• Journal of the Korean Geotechnical Society
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• v.21 no.8
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• pp.63-72
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• 2005

Rocks are dumped to soft marine ground in order to improve trafficability and construction conditions in the tideland reclamation construction sites. Though this rock layer under earth fill has caused in a serious seepage problems after construction, seepage behaviors of this embankment structure is not correctly investigated. Water flow through rock layers is, in general, known as Non-Darcy's flow. However, the embedded rock layer under earth fill is not known whether its flow is governed by Darcy's or Non-Darcy's law. Therefore, a numerical analysis, laboratory model test and filed investigations were performed for analyzing the those seepage characteristics in this research. Results show that there is significance of $95\%$ of confidence between observed heads and seepage rates, and the calculated ones by SAMTLE which is developed under the assumption that the water flows through the two-layer system obey the Darcy's flow. And after operating the hydraulic gradient(i) of $0.10\~0.55$ upon laboratory model, these seepage characteristics of the embedded rock layer show that Reynolds Numbers are less than 10 and the relationship between these velocities of rock layer(v) and hydraulic gradients(i) is linearly proportional with more than 0.79 of the coefficient of correlation $(R^2)$. And the Reynolds Number of the velocity calculated by the relation of v=ki in the embedded rock layer of OO sea dike is $1\~6$. It shows also laminar flow. Based on these results, it is concluded that the seepage characteristics of embedded rock layer under earth fill can be laminar and Darcy's flow.

• Journal of the Korea Society for Simulation
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• v.21 no.1
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• pp.81-88
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• 2012

In the M&S filed, The Battle Lab is available for acquisition, design, development tool, validation test, and training in the weapon system of development process. Recently, the Battle Lab in the military of Korea is still in an early stage, in spite of importance of battle lab construction. In the environment of network centric warfare, a practical use of the M&S which is connecting live, virtual and constructive model can be applied to all field of System Engineering process. It is necessary thar the Battle Lab is not restricted by time and space, and is possible for the technical implementation. In this paper, to guarantee the interoperability of live and virtual simulation, virtual simulators connect live simulators by using the tactical data link. To guarantee the interoperability of virtual and constructive simulation, both virtual simulators and constructive simulators use the RTI which is the standard tool of M&S. We propose the System that constructed the Air Defence Battle Lab. In case of the approach of target tracks, The Air Defence Battle Lab is the system for the engagement based on a command of an upper system in the engagement weapon system. Constructive simulators which are target track, missile, radar, and launcher simulator connect virtual simulators which are MCRC, battalion, and fire control center simulators using the RPR-FOM 1.0 that is a kind of RTI FOM. The interoperability of virtual simulators and live simulators can be guaranteed by the connection of the tactical data links which are Link-11B and ATDL-1.

• Journal of The Korean Association For Science Education
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• v.37 no.5
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• pp.879-889
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• 2017

The purpose of this study is to develop the evaluation criteria for students' research reports on online science inquiry problems that promote thinking abilities. The steps of developing the evaluation criteria are as follows; First, based on previous study results and literature review, the evaluation categories of the science inquiry contents were determined: 1) knowledge, 2) logical and analytical thinking, 3) critical thinking, 4) science process skills, 5) problem-solving, and 6) creative thinking. Second, evaluation criteria are developed according to the following steps: 1) define each category, 2) identify sub-category, 3) develop evaluation criteria for all categories that could serve as guidelines in the development of scoring rubrics, and 4) expert validation processes were performed. Finally, the usability test for these evaluation categories and criteria were done by being applied to the development of real scoring rubrics for 24 problems included in e-learning contents. Then the users' feedbacks were filed and the implications of this study were discussed.

