• Korean Journal of Animal Reproduction
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• v.23 no.1
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• pp.85-92
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• 1999

This study was designed to determine effect of cryoprotectant kinds and cell stages on OPP vitrification method in mouse embryos. The freezing speed, cryoprotectants and cell stage could affect of embryo viability following various vitrification methods. The vitrification solution used were consisting of 40% (v/v) ethylene glycol, 18% (w/v) Ficoll, 0.3 M sucrose solution in holding medium (D-PBS supplemented with 5% FCS: HM) (EFS) or 16.5% ethylene glycol , 16.5% dimethyl sulfoxide, 0.5 M sucrose in HM (EDS). The embryos were collected from oviduct at 18 h after hCG injection and then washed and cultured in mHTF medium until use. In experiment 1, the blastocysts were vitrified by OPP straw to determine the optimal vitrification solution of EFS or EDS. The post-thaw survival rates at re-expanded stage rates were significantly different between EFS and EDS (95.0 vs 100%), but at hatching stage was not different between EFS and EDS (90.0 vs 95.0%). respectively. In experiment 2, zygotes, 2-, 4-cell, morula and blastocysts were vitrified by OPP method to determine the acceptable of early stage embryos. The development rates to expanded blastocyst in zygote (70.0%) were significantly lower rather than those in 2-, 4- 8-cell, compacted morula or blastocyst (89.7, 90.0, 92.8, 97.6 or 97.5%), respectively. However, the cell number of post-thaw developed to expanded blastocyst in blastocyst and control blastocyst stage (39.6$\pm$2.81, 35.7$\pm$2.98) were significanty higher than those in zygote, 2-, 4-, 8-cell, compacted morula (29.8$\pm$3.21, 31.3$\pm$3.83, 29.3$\pm$3.58, 28.9$\pm$3.21 or 30.8$\pm$2.93). In experiment 3, the zygotes were exposed in VSl for 1, 2, and 3 min to the optimal exposed time. The cleavage rates (91.6, 88.5, 88.9%) and develop mental rates to blastocyst (83.3, 74.3 and 69.4%) depends on the exposed time in VSl were not significantly different among 1, 2, or 3 min, respectively. The cell number also were not significantly different among exposed time in VS1. respectively. These results indicate that OPP method could be useful for vitrification either EFS or EDS vitrification solution. The post-thaw survival rates at zygote were significantly lower than those at 2-, 4-, 8-cell, morula or blastocyst, respectively. The zygote stage were more sensitive rather than late stage embryos. The exposing time in VS1 for 1 min was better than that for 2 or 3 min, even it was not significantly different. The OPP vitrification method could be useful of mouse embryos either with EFS or EDS vitrification solution.

• Tuberculosis and Respiratory Diseases
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• v.52 no.1
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• pp.14-23
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• 2002

Background: The opitmal ventilator setting during partial liquid ventilation(PLV) is controversial. This study investigated the effects of various gas exchange parameters during PLV in normal rabbit lungs in order to aid in the development of an optimal ventilator setting during PLV. Methods: Seven New-Zealand white rabbits were ventilated in pressure-controlled mode with the following settings; tidal volume($V_T$) 8 mL/kg, positive end-expiratory pressure(PEEP) 4 $cmH_2O$, inspiratory-to-expiratory ratio(I:E ratio) 1:2, fraction of inspired oxygen($F_TO_2$) 1.0. The respiration rate(RR) was adjusted to keep $PaCO_2$ between 35~45 mmHg. The ventilator settings were changed every 30 min in the following sequence : (1) Baseline, as the basal ventilator setting, (2) Inverse ratio, I:E ratio 2:1, (3) high PEEP, adjust PEEP to achieve the same mean inspiratory pressure (MIP) as in the inverse ratio, (4) High $V_T$, $V_T$ 15 mL/kg, (5) high RR, the same minute ventilation (MV) as in the High $V_T$. Subsequently, the same protocol was repeated after instilling 18 mL/kg of perfluorodecalin for PLV. The parameters of gas exchange, lung mechanics, and hemodynamics were examined. Results: (1) The gas ventilation(GV) group showed no significant changes in the $PaO_2$ at all phases. The $PaCO_2$ was lower and the pH was higher at the high $V_T$ and high RR phases(p<0.05). No significant changes in the lung mechanics and hemodynamics parameters were observed. (2) The baseline $PaO_2$ for the PLV was $312{\pm}$ mmHg. This was significantly lower when decreased compared to the baseline $PaO_2$ for GV which was $504{\pm}81$ mmHg(p=0.001). During PLV, the $PaO_2$, was significantly higher at the high PEEP($452{\pm}38$ mmHg) and high $V_T$ ($461{\pm}53$ mmHg) phases compared with the baseline phase. However, it did not change significantly during the inverse I:E ratio or the high RR phases. (3) The $PaCO_2$ was significantly lower at high $V_T$ and RR phases for both the GV and PLV. During the PLV, $PaCO_2$ were significantly higher compared to the GV (p<0.05). (4) There were no important or significant changes in of baseline and high RR phases lung mechanics and hemodynamics parameters during the PLV. Conclusion: During PLV in the normal lung, adequate $V_T$ and PEEP are important for optimal oxygenation.

