• Journal of the Korean Institute of Telematics and Electronics
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• v.20 no.1
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• pp.22-26
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• 1983

P+N and P+NN+ solar cells with the area of 3.36 $\textrm{cm}^2$ were fabricated by thermal diffusion. Under the light intensity of 100 mW/$\textrm{cm}^2$, total area(active area) conversion efficiency was 13.4%(14.7%) for P+N cell fabricated by 15 min boron predeposition at 94$0^{\circ}C$ and 20 min annealing at 80$0^{\circ}C$, and 14.3%(15.6%) for P+NN+ cell processed by 15 min boron predeposition at 94$0^{\circ}C$ and 50 min annealing at 80$0^{\circ}C$ after 20 min back phosphorus diffusion at 1,05$0^{\circ}C$. The minority carrier lifetime in bulk of P+NN+ cells was increased about 2~3 times comparing with P+N cells because of guttering and BSF effect due to back phosphorus doping. The methods used for efficiency improvement were AR coating, Ag electroplating, back doping and fine grid pattern as well as the control of front doping profile.

• Journal of radiological science and technology
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• v.45 no.2
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• pp.111-116
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• 2022

In this study, the applicability of machine learning for the development of a simulator for general X-ray examination education is evaluated. To this end, k-nearest neighbor(kNN), support vector machine(SVM) and neural network(NN) classification models are analyzed to present the most suitable model by analyzing the results. Image data was obtained by taking 100 photos each corresponding to Posterior anterior(PA), Posterior anterior oblique(Obl), Lateral(Lat), Fan lateral(Fan lat). 70% of the acquired 400 image data were used as training sets for learning machine learning models and 30% were used as test sets for evaluation. and prediction model was constructed for right-handed PA, Obl, Lat, Fan lat image classification. Based on the data set, after constructing the classification model using the kNN, SVM, and NN models, each model was compared through an error matrix. As a result of the evaluation, the accuracy of kNN was 0.967 area under curve(AUC) was 0.993, and the accuracy of SVM was 0.992 AUC was 1.000. The accuracy of NN was 0.992 and AUC was 0.999, which was slightly lower in kNN, but all three models recorded high accuracy and AUC. In this study, right-handed PA, Obl, Lat, Fan lat images were classified and predicted using the machine learning classification models, kNN, SVM, and NN models. The prediction showed that SVM and NN were the same at 0.992, and AUC was similar at 1.000 and 0.999, indicating that both models showed high predictive power and were applicable to educational simulators.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.6
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• pp.1333-1342
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• 2018

Until now, Electroencephalography(: EEG) has been the most important and convenient method for the diagnosis and treatment of epilepsy. However, it is difficult to identify the wave characteristics of an epileptic EEG signals because it is very weak, non-stationary and has strong background noise. In this paper, we analyse the effect of dimensionality reduction methods on Epileptic EEG feature selection and classification. Three dimensionality reduction methods: Pincipal Component Analysis(: PCA), Kernel Principal Component Analysis(: KPCA) and Linear Discriminant Analysis(: LDA） were investigated. The performance of each method was evaluated by using Support Vector Machine SVM, Logistic Regression(: LR), K-Nearestneighbor(: K-NN), Decision Tree(: DR) and Random Forest(: RF). From the experimental result, PCA recorded 75% of highest accuracy in SVM, LR and K-NN. KPCA recorded 85% of best performance in SVM and K-KNN while LDA achieved 100% accuracy in K-NN. Thus, LDA dimensionality reduction is found to provide the best classification result for epileptic EEG signal.

• Journal of Physiology & Pathology in Korean Medicine
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• v.25 no.4
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• pp.614-619
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• 2011

Nelumbo nucifera(NN) is a oriental medicinal herb which has been used traditionally for the treatment of antidiarrhea, sedative action and various brain diseases including convulsion and epilepsy. In order to examine the mechanism of anticonvulsive effect, we treated the methanol extract of NN(100, 200 mg/kg, P.0) to the sleeping time and pentylenetetrazole(PTZ)-induced convulsive mice. The methanol extract of NN prolonged sleep time by pentobarbital. Methanol extracts of NN were not effected the concentration of GABA and GABA-T activity in the brain of PTZ-induced mice. Methanol extracts of NN significantly inhibited the convulsion state as well as the level of lipid peroxidation in the brain. The butanol and dichloromethane fraction of methanol extracts among the others effectively inhibited in vitro lipid peroxidation dose dependently($5.0{\times}10^{-6}\sim2.0{\times}10^{-5}\;g/ml$). These results suggest that the anticonvulsive effect of NN is possibly due to the antioxidative effects of the free radical formation at brain for the PTZ-induced convulsion if it were by due to generating system.