• Journal of Veterinary Clinics
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• v.33 no.2
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• pp.102-106
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• 2016

More than 20 years after the first report of porcine reproductive and respiratory syndrome virus (PRRSV) in Korea, the disease is still having major impact on domestic pig health and relevant industries. Although ELISA tests are commonly used by veterinarians to guide herd management, data on diagnostic performance of the test in field settings are very limited. The objective of this study was to evaluate two commercially available PRRSV ELISA (IDEXX PRRS X3 ELISA and Bionote PRRSV ELISA 4.0) to detect antibodies against PRRSV on serum samples. To this end, a total of 1,108 sera were recruited from 35 swine farms located in Gyeonggi province and tested at the Gyeonggi Province Veterinary Service Center. All tests were performed according to the manufacturer's instructions, by laboratory technicians who routinely perform PRRS testing on blood samples. Samples were collected from two sources of swine populations with different PRRS prevalence; 60 samples (5.4%) were originated from breeding farms and the remaining 1,048 samples (94.6%) were from farrow-to-finish farms. We applied Bayesian latent class model (LCM) for two-tests in the two-population when the accuracy of the gold standard is not available. The model estimated that Bionote ELISA was a bit more specific but slightly less sensitive. The estimated sensitivity and specificity of the IDEXX ELISA were 99.8% (95% CI 98.1-100%) and 86.4% (95% CI 81.4-96.5%), respectively. Sensitivity, specificity, positive predictive value and negative predictive value for Bionote kit were 98.7% (95% CI 92.8-100%), 89.8% (95% CI 86.2-93.1%), 93.8% (95% CI 91.5-96.0%), and 97.8% (95% CI 87.1-100%), respectively. Based on the Bayesian 95% credible intervals, the sensitivity and specificity of the two ELISAs were not significantly different each other when assuming that two kits were imperfect, indicating that two kits performed equally well in terms of sensitivity and specificity in our filed setting.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.26 no.3
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• pp.185-200
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• 2021

The Marine Environment QA/QC management system has been operated since 2010 to secure the reliability of data and improve the analysis capabilities of measurement and analysis institutions. From 2010 to 2020, the cumulative number of measurement and analysis institutions participated in the QA/QC management system was 266. And the number of certificates issued by the ministry of oceans and fisheries is 182. A total of 32 reference materials for proficiency testing and interlaboratory comparisons have been developed. They were first developed focusing on items (Nutrients, COD) commonly analyzed in marine environmental measuring network, marine pollution impact surveys, sea area utilization impact assessment, deepsea water surveys, and information network on fishing ground environments. In addition, it is time to expand the filed of the QA/QC management system, such as seawater temperature, salinity, PCBs and PAHs in sediments, which are mainly analyzed in most monitoring programs. On-site assessment has been conducted for 162 laboratories according to ISO/IEC 17025 to evaluate their conformity of the quality management system and deficiency. In terms of management and technology requirements, about 4.2% of organizations showed insufficient division of duties among employees 8.7% of them revealed the lack of employee training. By test item, about 6.3% of organizations showed the lack of standard substance management and the state of the cleaning glassware was pointed out in about 5.4% of them. The QA/QC management system should be continuously supplemented by identifying the causes of nonconformities and area for improvement.

• Korean Journal of Occupational Health Nursing
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• v.13 no.1
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• pp.5-18
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• 2004

