• Toxicological Research
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• v.32 no.4
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• pp.337-343
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• 2016

We determined the toxicity of mixtures of ethyl acetate (EA), isopropyl alcohol (IPA), methyl ethyl ketone (MEK), toluene (TOL) and xylene (XYL) with half-maximal effective concentration ($EC_{50}$) values obtained using human hepatocytes cells. According to these data, quantitative property-activity relationships (QPAR) models were successfully proposed to predict the toxicity of mixtures by multiple linear regressions (MLR). The leave-one-out cross validation method was used to find the best subsets of descriptors in the learning methods. Significant differences in physico-chemical properties such as boiling point (BP), specific gravity (SG), Reid vapor pressure (rVP) and flash point (FP) were observed between the single substances and the mixtures. The $EC_{50}$ of the mixture of EA and IPA was significantly lower than that of contained TOL and XYL. The mixture toxicity was related to the mixing ratio of MEK, TOL and XYL (MLR equation $EC_{50}=3.3081-2.5018{\times}TOL-3.2595{\times}XYL-12.6596{\times}MEK{\times}XYL$), as well as to BP, SG, VP and FP (MLR equation $EC_{50}=1.3424+6.2250{\times}FP-7.1198{\times}SG{\times}FP-0.03013{\times}rVP{\times}FP$). These results suggest that QPAR-based models could accurately predict the toxicity of polar and nonpolar mixtures used in rotogravure printing industries.

• Food Science of Animal Resources
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• v.31 no.4
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• pp.506-512
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• 2011

This study was conducted to validate the theoretical feasibility of a technique to identify biomarkers in Korean native black pig (KNP) and a commercial Landrace breed. Using two-dimensional electrophoresis, we found six proteins (NADH dehydrogenase Fe-S protein 1, an unnamed protein product, similar to T-complex protein 1, annexin V = CaBP33 isoform, fatty acid-binding protein, and catechol O-methyltransferase), which appeared in KNP alone. We raised polyclonal antibodies (used as the primary antibody) for Western blotting to confirm the characteristics of the six KNP proteins. As a result, catechol O-methyltransferase, annexin V = CaBP33 isoform, and the unnamed protein product presented thicker bands in KNP than those in Landrace. Moreover, catechol O-methyltransferase was shown to be more feasible as a biomarker for KNP. However, cross-reactivity was observed with the polyclonal antibodies for KNP and the other three proteins (NADH dehydrogenase, a protein similar to T-complex protein 1, and fatty acid-binding protein). This study only showed limited results from a limited number of animals; however, our research suggests possibilities for future studies.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.139-146
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• 2014

This paper proposes an efficient method for automatically distinguishing various facial expressions. To recognize the emotions from facial expressions, the facial images are obtained by digital cameras, and a number of feature points were extracted. The extracted feature points are then transformed to 49-dimensional feature vectors which are robust to scale and translational variations, and the facial emotions are recognized by statistical pattern classifiers such Naive Bayes, MLP (multi-layer perceptron), and SVM (support vector machine). Based on the experimental results with 5-fold cross validation, SVM was the best among the classifiers, whose performance was obtained by 50.8% for 6 emotion classification, and 78.0% for 3 emotions.

• Bulletin of the Korean Chemical Society
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• v.35 no.12
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• pp.3637-3641
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• 2014

In this study, we analyzed the toxicity of mixtures of dimethylformamide (DMF) and methyl ethyl ketone (MEK) or DMF and toluene (TOL) and predicted their toxicity using quantitative structure-activity relationships (QSAR). A QSAR model for single substances and mixtures was analyzed using multiple linear regression (MLR) by taking into account the statistical parameters between the observed and predicted $EC_{50}$. After preprocessing, the best subsets of descriptors in the learning methods were determined using a 5-fold cross-validation method. Significant differences in physico-chemical properties such as boiling point (BP), specific gravity (SG), Reid vapor pressure (rVP), flash point (FP), low explosion limit (LEL), and octanol/water partition coefficient (Pow) were observed between the single substances and the mixtures. The $EC_{50}$ of the mixture of DMF and TOL was significantly lower than that of DMF. The mixture toxicity was directly related to the mixing ratio of TOL and MEK (MLR $EC_{50}$ equation = $1.76997-1.12249{\times}TOL+1.21045{\times}MEK$), as well as to SG, VP, and LEL (MLR equation $EC_{50}=15.44388-19.84549{\times}SG+0.05091{\times}VP+1.85846{\times}LEL$). These results show that QSAR-based models can be used to quantitatively predict the toxicity of mixtures used in manufacturing industries.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.1
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• pp.64-72
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• 2016

In this paper, we utilize a Gaussian process to predict the power consumption in the air-conditioning system. As the power consumption in the air-conditioning system takes a form of a time-series and the prediction of the power consumption becomes very important from the perspective of the efficient energy management, it is worth to investigate the time-series model for the prediction of the power consumption. To this end, we apply the Gaussian process to predict the power consumption, in which the Gaussian process provides a prior probability to every possible function and higher probabilities are given to functions that are more likely consistent with the empirical data. We also discuss how to estimate the hyper-parameters, which are parameters in the covariance function of the Gaussian process model. We estimated the hyper-parameters with two different methods (marginal likelihood and leave-one-out cross validation) and obtained a model that pertinently describes the data and the results are more or less independent of the estimation method of hyper-parameters. We validated the prediction results by the error analysis of the mean relative error and the mean absolute error. The mean relative error analysis showed that about 3.4% of the predicted value came from the error, and the mean absolute error analysis confirmed that the error in within the standard deviation of the predicted value. We also adopt the non-parametric Wilcoxon's sign-rank test to assess the fitness of the proposed model and found that the null hypothesis of uniformity was accepted under the significance level of 5%. These results can be applied to a more elaborate control of the power consumption in the air-conditioning system.