• The Journal of Korean Academy of Prosthodontics
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• v.47 no.2
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• pp.108-118
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• 2009

Statement of problem: Volume stability, microstructure reproducibility and fluidity along with compatibility with dental stone must be in consideration in order to use tissue conditioner as a material for functional impression. There are few studies concerning the influence of time factor in oral condition on surface roughness of the stone and optimal retention period in the oral cavity considering such changes in surface roughness. Purpose: The purpose of this study was to find out the influence of various kinds of tissue conditioner, its powder/liquid ratio and immersion time on surface roughness of the stone. Material and methods: Materials used in this study were the three kinds of tissue conditioners(Coe-Comfort, Visco-Gel, Soft-Liner) and were grouped into three: group R-mixed with standard powder/liquid ratio that was recommended by the manufacturers, group M-mixed with 20% more powder, group L-mixed with 20% less powder. Specimens were made with the size of 20 mm diameter and 2 mm width. Each tissue conditioner specimens were subdivided into 5 groups according to the immersion time(0 hour, 1 day, 3 days, 5 days, 7 days), completely immersed into artificial saliva and were stored under $37^{\circ}C$. Specimens of which the given immersion time elapsed were taken out and were poured with improved stone, making the stone specimens. Surface roughness of the stone specimens was measured by a profilometer. Results: Within the limitation of this study, the following results were drawn. 1. Major influencing factor on surface roughness of the stone model made from tissue conditioner was the retention period(contribution ratio($\rho$)=62.86%, P<.05) of the tissue conditioner in oral cavity to make functional impression. 2. In case of Coe-Comfort, higher mean surface roughness value of the stone model with statistical significance was observed compared to that of Soft-Liner and Visco-Gel as immersion time changes(P<.05). 3. In case of group L(less), higher mean surface roughness value of the stone model with statistical significance was observed compared to that of R(recommended) and M(more) group as immersion time changes(P<.05). Conclusion: We may conclude that as the retention period of time in oral cavity influences surface roughness of the stone model the most and as the kind of tissue conditioner and its P/L ratio may influence also, clinician should well understand the optimal retention period in oral cavity and choose the right tissue conditioner for the functional impression, thus making the functional impression with tissue conditioner usefully.

• Pediatric Infection and Vaccine
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• v.9 no.1
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• pp.67-73
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• 2002

