• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.377-383
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• 2021

The purpose of this study is to present the direction of elementary school AI education by analyzing cases of classes related to AI education in actual school settings. For this purpose, 19 classes were collected as elementary school class cases based on AI education. According to the result of analyzing the class case, it was confirmed that the class was designed in a hybrid aspect of learning content and method using AI. As a result of analyzing the achievement standards and learning goals, action verbs related to memory, understanding, and application were found in 8 classes using AI from a tool perspective. When class was divided into introduction, development, and rearrangement stages, the AI education element appeared the most in the development stage. On the other hand, when looking at the ratio of learning content and learning method of AI education elements in the development stage, the learning time for approaching AI education as a learning method was overwhelmingly high. Based on this, the following implications were derived. First, when designing the curriculum for schools and grades, it should be designed to comprehensively deal with AI as a learning content and method. Second, to supplement the understanding of AI, in the short term, it is necessary to secure the number of hours in practical subjects or creative experience activities, and in the long term, it is necessary to secure information subjects.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.661-667
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• 2023

Five commercially available edible sweeteners are used as diet products because they can replace sucrose. In studies on the effects on animals and the human body, stability has been proven by excreting-oriented studies with characteristics of animal cells, and accumulation in small amounts has been ignored. On the other hand, plants can absorb, degrade, and accumulate foreign substances, so the effect of degradability and accumulation potential can be studied using plants. Metabolic effects in plants of commercially available saccharin and acesulfame potassium (Ace K) were tested using germinated barley and bean sprouts. In germinated barley and bean sprouts, saccharin and ace K showed inhibitory effects on plant growth in all organs from low concentrations in leaves, stems and roots. In addition, it can be observed that the symptoms of death appear clearly over time, so it can be seen that they are accumulated in the body of the plant. As the accumulated amount increases, the toxic effect increases and the plant reaches a state where it is unable to metabolize, turning black from the tip of the leaf and reaching a state of death. In order to remove the accumulated artificial sweetener, recovery was attempted by culturing in distilled water, but it acts as a substance that is not degraded and dies without avoiding toxicity. Saccharin and ace K cannot be excreted from the cell. Its toxic effects are thought to be persistent, inhibiting growth and eventually leading to cell death.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.14 no.1
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• pp.10-21
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• 2009

Muan Bay has extensively undertaken artificial influences through a series of construction of dams and dykes nearby resulting in a substantial increase in highest high water level. To unravel sedimentary responses to the water level rise, we collected a number of surface sediment samples and hydrodynamic data from in-situ observations of tidal currents in Muan Bay in 1998 and 2007. Comparison of the data between 1998 and 2007 shows that the relative content of coarse fractions, sand and gravel, in the sediment samples has increased with a decreased mean size, on average, from 6.2 to 5.8${\phi}$ at the expense of silt contents. Such a coarsening trend, which is more evident around high water level, particularly on the tidal flats of Dongam-ri, Guro-ri and Aphae-do, is most likely attributable to rising water level. On the other hand, an increase of fine fractions locally in the western entrance of the bay can be explained with changes in characteristics of tidal currents imposed by construction of bridges therein, such as decreased velocities and varied direction and phase of the tidal currents.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.157-166
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• 2024

The Army TIGER System, which is being deployed to implement a future combat system, is expected to bring innovative changes to the army's combat methods and comabt execution capability such as mobility, networking and intelligence. To this end, the Army will introduce various systems using drones, robots, unmanned vehicles, AI(Artificial Intelligence), etc. and utilize them in combat. The use of various unmanned vehicles and AI is expected to result in the introduction of equipment with new technologies into the army and an increase in various types of transmitted information, i.e. data. However, currently in the military, there is an acceleration in research and combat experimentations on warfigthing options using Army TIGER forces system for specific functions. On the other hand, the current reality is that research on cyber threats measures targeting information systems related to the increasing number of unmanned systems, data production, and transmission from unmanned systems, as well as the establishment of cloud centers and AI command and control center driven by the new force systems, is not being pursued. Accordingly this paper analyzes the structure and characteristics of the Army TIGER force integration system and makes suggestions for necessity of building, available cyber defense solutions and Army TIGER integrated cyber protections system that can respond to cyber threats in the future.