This study aims to investigate the use state of the health service computerization system in the occupational nursing field and the occupational nursers' satisfaction level, and provide basic data to promote the development of the health service computerization system for the nursing field. For this study, a questionnaire was provided to 118 occupational nurses who belong to Busan and Gyeongnam branches of KAOHN(Korean Association of Occupational Health Nurses) for 2 months (from Dec. 1, 2002 to Jan. 31, 2003). A tool of Choi Yong-Heui(2000) was used to investigate the satisfaction level of using the health service computerization system. The collected materials were analyzed in real number and percentage, average and standard deviation, t-test and ANOVA by using the SPSS WIN 10.0 program. This study is summarized as follows: 1. The average age was $31.99{\pm}5.58$ old in this study. The married were 54.2%. Participants who graduated from a junior college was 76.9%. The average service period was $4.48{\pm}4.68$ years. In service types, 79.7% of participants served in a health care center. The average service period was $3.22{\pm}2.89$ years. The service place which had 1000 workers or more was 35.6%. 2. Only 20.3% of participants in this study had a computer use education. 3. The field who participants used mostly was communication/internet, $3.29{\pm}.85$ hours in average. 4. 97.1% of occupational fields had computers and peripheral devices: 71.4% in pentium computer, 42.8% in the hard disk capacity of 20-29GB, 60.0% in 15 inch monitors, 86.2% in printers, 18.1% in digital cameras, 12.4% in LAN, and 9.5% in scanners. 80.1% of the occupational fields which were objects of study could use communication. 5. The occupational fields which did not introduced the health service computerization system were 62.8%. The main cause was attributable to entrepreneurs' insufficient recognition 66.6%. 51.5% of the entrepreneurs did not have an introduction plan. 37.2% of participating companies had the health service computerization system. 56.4% of them introduced it since the year 2000. 81.6% of the introduction motivation aimed to the efficiency of health service. The most issue upon introduction was insufficient understanding of a person in charge - 25.6%. The in-house development of the system covered 56.4%. 61.5% of the participants accepted their demands from the first stage of development. The direct effect of computerization showed the increase of 25.9% in the quickness and continuity of service treatment, and 25.9% in the serviceability of statistical treatment. 6. 22.0% of the participants had a computerization system use education. 69.2% of them had a in-house education. An educational method by nurses who used the computerization system was 76.9%. 92.3% of the education was helpful for practical duties. 7. An analysis of the computer use by health service fields showed that the medicine management in a health management field was 15.9%. the work environment measuring management in a work environment filed was 32.9%. the employment. general and special examination management in a heal th management field was 61.1 %. the various reports management in an administrative field was 64%. the health education data preparation management in an educational field was 58.0%. and the medicine and expendables management in an equipment management field was 51.6%. An analysis of the computerization system use showed that the various statistical data manage in a health management field was 13.0%. the work environment measuring management in a health management field was 34.8%. the personal disease management in a health management field was 51.9%. the heal education data preparation management in an educational field was 54.5%. and the equipment management of health care centers in an equipment management field was 52.6%. 8. 31.6% of the participants wanted that health service computerization system would include the generals of health services. 42.4% of the participants thought that first of all. the aggressive interest and investment of employers were required to build the health service computerization system. 9. The participants' satisfaction level on the computerization system use was $3.51{\pm}.57$ points. An analysis by each factor showed $3.62{\pm}.68$ points in a service change factor. $3.15{\pm}.63$ points in a computer program use factor, and $3.45{\pm}.71$ points in a continuous computerization use factor. 10. An analysis of the computerization system use by general characteristics of participants showed that the married (p = .022) had the satisfaction level higher than the unmarried. 11. The satisfaction level of the computerization system use by participants' computer use ability tended to be higher in proportion to the increase of computer use abilities in spreadsheet (F=2.606. p=.048). presentation (F=3.62. p=.012) and communication/internet(F=2.885. p=.0321. Based on the study results mentioned above. I will suggest as follows : The nationwide enlargement and repetition study is required for occupational nurses who serve in occupational nursing fields. The computerization system in a health service field is inferior comparing with other fields. The computerization system standard by business types and characteristics should be prepared through employers's aggressive participation and national support. Therefore various statistical data which occurs in occupational fields will be managed systematically and efficiently. A regular and systematic computer education plan for occupational nurses in charge of health services in the filed is urgently required to efficiently manage and improve the health of on-site workers.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.121-139
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• 2014

