• Journal of the Daesoon Academy of Sciences
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• v.37
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• pp.53-105
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• 2021

The purpose of this study is to clarify the meaning of Gwonji (權智, Authority and Foreknowledge) through the phrases contained in the section, Gwonji of the Jeon-gyeong (known in English as The Canonical Scripture), and to compare the changes that each verse from Gwonji underwent by juxtaposing it against the sixth edition of Daesoon Jeong-gyeong (which was published prior to the Jeon-gyeong) to explore the term's literary meaning. In order to save the world, Sangje descended to human world and performed the Cheonjigongsa (Reordering Works of the Universe) for nine years with the power he exercises over the Three Realms of Heaven, Earth, and Humanity. Based on the plan set by the Cheonjigongsa, Sangje's teachings were spread to humanity and provided as the basis for building the earthly paradise. From this perspective, this study demonstrates its significance by providing a comprehensive approach to the Jeon-gyeong by highlighting the subject of Sangje's authority and wisdom as recorded in the section titled Gwonji. There is also value in the variant verses from Gwonji that the study discovered by comparing and analyzing the phrases from chapters one and two of Gwonji as they appear in the Jeon-gyeong with their equivalents from the sixth edition of Daesoon Jeong-gyeong, which was published in 1965, nearly a decade before Daesoon Jinrihoe's publication of the Jeon-gyeong in 1974. The results of this comparative study of parallel passages related to Gwonji are as follows: First, Gwonji can be understood as the authority and wisdom of Sangje, and this is the core element in realizing the Earthly Paradise through His Cheonjigongsa. Second, phrases related to Sangje's authority and wisdom are spread out in the seven sections of the Jeon-gyeong, and they were written to emphasize the main purpose suggested in each section or chapter. Third, in sections other than Gwonji, the great power of Sangje is exercised to treat matters related to deities and social problems, whereas in Gwonji part, it is dedicated to the performance of Cheonjigongsa. Fourth, there are five sections of the Jeon-gyeong which are organized into chapters. All of these sections and their chapters indicate the year when key events transpired. Fifth, when passages from chapter one of Gwonji is compared to parallel passages from Daesoon Jeon-gyeong, there are several verses that vary in terms of their wording and also sentences that indicate a different dates or times for certain events.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1353-1369
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• 2023

In the event of a disaster accident at sea, the scale of damage will vary due to weather effects such as wind, currents, and tidal waves, and it is obligatory to minimize the scale of damage by establishing appropriate control plans through quick on-site identification. In particular, it is difficult to identify pollutants that exist in a thin film at sea surface due to their relatively low viscosity and surface tension among pollutants discharged into the sea. Therefore, this study aims to develop an algorithm to detect suspended pollutants on the sea surface in RGB images using imaging equipment that can be easily used in the field, and to evaluate the performance of the algorithm using input data obtained from actual waters. The developed algorithm uses image enhancement techniques to improve the contrast between the intensity values of pollutants and general sea surfaces, and through histogram analysis, the background threshold is found,suspended solids other than pollutants are removed, and finally pollutants are classified. In this study, a real sea test using substitute materials was performed to evaluate the performance of the developed algorithm, and most of the suspended marine pollutants were detected, but the false detection area occurred in places with strong waves. However, the detection results are about three times better than the detection method using a single threshold in the existing algorithm. Through the results of this R&D, it is expected to be useful for on-site control response activities by detecting suspended marine pollutants that were difficult to identify with the naked eye at existing sites.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.29-45
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• 2012