• International Journal of Computer Science & Network Security
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• v.24 no.9
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• pp.30-40
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• 2024

Building an accurate 3-D spatial road network model has become an active area of research now-a-days that profess to be a new paradigm in developing Smart roads and intelligent transportation system (ITS) which will help the public and private road impresario for better road mobility and eco-routing so that better road traffic, less carbon emission and road safety may be ensured. Dealing with such a large scale 3-D road network data poses challenges in getting accurate elevation information of a road network to better estimate the CO₂ emission and accurate routing for the vehicles in Internet of Vehicle (IoV) scenario. Clustering and regression techniques are found suitable in discovering the missing elevation information in 3-D spatial road network dataset for some points in the road network which is envisaged of helping the public a better eco-routing experience. Further, recently Explainable Artificial Intelligence (xAI) draws attention of the researchers to better interprete, transparent and comprehensible, thus enabling to design efficient choice based models choices depending upon users requirements. The 3-D road network dataset, comprising of spatial attributes (longitude, latitude, altitude) of North Jutland, Denmark, collected from publicly available UCI repositories is preprocessed through feature engineering and scaling to ensure optimal accuracy for clustering and regression tasks. K-Means clustering and regression using Support Vector Machine (SVM) with radial basis function (RBF) kernel are employed for 3-D road network analysis. Silhouette scores and number of clusters are chosen for measuring cluster quality whereas error metric such as MAE ( Mean Absolute Error) and RMSE (Root Mean Square Error) are considered for evaluating the regression method. To have better interpretability of the Clustering and regression models, SHAP (Shapley Additive Explanations), a powerful xAI technique is employed in this research. From extensive experiments , it is observed that SHAP analysis validated the importance of latitude and altitude in predicting longitude, particularly in the four-cluster setup, providing critical insights into model behavior and feature contributions SHAP analysis validated the importance of latitude and altitude in predicting longitude, particularly in the four-cluster setup, providing critical insights into model behavior and feature contributions with an accuracy of 97.22% and strong performance metrics across all classes having MAE of 0.0346, and MSE of 0.0018. On the other hand, the ten-cluster setup, while faster in SHAP analysis, presented challenges in interpretability due to increased clustering complexity. Hence, K-Means clustering with K=4 and SVM hybrid models demonstrated superior performance and interpretability, highlighting the importance of careful cluster selection to balance model complexity and predictive accuracy.

• Journal of Environmental Impact Assessment
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• v.26 no.2
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• pp.93-104
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• 2017

CCS (Carbon Capture and Storage) is a technical process to capture $CO_2$ from industrial and energy-based sources, to transfer and sequestrate impressed $CO_2$ in geological formations, oceans, or mineral carbonates. However, potential $CO_2$ leakage exists and causes environmental problems. Thus, this study was conducted to analyze the spatial and temporal variations of $CO_2$ fluxes and concentrations after artificial $CO_2$ release. The Environmental Impact Evaluation Test Facility (EIT) was built in Eumseong, Korea in 2015. Approximately 34kg $CO_2$ /day/zone were injected at Zones 2, 3, and 4 among the total of 5 zones from October 26 to 30, 2015. $CO_2$ fluxes were measured every 30 minutes at the surface at 0m, 1.5m, 2.5m, and 10m from the $CO_2$ releasing well using LI-8100A until November 13, 2015, and $CO_2$ concentrations were measured once a day at 15cm, 30cm, and 60cm depths at every 0m, 1.5m, 2.5m, 5m, and 10m from the well using GA5000 until November 28, 2015. $CO_2$ flux at 0m from the well started increasing on the fifth day after $CO_2$ release started, and continued to increase until November 13 even though the artificial $CO_2$ release stopped. $CO_2$ fluxes measured at 2.5m, 5.0m, and 10m from the well were not significantly different with each other. On the other hand, soil $CO_2$ concentration was shown as 38.4% at 60cm depth at 0m from the well in Zone 3 on the next day after $CO_2$ release started. Soil $CO_2$ was horizontally spreaded overtime, and detected up to 5m away from the well in all zones until $CO_2$ release stopped. Also, soil $CO_2$ concentrations at 30cm and 60cm depths at 0m from the well were measured similarly as $50.6{\pm}25.4%$ and $55.3{\pm}25.6%$, respectively, followed by 30cm depth ($31.3{\pm}17.2%$) which was significantly lower than those measured at the other depths on the final day of $CO_2$ release period. Soil $CO_2$ concentrations at all depths in all zones were gradually decreased for about 1 month after $CO_2$ release stopped, but still higher than those of the first day after $CO_2$ release stared. In conclusion, the closer the distance from the well and the deeper the depth, the higher $CO_2$ fluxes and concentrations occurred. Also, long-term monitoring should be required because the leaked $CO_2$ gas can remains in the soil for a long time even if the leakage stopped.