• Tunnel and Underground Space
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• v.16 no.2 s.61
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• pp.135-145
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• 2006

In this study, conditional simulation was conducted to estimate rock mass rating(RMR) in unsurveyed regions. Sequential Gaussian simulation(SGS) and sequential indicator simulation(SIS) were applied for estimating RMR from the bore hole logging data. The uncertainty of SGS and SIS was verified by sample cross validation. A subset composed of 5 bore hole logging data among the original 30 bore hole logging data was set aside as test data. The remainder was training data. The quality of SGS and SIS estimation on the testing data reflects how well it would perform in an unsupervised setting. SGS and SIS were useful stochastic methods to estimate the spatial distribution of rock mass classes correctly and assess the uncertainty of estimation quantitatively. The result of conditional simulation can offer useful information of rock mass classes such as RMR in unsurveyed regions.

• Journal of The Korean Astronomical Society
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• v.52 no.6
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• pp.217-225
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• 2019

We apply a modified Convolutional Neural Network (CNN) model in conjunction with transfer learning to predict whether an active region (AR) would produce a ≥C-class or ≥M-class flare within the next 24 hours. We collect line-of-sight magnetogram samples of ARs provided by the SHARP from May 2010 to September 2018, which is a new data product from the HMI onboard the SDO. Based on these AR samples, we adopt the approach of shuffle-and-split cross-validation (CV) to build a database that includes 10 separate data sets. Each of the 10 data sets is segregated by NOAA AR number into a training and a testing data set. After training, validating, and testing our model, we compare the results with previous studies using predictive performance metrics, with a focus on the true skill statistic (TSS). The main results from this study are summarized as follows. First, to the best of our knowledge, this is the first time that the CNN model with transfer learning is used in solar physics to make binary class predictions for both ≥C-class and ≥M-class flares, without manually engineered features extracted from the observational data. Second, our model achieves relatively high scores of TSS = 0.640±0.075 and TSS = 0.526±0.052 for ≥M-class prediction and ≥C-class prediction, respectively, which is comparable to that of previous models. Third, our model also obtains quite good scores in five other metrics for both ≥C-class and ≥M-class flare prediction. Our results demonstrate that our modified CNN model with transfer learning is an effective method for flare forecasting with reasonable prediction performance.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.24 no.1
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• pp.1-8
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• 2017

Purpose: The purpose of this study was to evaluate the psychometric properties of the Hypertension Self-Care Behavior Scale for older adults with hypertension in Korea. Methods: A cross-sectional descriptive study was used with 196 participants. Translation and back-translation were performed by bilingual nursing professionals and a nutritionist. Reliability and validity such as content validity, construct validity, and concurrent validity were conducted. To evaluate the concurrent validity, the correlation coefficients between the Korean version of Hypertension Self-Care Behavior and concurrent scales (hypertension adherence scale and self-efficacy scale) were calculated. Results: The total 20 items for the Korean version of the Hypertension Self-Care (HBP-SC) Behavior Scale were retained during item-analysis. In explanatory factor analysis, a two-factor solution was proposed and the two factors named, 'HBP-SC Diet behavior' and 'HBP-SC Health behavior (except diet)'. The two factors accounted for 48.9% of the variances. The Korean version of the Hypertension Self-Care Behavior Scale correlated with concurrent variables such as hypertension adherence and self-efficacy. For reliability of the Korean version of the Hypertension Self-Care Behavior, Cronbach's ${\alpha}=.92$. Conclusion: Findings show that the Korean version of the Hypertension Self-Care Behavior is reliable and valid for measuring self-care behavior of older adults with hypertension.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.7
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• pp.71-78
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• 2017

There are several algorithms to classify emotion, such as Support-vector-machine (SVM), Bayesian decision rule, etc. However, many researchers have insisted that these methods have minor problems. Therefore, in this paper, we propose a novel method for emotion recognition based on Electroencephalogram (EEG) signal using the Gradient method which was proposed by Han. We also utilize a database for emotion analysis using physiological signals (DEAP) to obtain objective data. And we acquire four channel brainwaves, including Fz (${\alpha}$), Fp2 (${\beta}$), F3 (${\alpha}$), F4 (${\alpha}$) which are selected in previous study. We use 4 features which are power spectral density (PSD) of the above channels. According to performance evaluation (4-fold cross validation), we could get 85% accuracy in valence axis and 87.5% in arousal. It is 5-7% higher than existing method's.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.9
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• pp.800-807
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• 2016

In this paper, we study the characteristics of dual band microstip antenna with modified inset feeder and a single slot. The modified inset feeder consists of the vertical inset feeder placed in x direction and the horizontal one in y direction for shortening the total length of inset feeder. The optimun feeding position for good impedance matching at two resonant frequencies can be easily found by adjusting the horizontal inset distance. And Various frequency ratios can be simply obtained by the parameters of slot. The measurements for fabricated antenna prototypes are carried out for validation. The measured results show a tunable frequency ratio from 1.25 to 1.88 with the variation of slot parameters. It is worthwhile to point out that the radiation patterns are similar at both bands. and below -20.0 dB of cross polarization level at the E plane.