• Tuberculosis and Respiratory Diseases
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• v.44 no.6
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• pp.1318-1325
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• 1997

Background : Since the late 1960s, mechanical ventilation has been accomplished primarily using volume controlled ventilation(VCV). While VCV allows a set tidal volume to be guaranteed, VCV could bring about excessive airway pressures that may be lead to barotrauma in the patients with acute lung injury. With the increment of knowledge related to ventilator-induced lung injury, pressure controlled ventilation(PCV) has been frequently applied to these patients. But, PCV has a disadvantage of variable tidal volume delivery as pulmonary impedance changes. Since the concept of combining the positive attributes of VCV and PCV(dual control ventilation, DCV) was described firstly in 1992, a few DCV modes were introduced. Pressure-regulated volume control(PRVC) mode, a kind of DCV, is pressure-limited, time-cycled ventilation that uses tidal volume as a feedback control for continuously adjusting the pressure limit However, no clinical studies were published on the efficacy of PRVC until now. 'This investigation studied the efficacy of PRVC in the patients with unstable respiratory mechanics. Methods : The subjects were 8 mechanically ventilated patients(M : F=6 : 2, $56{\pm}26$ years) who showed unstable respiratory mechanics, which was defined by the coefficients of variation of peak inspiratory pressure for 15 minutes greater than 10% under VCV, or the coefficients of variation of tidal volume greater than 10% under PCV. The study was consisited of 3 modes application with VCV, PCV and PRVC for 15 minutes by random order. To obtain same tidal volume, inspiratory pressure setting was adjusted in PCV. Respiratory parameters were measured by pulmonary monitor(CP-100 pulmonary monitor, Bicore, Irvine, CA, USA). Results : 1) Mean tidal volumes($V_T$) in each mode were not different(VCV, $431{\pm}102ml$ ; PCV, $417{\pm}99ml$ ; PRVC, $414{\pm}97ml$) 2) The coefficient of variation(CV) of $V_T$ were $5.2{\pm}3.9%$ in VCV, $15.2{\pm}7.5%$ in PCV and $19.3{\pm}10.0%$ in PRVC. The CV of $V_T$ in PCV and PRVC were significantly greater than that in VCV(p<0.01). 3) Mean peak inspiratory pressure(PIP) in VCV($31.0{\pm}6.9cm$ $H_2O$) was higher than PIP in PCV($26.0{\pm}6.5cm$ $H_2O$) or PRVC($27.0{\pm}6.4cm$ $H_2O$)(p<0.05). 4) The CV of PIP were $13.9{\pm}3.7%$ in VCV, $4.9{\pm}2.6%$ in PVC and $12.2{\pm}7.0%$ in PRVC. The CV of PIP in VCV and PRVC were greater than that in PCV(p<0.01). Conclusions : Because of wide fluctuations of VT and PIP, PRVC mode did not seem to have advantages compared to VCV or PCV in the patients with unstable respiratory mechanics.

• Tuberculosis and Respiratory Diseases
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• v.48 no.1
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• pp.14-23
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• 2000

Background: The evaluation of candidates for successful lung resection is important. Our study was conducted to determine the preoperative predictors of postoperative mortality and morbidity in lung cancer patients with impaired lung function. Method; Between October 1, 1995 and August 31, 1997, 36 lung resection candidates for lung cancer with $FEV_1$ of less than 2L or 60% of predicted value were included prospectively. Age, sex, weight loss, hematocrit, serum albumin, EKG and concomitant illness were considered as systemic potential predictors for successful lung resection. Smoking history, presence of pneumonia, dyspnea scale(l to 4), arterial blood gas analysis with room air breathing, routine pulmonary function test were also included for the analysis. In addition, predicted postoperative(ppo) pulmonary factors such as ppo-$FEV_1$ ppo-diffusing capacity(DLco), predicted postoperative product(PPP) of ppo-$FEV_1%{\times}$ppo-DLco% and ppo-maximal $O_2$ uptake($VO_2$max) were also measured. Results: There were 31 men and 5 women with the median age of 65 years(range, 44 to 82) and a mean $FEV_1$ of $1.78{\pm}0.06L$. Pneumonectomy was performed in 14 patients, bilobectomy in 8, lobectomy in 14. Pulmonary complications developed in 10 patients; cardiac complications in 3, other complications(empyema, air leak, bleeding) in 4. Twelve patients were managed in the intensive care unit for more than 48 hours. Two patients died within 30 days after operation. The ppo-$VO_2$max was less than 10 ml/kg/min in these two patients. MVV was the only predictor for the pulmonary complications. However, there was no predictor for the post operative death in this study. Conclusions: Based on the results, MVV was the useful predictor for postoperative pulmonary complications in lung cancer resection candidates with impaired lung function In addition, ppo-$VO_2$max value less than 10 ml/kg/min was associated with postoperative death, so exercise pulmonary function test could be useful as preoperative test. But further studies are needed to validate this result.