• Journal of Aquaculture
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• v.9 no.1
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• pp.25-42
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• 1996

The study has been conducted to know an appropriate feeding strategy and effects of the rearing density on larval growth of the rockfish, Sebastes schlegeli. The results obtained are as fellowed ; 1. Thirty-day-old larvae reached at $25.25{\pm}3.76$ mm in total length and $0.23{\pm}0.07$ g in body weight in experiment A, at which rotifer was provided from the beginning to the end of 30-day experiment, Anemia from 3th to 18th day, and artificial feed from 13th to 30th day after hatching. When rotifer was provided for 30 days, Artemia from 6th to 18th day, and artificial feed from 18th to 30th day after hatching (experiment B), these larvae grew up to $27.52{\pm}2.50$ mm in total length and $0.26{\pm}0.06$ g in body weight. On the other hand, when rotifer and artificial feed were supplied with the same time schedule as shown in experiment B, and Artemia was feed from 6th to 30th day after hatching (experiment C), the total length and body weight of those larvae were $23.22{\pm}3.44$ mm and $0.15{\pm}0.05$ g, respectively. The best result for larval growth was obtained from experiment B. The survival rates estimated were $57.6\%$ in experiment A, $66.4\%$ in experiment B, and $44.4\%$ in experiment C. 2. The growth in total length of the larvae according to their rearing days could be represented by the following equations : Experiment A : Y=4.350+0.116X+$1.887X^2$ (r=0.993) Experiment B : Y=4.500+8.931X+$2.221X^2$ (r=0.994) Experiment C : Y=4.478+5.734X+$1.881X^2$(r=0.990) The average number of Artemia nauplius intaken by the larvae was rapidly increased between 15th and 20th day afer hatching, and 9, 212, 242, 750, and 1,171 nauplius were found in the different sizes of larvae, whose total length were 5.65, 6.81, 9.45, 14.96, and 24.52 mm, respectively. 3. Larval growth in total length and body weight reared at four different densites (A: 1.8 $kg/m^3$, B; 4.0 $kg/m^3$, C; 5.0 $kg/m^3$, D; 6.2 $kg/m^3$) indicated that the best growth was found in experiment A, at which the larval were reared at the lower density and the final survival rates extimated were $92.9\%$ in exp. A, $99.5\%$ in exp. C, $89.0\%$ in exp. B, and $88.2\%$ in exp. D. The amount of production per cubic meter turned out to be 30.45 kg in exp. D, 25.89 kg in exp. C, 20.75 kg in exp. B and 10.48 kg in exp. A. therefore, considering both larval growth and survival rate, higher yields seemed to be attainable at the relatively high-rearing density.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.83-102
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• 2021

