• Journal of Internet Computing and Services
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• v.21 no.1
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• pp.169-178
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• 2020

The reductions of troops/human resources, and improvement in combat power have made Korean Department of Defense actively adapt 4th Industrial Revolution technology (Artificial Intelligence, Big Data). The defense information system has been developed in various ways according to the task and the uniqueness of each military. In order to take full advantage of the 4th Industrial Revolution technology, it is necessary to improve the closed defense datamanagement system.However, the establishment and usage of data standards in all information systems for the utilization of defense big data and artificial intelligence has limitations due to security issues, business characteristics of each military, anddifficulty in standardizing large-scale systems. Based on the interworking requirements of each system, data sharing is limited through direct linkage through interoperability agreement between systems. In order to implement smart defense using the 4th Industrial Revolution technology, it is urgent to prepare a system that can share defense data and make good use of it. To technically support the defense, it is critical to develop Multi Repository Meta-Data Management (MRMM) that supports systematic standard management of defense data that manages enterprise standard and standard mapping for each system and promotes data interoperability through linkage between standards which obeys the Defense Interoperability Management Development Guidelines. We introduced MRMM, and implemented by using vocabulary similarity using machine learning and statistical approach. Based on MRMM, We expect to simplify the standardization integration of all military databases using artificial intelligence and bigdata. This will lead to huge reduction of defense budget while increasing combat power for implementing smart defense.

• Journal of the Korean Society of Food Science and Nutrition
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• v.5 no.1
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• pp.31-37
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• 1976

1. In order to increase our physical power through raising the amount of Hb to normal level and thus enrich our national power, it is earnestly required to improve the general eating habits in the direction of taking enough animal protein (nutrition food) that is required to form Hb and adequate administrative procedures of the nursery school are to be taken at the same time. 2. The genetic amentia's development of skeleton is generally under the normal level. And so their physical condition should be inferior to the standard growth rate of the same age. But the fact is that their physical growth is almost the same as the same age with only few exceptions. Besides, considering the fact that their amount of Hb is less than that of the normal level, I think we can conclude that the majority of the amentia in the nursery school were malnutrition during their prenatal period or during their infancy. We need continuous statistical study concerning many amentia that is scattered all part of our country, to make our amentia's hereditary transmission and the expression clear. And so the Intelligence Quotient of the amentia are from 26 to 80, we consider to need nourishing meal in ordinary times to make more efficient development of intellectual faculties. 3. As to the relation between blood type and disease, there are much debates going on in many countries. To get more apodictic results, however, continuous study is desired to be made in the future.

• The Korean Journal of Emergency Medical Services
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• v.13 no.3
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• pp.41-58
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• 2009

Objective : The purpose of this study is to identify actual operations and issues of wireless paging system operation for the aged living alone as the end users of wireless paging system primarily in Gwangyang city, and thereby to explore possible advanced and integrated ways to promote social safety network for the aged. Methods : The survey tool used in this study was a structured questionnaire form consisting of question items. The researcher hereof conducted this survey by means of direct visit and interview during two seasons, i.e. from February to August, 2008 and from December 2008 to March 2009, respectively. Results : 1) For general demographic characteristics, it was found that 90.9% of all respondents were women and 61.2% of all respondents were at age 75 to 84. for health conditions, it was found that more than 90% of all respondents often took medicines due to their unhealthy body, and most of respondents suffered from musculoskeletal diseases 79.3% and circulatory diseases 61.6%. for walking capacity, it was found that 45.5% of all respondents used walking aids, and disable respondents (11.5% of all respondents) were represented primarily by those with physical disability (52.6% of disable respondents). for actual use of medical institutions, it was found 47.3% of all respondents relied on local clinics, since they preferred neighborhood hospitals or clinics they can trust for medical care. for social activities and supports, it was found that 43.6% respondents had 'needs for assistance at times' and 33.9% respondents have 'no need for assistance'. And it was found that the major difficulties in living alone at old age were represented primarily by health problems 37.8% and economic difficulties 33.5%. 2) For characteristics related to wireless paging system, it was found that 90.3% respondents used wireless paging system recommended by firemen, and 28.5% respondents used this system. and it was found that 59.6% respondents used this system once, and 85.2% respondents used it because of acute or chronic diseases. more than 90% respondents thought that they knew about wireless paging system and considered themselves safe, but 83.6% respondents didn't attach a remote control on their upper clothes, and even 49.1% respondents turned off the power of wireless paging system due to their concern about electricity bill and noise. 3) It was found that 83.6% respondents felt it necessary to use wireless paging system, and wireless paging users felt more satisfied with using the system than non-users, and 50.7% showed high satisfaction at certain psychological benefits like 'confidence in coping with critical situations' and 'a sense of relief'. In addition, it was found that some respondents who answered that 'they didn't turn off the paging system as they knew how it works' and those who answered that they knew 'how to use it' showed relatively high satisfaction. And some respondents who kept it well and felt it necessary also showed high satisfaction. 4) It was found that the level of satisfaction our respondents felt with using wireless paging system varied significantly availability($x^{2}$ = 12.759, p = .002), psychological advantages($x^{2}$ = 12.174, p = .002), knowledge about how to use system($x^{2}$ = 7.021, p = .016), power on/off($x^{2}$ = 13.221, p = .001), level of knowledge about system($x^{2}$ = 21.002, p = .000), maintenance($x^{2}$ = 9.871, p = .007) and level of necessity($x^{2}$ = 34.939, p = .000) on the statistical basis.