• Tuberculosis and Respiratory Diseases
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• v.50 no.1
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• pp.52-66
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• 2001

Background : NF-${\kappa}B$ is the most important transcriptional factor in IL-8 gene expression. Triptolide is a new compound that recently has been shown to inhibit NF-${\kappa}B$ activation. The purpose of this study is to investigate how triptolide inhibits NF-${\kappa}B$-dependent IL-8 gene transcription in lung epithelial cells and to pilot the potential for the clinical application of triptolide in inflammatory lung diseases. Methods : A549 cells were used and triptolide was provided from Pharmagenesis Company (Palo Alto, CA). In order to examine NF-${\kappa}B$-dependent IL-8 transcriptional activity, we established stable A549 IL-8-NF-${\kappa}B$-luc. cells and performed luciferase assays. IL-8 gene expression was measured by RT-PCR and ELISA. A Western blot was done for the study of $I{\kappa}B{\alpha}$ degradation and an electromobility shift assay was done to analyze NF-${\kappa}B$ DNA binding. p65 specific transactivation was analyzed by a cotransfection study using a Gal4-p65 fusion protein expression system. To investigate the involvement of transcriptional coactivators, we perfomed a transfection study with CBP and SRC-1 expression vectors. Results : We observed that triptolide significantly suppresses NF-${\kappa}B$-dependent IL-8 transcriptional activity induced by IL-$1{\beta}$ and PMA. RT-PCR showed that triptolide represses both IL-$1{\beta}$ and PMA-induced IL-8 mRNA expression and ELISA confirmed this triptolide-mediated IL-8 suppression at the protein level. However, triptolide did not affect $I{\kappa}B{\alpha}$ degradation and NF-$_{\kappa}B$ DNA binding. In a p65-specific transactivation study, triptolide significantly suppressed Gal4-p65T Al and Gal4-p65T A2 activity suggesting that triptolide inhibits NF-${\kappa}B$ activation by inhibiting p65 transactivation. However, this triptolide-mediated inhibition of p65 transactivation was not rescued by the overexpression of CBP or SRC-1, thereby excluding the role of transcriptional coactivators. Conclusions : Triptolide is a new compound that inhibits NF-${\kappa}B$-dependent IL-8 transcriptional activation by inhibiting p65 transactivation, but not by an $I{\kappa}B{\alpha}$-dependent mechanism. This suggests that triptolide may have a therapeutic potential for inflammatory lung diseases.

• Tuberculosis and Respiratory Diseases
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• v.60 no.6
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• pp.653-662
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• 2006

Background: The changes in the pulmonary function observed in burn patients with an inhalation injury are probably the result of a combination of airway inflammation, chest wall and muscular abnormalities, and scar formation. In addition, it appears that prolonged ventilatory support and an episode of pneumonia contribute to the findings. This study investigated the changes in the pulmonary function in patients with inhalation injury at the early and late post-burn periods. Methods: From August 1, 2002, to August 30, 2005, surviving burn patients who had an inhalation injury were enrolled prospectively. An inhalation injury was identified by bronchoscopy within 48hours after admission. Spirometry was performed at the early phase during admission and the recovery phase after discharge, and the changes in the pulmonary function were compared. Results: 37 patients (M=28, F=9) with a total burn surface area (% TBSA), ranging from 0 to 18%, were included. The initial $PaO_2/$FiO_2$ratio and COHb were $286.4{\pm}129.6mmHg$ and $7.8{\pm}6.6%$. Nine cases (24.3%) underwent endotracheal intubation and 3 cases (8.1%) underwent mechanical ventilation. The initial X-ray findings revealed abnormalities in, 18 cases (48.6%) with 15 (83.3%) of these being completely resolved. However, 3 (16.7%) of these had residual sequela. The initial pulmonary function test, showed an obstructive pattern in 9 (24.3%) with 4 (44.4%) of these showing a positive bronchodilator response, A restrictive pattern was also observed in 9 (24.3%) patients. A lower DLco was observed in only 4 (17.4%) patients of which 23 had undergone DLco. In the follow-up study, an obstructive and restrictive pattern was observed in only one (2.7%) case each. All the decreased DLco returned to mormal. Conclusions: Most surviving burn patients with an inhalation injury but with a small burn size showed initial derangements in the pulmonary function test that was restored to a normal lung function during the follow up period.