Purpose : Despite of the appropriate measles vaccination programs, epidemics occur every 2~3 years and especially occurred in large group in late of 2000 and early of 2001. To evaluate the effect of the vaccination, needs for revaccination and to determine the optimal age for revaccination, we examined measles specific IgG and IgM in mealses patients and investigated different antibody appearance according to vaccination history. Methods : Anti-measles antibodies were checked in sera of 201 patients(male : 117, female : 84) that are responsible for Criteria for Disease Control among 298 patients that are suspicious of measles including inpatients and outpatients in Wonju Christian Hospital from June in 2000 to June in 2001. They were checked by immunofluorescent assay. Then we classified them according to sex, month, distribution of age due to vaccination and appearance of measles antibody. Results : The ratio of male and female was 1.4 : 1. The maximum incidence was 38 cases(18.9%) in May in 2001. Incidence was increased from November in 2000 to January in 2001 and decreased in February and March in 2001. Thereafter it was increased from April in 2001 again and decreased from June. There were 93 cases(46.3%) in vaccinated group and 108 cases(53.7%) in unvaccinated group. In the distribution according to age in vaccinated group, there were 54 cases(58.1%) in more than 10 years old, 15 cases(16.0%) between 7 and 10 years old, 12 cases(12.9%) between 15 months and 3 years old, 6 cases (6.5%) between 4 and 6 years old and 6 cases(6.5%) between 6 months and 14 months old. In the distribution according to age in unvaccinated group, there were 88 cases(81.5%) between 6 months and 14 months old, 9 cases(8.3%) between 15 months and 3 years old, 7 cases(6.5%) less than 6 months old, 3 cases(2.8%) more than 10 years old and 1 case(0.9%) between 7 and 10 years old. In the distribution of measles specific IgG and IgM, 78 cas (87.6%) were IgG(+), IgM(+) and 11 cases(12.4%) are IgG(+), IgM(-) in vaccinated group. In unvaccinated group, there were 69 cases(63.9%) of IgG(+), IgM(+) and 39 cases (36.1%) of IgG(-), IgM(+). Con c lu s i on s : We thought that measles incidence was peaked between 6 months and 14 months old in unvaccinated group because of maximum decrement of transplacental matenal antibody and was peaked in more than 10 years old in vaccinated group because of maximum decrement of measles specific IgG. We think that measles revaccination as well as vaccination and especially optimal age for revaccination is very important to prevent measles successfully.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.73-95
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• 2021

This study uses Node2vec graph embedding method and Light GBM link prediction to explore undeveloped export candidate countries in Korea's food and beverage industry. Node2vec is the method that improves the limit of the structural equivalence representation of the network, which is known to be relatively weak compared to the existing link prediction method based on the number of common neighbors of the network. Therefore, the method is known to show excellent performance in both community detection and structural equivalence of the network. The vector value obtained by embedding the network in this way operates under the condition of a constant length from an arbitrarily designated starting point node. Therefore, it has the advantage that it is easy to apply the sequence of nodes as an input value to the model for downstream tasks such as Logistic Regression, Support Vector Machine, and Random Forest. Based on these features of the Node2vec graph embedding method, this study applied the above method to the international trade information of the Korean food and beverage industry. Through this, we intend to contribute to creating the effect of extensive margin diversification in Korea in the global value chain relationship of the industry. The optimal predictive model derived from the results of this study recorded a precision of 0.95 and a recall of 0.79, and an F1 score of 0.86, showing excellent performance. This performance was shown to be superior to that of the binary classifier based on Logistic Regression set as the baseline model. In the baseline model, a precision of 0.95 and a recall of 0.73 were recorded, and an F1 score of 0.83 was recorded. In addition, the light GBM-based optimal prediction model derived from this study showed superior performance than the link prediction model of previous studies, which is set as a benchmarking model in this study. The predictive model of the previous study recorded only a recall rate of 0.75, but the proposed model of this study showed better performance which recall rate is 0.79. The difference in the performance of the prediction results between benchmarking model and this study model is due to the model learning strategy. In this study, groups were classified by the trade value scale, and prediction models were trained differently for these groups. Specific methods are (1) a method of randomly masking and learning a model for all trades without setting specific conditions for trade value, (2) arbitrarily masking a part of the trades with an average trade value or higher and using the model method, and (3) a method of arbitrarily masking some of the trades with the top 25% or higher trade value and learning the model. As a result of the experiment, it was confirmed that the performance of the model trained by randomly masking some of the trades with the above-average trade value in this method was the best and appeared stably. It was found that most of the results of potential export candidates for Korea derived through the above model appeared appropriate through additional investigation. Combining the above, this study could suggest the practical utility of the link prediction method applying Node2vec and Light GBM. In addition, useful implications could be derived for weight update strategies that can perform better link prediction while training the model. On the other hand, this study also has policy utility because it is applied to trade transactions that have not been performed much in the research related to link prediction based on graph embedding. The results of this study support a rapid response to changes in the global value chain such as the recent US-China trade conflict or Japan's export regulations, and I think that it has sufficient usefulness as a tool for policy decision-making.

