• Korea Science and Art Forum
• /
• v.19
• /
• pp.293-305
• /
• 2015

At the same time the unique cultural traits of each country are valued, it has become an essential element to establish the cultural identity of a country. This study is aimed at comparing the residence architectural cultures in East-Asia and thus identifying Korea's own unique traits by determining the application characteristics of traditional architectures of Korea, China and Japan through practical investigation of materials, a basic element of architectural shaping. Literature survey and field study were conducted in parallel for this study, and architectural buildings under investigation included Mucheomdang House in Korea, Prince Gong Mansion in China and Dokyudo Building in Japan. Construction materials in Korea, China and Japan include natural materials such as wood, stone and clay, and artificial materials such as metals, paper, roof tiles, plug and glass. and the buildings were constructed with the combination of these materials. This commonality can be often found in the architectural composition. However, in the interior composition, the choice and application of different materials were clear between three countries, which were shown to be different depending on climates, processing methods and living culture of each country. First of all, since each country selected materials under the influence of its own vegetation and climates, living environment of each country could be seen via its residence. Also, it could be seen that while Korea and Japan show a certain similarity such as the traits of standing-sitting culture and the finish of paper in the interior, China is clearly different. In particular, regarding the material processing, the artificial processing was minimized in Korea, which mainly gave rough and crude feelings while due to the use of straight timbers, the architectural representation with organized and refined feelings was made in Japan. China showed the highest percentage of artificial processing of materials among three countries, which was highly associated with the coloring culture of China. Also, it could be seen that technology related to fine architectural materials such as bricks and glass was greatly advanced in China. Thus, how immaterial elements such as natural characteristics, functionality and aesthetics were applied in relation to residence in Korea, Japan and China could be determined through the comparison of architectural materials.

• Korean Journal of Environment and Ecology
• /
• v.37 no.2
• /
• pp.151-162
• /
• 2023

This study investigated the characteristics of fish communities and inhabiting status of the endangered species, Rhodeus pseudosericeus, in the Geumdang Stream in Korea from March to October 2021. A total of 1,698 fish in 5 families and 25 species were collected from 7 survey stations during the survey period. The dominant species was Zacco platypus (relative abundance, 46.5%), and the subdominant species was Squalidus gracilis majimae (16.7%), followed by Rhynchocypris oxycephalus (12.0%), Z. koreanus (5.7%), Pungtungia herzi (3.2%), R. pseudosericeus (2.0%), R. notatus (1.9%), and Acheilognathus rhombeus (1.8%). Nine Korean endemic species (36.0%) were collected, including R. pseudosericeus, R. uyekii, Sarcocheilichthys variegatus wakiyae, Microphysogobio yaluensis, S. gracilis majimae, Z. koreanus, Cobitis nalbanti, Iksookimia koreensis, and Odontobutis interrupta. An exotic species, Micropterus salmoides, designated as an invasive alien species (IAS), was collected downstream. The investigation of the habitat patterns of the endangered species (class II), Rhodeus pseudosericeus, showed a habitat range of about 6 to 7 km in the middle of Geumdang Stream (RP-1 to RP-4), and this species inhabited the edge with water depths of 0.3 through 1.0 m with slow water flow and many aquatic plants. According to the community analysis results, the overall dominance and evenness indexes were low, while diversity and richness indexes were high, and the cluster structure was largely divided into upstream and middle-downstream areas. The river health (fish assessment index) evaluated using fish was assessed as good (3 stations), normal (3 stations), and bad (1 station), and water quality was evaluated as good both upstream and downstream. Compared to previous studies, the number of species was relatively similar, and among the species that appeared in the past, 13 species did not appear in this survey, while 6 species appeared for the first time in this survey. Disturbance factors included river construction, many weirs, and the appearance of the ecosystem-disturbing species, M. salmoides. Since Geumdang Strem has high conservation value because it is home to many species in the Acheilognathinae subfamily, including the endangered species R. pseudosericeus, continuous attention and systematic conservation measures are required.