• 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.

• Magazine of the Korean Society of Agricultural Engineers
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• v.13 no.4
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• pp.2456-2470
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• 1971

Compaction of soil is very important for construction of soil structures such as highway fills, embankment of reservoir and seadike. With increasing compaction effort, the strength of soil, interor friction and Cohesion increas greatly while the reduction of permerbilityis evident. Factors which may influence compaction effort are moisture content, grain size, grain distribution and other physical properties as well as the variable method of compaction. The moisture content among these parameter is the most important thing. For making the maximum density to a given soil, the comparable optimum water content is required. If there is a slight change in water content when compared with optimum water content, the compaction ratio will decrease and the corresponding mechanical properties will change evidently. The results in this study of soil compaction with different water content are summarized as follows. 1) The maximum dry density increased and corresponding optimum moisture content decreased with increasing of coarse grain size and the compaction curve is steeper than increasing of fine grain size. 2) The maximum dry density is decreased with increasing of the optimum water content and a relationship both parameter becomes rdam-max=2.232-0.02785 $W_0$ But this relstionship will be change to $r_d=ae^{-bw}$ when comparable water content changes. 3) In case of most soils, a dry condition is better than wet condition to give a compactive effort, but the latter condition is only preferable when the liquid limit of soil exceeds 50 percent. 4) The compaction ratio of cohesive soil is greeter than cohesionless soil even the amount of coarse grain sizes are same. 5) The relationship between the maximum dry density and porosity is as rdmax=2,186-0.872e, but it changes to $r_d=ae^{be}$ when water content vary from optimum water content. 6) The void ratio is increased with increasing of optimum water content as n=15.85+1.075 w, but therelation becames $n=ae^{bw}$ if there is a variation in water content. 7) The increament of permeabilty is high when the soil is a high plasticity or coarse. 8) The coefficient of permeability of soil compacted in wet condition is lower than the soil compacted in dry condition. 9) Cohesive soil has higher permeability than cohesionless soil even the amount of coarse particles are same. 10) In generall, the soil which has high optimum water content has lower coefficient of permeability than low optimum water content. 11) The coefficient of permeability has a certain relations with density, gradation and void ratio and it increase with increasing of saturation degree.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.77-97
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• 2010

Market timing is an investment strategy which is used for obtaining excessive return from financial market. In general, detection of market timing means determining when to buy and sell to get excess return from trading. In many market timing systems, trading rules have been used as an engine to generate signals for trade. On the other hand, some researchers proposed the rough set analysis as a proper tool for market timing because it does not generate a signal for trade when the pattern of the market is uncertain by using the control function. The data for the rough set analysis should be discretized of numeric value because the rough set only accepts categorical data for analysis. Discretization searches for proper "cuts" for numeric data that determine intervals. All values that lie within each interval are transformed into same value. In general, there are four methods for data discretization in rough set analysis including equal frequency scaling, expert's knowledge-based discretization, minimum entropy scaling, and na$\ddot{i}$ve and Boolean reasoning-based discretization. Equal frequency scaling fixes a number of intervals and examines the histogram of each variable, then determines cuts so that approximately the same number of samples fall into each of the intervals. Expert's knowledge-based discretization determines cuts according to knowledge of domain experts through literature review or interview with experts. Minimum entropy scaling implements the algorithm based on recursively partitioning the value set of each variable so that a local measure of entropy is optimized. Na$\ddot{i}$ve and Booleanreasoning-based discretization searches categorical values by using Na$\ddot{i}$ve scaling the data, then finds the optimized dicretization thresholds through Boolean reasoning. Although the rough set analysis is promising for market timing, there is little research on the impact of the various data discretization methods on performance from trading using the rough set analysis. In this study, we compare stock market timing models using rough set analysis with various data discretization methods. The research data used in this study are the KOSPI 200 from May 1996 to October 1998. KOSPI 200 is the underlying index of the KOSPI 200 futures which is the first derivative instrument in the Korean stock market. The KOSPI 200 is a market value weighted index which consists of 200 stocks selected by criteria on liquidity and their status in corresponding industry including manufacturing, construction, communication, electricity and gas, distribution and services, and financing. The total number of samples is 660 trading days. In addition, this study uses popular technical indicators as independent variables. The experimental results show that the most profitable method for the training sample is the na$\ddot{i}$ve and Boolean reasoning but the expert's knowledge-based discretization is the most profitable method for the validation sample. In addition, the expert's knowledge-based discretization produced robust performance for both of training and validation sample. We also compared rough set analysis and decision tree. This study experimented C4.5 for the comparison purpose. The results show that rough set analysis with expert's knowledge-based discretization produced more profitable rules than C4.5.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.105-129
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• 2020