Bond rating is regarded as an important event for measuring financial risk of companies and for determining the investment returns of investors. As a result, it has been a popular research topic for researchers to predict companies' credit ratings by applying statistical and machine learning techniques. The statistical techniques, including multiple regression, multiple discriminant analysis (MDA), logistic models (LOGIT), and probit analysis, have been traditionally used in bond rating. However, one major drawback is that it should be based on strict assumptions. Such strict assumptions include linearity, normality, independence among predictor variables and pre-existing functional forms relating the criterion variablesand the predictor variables. Those strict assumptions of traditional statistics have limited their application to the real world. Machine learning techniques also used in bond rating prediction models include decision trees (DT), neural networks (NN), and Support Vector Machine (SVM). Especially, SVM is recognized as a new and promising classification and regression analysis method. SVM learns a separating hyperplane that can maximize the margin between two categories. SVM is simple enough to be analyzed mathematical, and leads to high performance in practical applications. SVM implements the structuralrisk minimization principle and searches to minimize an upper bound of the generalization error. In addition, the solution of SVM may be a global optimum and thus, overfitting is unlikely to occur with SVM. In addition, SVM does not require too many data sample for training since it builds prediction models by only using some representative sample near the boundaries called support vectors. A number of experimental researches have indicated that SVM has been successfully applied in a variety of pattern recognition fields. However, there are three major drawbacks that can be potential causes for degrading SVM's performance. First, SVM is originally proposed for solving binary-class classification problems. Methods for combining SVMs for multi-class classification such as One-Against-One, One-Against-All have been proposed, but they do not improve the performance in multi-class classification problem as much as SVM for binary-class classification. Second, approximation algorithms (e.g. decomposition methods, sequential minimal optimization algorithm) could be used for effective multi-class computation to reduce computation time, but it could deteriorate classification performance. Third, the difficulty in multi-class prediction problems is in data imbalance problem that can occur when the number of instances in one class greatly outnumbers the number of instances in the other class. Such data sets often cause a default classifier to be built due to skewed boundary and thus the reduction in the classification accuracy of such a classifier. SVM ensemble learning is one of machine learning methods to cope with the above drawbacks. Ensemble learning is a method for improving the performance of classification and prediction algorithms. AdaBoost is one of the widely used ensemble learning techniques. It constructs a composite classifier by sequentially training classifiers while increasing weight on the misclassified observations through iterations. The observations that are incorrectly predicted by previous classifiers are chosen more often than examples that are correctly predicted. Thus Boosting attempts to produce new classifiers that are better able to predict examples for which the current ensemble's performance is poor. In this way, it can reinforce the training of the misclassified observations of the minority class. This paper proposes a multiclass Geometric Mean-based Boosting (MGM-Boost) to resolve multiclass prediction problem. Since MGM-Boost introduces the notion of geometric mean into AdaBoost, it can perform learning process considering the geometric mean-based accuracy and errors of multiclass. This study applies MGM-Boost to the real-world bond rating case for Korean companies to examine the feasibility of MGM-Boost. 10-fold cross validations for threetimes with different random seeds are performed in order to ensure that the comparison among three different classifiers does not happen by chance. For each of 10-fold cross validation, the entire data set is first partitioned into tenequal-sized sets, and then each set is in turn used as the test set while the classifier trains on the other nine sets. That is, cross-validated folds have been tested independently of each algorithm. Through these steps, we have obtained the results for classifiers on each of the 30 experiments. In the comparison of arithmetic mean-based prediction accuracy between individual classifiers, MGM-Boost (52.95%) shows higher prediction accuracy than both AdaBoost (51.69%) and SVM (49.47%). MGM-Boost (28.12%) also shows the higher prediction accuracy than AdaBoost (24.65%) and SVM (15.42%)in terms of geometric mean-based prediction accuracy. T-test is used to examine whether the performance of each classifiers for 30 folds is significantly different. The results indicate that performance of MGM-Boost is significantly different from AdaBoost and SVM classifiers at 1% level. These results mean that MGM-Boost can provide robust and stable solutions to multi-classproblems such as bond rating.

• Journal of the Economic Geographical Society of Korea
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• v.8 no.1
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• pp.153-169
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• 2005

In this study, we analysed the state of the fisheries in Chungnam around 1910 from Hangook Susanji. As a result, there were about 30 ports in the west coast area in Chungnam, and we can classify their locations into 5 types Type I is located in small and mid sized rivers. Type II is located in a costal port. Type III is ports facing the open sea, and type IV is ports in a bay. Type V is ports on islands of coast. Species of fish are porges, mackerels, sting rays, croakers, hairtails, shrimps, etc. The base of fishing porge was Jukdo and Yeondo. The fishing banks of croakers are formed from Chilsantan, Jeonlado to the area of seashore, Chungnam. Hairtails were caught near all the areas of seashore. Salt manufacturing is done near all coasts of Chungnam, Seocheon-bay, Ungcheon-bay, Ocheon-bay, Anmyeon island, Taean, Dangjin area, etc represent this work. Especially, the salt which was produced in Taeangun was so famous that it was called ' Taeansalt'. In the Kum-river area there were 32 fishing villages. Freshwater fish were caught in the upper stream area and the mouth of Geumgang, down stream, was the center for producing Baengeo. There were 23 fishing villages, and the species consisted of croaker, hairtail, Forge, gray mullet, sting ray, sharks, anchovy, shrimps, etc in Biin-bay. The coast of Boryeong had about 33 fishing villages, but their fishing industry was not developed more than their good salt manufacturing. Though there are records that Chunsu-bay had 28 fishing villages, Taean peninsula and Garolim-bay had about 70 fishing villages, and Asan-bay area had about 55 fishing villages, they were developed a little, but not more than Weir fisheries or salt manufacture on the base of salt area and the tideland because these areas were just for farming. South of Anmyeon island of West coast island areas is the biggest area of Stow nets on stakes fishing and the island areas down mouth of Kum river were centers for producing porge.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.17 no.3
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• pp.188-201
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• 2005