• (The) Research of the performance art and culture
• /
• no.39
• /
• pp.69-96
• /
• 2019

North Korea has conserved operas in a selective manner. The subject matters of operas recorded in the history of North Korea can be divided into classical tales, translated foreign works, Korean War and war against Japan. Operas that adapted folk classics of the 1950s are considered valuable materials to verify the changes of genres posterior to division of regime between North and South Korea. The officially confirmed works include "Kumgangsan Palseonnyeo (Gyeonwoo Jiknyeo)," "Chunhyangjeon." "Kongjwi Patjwi (Kotsin)," "Ondal," and "Geumnaneui Dal." These works had gone through recreation in terms of realistic situation setting, abolition of class difference, adjustment of social rank and punishment of evil while the base lies in the original folk classics. People emphasized in adapted folk operas are described as those who are hard-working souls without giving importance of difference of social rank, content with the currently living space, devoted to their parents and full of patriotic spirit, and members of community who participate in organized fights against unfair exploitation. This was the fruit of encouragement of work creation supporting union between labor and individual life, destruction of old things and fight promoting this destruction. Folk operas of South and North Korea posterior to Korean War have similarities in that both deal with a love story transcending social ranks and the concomitant conflicts and they focus on the audience who enjoy the operas. Nonetheless, they are different in that this love in North Korea became a tool of educating people wished by the regime, while it became an object of securing the audience by adding the tragic element to love in South Korea. North Korean operas of the initial stage are characterized by playwriting method emphasizing difficult life and compensation of common people, realistic stage expression, accentuation of melody and agreement between notes and lyrics. This was efforts designed to continuously lead senses concentrated from the theater to everyday life of people. In effect, this is in line with the playwriting method of revolutionary operas. Adapted folk operas were subject matters ideal for easily approaching the audience and leaving them good memories at the same time. To realize socialist realism, they went through an experiment of reviewing "people" through the classic folk operas. The possibility of continuation of a work was determined by thorough evaluation after carrying out an experiment in terms of subject matters, theme, music and operation plans from the moment of which the work was on the stage. The sign consisted in the possibility of visit of "Kim Il-sung" to appreciate the work and presentation of directionality. By proposing the clear directionality of which hard-working people who deny social status system can be duly compensated, it encouraged the audience who saw the opera to voluntarily put this in practice. Thus, operas established the directionality through selective processes for creating public communion even before revolutionary operas.

• KIPS Transactions on Software and Data Engineering
• /
• v.12 no.11
• /
• pp.471-480
• /
• 2023

The Korean construction order volume in South Korea grew significantly from 91.3 trillion won in public orders in 2013 to a total of 212 trillion won in 2021, particularly in the private sector. As the size of the domestic and overseas markets grew, the scale and complexity of EPC (Engineering, Procurement, Construction) projects increased, and risk management of project management and ITB (Invitation to Bid) documents became a critical issue. The time granted to actual construction companies in the bidding process following the EPC project award is not only limited, but also extremely challenging to review all the risk terms in the ITB document due to manpower and cost issues. Previous research attempted to categorize the risk terms in EPC contract documents and detect them based on AI, but there were limitations to practical use due to problems related to data, such as the limit of labeled data utilization and class imbalance. Therefore, this study aims to develop an AI model that can categorize the contract terms based on the FIDIC Yellow 2017(Federation Internationale Des Ingenieurs-Conseils Contract terms) standard in detail, rather than defining and classifying risk terms like previous research. A multi-text classification function is necessary because the contract terms that need to be reviewed in detail may vary depending on the scale and type of the project. To enhance the performance of the multi-text classification model, we developed the ELECTRA PLM (Pre-trained Language Model) capable of efficiently learning the context of text data from the pre-training stage, and conducted a four-step experiment to validate the performance of the model. As a result, the ensemble version of the self-developed ITB-ELECTRA model and Legal-BERT achieved the best performance with a weighted average F1-Score of 76% in the classification of 57 contract terms.

• Journal of the Korean Society of Earth Science Education
• /
• v.16 no.3
• /
• pp.319-327
• /
• 2023

This study involved 22 students in one class of 4th year science intensive course at B College of Education. We investigated the changes in the acquisition of knowledge in the field of geology and the perception of geological exploration among pre-service teachers. For this study, a period of four weeks was designated for a semester to a geological field trip. For the geological exploration, the Geoparks of City B (Geumjeongsan Mountain, Amnam Park, Igidae, Dusong Peninsula, Jangsan, Taejongdae, and Hwangnyeongsan Mountain) were designated. The concept of geology and rocks has been extracted from the concepts that can be found in the Geopark. The composition of the group was composed of one group of four members autonomously. The other two of the pre-service teachers joined a group of friends with whom they had an affinity. After the geological field trip, the materials were organized by group and PPT presentations were made during the lecture time where all the members could listen. The extent to which the pre-service teachers acquired the concepts of geology and rocks after conducting the geological field trip was interpreted as the result of pre- and post-statistical processing. In addition, we interpreted what kind of perception the pre-service teachers had after the geological field trip as a result of the statistical processing before and after. Based on the results of the study, the following conclusions were drawn: First, it was effective for the pre-service teachers to acquire the concepts of strata and rocks after the geological field trip. The reason for this is that the experience of the pre-service teachers in conducting geological field trips has changed their perception of geological field trips. In addition, it is interpreted that these results were obtained because the pre-service teachers had a high level of interest in geology and rocks. Second, the pre-service teachers were able to gain confidence after the geological field trip. This reason is interpreted as the fact that they were able to gain confidence in geological exploration by exploring and experiencing the sites of the Geopark for each group.