• Korean Journal of Soil Science and Fertilizer
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• v.45 no.2
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• pp.293-300
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• 2012

This study was to investigate the unsuitable rate of the storage facilities, the changes in corrosion process over time after installation according to the status, the time to install the facilities, years elapsed after facilities installation, inspection of methods and motivation, and so on, based on the results of the inspection at the petroleum storage facilities conducted by domestic soil-relate specialized agency to derive optimal management plans which meet the status of soil contamination facilities. The results showed that the facilities more than 5 years after the initial leak test at the time of the installation need to be inspected periodically by considering costs of leak test and remediation of polluted soil. The inspection period can be decided by cost and leak test methods showing discrepancies for the results obtained from individual test whether it was direct or indirect. To compensate these matters, we suggested that the direct inspection method on regular schedule is recommended. On the other hand, the inspection can be voluntarily completed to ease burden of the results by inspection or equivalent level to this inspection method. Also, it may need improved construction supervision and performance test system to minimize the occurrence of the nature defects in installing the facilities as well as the upgrade program for the facilities during intervals of inspection period.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.47-73
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• 2020

KTX rolling stocks are a system consisting of several machines, electrical devices, and components. The maintenance of the rolling stocks requires considerable expertise and experience of maintenance workers. In the event of a rolling stock failure, the knowledge and experience of the maintainer will result in a difference in the quality of the time and work to solve the problem. So, the resulting availability of the vehicle will vary. Although problem solving is generally based on fault manuals, experienced and skilled professionals can quickly diagnose and take actions by applying personal know-how. Since this knowledge exists in a tacit form, it is difficult to pass it on completely to a successor, and there have been studies that have developed a case-based rolling stock expert system to turn it into a data-driven one. Nonetheless, research on the most commonly used KTX rolling stock on the main-line or the development of a system that extracts text meanings and searches for similar cases is still lacking. Therefore, this study proposes an intelligence supporting system that provides an action guide for emerging failures by using the know-how of these rolling stocks maintenance experts as an example of problem solving. For this purpose, the case base was constructed by collecting the rolling stocks failure data generated from 2015 to 2017, and the integrated dictionary was constructed separately through the case base to include the essential terminology and failure codes in consideration of the specialty of the railway rolling stock sector. Based on a deployed case base, a new failure was retrieved from past cases and the top three most similar failure cases were extracted to propose the actual actions of these cases as a diagnostic guide. In this study, various dimensionality reduction measures were applied to calculate similarity by taking into account the meaningful relationship of failure details in order to compensate for the limitations of the method of searching cases by keyword matching in rolling stock failure expert system studies using case-based reasoning in the precedent case-based expert system studies, and their usefulness was verified through experiments. Among the various dimensionality reduction techniques, similar cases were retrieved by applying three algorithms: Non-negative Matrix Factorization(NMF), Latent Semantic Analysis(LSA), and Doc2Vec to extract the characteristics of the failure and measure the cosine distance between the vectors. The precision, recall, and F-measure methods were used to assess the performance of the proposed actions. To compare the performance of dimensionality reduction techniques, the analysis of variance confirmed that the performance differences of the five algorithms were statistically significant, with a comparison between the algorithm that randomly extracts failure cases with identical failure codes and the algorithm that applies cosine similarity directly based on words. In addition, optimal techniques were derived for practical application by verifying differences in performance depending on the number of dimensions for dimensionality reduction. The analysis showed that the performance of the cosine similarity was higher than that of the dimension using Non-negative Matrix Factorization(NMF) and Latent Semantic Analysis(LSA) and the performance of algorithm using Doc2Vec was the highest. Furthermore, in terms of dimensionality reduction techniques, the larger the number of dimensions at the appropriate level, the better the performance was found. Through this study, we confirmed the usefulness of effective methods of extracting characteristics of data and converting unstructured data when applying case-based reasoning based on which most of the attributes are texted in the special field of KTX rolling stock. Text mining is a trend where studies are being conducted for use in many areas, but studies using such text data are still lacking in an environment where there are a number of specialized terms and limited access to data, such as the one we want to use in this study. In this regard, it is significant that the study first presented an intelligent diagnostic system that suggested action by searching for a case by applying text mining techniques to extract the characteristics of the failure to complement keyword-based case searches. It is expected that this will provide implications as basic study for developing diagnostic systems that can be used immediately on the site.