Predicting corporate failure has been an important topic in accounting and finance. The costs associated with bankruptcy are high, so the accuracy of bankruptcy prediction is greatly important for financial institutions. Lots of researchers have dealt with the topic associated with bankruptcy prediction in the past three decades. The current research attempts to use ensemble models for improving the performance of bankruptcy prediction. Ensemble classification is to combine individually trained classifiers in order to gain more accurate prediction than individual models. Ensemble techniques are shown to be very useful for improving the generalization ability of the classifier. Bagging is the most commonly used methods for constructing ensemble classifiers. In bagging, the different training data subsets are randomly drawn with replacement from the original training dataset. Base classifiers are trained on the different bootstrap samples. Instance selection is to select critical instances while deleting and removing irrelevant and harmful instances from the original set. Instance selection and bagging are quite well known in data mining. However, few studies have dealt with the integration of instance selection and bagging. This study proposes an improved bagging ensemble based on instance selection using genetic algorithms (GA) for improving the performance of SVM. GA is an efficient optimization procedure based on the theory of natural selection and evolution. GA uses the idea of survival of the fittest by progressively accepting better solutions to the problems. GA searches by maintaining a population of solutions from which better solutions are created rather than making incremental changes to a single solution to the problem. The initial solution population is generated randomly and evolves into the next generation by genetic operators such as selection, crossover and mutation. The solutions coded by strings are evaluated by the fitness function. The proposed model consists of two phases: GA based Instance Selection and Instance based Bagging. In the first phase, GA is used to select optimal instance subset that is used as input data of bagging model. In this study, the chromosome is encoded as a form of binary string for the instance subset. In this phase, the population size was set to 100 while maximum number of generations was set to 150. We set the crossover rate and mutation rate to 0.7 and 0.1 respectively. We used the prediction accuracy of model as the fitness function of GA. SVM model is trained on training data set using the selected instance subset. The prediction accuracy of SVM model over test data set is used as fitness value in order to avoid overfitting. In the second phase, we used the optimal instance subset selected in the first phase as input data of bagging model. We used SVM model as base classifier for bagging ensemble. The majority voting scheme was used as a combining method in this study. This study applies the proposed model to the bankruptcy prediction problem using a real data set from Korean companies. The research data used in this study contains 1832 externally non-audited firms which filed for bankruptcy (916 cases) and non-bankruptcy (916 cases). Financial ratios categorized as stability, profitability, growth, activity and cash flow were investigated through literature review and basic statistical methods and we selected 8 financial ratios as the final input variables. We separated the whole data into three subsets as training, test and validation data set. In this study, we compared the proposed model with several comparative models including the simple individual SVM model, the simple bagging model and the instance selection based SVM model. The McNemar tests were used to examine whether the proposed model significantly outperforms the other models. The experimental results show that the proposed model outperforms the other models.

• Restorative Dentistry and Endodontics
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• v.32 no.5
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• pp.469-475
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• 2007

The purpose of this study was to evaluate the effect of a new resin monomer on the microleakage of composite resin restorations. By adding new methoxylated Bis-GMA (Bis-M-GMA, 2,2-bis[4-(2-methoxy-3-methacryloyloxy propoxy) phenyl] propane) having low viscosity, the content of TEGDMA which has adverse effects on polymerization shrinkage might be decreased. As a result, microleakage might be improved. $2\;mm\;{\times}\;2\;mm\;{\times}\;2\;mm$ cavities with occlusal margins in enamel and gingival margins in dentin were prepared on buccal and lingual surfaces of 40 extracted human premolars. Prepared teeth were randomly divided into four groups and restored with Clearfil SE bond (Kuraray, Japan) and one of experimental composite resins; EX1, Experimental composite resin1 (Bis-M-GMA/TEGDMA = 95/5 wt%, 40 mm nanofillers); EX2, Experimental composite resin2 (Bis-M-GMA/TEGDMA = 95/5 wt%, 20 mm nanofillers); EX3, Experimental composite resin3 (Bis-GMA/TEGDMA = 70/30 wt%, 40 nm nanofillers); and Filtek Z250 (3M ESPE, USA) was filed as a control group. The restored teeth were thermocycled, and immersed in 2% methylene blue solution for 24 hours. The teeth were sectioned buccolingually with a low speed diamond saw and evaluated for microleakage under stereomicroscope. The data were statistically analyzed by Pearson Chi-Square test and Fisher Exact test (p = 0.05). The microleakage scores seen at the enamel margin were significantly lower than those of dentin margin (p = 0.007). There were no significant differences among the composite resins in the microleakage scores within each margin (p > 0.05). Bis-M-GMA, a new resin monomer having low viscosity, might in part replace high viscous Bis-CMA and might improve the quality of composite resin.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.31 no.1
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• pp.71-76
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• 1998