• Journal of The Korean Association For Science Education
• /
• v.44 no.2
• /
• pp.167-178
• /
• 2024

In this study, we investigated the perceptions of science-related careers and career education among middle school science teachers. Sixty-four science teachers experienced in teaching unit 7 in the first year of middle school participated. The results of the study revealed that not only careers in science but also careers with science were found to be quite high when teachers were asked to provide examples of science-related careers. Jobs related to research/engineering, which are careers in science, comprised the highest proportion of teachers' answers, followed by jobs related to education/law/social welfare/police/firefighting/military, and health/medical, which are careers with science. However, the proportion of jobs mentioned related to installation/maintenance/production was extremely low. The skills required for science-related careers were mainly perceived to consist of tools for working and ways of working. The number of skills classified under living in the world was perceived to be extremely low across most careers, irrespective of career type. Most teachers only taught unit 7 for two to four sessions and devoted little time to science-related career education, even in general science classes. In the free semester system, a significant number of teachers responded that they provide science-related career education for more than 8 hours. Teachers mainly utilize lecture, discussion/debate, and self-study activities. Meanwhile, in the free semester system, the resource-based learning method was utilized at a high proportion compared to other class situations. Teachers generally made much use of media materials, with the use of textbooks and teacher guides found to be lower than expected. There were also cases of using materials supported by science museums or the Ministry of Education. Teachers preferred to implementing student-centered classes and utilizing various teaching and learning methods. Based on the above research results, discussions were proposed to improve teachers' perceptions of science-related careers and career education.

• Journal of the Korean Wood Science and Technology
• /
• v.2 no.2
• /
• pp.8-12
• /
• 1974

1. If one unity is given to the prongs whose ends touch each other for estimating the internal stresses occuring in it, the internal stresses which are developed in the open prongs can be evaluated by the ratio to the unity. In accordance with the above statement, an equation was derived as follows. For employing this equation, the prongs should be made as shown in Fig. I, and be measured A and B' as indicated in Fig. l. A more precise value will result as the angle (J becomes smaller. $CH=\frac{(A-B') (4W+A) (4W-A)}{2A[(2W+(A-B')][2W-(A-B')]}{\times}100%$ where A is thickness of the prong, B' is the distance between the two prongs shown in Fig. 1 and CH is the value of internal stress expressed by percentage. It precision is not required, the equation can be simplified as follows. $CH=\frac{A-B'}{A}{\times}200%$ 2. Under scheduled drying condition III the kiln, when the weight of a sample board is constant, the moisture content of the shell of a sample board in the case of a normal casehardening is lower than that of the equilibrium moisture content which is indicated by the Forest Products Laboratory, U. S. Department of Agriculture. This result is usually true, especially in a thin sample board. A thick unseasoned or reverse casehardened sample does not follow in the above statement. 3. The results in the comparison of drying rate with five different kinds of wood given in Table 1 show that the these drying rates, i.e., the quantity of water evaporated from the surface area of I centimeter square per hour, are graded by the order of their magnitude as follows. (1) Ginkgo biloba Linne (2) Diospyros Kaki Thumberg. (3) Pinus densiflora Sieb. et Zucc. (4) Larix kaempheri Sargent (5) Castanea crenata Sieb. et Zucc. It is shown, for example, that at the moisture content of 20 percent the highest value revealed by the Ginkgo biloba is in the order of 3.8 times as great as that for Castanea crenata Sieb. & Zucc. which has the lowest value. Especially below the moisture content of 26 percent, the drying rate, i.e., the function of moisture content in percentage, is represented by the linear equation. All of these linear equations are highly significant in testing the confficient of X i. e., moisture content in percentage. In the Table 2, the symbols are expressed as follows; Y is the quantity of water evaporated from the surface area of 1 centimeter square per hour, and X is the moisture content of the percentage. The drying rate is plotted against the moisture content of the percentage as in Fig. 2. 4. One hundred times the ratio(P%) of the number of samples occuring in the CH 4 class (from 76 to 100% of CH ratio) within the total number of saplmes tested to those of the total which underlie the given SR ratio is measured in Table 3. (The 9% indicated above is assumed as the danger probability in percentage). In summarizing above results, the conclusion is in Table 4. NOTE: In Table 4, the column numbers such as 1. 2 and 3 imply as follows, respectively. 1) The minimum SR ratio which does not reveal the CH 4, class is indicated as in the column 1. 2) The extent of SR ratio which is confined in the safety allowance of 30 percent is shown in the column 2. 3) The lowest limitation of SR ratio which gives the most danger probability of 100 percent is shown in column 3. In analyzing above results, it is clear that chestnut and larch easly form internal stress in comparison with persimmon and pine. However, in considering the fact that the revers, casehardening occured in fir and ginkgo, under the same drying condition with the others, it is deduced that fir and ginkgo form normal casehardening with difficulty in comparison with the other species tested. 5. All kinds of drying defects except casehardening are developed when the internal stresses are in excess of the ultimate strength of material in the case of long-lime loading. Under the drying condition at temperature of $170^{\circ}F$ and the lower humidity. the drying defects are not so severe. However, under the same conditions at $200^{\circ}F$, the lower humidity and not end coated, all sample boards develop severe drying defects. Especially the chestnut was very prone to form the drying defects such as casehardening and splitting.