• Journal of the Korean Society of Food Science and Nutrition
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• v.43 no.3
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• pp.425-430
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• 2014

Foods contain various nutrients such as carbohydrates, protein, oil, vitamins, and minerals. Among them, carbohydrates, protein, and oil are the main constituents of foods. Usually, these constituents are analyzed by the Kjeldahl and Soxhlet method and so on. However, these analytical methods are complex, costly, and time-consuming. Thus, this study aimed to rapidly and effectively analyze carbohydrate, protein, and oil contents with near-infrared reflectance spectroscopy (NIRS). A total of 517 food samples were measured within the wavelength range of 400 to 2,500 nm. Exactly 412 food calibration samples and 162 validation samples were used for NIRS equation development and validation, respectively. In the NIRS equation of carbohydrates, the most accurate equation was obtained under 1, 4, 5, 1 (1st derivative, 4 nm gap, 5 points smoothing, and 1 point second smoothing) math treatment conditions using the weighted MSC (multiplicative scatter correction) scatter correction method with MPLS (modified partial least square) regression. In the case of protein and oil, the best equation were obtained under 2, 5, 5, 3 and 1, 1, 1, 1 conditions, respectively, using standard MSC and standard normal variate only scatter correction methods with MPLS regression. Calibrations of these NIRS equations showed a very high coefficient of determination in calibration ($R^2$: carbohydrates, 0.971; protein, 0.974; oil, 0.937) and low standard error of calibration (carbohydrates, 4.066; protein, 1.080; oil, 1.890). Optimal equation conditions were applied to a validation set of 162 samples. Validation results of these NIRS equations showed a very high coefficient of determination in prediction ($r^2$: carbohydrates, 0.987; protein, 0.970; oil, 0.947) and low standard error of prediction (carbohydrates, 2.515; protein, 1.144; oil, 1.370). Therefore, these NIRS equations can be applicable for determination of carbohydrates, proteins, and oil contents in various foods.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.185-202
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• 2012

.Since the value of information has been realized in the information society, the usage and collection of information has become important. A facial expression that contains thousands of information as an artistic painting can be described in thousands of words. Followed by the idea, there has recently been a number of attempts to provide customers and companies with an intelligent service, which enables the perception of human emotions through one's facial expressions. For example, MIT Media Lab, the leading organization in this research area, has developed the human emotion prediction model, and has applied their studies to the commercial business. In the academic area, a number of the conventional methods such as Multiple Regression Analysis (MRA) or Artificial Neural Networks (ANN) have been applied to predict human emotion in prior studies. However, MRA is generally criticized because of its low prediction accuracy. This is inevitable since MRA can only explain the linear relationship between the dependent variables and the independent variable. To mitigate the limitations of MRA, some studies like Jung and Kim (2012) have used ANN as the alternative, and they reported that ANN generated more accurate prediction than the statistical methods like MRA. However, it has also been criticized due to over fitting and the difficulty of the network design (e.g. setting the number of the layers and the number of the nodes in the hidden layers). Under this background, we propose a novel model using Support Vector Regression (SVR) in order to increase the prediction accuracy. SVR is an extensive version of Support Vector Machine (SVM) designated to solve the regression problems. The model produced by SVR only depends on a subset of the training data, because the cost function for building the model ignores any training data that is close (within a threshold ${\varepsilon}$) to the model prediction. Using SVR, we tried to build a model that can measure the level of arousal and valence from the facial features. To validate the usefulness of the proposed model, we collected the data of facial reactions when providing appropriate visual stimulating contents, and extracted the features from the data. Next, the steps of the preprocessing were taken to choose statistically significant variables. In total, 297 cases were used for the experiment. As the comparative models, we also applied MRA and ANN to the same data set. For SVR, we adopted '${\varepsilon}$-insensitive loss function', and 'grid search' technique to find the optimal values of the parameters like C, d, ${\sigma}^2$, and ${\varepsilon}$. In the case of ANN, we adopted a standard three-layer backpropagation network, which has a single hidden layer. The learning rate and momentum rate of ANN were set to 10%, and we used sigmoid function as the transfer function of hidden and output nodes. We performed the experiments repeatedly by varying the number of nodes in the hidden layer to n/2, n, 3n/2, and 2n, where n is the number of the input variables. The stopping condition for ANN was set to 50,000 learning events. And, we used MAE (Mean Absolute Error) as the measure for performance comparison. From the experiment, we found that SVR achieved the highest prediction accuracy for the hold-out data set compared to MRA and ANN. Regardless of the target variables (the level of arousal, or the level of positive / negative valence), SVR showed the best performance for the hold-out data set. ANN also outperformed MRA, however, it showed the considerably lower prediction accuracy than SVR for both target variables. The findings of our research are expected to be useful to the researchers or practitioners who are willing to build the models for recognizing human emotions.