The government recently announced various policies for developing big-data and artificial intelligence fields to provide a great opportunity to the public with respect to disclosure of high-quality data within public institutions. KSURE(Korea Trade Insurance Corporation) is a major public institution for financial policy in Korea, and thus the company is strongly committed to backing export companies with various systems. Nevertheless, there are still fewer cases of realized business model based on big-data analyses. In this situation, this paper aims to develop a new business model which can be applied to an ex-ante prediction for the likelihood of the insurance accident of credit guarantee. We utilize internal data from KSURE which supports export companies in Korea and apply machine learning models. Then, we conduct performance comparison among the predictive models including Logistic Regression, Random Forest, XGBoost, LightGBM, and DNN(Deep Neural Network). For decades, many researchers have tried to find better models which can help to predict bankruptcy since the ex-ante prediction is crucial for corporate managers, investors, creditors, and other stakeholders. The development of the prediction for financial distress or bankruptcy was originated from Smith(1930), Fitzpatrick(1932), or Merwin(1942). One of the most famous models is the Altman's Z-score model(Altman, 1968) which was based on the multiple discriminant analysis. This model is widely used in both research and practice by this time. The author suggests the score model that utilizes five key financial ratios to predict the probability of bankruptcy in the next two years. Ohlson(1980) introduces logit model to complement some limitations of previous models. Furthermore, Elmer and Borowski(1988) develop and examine a rule-based, automated system which conducts the financial analysis of savings and loans. Since the 1980s, researchers in Korea have started to examine analyses on the prediction of financial distress or bankruptcy. Kim(1987) analyzes financial ratios and develops the prediction model. Also, Han et al.(1995, 1996, 1997, 2003, 2005, 2006) construct the prediction model using various techniques including artificial neural network. Yang(1996) introduces multiple discriminant analysis and logit model. Besides, Kim and Kim(2001) utilize artificial neural network techniques for ex-ante prediction of insolvent enterprises. After that, many scholars have been trying to predict financial distress or bankruptcy more precisely based on diverse models such as Random Forest or SVM. One major distinction of our research from the previous research is that we focus on examining the predicted probability of default for each sample case, not only on investigating the classification accuracy of each model for the entire sample. Most predictive models in this paper show that the level of the accuracy of classification is about 70% based on the entire sample. To be specific, LightGBM model shows the highest accuracy of 71.1% and Logit model indicates the lowest accuracy of 69%. However, we confirm that there are open to multiple interpretations. In the context of the business, we have to put more emphasis on efforts to minimize type 2 error which causes more harmful operating losses for the guaranty company. Thus, we also compare the classification accuracy by splitting predicted probability of the default into ten equal intervals. When we examine the classification accuracy for each interval, Logit model has the highest accuracy of 100% for 0~10% of the predicted probability of the default, however, Logit model has a relatively lower accuracy of 61.5% for 90~100% of the predicted probability of the default. On the other hand, Random Forest, XGBoost, LightGBM, and DNN indicate more desirable results since they indicate a higher level of accuracy for both 0~10% and 90~100% of the predicted probability of the default but have a lower level of accuracy around 50% of the predicted probability of the default. When it comes to the distribution of samples for each predicted probability of the default, both LightGBM and XGBoost models have a relatively large number of samples for both 0~10% and 90~100% of the predicted probability of the default. Although Random Forest model has an advantage with regard to the perspective of classification accuracy with small number of cases, LightGBM or XGBoost could become a more desirable model since they classify large number of cases into the two extreme intervals of the predicted probability of the default, even allowing for their relatively low classification accuracy. Considering the importance of type 2 error and total prediction accuracy, XGBoost and DNN show superior performance. Next, Random Forest and LightGBM show good results, but logistic regression shows the worst performance. However, each predictive model has a comparative advantage in terms of various evaluation standards. For instance, Random Forest model shows almost 100% accuracy for samples which are expected to have a high level of the probability of default. Collectively, we can construct more comprehensive ensemble models which contain multiple classification machine learning models and conduct majority voting for maximizing its overall performance.

• Journal of Sericultural and Entomological Science
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• v.23 no.1
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• pp.47-55
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• 1981

Silk textile finishing has been studied for many years by many workers in order to meet more utilities for various endusers. Such studies, however, could not be successful because any natural fibers are hardly change their natures by artificial treating methods. Textile finishing is of course to improve the mechandise qualities and the poor natures of silk so that it may be available as the best textile fiber in the world. Sometimes, famous trade marked textile plays more power than its quality in the silk market, nevertheless, this should be over line of research activities. Meantime, the silk demand has been also transferred from ladies stocking to other clothes since nylon or other synthetic fibers were developed. That is why, the extension of silk demand should be developed by various research works. Specially, silk is known as difficult textile to handle it during washing or ironing process which happened to depress down the silk usage for house wives. In order to solve such problems, the reporter has been worked for many years and now, he believes that he has developed a proper finishing method to coversuch problems. The developed finishing method may be said to eligible with economical aspect and shorten the dry duration after water washing in half against normal silk textile without harming the specific silk nature. As all of us know, silk fiber starts to denature since it was spinned by silkworm and the fiber is formed as overlapped "S" type curves during its concooning process. After it is made as raw silk or sericin silk, it shows as straight line form, but it changes in to waved form in case refining or degumming process in order return to its original spinned form. Such nature is continued during its textile form and ends with hard ironing nature than other textile fibers. Mean while, the silk fiber keeps to continue its denaturing and this is iniciated by repeat of washing and drying which takes many years to reach its final stage, The reporter has found the iniciating denature of silk by his finishing process, with out heat, decreasing the swollen nature which ended with shortening the drying duration after wash. Each washing was carried out by soaking the previously weighed sample in cold water for one hour, then pressed the sample for ten minutes to eliminate its free water component before weighing with same condition. According to this, the treated silk showed much denaturing after the finishing, but the standard silk progressed the denaturing by and by with the repeat of washing and drying, finally reached the same swollen degree of treated silk, Such treating result explains that the treated silk happened to be stebilized nature by the treating immediately. On the other that the treated silk happened to be stebilized nature by the treating immediately. On the other hand, standard silk may reach to such condition by the time of worn out clothes after repeat of washing and drying for many years while the clothes will be no more useful. The decreased swelling nature has brought about the drying period in half against standard silk after all. Not only the tests of tenacity and elongation but also crease resistance recovery, stiffness and shrinkage tests were carried out after each washing and drying which he has found better result on the treated silk textile against the standard silk. The most important thing was to keep the textile feeling of silk by such finishing work before improve any poor nature of silk. The general silk has a nature to absorb smoke or dirt from its surrounding air and reaches to dirty color shade upon such exposure, but the treated one has improved such nature because of its artificial denaturing, another word, it keeps clean longer than the normal silk. Many previous finishing works could improve some specific nature of silk, but it happened to deprave other important natures. The reporters work is, however, specialized to improve the silk to be useful as Wash and Wear Silk without harming its standard natures. So far, this work happened to be a overall innovative finishing method of silk textile.