To know the antibiotic specificity of a Dinoflagellate, Cochlodinium polykrikoides, we investigated the survival time of C. polykrikoides against several concentrations of antibiotics and judged the selective specificity of antibiotics based on the $LT_50$ ($50\%$ of lethal time). The result showed that C. polykrikoides was sensitive to tetracycline and chloramphenicol, and resistant to polymixin-B, ampicillin, penicillin-G, dihydrostreptomycin, and neomycin. In the case of sensitive antibiotics to C. polykrikoides, tetracycline and chloramphenicol, the safety concentrations of both antibiotics were determined and the antibiotic specificity based or the plotted survival curve was analyzed. Before antibiotic treatment, we tested the antibiotic susceptibility of the contaminated bacterial population in tile culture of C. polykrikoides, and decided the proper kinds of antibiotics and concentrations before percoll-centrifugation. By percoll-centrifugation, we reduced bacteria, removed fungi, collected the algal pellet, and made axonic culture by antibiotic cascade procedure based on the result of antibiotic susceptibility test. We observed that axonic C. polykrikoides culture entered the logarthmic phase of growth when cell density was over 740 cells/ml and propagated to 5,800 cells/ml maximally. Divisions per day, k value of C. polykrikoides represented a good index for growth at the low density of cells. There was a highest k value shift before reaching to the logarithmic phase. We suggested that the preceeding highest k value shift stage is a good indicator for accurate broadcasting for red. tide blooming in the field, and the stage is also a good time for controlling red tide blooming in the filed, either.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.139-157
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• 2016

Bankruptcy involves considerable costs, so it can have significant effects on a country's economy. Thus, bankruptcy prediction is an important issue. Over the past several decades, many researchers have addressed topics associated with bankruptcy prediction. Early research on bankruptcy prediction employed conventional statistical methods such as univariate analysis, discriminant analysis, multiple regression, and logistic regression. Later on, many studies began utilizing artificial intelligence techniques such as inductive learning, neural networks, and case-based reasoning. Currently, ensemble models are being utilized to enhance the accuracy of bankruptcy prediction. Ensemble classification involves combining multiple classifiers to obtain more accurate predictions than those obtained using individual models. Ensemble learning techniques are known to be very useful for improving the generalization ability of the classifier. Base classifiers in the ensemble must be as accurate and diverse as possible in order to enhance the generalization ability of an ensemble model. Commonly used methods for constructing ensemble classifiers include bagging, boosting, and random subspace. The random subspace method selects a random feature subset for each classifier from the original feature space to diversify the base classifiers of an ensemble. Each ensemble member is trained by a randomly chosen feature subspace from the original feature set, and predictions from each ensemble member are combined by an aggregation method. The k-nearest neighbors (KNN) classifier is robust with respect to variations in the dataset but is very sensitive to changes in the feature space. For this reason, KNN is a good classifier for the random subspace method. The KNN random subspace ensemble model has been shown to be very effective for improving an individual KNN model. The k parameter of KNN base classifiers and selected feature subsets for base classifiers play an important role in determining the performance of the KNN ensemble model. However, few studies have focused on optimizing the k parameter and feature subsets of base classifiers in the ensemble. This study proposed a new ensemble method that improves upon the performance KNN ensemble model by optimizing both k parameters and feature subsets of base classifiers. A genetic algorithm was used to optimize the KNN ensemble model and improve the prediction accuracy of the ensemble model. The proposed model was applied to a bankruptcy prediction problem by using a real dataset from Korean companies. The research data included 1800 externally non-audited firms that filed for bankruptcy (900 cases) or non-bankruptcy (900 cases). Initially, the dataset consisted of 134 financial ratios. Prior to the experiments, 75 financial ratios were selected based on an independent sample t-test of each financial ratio as an input variable and bankruptcy or non-bankruptcy as an output variable. Of these, 24 financial ratios were selected by using a logistic regression backward feature selection method. The complete dataset was separated into two parts: training and validation. The training dataset was further divided into two portions: one for the training model and the other to avoid overfitting. The prediction accuracy against this dataset was used to determine the fitness value in order to avoid overfitting. The validation dataset was used to evaluate the effectiveness of the final model. A 10-fold cross-validation was implemented to compare the performances of the proposed model and other models. To evaluate the effectiveness of the proposed model, the classification accuracy of the proposed model was compared with that of other models. The Q-statistic values and average classification accuracies of base classifiers were investigated. The experimental results showed that the proposed model outperformed other models, such as the single model and random subspace ensemble model.