• The Korean Journal of Applied Statistics
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• v.36 no.1
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• pp.49-62
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• 2023

Solar energy, which is rapidly increasing in proportion, is being continuously developed and invested. As the installation of new and renewable energy policy green new deal and home solar panels increases, the supply of solar energy in Korea is gradually expanding, and research on accurate demand prediction of power generation is actively underway. In addition, the importance of solar radiation prediction was identified in that solar radiation prediction is acting as a factor that most influences power generation demand prediction. In addition, this study can confirm the biggest difference in that it attempted to predict solar radiation using medium-term forecast weather data not used in previous studies. In this paper, we combined the multi-linear regression model, KNN, random fores, and SVR model and the clustering technique, K-means, to predict solar radiation by hour, by calculating the probability density function for each cluster. Before using medium-term forecast data, mean absolute error (MAE) and root mean squared error (RMSE) were used as indicators to compare model prediction results. The data were converted into daily data according to the medium-term forecast data format from March 1, 2017 to February 28, 2022. As a result of comparing the predictive performance of the model, the method showed the best performance by predicting daily solar radiation with random forest, classifying dates with similar climate factors, and calculating the probability density function of solar radiation by cluster. In addition, when the prediction results were checked after fitting the model to the medium-term forecast data using this methodology, it was confirmed that the prediction error increased by date. This seems to be due to a prediction error in the mid-term forecast weather data. In future studies, among the weather factors that can be used in the mid-term forecast data, studies that add exogenous variables such as precipitation or apply time series clustering techniques should be conducted.

• Journal of Korean Dental Hygiene Science
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• v.1 no.2
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• pp.9-19
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• 2018