This is the first part of a two-part paper which describes comparison of reliability design methods by application to Donghae Harbor Breakwaters. This paper, Part 1, is restricted to stability of armor blocks, while Part 2 deals with sliding of caissons. Reliability design methods have been developed fur breakwater designs since the mid-1980s. The reliability design method is classified into three categories depending on the level of probabilistic concepts being employed. In the Level 1 method, partial safety factors are used, which are predetermined depending on the allowable probability of failure. In the Level 2 method, the probability of failure is evaluated with the reliability index, which is calculated using the means and standard deviations of the load and resistance. The load and resistance are assumed to distribute normally. In the Level 3 method, the cumulative quantity of failure (e.g. cumulative damage of armor blocks) during the lifetime of the breakwater is calculated without assumptions of normal distribution of load and resistance. Each method calculates different design parameters, but they can be expressed in terms of probability of failure so that tile difference can be compared among the different methods. In this study, we applied the reliability design methods to the stability of armor blocks of the breakwaters of Donghae Harbor, which was constructed by traditional deterministic design methods to be damaged in 1987. Analyses are made for the breakwaters before the damage and after reinforcement. The probability of failure before the damage is much higher than the target probability of failure while that for the reinforced breakwater is much lower than the target value, indicating that the breakwaters before damage and after reinforcement were under- and over-designed, respectively. On the other hand, the results of the different reliability design methods were in fairly good agreement, confirming that there is not much difference among different methods.

• Korean Journal of Agricultural and Forest Meteorology
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• v.15 no.2
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• pp.85-101
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• 2013

In order to search for distribution characteristics on C4 plants at the paddy fields, uplands, orchard and roadside in South Korea, vascular plants were investigated. Flora investigation had been carried out from May 2002 to October 2006 at 241 plots. In the results of survey, the flora of these areas consist of 74 families, 231 genera and 352 species totally. The class frequencies were arranged by the order of Magnoliopsidae (255 species), Monocotyledoneae (89 species), Pteropsida (7 species) and Sphenopsida (1 species). The number of species in each investigated agricultural field types was 55 families with 203 species in paddy field, 49 families with 218 species in uplands, 44 families with 115 species in orchard and 48 families with 202 species in roadside respectiviely. Representative species compositions of these four agricultural field types were characterized by Artemisia princeps, Persicaria thunbergii in paddy field, Artemisia princeps, Erigeron annuus in upland and roadside, Commelina communis, Digitaria ciliaris in orchard, respectively. Therefore, indicative species in agricultural ecosystem was Artemisia princeps. Among the investigated 352 species, $C_4$ plants identified were 38 species, and the occurrence ratio of $C_4$ monocotyledonous plants were higher in paddy field, orchard and roadside than upland. Such differences in the occurrence ratio of $C_4$ plants under diverse agricultural field types reflect differences in environmental condition such as micro-climate, soil moisture under various agricultural fields. Dominant $C_4$ monocotyledonous plants were Digitaria ciliaris and Commelina communis, while $C_4$ dicotyledonous plants were Amaranthus mangostanus and Chenopodium album var. centrorubrum in agricultural fields. Naturalized plants were identified as 47 species and occurrence ratio were higher in upland and roadside than other agricultural field types. Among the investigated naturalized plants, $C_4$ plants were Amaranthus mangostanus and Amaranthus retroflexus. Distribution characteristics of representative $C_4$ plants in agricultural field types, revealed that the projected increase in temperature due to climate change may provide better conditions for the growth of $C_4$ plants. Thus, the necessity of long-term monitoring should be conducted on the diffusion of $C_4$ plants that may threaten influence agroecosystem in Korea.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.7
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• pp.3293-3300
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• 2013

Recently, Korean prefer the slim and skinny body. Even though they are normal or underweight, they strive for weight control routinely. Due to the appearance-oriented trend prevalent in our society, severe losing weight for women has become a social problem. The purpose of this study is to examine the relationship between body dysmorphic disorder and depression. Health-related and health-unrelated college students were classified into three different groups according to BMI. This study was performed of 200 health-related and 200 health-unrelated college students respectively at K college in Gangwon province. A self-administered survey was conducted from September 10 to 21, 2012, and the 319 questionnaires were analyzed. The collected data were analyzed by the SPSS(statistical package for the social science) WIN 18.0. Regarding the relationship between the BMI of the female students and their unsatisfied parts of the body, the overweight female students were more dissatisfied with the entire lower parts of their body(${\chi}^2$=6.97, p<.05). About the waist and belly, the female students of normal weight were the most dissatisfied but of under weight were less dissatisfied than the other groups and the differences among them were statistically significant(${\chi}^2$=8.12, p<.05). About the chest and breasts, the female students of under weight were more dissatisfied than the other groups and there were significant differences according to BMI. As a result of analyzing the relationship between the BMI of the female students and their dissatisfied parts of the body, the female students of over weight were more dissatisfied with the entire lower parts of their body and whole body, and the female students of normal weight were more dissatisfied with their waist and belly than the other groups. The female students of under weight were more dissatisfied with their chest and breasts. But, there were no differences in the way they want to try for a change of the dissatisfied part of the body. Because this body dysmorphic disorder may be associated with depression and cause the social and cultural problems, the development of counseling programs and additional research should be needed.