• Journal of the Korean Society of Groundwater Environment
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• v.7 no.3
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• pp.103-115
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• 2000

The formation of brown-colored precipitates is one of the serious problems frequently encountered in the development and supply of groundwater in Korea, because by it the water exceeds the drinking water standard in terms of color. taste. turbidity and dissolved iron concentration and of often results in scaling problem within the water supplying system. In groundwaters from the Pajoo area, brown precipitates are typically formed in a few hours after pumping-out. In this paper we examine the process of the brown precipitates' formation using the equilibrium thermodynamic and kinetic approaches, in order to understand the origin and geochemical pathway of the generation of turbidity in groundwater. The results of this study are used to suggest not only the proper pumping technique to minimize the formation of precipitates but also the optimal design of water treatment methods to improve the water quality. The bed-rock groundwater in the Pajoo area belongs to the Ca-$HCO_3$type that was evolved through water/rock (gneiss) interaction. Based on SEM-EDS and XRD analyses, the precipitates are identified as an amorphous, Fe-bearing oxides or hydroxides. By the use of multi-step filtration with pore sizes of 6, 4, 1, 0.45 and 0.2 $\mu\textrm{m}$, the precipitates mostly fall in the colloidal size (1 to 0.45 $\mu\textrm{m}$) but are concentrated (about 81%) in the range of 1 to 6 $\mu\textrm{m}$in teams of mass (weight) distribution. Large amounts of dissolved iron were possibly originated from dissolution of clinochlore in cataclasite which contains high amounts of Fe (up to 3 wt.%). The calculation of saturation index (using a computer code PHREEQC), as well as the examination of pH-Eh stability relations, also indicate that the final precipitates are Fe-oxy-hydroxide that is formed by the change of water chemistry (mainly, oxidation) due to the exposure to oxygen during the pumping-out of Fe(II)-bearing, reduced groundwater. After pumping-out, the groundwater shows the progressive decreases of pH, DO and alkalinity with elapsed time. However, turbidity increases and then decreases with time. The decrease of dissolved Fe concentration as a function of elapsed time after pumping-out is expressed as a regression equation Fe(II)=10.l exp(-0.0009t). The oxidation reaction due to the influx of free oxygen during the pumping and storage of groundwater results in the formation of brown precipitates, which is dependent on time, $Po_2$and pH. In order to obtain drinkable water quality, therefore, the precipitates should be removed by filtering after the stepwise storage and aeration in tanks with sufficient volume for sufficient time. Particle size distribution data also suggest that step-wise filtration would be cost-effective. To minimize the scaling within wells, the continued (if possible) pumping within the optimum pumping rate is recommended because this technique will be most effective for minimizing the mixing between deep Fe(II)-rich water and shallow $O_2$-rich water. The simultaneous pumping of shallow $O_2$-rich water in different wells is also recommended.