This study uses corporate data from 2012 to 2018 when K-IFRS was applied in earnest to predict default risks. The data used in the analysis totaled 10,545 rows, consisting of 160 columns including 38 in the statement of financial position, 26 in the statement of comprehensive income, 11 in the statement of cash flows, and 76 in the index of financial ratios. Unlike most previous prior studies used the default event as the basis for learning about default risk, this study calculated default risk using the market capitalization and stock price volatility of each company based on the Merton model. Through this, it was able to solve the problem of data imbalance due to the scarcity of default events, which had been pointed out as the limitation of the existing methodology, and the problem of reflecting the difference in default risk that exists within ordinary companies. Because learning was conducted only by using corporate information available to unlisted companies, default risks of unlisted companies without stock price information can be appropriately derived. Through this, it can provide stable default risk assessment services to unlisted companies that are difficult to determine proper default risk with traditional credit rating models such as small and medium-sized companies and startups. Although there has been an active study of predicting corporate default risks using machine learning recently, model bias issues exist because most studies are making predictions based on a single model. Stable and reliable valuation methodology is required for the calculation of default risk, given that the entity's default risk information is very widely utilized in the market and the sensitivity to the difference in default risk is high. Also, Strict standards are also required for methods of calculation. The credit rating method stipulated by the Financial Services Commission in the Financial Investment Regulations calls for the preparation of evaluation methods, including verification of the adequacy of evaluation methods, in consideration of past statistical data and experiences on credit ratings and changes in future market conditions. This study allowed the reduction of individual models' bias by utilizing stacking ensemble techniques that synthesize various machine learning models. This allows us to capture complex nonlinear relationships between default risk and various corporate information and maximize the advantages of machine learning-based default risk prediction models that take less time to calculate. To calculate forecasts by sub model to be used as input data for the Stacking Ensemble model, training data were divided into seven pieces, and sub-models were trained in a divided set to produce forecasts. To compare the predictive power of the Stacking Ensemble model, Random Forest, MLP, and CNN models were trained with full training data, then the predictive power of each model was verified on the test set. The analysis showed that the Stacking Ensemble model exceeded the predictive power of the Random Forest model, which had the best performance on a single model. Next, to check for statistically significant differences between the Stacking Ensemble model and the forecasts for each individual model, the Pair between the Stacking Ensemble model and each individual model was constructed. Because the results of the Shapiro-wilk normality test also showed that all Pair did not follow normality, Using the nonparametric method wilcoxon rank sum test, we checked whether the two model forecasts that make up the Pair showed statistically significant differences. The analysis showed that the forecasts of the Staging Ensemble model showed statistically significant differences from those of the MLP model and CNN model. In addition, this study can provide a methodology that allows existing credit rating agencies to apply machine learning-based bankruptcy risk prediction methodologies, given that traditional credit rating models can also be reflected as sub-models to calculate the final default probability. Also, the Stacking Ensemble techniques proposed in this study can help design to meet the requirements of the Financial Investment Business Regulations through the combination of various sub-models. We hope that this research will be used as a resource to increase practical use by overcoming and improving the limitations of existing machine learning-based models.