• The Journal of Korean Academy of Prosthodontics
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• v.51 no.4
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• pp.261-268
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• 2013

Purpose: The purpose of this study was to investigate the effect of geometrically different wax pattern shapes and sizes on the castability of Grade2 Cp-Ti (commercially pure titanium). Materials and methods: Total of 40 mesh wax pattern ($61mm{\times}24mm$, 207 grids), ($61mm{\times}17mm$, 138 grids) was cast in this experiment. Depending on the geometrical shape of the wax pattern, 8 groups was organized; Flat, Semicircular, Horse-shoe and V-shape, each consisting 5 samples. Runner-bar sprue was used in all patterns. The number of completely cast grid in wax pattern served as a measure for the castability of comercially pure titanium. Results: The mean value of square count in each group was as followed; 133.20 squares in group SS (96.52%), 132.40 squares in group SH (95.94%), 132.00 squares in group SF (95.65%), 127.60 squares in SV (91.43%), 198.60 squares in group LF (95.94%), 197.80 squares in group LV (95.56%), 196.40 squares in group LS (94.88%), and 188.00 squares in group LH (90.82%). Conclusion: Within the limitations of this study the results indicate that there were no sttistically significant difference in castability of titanium regarding wax pattern shape (P>.05). However, Small size wax patterns were showing the noticeable castability more than Large size pattern.

• Management & Information Systems Review
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• v.39 no.2
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• pp.181-193
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• 2020

This study is a study that analyzes consumer perception by utilizing text mining, which is a recent issue. we analyzed the consumer's perception of Samsung Galaxy by analyzing consumer reviews of Samsung Galaxy YouTube ads. for analysis, 1,819 consumer reviews of YouTube ads were extracted. through this data pre-processing, keywords for advertisements were classified and extracted into nouns, adjectives, and adverbs. after that, frequency analysis and emotional analysis were performed. Finally, clustering was performed through CONCOR. the summary of this study is as follows. the first most frequently mentioned words were Galaxy Note (n = 217), Good (n = 135), Pen (n = 40), and Function (n = 29). it can be judged through the advertisement that consumers "Galaxy Note", "Good", "Pen", and "Features" have good functional aspects for Samsung mobile phone products and positively recognize the Note Pen. in addition, the recognition of "Samsung Pay", "Innovation", "Design", and "iPhone" shows that Samsung's mobile phone is highly regarded for its innovative design and functional aspects of Samsung Pay. second, it is the result of sentiment analysis on YouTube advertising. As a result of emotional analysis, the ratio of emotional intensity was positive (75.95%) and higher than negative (24.05%). this means that consumers are positively aware of Samsung Galaxy mobile phones. As a result of the emotional keyword analysis, positive keywords were "good", "good", "innovative", "highest", "fast", "pretty", etc., negative keywords were "frightening", "I want to cry", "discomfort", "sorry", "no", etc. were extracted. the implication of this study is that most of the studies by quantitative analysis methods were considered when looking at the consumer perception study of existing advertisements. In this study, we deviated from quantitative research methods for advertising and attempted to analyze consumer perception through qualitative research. this is expected to have a great influence on future research, and I am sure that it will be a starting point for consumer awareness research through qualitative research.

• Journal of Science Education
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• v.33 no.2
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• pp.336-345
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• 2009

The purpose of this study is to analysis ERF components patterns of causal questions generated during the observation of biological phenomenon. First, the system that shows pictures causing causal questions based on biological phenomenon (evoked picture system) was developed in a way of cognitive psychology. The ERF patterns of causal questions based on time-series brain processing was observed using MEG. The evoked picture system was developed by R&D method consisting of scientific education experts and researchers. Tasks were classified into animal (A), microbe (M), and plant (P) tasks according to biological species and into interaction (I), all (A), and part (P) based on the interaction between different species. According to the collaboration with MEG team in the hospital of Seoul National University, the paradigm of MEG task was developed. MEG data about the generation of scientific questions in 5 female graduate student were collected. For examining the unique characteristic of causal question, MEG ERF components were analyzed. As a result, total 100 pictures were produced by evoked picture and 4 ERF components, M1(100~130ms), M2(220~280ms), M3(320~390ms), M4(460~520ms). The present study could guide personalized teaching-learning method through the application and development of scientific question learning program.