammar method in various approach of syntactic pattern recognition. A microcomputer, a digisector, and a C.C. TV camera were used as instruments for simulation. The most significant factor that improved recognition-success-ratio was illumination.
Cheong, Jae Chul,Suh, Sung Ill,Jun Ko, Beom,Kim, Jin Young,In, Moon Kyo,Cheong, Won Jo WILEY-VCH Verlag 2010 Journal of separation science Vol.33 No.12
<P>A simple and rapid GC-MS method has been developed for the screening and quantification of many illicit drugs and their metabolites in human urine by using automatic SPE and trimethylsilylation. Sixty illicit drugs, including parent drugs and their metabolites that are possibly abused in Korea, can be monitored by this method. Among them, 24 popularly abused illicit drugs were selected for quantification. Very delicate optimizations were carried out in SPE, trimethylsilylation derivatization, and GC/MS to enable such remarkable achievements. Trimethylsilylated analytes were well separated within 21 min by GC-MS. In the validation results, the LOD of all the analytes were in the range of 2–75 ng/mL. The LOQ of the quantified analytes were in the range of 5–98 ng/mL. The linearity (r<SUP>2</SUP>) of the quantified analytes ranged 0.990–1.000 in each concentration range between 10 and 1000 ng/mL. The mean recoveries ranged from 62 to 126% at three different concentrations of each analyte. The inter-day and inter-person accuracies were within −13.3∼14.9%, and −10.1∼13.0%, respectively, and the inter-day and inter-person precisions were less than 12.9%. The method was reliable and efficient for the screening and quantification of abused illicit drugs in routine urine analysis.</P>