• The Korean Journal of Nuclear Medicine Technology
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• v.21 no.1
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• pp.39-43
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• 2017

Purpose Thyroglobulin (Tg) is a biologic marker of differentiated thyroid carcinoma (DTC), produced by normal thyroid tissue or thyroid cancer tissue. Therefore, the Tg values of DTC patients is the most specific indicator for judging whether recurrence occur or whether the remaining thyroid cancer is present. Thyroid cancer is currently the most common cancer in Korea, of which 90% is differentiated thyroid cancer. The number of patients with thyroid disease of this application also increased, and an accurate and prompt results are required. However, the incubation time of the Tg commonly takes about 24 hours in our hospital, and the result reporting time is delayed, and We could not satisfied with the requirements of clinical departments and patients. In order to fulfill these requirements, experiments were conducted by shortening the incubation time between company B's Kit currently in use and company C's Kit used in other hospitals. Through these experiments, we could perform the correlation with the original method and shortening method, and could find the optimum reaction time to satisfy the needs of the departments and the patients, and we will improve the competitiveness with the EIA examination. Materials and Methods In September 2016, we tested 65 patients company B's kit and company C's kit by three incubation ways. First method $37^{\circ}C$ shaking 2hr/2hr, Second method RT shaking 3hr/2hr, Third method 1hr/1hr shaking at $37^{\circ}C$. Fourth method RT shaking 3hr method which is the original method of Company C's Kit. Fifth method, the incubation time was shortened under room temperature shaking 2hr, Sixth method $37^{\circ}C$ shaking 2hr. And we performed and compared the correlation and coefficient of each methods. Results As a result of performing shortening method on company B currently in use, when comparing the Original method of company B kit, First method $37^{\circ}C$ shaking 2hr/2hr was less than Tg 1.0 ng/mL and the ratio of $R^2=0.5906$, above 1.0 ng/mL In the value, $R^2=0.9597$. Second method RT shaking 3hr/2hr was $R^2=0.7262$ less than value of 1.0 ng/mL, $R^2=0.9566$ above than value of 1.0 ng/mL. Third method $37^{\circ}C$ shaking 1hr/1hr was $R^2=0.7728$ less than value of 1.0 ng/mL, $R^2=0.8904$ above than value of 1.0 ng/mL. Forth, Company C's The original method, RT shaking 3hr was $R^2=0.7542$ less than value of 1.0 ng/mL, and $R^2=0.9711$ above than value of 1.0 ng/mL. Fifth method RT shaking 2hr was $R^2=0.5477$ less than value of 1.0 ng/mL, $R^2=0.9231$ above than value of 1.0 ng/mL. Sixth method $37^{\circ}C$ shaking 2hr showed $R^2=0.2848$ less than value of 1.0 ng/mL, $R^2=0.9028$ above than value of 1.0 ng/mL. Conclusion Samples with both values of 1.0 ng/mL or higher in both of the six methods showed relatively high correlation, but the correlation was relatively low less than value of 1.0 ng/mL. Especially, the $37^{\circ}C$ shaking 2hr method of company C showed a sharp fluctuation from the low concentration value of 1.0 ng/mL or less. Therefore, we are planning to continuously test the time, equipment, incubation temperature and so on for the room temperature shaking 2hr method and $37^{\circ}C$ shaking 1hr/1hr of company C which showed a relatively high correlation. After that, we can search for an appropriate shortening method through additional experiments such as recovery test, dilution test, sensitivity test, and provide more accurate and prompt results to the department of medical treatment, It is competitive with EIA test.

• Current Research on Agriculture and Life Sciences
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• v.4
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• pp.141-153
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• 1986

This study intends to document the existing cyclical fluctuations of garic and onion price at farm gate level during the period of 1966-1986 in Korea. The existing patterns of such cyclical fluctuations were estimated systematically by removing the seasonal fluctuation and irregular movement as well as secular trend from the original price through the moving average method. It was found that the cyclical fluctuations of garic and onion prices repeated six and seven times respectively during the same period, also the amplitude coefficient of cyclical fluctuations showed speed up in recent years. It was noticed that the cyclical fluctuations of price in onion was higher than that of in garic.