• Korean Journal of Crystallography
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• v.11 no.1
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• pp.46-51
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• 2000

The molecular structures of 2-SC₄H₃CH=NN(H)C/sub 6/H/sub 5/(C/sub 11/H/sub 10/N₂S) and (GaMe₂)₂(2-SC₄H₃CH=NNC/sub 6/H/sub 5/)₂(C/sub 26/H/sub 30/Ga₂N₄S₂) have been determined by X-ray diffraction. Crystallographic data for 2-SC₄H₃CH=NN(H)C/sub 6/H/sub 5/:orthorhombic space group P2₁2₁2₁, a=6.108(1)Å, b=7.593(1)Å, c=22.356(2)Å, V=1037.1(3)ų, Z=4, R=0.0613. Crystallographic data for (GaMe₂)₂(2-SC₄H₃CH=NNC/sub 6/H/sub 5/)₂:monoclinic space group P2₁/n, a=15.996(2) Å, c=9.879(3)Å, β=100.07.(2)°, V=2764.599)ų, Z=4, R=0.0503.

• Journal of Life Science
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• v.20 no.8
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• pp.1241-1248
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• 2010

The solvent extracts of Nelumbo nucifera G. were investigated for antioxidant activities, whitening and anti-wrinkle effects to apply as a functional ingredient in cosmetic products. For their industrial application, the cosmetic products were also prepared with advanced formulation techniques such as W/O/W multiple emulsion. Total phenolic and flavonoids contents increased in Nelumbo nucifera G.-Leaf (NN-L). The electron donating ability of Nelumbo nucifera G.-Flower (NN-F) or Nelumbo nucifera G.-Leaf (NN-L) extracts were above 85% at a concentration of 500 ppm. The superoxide dismutase (SOD)-like activity of Nelumbo nucifera G. (NN-L) extracts was about 60% at a concentration of 1,000 ppm. The xanthine oxidase inhibitory effect of NN-L extract was higher than that of NN-F and NN-S extracts. The tyrosinase inhibitory effect, which is related to skin-whitening, was 36% in NN-F at 1,000 ppm. For anti-wrinkle effect, the elastase inhibition activity of NN-L was about 30% at 1,000 ppm. The results of stability test showed that W/O/W multiple emulsion (ME) containing Nelumbo nucifera G. extracts. The electron donating ability of the ME containing NN-F and NN-L were about 60% at a concentration of 100 ppm. The superoxide dismutase (SOD)-like activity of the ME containing NN-L was 30% at 1,000 ppm. The tyrosinase inhibitory effect, which is related to skin-whitening, was 34% in the ME containing NN-F at 1,000 ppm. In anti-wrinkle effect, the elastase inhibition activity of the ME containing NN-L was about 55% at 1,000 ppm.

• Composites Research
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• v.33 no.3
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• pp.108-114
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• 2020

Piecewise Integrated Composite (PIC) beam is composed of different stacking against loading type depending upon location. The aim of current study is to assign robust stacking sequences against external loading to every corresponding part of the PIC beam based on the value of stress triaxiality at generated reference points using the k-NN (k-Nearest Neighbor) classification, which is one of representative machine learning techniques, in order to excellent superior bending characteristics. The stress triaxiality at reference points is obtained by three-point bending analysis of the Al beam with training data categorizing the type of external loading, i.e., tension, compression or shear. Loading types of each plane of the beam were classified by independent plane scheme as well as total beam scheme. Also, loading fidelities were calibrated for each case with the variation of hyper-parameters. Most effective stacking sequences were mapped into the PIC beam based on the k-NN classification model with the highest loading fidelity. FE analysis result shows the PIC beam has superior external loading resistance and energy absorption compared to conventional beam.