The purpose of this study was to examine the state of conflicts among dental health care workers. A survey was conducted on 266 dental hygienists and nursing assistants who worked in dental institutions from September 12 to November 13, 2017, and SPSS(statistical package for the social science) version 20.0 was employed to analyze the collected data. The findings of the study were as follows: 1. The most common reason of the dental hygienists for turnover was working hours and heavy workload(24.6%), followed by pay (22.6%), conflicts with dentists(16.0%) and conflicts with colleagues (11.3%). The most dominant reason of the nursing assistants for turnover was pay(31.1%), followed by working hours(24.4%), heavy workload(17.8%), conflicts with dentists(15.6%) and conflicts with colleagues(8.9%). 2. The largest reason for unsuccessful communication with dentists was that heavy workload reduced the opportunity to communicate well(54.5%). The second biggest reason was that they couldn't communicate well though they had the opportunity(24.0%), and the third greatest reason was that they tended to lag behind dentists in terms of professional knowledge(16.9%). 3. The biggest reason for unsuccessful communication among the dental health care workers was that they didn't have a lot of chances to communicate well on account of heavy workload(41.0%). The second largest reason was the differences in professional knowledge(24.9%), and the third greatest reason was that they couldn't communicate well though they had the chance(23.7%). 4. The most dominant reason for conflicts with dentists was the difference in power(24.0%), followed by poor communication skills(22.1%) and a lack of mutual respect(18.1%). But the opinions of the nursing assistants were different from those of the dental hygienists, as they cited poor communication skills as the most common reason, which was followed by the difference in power and a shortage of understanding of each other's work. 5. The most common reason for conflicts among the dental health care workers was a shortage of communication and communication skills(22.9%), and the second most dominant reasons were a lack of mutual respect and poor understanding of each other's work(17.5%), followed by a lack of mutual respect(17.2%). 6. As to the ways of resolving conflicts with dentists, the most common case was making some mutual concessions to compromise (28.9%), followed by delivering opinions through the staff meeting (23.9%), resolving conflicts by candidly exchanging opinions(15.8%), avoiding each other in moderation(11.7%) and following the opinions or assertions of dentists(1.3%). 7. Concerning the conflict resolution methods among the dental health care workers, the most prevalent way was making some mutual concessions to compromise(36.4%), followed by resolving conflicts by candidly exchanging opinions(23.0%) and conveying opinions through the staff meeting(18.5%). 8. Regarding communication among the dental health care workers, the dental hygienists(3.53±.729) considered themselves to be better at communicating than the nursing assistants(3.29±.745) did(p<0.05), and the dental hygienists(3.45±.809) who thought there was respectful treatment among workers who were different in occupational categories found themselves to be better than the nursing assistants(3.21±.952) who had the same thought did(p<0.05). As a result of analyzing whether frequent job-related meetings occurred among the workers whose occupational categories were different, the dental hygienists(3.05±.975) perceived that there were more frequent meetings than the nursing assistants(2.67±.955) did (p<0.01).

• 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.

• Asia Marketing Journal
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• v.14 no.1
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• pp.1-24
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• 2012

Nowadays, customer satisfaction has been one of company's major objectives, and the index to measure and communicate customer satisfaction has been generally accepted among business practices. The major issues of CSI(customer satisfaction index) are three questions, as follows: (a)what level of customer satisfaction is tolerable, (b)whether customer satisfaction and company performance has positive causality, and (c)what to do to improve customer satisfaction. Among these, the second issue is recently attracting academic research in several perspectives. On this study, the second issue will be addressed. Many researchers including Anderson have regarded customer satisfaction as core competencies, such as brand equity, customer equity. They want to verify following causality "customer satisfaction → market performance(market share, sales growth rate) → financial performance(operating margin, profitability) → corporate value performance(stock price, credit ratings)" based on the process model of marketing performance. On the other hand, Insoo Jeon and Aeju Jeong(2009) verified sequential causality based on the process model by the domestic data. According to the rejection of several hypotheses, they suggested the balance model of marketing performance as an alternative. The objective of this study, based on the existing process model, is to examine the causal relationship between customer satisfaction and corporate value performance. Anderson and Mansi(2009) proved the relationship between ACSI(American Customer Satisfaction Index) and credit ratings using 2,574 samples from 1994 to 2004 on the assumption that credit rating could be an indicator of a corporate value performance. The similar study(Sangwoon Yoon, 2010) was processed in Korean data, but it didn't confirm the relationship between KCSI(Korean CSI) and credit ratings, unlike the results of Anderson and Mansi(2009). The summary of these studies is in the Table 1. Two studies analyzing the relationship between customer satisfaction and credit ratings weren't consistent results. So, in this study we are to test the conflicting results of the relationship between customer satisfaction and credit ratings based on the research model considering Korean credit ratings. To prove the hypothesis, we suggest the research model as follows. Two important features of this model are the inclusion of important variables in the existing Korean credit rating system and government support. To control their influences on credit ratings, we included three important variables of Korean credit rating system and government support, in case of financial institutions including banks. ROA, ER, TA, these three variables are chosen among various kinds of financial indicators since they are the most frequent variables in many previous studies. The results of the research model are relatively favorable : R², F-value and p-value is .631, 233.15 and .000 respectively. Thus, the explanatory power of the research model as a whole is good and the model is statistically significant. The research model has good explanatory power, the regression coefficients of the KCSI is .096 as positive(+) and t-value and p-value is 2.220 and .0135 respectively. As a results, we can say the hypothesis is supported. Meanwhile, all other explanatory variables including ROA, ER, log(TA), GS_DV are identified as significant and each variables has a positive(+) relationship with CRS. In particular, the t-value of log(TA) is 23.557 and log(TA) as an explanatory variables of the corporate credit ratings shows very high level of statistical significance. Considering interrelationship between financial indicators such as ROA, ER which include total asset in their formula, we can expect multicollinearity problem. But indicators like VIF and tolerance limits that shows whether multicollinearity exists or not, say that there is no statistically significant multicollinearity in all the explanatory variables. KCSI, the main subject of this study, is a statistically significant level even though the standardized regression coefficients and t-value of KCSI is .055 and 2.220 respectively and a relatively low level among explanatory variables. Considering that we chose other explanatory variables based on the level of explanatory power out of many indicators in the previous studies, KCSI is validated as one of the most significant explanatory variables for credit rating score. And this result can provide new insights on the determinants of credit ratings. However, KCSI has relatively lower impact than main financial indicators like log(TA), ER. Therefore, KCSI is one of the determinants of credit ratings, but don't have an exceedingly significant influence. In addition, this study found that customer satisfaction had more meaningful impact on corporations of small asset size than those of big asset size, and on service companies than manufacturers. The findings of this study is consistent with Anderson and Mansi(2009), but different from Sangwoon Yoon(2010). Although research model of this study is a bit different from Anderson and Mansi(2009), we can conclude that customer satisfaction has a significant influence on company's credit ratings either Korea or the United State. In addition, this paper found that customer satisfaction had more meaningful impact on corporations of small asset size than those of big asset size and on service companies than manufacturers. Until now there are a few of researches about the relationship between customer satisfaction and various business performance, some of which were supported, some weren't. The contribution of this study is that credit rating is applied as a corporate value performance in addition to stock price. It is somewhat important, because credit ratings determine the cost of debt. But so far it doesn't get attention of marketing researches. Based on this study, we can say that customer satisfaction is partially related to all indicators of corporate business performances. Practical meanings for customer satisfaction department are that it needs to actively invest in the customer satisfaction, because active investment also contributes to higher credit ratings and other business performances. A suggestion for credit evaluators is that they need to design new credit rating model which reflect qualitative customer satisfaction as well as existing variables like ROA, ER, TA.