• Journal of Intelligence and Information Systems
• /
• v.23 no.1
• /
• pp.95-108
• /
• 2017

Recently, AlphaGo which is Bakuk (Go) artificial intelligence program by Google DeepMind, had a huge victory against Lee Sedol. Many people thought that machines would not be able to win a man in Go games because the number of paths to make a one move is more than the number of atoms in the universe unlike chess, but the result was the opposite to what people predicted. After the match, artificial intelligence technology was focused as a core technology of the fourth industrial revolution and attracted attentions from various application domains. Especially, deep learning technique have been attracted as a core artificial intelligence technology used in the AlphaGo algorithm. The deep learning technique is already being applied to many problems. Especially, it shows good performance in image recognition field. In addition, it shows good performance in high dimensional data area such as voice, image and natural language, which was difficult to get good performance using existing machine learning techniques. However, in contrast, it is difficult to find deep leaning researches on traditional business data and structured data analysis. In this study, we tried to find out whether the deep learning techniques have been studied so far can be used not only for the recognition of high dimensional data but also for the binary classification problem of traditional business data analysis such as customer churn analysis, marketing response prediction, and default prediction. And we compare the performance of the deep learning techniques with that of traditional artificial neural network models. The experimental data in the paper is the telemarketing response data of a bank in Portugal. It has input variables such as age, occupation, loan status, and the number of previous telemarketing and has a binary target variable that records whether the customer intends to open an account or not. In this study, to evaluate the possibility of utilization of deep learning algorithms and techniques in binary classification problem, we compared the performance of various models using CNN, LSTM algorithm and dropout, which are widely used algorithms and techniques in deep learning, with that of MLP models which is a traditional artificial neural network model. However, since all the network design alternatives can not be tested due to the nature of the artificial neural network, the experiment was conducted based on restricted settings on the number of hidden layers, the number of neurons in the hidden layer, the number of output data (filters), and the application conditions of the dropout technique. The F1 Score was used to evaluate the performance of models to show how well the models work to classify the interesting class instead of the overall accuracy. The detail methods for applying each deep learning technique in the experiment is as follows. The CNN algorithm is a method that reads adjacent values from a specific value and recognizes the features, but it does not matter how close the distance of each business data field is because each field is usually independent. In this experiment, we set the filter size of the CNN algorithm as the number of fields to learn the whole characteristics of the data at once, and added a hidden layer to make decision based on the additional features. For the model having two LSTM layers, the input direction of the second layer is put in reversed position with first layer in order to reduce the influence from the position of each field. In the case of the dropout technique, we set the neurons to disappear with a probability of 0.5 for each hidden layer. The experimental results show that the predicted model with the highest F1 score was the CNN model using the dropout technique, and the next best model was the MLP model with two hidden layers using the dropout technique. In this study, we were able to get some findings as the experiment had proceeded. First, models using dropout techniques have a slightly more conservative prediction than those without dropout techniques, and it generally shows better performance in classification. Second, CNN models show better classification performance than MLP models. This is interesting because it has shown good performance in binary classification problems which it rarely have been applied to, as well as in the fields where it's effectiveness has been proven. Third, the LSTM algorithm seems to be unsuitable for binary classification problems because the training time is too long compared to the performance improvement. From these results, we can confirm that some of the deep learning algorithms can be applied to solve business binary classification problems.