• Reproductive and Developmental Biology
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• v.28 no.1
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• pp.37-43
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• 2004

This study was carried out to investigate PSS (Porcine Stress Syndrome) with the PSE (Pale, Soft, Exudative) in 319 different pigs(Yorkshire 150; Landrace 89 and Duroc 80). The PCR-RFLP method was adapted to detect the ryanodine receptor (RYR 1) gene mutation and to estimate the genotype frequency of the RYR1 gene in breeding pig population. The DNA samples were collected from hair follicles of pigs of Yorkshire, Landrace and Duroc. After DNA amplification by PCR, the PCR products were digested by restriction enzyme, Cfo I. Primary PCR products of ryanodine receptor gene were length of 659 bp in hair follicle and their second PCR products were length of 522 bp in hair follicle. The exon region (522 bp) including point mutation ($C \arrow T; Arg \arrow Cys$) in the porcine ryanodine receptor gene, which is a causal mutation for PSS, was digested with Cfo I restriction enzyme. The RYR1 gene was classifed into three genotypes by agarose gel electrophoresis. The normal homozygous (NN) individuals showed two DNA fragments consisted of 439 and 83 bp. The mutant homozygous (nn) individuals showed only one DNA fragment 522 bp. In addition, all three fragments (522, 439 and 83 bp) were showed in heterozygous (Nn) carrier animals. The normal homozygous (NN), heterozygous (Nn) and mutant homozygous (nn) were 98.00, 2.00 and 0.00% in Yorkshire pigs, 87.64, 11.24 and 1.12% in Landrace, 100.00, 0.00 and 0.00% in Duroc, respectively. The gene frequencies of N and n were 0.990 and 0.010 in Yorkshire pigs, 0.933 and 0.067 in Landrace, 1.000 and 0.000 in Duroc, respectively.

• Investigative Magnetic Resonance Imaging
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• v.25 no.1
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• pp.10-22
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• 2021

Purpose: To overcome the difficulty in building a large data set with a high-quality in medical imaging, a concept of 'blended-transfer learning' (BTL) using a combination of both source data and target data is proposed for the target task. Materials and Methods: Source and target tasks were defined as training of the source and target networks to reconstruct cardiac CINE images from undersampled data, respectively. In transfer learning (TL), the entire neural network (NN) or some parts of the NN after conducting a source task using an open data set was adopted in the target network as the initial network to improve the learning speed and the performance of the target task. Using BTL, an NN effectively learned the target data while preserving knowledge from the source data to the maximum extent possible. The ratio of the source data to the target data was reduced stepwise from 1 in the initial stage to 0 in the final stage. Results: NN that performed BTL showed an improved performance compared to those that performed TL or standalone learning (SL). Generalization of NN was also better achieved. The learning curve was evaluated using normalized mean square error (NMSE) of reconstructed images for both target data and source data. BTL reduced the learning time by 1.25 to 100 times and provided better image quality. Its NMSE was 3% to 8% lower than with SL. Conclusion: The NN that performed the proposed BTL showed the best performance in terms of learning speed and learning curve. It also showed the highest reconstructed-image quality with the lowest NMSE for the test data set. Thus, BTL is an effective way of learning for NNs in the medical-imaging domain where both quality and quantity of data are always limited.

• Toxicological Research
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• v.3 no.1
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• pp.27-32
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• 1987

Ethyl acetate extracts of 6 commercial amaranths produced in 1985 and 1986 were analyzed with a gas chromatograph. The ${\alpha}$-naphthylamine ranging from 142 ppb to 4216 ppb was detected, but the ${\beta}$ naphthylamine was not detected. The mutagenicity of the ethyl acetate extract was tested using Salmonella typhimurium TA100 in the presence of the S-9 fraction. Significant mutagenic activity was seen in samples containing high levels of ${\alpha}$-naphthylamine. It is suggested that the potential hazard of amaranth to the general public should be reconsidered from the point that the impurities contained in amaranth preparations are the main sources of mutagenicity or carcinogenicity.