• Journal of Veterinary Clinics
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• v.24 no.4
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• pp.514-521
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• 2007

The sympathetic nerve block improves the blood flow in the innervated regions. For this region, the sympathetic nerve block has been performed in the neural and cerebral disorders. However, the cerebral blood flow regulation of the cranial cervical ganglion block in dogs have not been well defined and the correlation to the changes in the cerebral circulation and the changes in the electroencephalogram is not well defined in dogs yet. Therefore, we investigated the hypothesis that changes in the EEG could be affected by the changes in cerebral blood flow following the cranial cervical ganglion block in dogs. Twenty five beagle dogs were divided into 3 groups; group I(LCCGB, n=10) underwent left sided cranial cervical ganglion block using the 1% lidocaine, group II(L, n=10) injected the 1% lidocaine into the right or left sided digastricus muscle, group III(N/SCCGB, n=5, served as control) underwent the left sided cranial cervical ganglion block using saline. A statistical difference was not found between the control group and the LCCGB group in the 95% spectral edge frequency(SEF) and the median frequency(MF). In the relative band power, the $\delta$ frequency was decreased during 5-25 min, while the $\alpha$ frequency was increased during the same time(p<0.05). But the $\theta$ frequency and the $\beta$ frequency were not shown the significant changes compared with the control group during the same time(p<0.05). These results suggest that the left cranial cervical ganglion block does not induce the change of the cerebral blood flow and its effect is insignificant.

• Journal of Korean Academy of Nursing
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• v.13 no.1
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• pp.7-21
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• 1983