• Journal of Chest Surgery
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• v.12 no.4
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• pp.383-394
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• 1979

Treatment of valvular heart disease with valve replacement has been one of the most popular procedures in cardiac surgery recently. Although, first effort was directed toward the prosthetic valve, it soon became popular that bioprosthesis, the valvular xenograft, was prefered in the majority cases. Valvular xenograft has some superiority to the artificial prosthetic valve in some points of thromboembolism and hemolytic anemia, and it also has some inferiority of durability, immunologic reaction and resistance to Infection. Tremendous efforts were made to cover the inferiority with several methods of collection, preservation, and valve mounting of the porcine valve or pericardium of the calf, and also with surgical technique of the valvular xenograft replacement. Auther has collected 320 porcine aortic valves immediately after slaughter, and aortic cusps were coapted with cotton balls in the Valsalva sinuses to protect valve deformity after immersion in the Hanks' solution, and oxidation, cross-linking and reduction procedures were completed after the proposal of Carpentier in 1972. Well preserved aortic valves were suture mounted in the hand-made tissue valve frame of 19, 21, and 23 mm J.d., and also in the prosthetic vascular segment of 19 mm Ld. with 4-0 nylon sutures after careful trimming of the aortic valves. Completed valves were evaluated with bacteriologic culture, pressure tolerance test with tolerane gauge, valve durability test in the saline glycerine mixed solution with tolerance test machine in the speed of 300 rpm, and again with pathologic changes to obtain following results: 1. Bacteriologic culture of the valve tissue in five different preservation method for two weeks revealed excellent and satisfactory result in view of sterilization including 0.65% glutaraldehyde preservation group for one week bacteriologic culture except one tissue with Citobacter freundii in 75% ethanol preserved group. 2. Pressure tolerance test was done with an apparatus composed of V-connected manometer and pressure applicator. Tolerable limit of pressure was recorded when central leaking jet of saline was observed. Average pressure tolerated in each group was 168 mmHg in glutaraldehyde, 128 mmHg in formaldehyde, 92 mmHg in Dakin's solution, 48 mmHg in ethylene oxide gas, and 26 mmHg in ethanol preserved group in relation to the control group of Ringer's 90 mmHg respectively. 3. Prolonged durability test was performed in the group of frame mounted xenograft tissue valve with 300 up-and-down motion tolerance test machine/min. There were no specific valve deformity or wearing in both 19, 21, and 23 mm valves at the end of 3 months (actually 15 months), and another 3 months durability test revealed minimal valve leakage during pressure tolerance test due to contraction deformity of the non-coronary cusp at the end of 6 months (actually 30 months) in the largest 23 mm group. 4. Histopathologic observation was focussed in three view points, endothelial cell lining, collagen and elastic fiber destructions in each preservation methods and long durable valvular tolerance test group. Endothel ial cell lining and collagen fiber were well preserved in the glutaraldehyde and formaldehyde treated group with minimal destruction of elastic fiber. In long durable tolerance test group revealed complete destruction of the endothelial cell lining with minimal destruction of the collagen and elastic fiber in 3 month and 6 month group in relation to the time and severity. In conclusion, porcine xenograft treated after the proposal of Carpentier in 1972 and preserved in the glutaraldehyde solution was the best method of collection, preservation and valve mounting. Pressure tolerance and valve motion tolerance test, also, revealed most satisfactory results in the glutaraldehyde preserved group.