For the flexible and rational distribution of limited existing health resources based on measurements of individual risk, the socalled Risk Approach is being proposed by the World Health Organization as a managerial tool in maternal and child health care program. This approach, in principle, puts us under the necessity of developing a technique by which we will be able to measure the degree of risk or to discriminate the future outcomes of pregnancy on the basis of prior information obtainable at prenatal care delivery settings. Numerous recent studies have focussed on the identification of relevant risk factors as the Prior infer mation and on defining the adverse outcomes of pregnancy to be dicriminated, and also have tried on how to develope scoring system of risk factors for the quantitative assessment of the factors as the determinant of pregnancy outcomes. Once the scoring system is established the technique of classifying the patients into with normal and with adverse outcomes will be easily de veloped. The scoring system should be developed to meet the following four basic requirements. 1) Easy to construct 2) Easy to use 3) To be theoretically sound 4) To be valid In searching for a feasible methodology which will meet these requirements, the author has attempted to apply the“Likelihood Method”, one of the well known principles in statistical analysis, to develop such scoring system according to the process as follows. Step 1. Classify the patients into four groups: Group $A_1$: With adverse outcomes on fetal (neonatal) side only. Group $A_2$: With adverse outcomes on maternal side only. Group $A_3$: With adverse outcome on both maternal and fetal (neonatal) sides. Group B: With normal outcomes. Step 2. Construct the marginal tabulation on the distribution of risk factors for each group. Step 3. For the calculation of risk score, take logarithmic transformation of relative proport-ions of the distribution and round them off to integers. Step 4. Test the validity of the score chart. h total of 2, 282 maternity records registered during the period of January 1, 1982-December 31, 1982 at Ewha Womans University Hospital were used for this study and the“Questionnaire for Maternity Record for Prenatal and Intrapartum High Risk Screening”developed by the Korean Institute for Population and Health was used to rearrange the information on the records into an easy analytic form. The findings of the study are summarized as follows. 1) The risk score chart constructed on the basis of“Likelihood Method”ispresented in Table 4 in the main text. 2) From the analysis of the risk score chart it was observed that a total of 24 risk factors could be identified as having significant predicting power for the discrimination of pregnancy outcomes into four groups as defined above. They are: (1) age (2) marital status (3) age at first pregnancy (4) medical insurance (5) number of pregnancies (6) history of Cesarean sections (7). number of living child (8) history of premature infants (9) history of over weighted new born (10) history of congenital anomalies (11) history of multiple pregnancies (12) history of abnormal presentation (13) history of obstetric abnormalities (14) past illness (15) hemoglobin level (16) blood pressure (17) heart status (18) general appearance (19) edema status (20) result of abdominal examination (21) cervix status (22) pelvis status (23) chief complaints (24) Reasons for examination 3) The validity of the score chart turned out to be as follows: a) Sensitivity: Group $A_1$: 0.75 Group $A_2$: 0.78 Group $A_3$: 0.92 All combined : 0.85 b) Specificity : 0.68 4) The diagnosabilities of the“score chart”for a set of hypothetical prevalence of adverse outcomes were calculated as follows (the sensitivity“for all combined”was used). Hypothetidal Prevalence : 5％ 10％ 20％ 30％ 40％ 50％ 60％ Diagnosability : 12% 23% 40% 53% 64% 75% 80%.

• Journal of the Korean earth science society
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• v.41 no.2
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• pp.95-110
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• 2020

Comparisons between two different surface temperatures from high-resolution ECMWF ReAnalysis 5 (ERA5) and Automated Synoptic Observing System (ASOS) observations were performed to investigate the reliability of the new reanalysis data over South Korea. As ERA5 has been recently produced and provided to the public, it will be highly used in various research fields. The analysis period in this study is limited to 1999-2018 because regularly recorded hourly data have been provided for 61 ASOS stations since 1999. Topographic characteristics of the 61 ASOS locations are classified as inland, coastal, and mountain based on Digital Elevation Model (DEM) data. The spatial distributions of whole period time-averaged temperatures for ASOS and ERA5 were similar without significant differences in their values. Scatter plots between ASOS and ERA5 for three different periods of yearlong, summer, and winter confirmed the characteristics of seasonal variability, also shown in the time-series of monthly error probability density functions (PDFs). Statistical indices NMB, RMSE, R, and IOA were adopted to quantify the temperature differences, which showed no significant differences in all indices, as R and IOA were all close to 0.99. In particular, the daily mean temperature differences based on 1-hour-averaged temperature had a smaller error than the classical daily mean temperature differences, showing a higher correlation between the two data. To check if the complex topography inside one ERA5 grid cell is related to the temperature differences, the kurtosis and skewness values of 90-m DEM PDFs in a ERA5 grid cell were compared to the one-year period amplitude among those of the power spectrum in the time-series of monthly temperature error PDFs at each station, showing positive correlations. The results account for the topographic effect as one of the largest possible drivers of the difference between ASOS and ERA5.