• The Korean Journal of Food And Nutrition
• /
• v.30 no.3
• /
• pp.539-551
• /
• 2017

This study investigated the current status and needs for nutrition education to help reduce children's sugars intake at the Center for Children's Foodservice Management (CCFM, n=115), and Child Care Facilities (CCF, n=646) through an online survey conducted from October $5^{th}$ to $30^{th}$ 2015. A total of 14.8% of CCFM respondents and 31.9% of CCF respondents provided nutrition education on sugars intake to young children as a main topic (p<0.001). A higher percentage (CCFM 47.8%: CCF 42.4%) delivered nutrition education on sugars intake to young children as a sub-component (p<0.001). Over 90% of the CCFM and CCF participants agreed on the necessity of providing nutrition education on sugars intake to children. The most common reasons given for delivering nutrition education on children's sugar intake were "there are many more urgent nutrition education topics" for CCFM, and "insufficient nutrition education information and materials" for CCF. The percentage of nutrition education on children's sugar intake provided to the children's parents was low showing about 20% in the both groups. The percentage of CCFM participants providing nutrition, education on children's sugar intake to the teachers in CCF was also low, showing about 14.8%; however, 68.0% of the CCF participants wanted to received teacher's education on guiding children's sugar intake. Regarding ideas about a nutrition education program on children's sugar intake for young children, most respondents in both groups answered "sugar intake and dental cavities or obesity" for appropriate education contents, "story telling or puppet show" for appropriate education methods, and "dietitian from CCFM and class teacher together" for appropriate educator. For appropriate education time, there was a significantl difference between the CCFM responses (average 2.7 times) and the CCF responses (average 4 times). Based on the above results, we found that implementing nutrition education on children's sugar intake at the CCFM and CCF, was low; however, awareness of the need for nutrition education on children's sugar intake and the program development and supply was very high. Also, the opinions of CCFM and CCF participants about a nutrition education program on children's sugar intake for young children can provide foundation data to develop and implement the CCFM-based nutrition education program.

• Journal of Intelligence and Information Systems
• /
• v.23 no.4
• /
• pp.147-168
• /
• 2017

There have been many studies on accurate stock market forecasting in academia for a long time, and now there are also various forecasting models using various techniques. Recently, many attempts have been made to predict the stock index using various machine learning methods including Deep Learning. Although the fundamental analysis and the technical analysis method are used for the analysis of the traditional stock investment transaction, the technical analysis method is more useful for the application of the short-term transaction prediction or statistical and mathematical techniques. Most of the studies that have been conducted using these technical indicators have studied the model of predicting stock prices by binary classification - rising or falling - of stock market fluctuations in the future market (usually next trading day). However, it is also true that this binary classification has many unfavorable aspects in predicting trends, identifying trading signals, or signaling portfolio rebalancing. In this study, we try to predict the stock index by expanding the stock index trend (upward trend, boxed, downward trend) to the multiple classification system in the existing binary index method. In order to solve this multi-classification problem, a technique such as Multinomial Logistic Regression Analysis (MLOGIT), Multiple Discriminant Analysis (MDA) or Artificial Neural Networks (ANN) we propose an optimization model using Genetic Algorithm as a wrapper for improving the performance of this model using Multi-classification Support Vector Machines (MSVM), which has proved to be superior in prediction performance. In particular, the proposed model named GA-MSVM is designed to maximize model performance by optimizing not only the kernel function parameters of MSVM, but also the optimal selection of input variables (feature selection) as well as instance selection. In order to verify the performance of the proposed model, we applied the proposed method to the real data. The results show that the proposed method is more effective than the conventional multivariate SVM, which has been known to show the best prediction performance up to now, as well as existing artificial intelligence / data mining techniques such as MDA, MLOGIT, CBR, and it is confirmed that the prediction performance is better than this. Especially, it has been confirmed that the 'instance selection' plays a very important role in predicting the stock index trend, and it is confirmed that the improvement effect of the model is more important than other factors. To verify the usefulness of GA-MSVM, we applied it to Korea's real KOSPI200 stock index trend forecast. Our research is primarily aimed at predicting trend segments to capture signal acquisition or short-term trend transition points. The experimental data set includes technical indicators such as the price and volatility index (2004 ~ 2017) and macroeconomic data (interest rate, exchange rate, S&P 500, etc.) of KOSPI200 stock index in Korea. Using a variety of statistical methods including one-way ANOVA and stepwise MDA, 15 indicators were selected as candidate independent variables. The dependent variable, trend classification, was classified into three states: 1 (upward trend), 0 (boxed), and -1 (downward trend). 70% of the total data for each class was used for training and the remaining 30% was used for verifying. To verify the performance of the proposed model, several comparative model experiments such as MDA, MLOGIT, CBR, ANN and MSVM were conducted. MSVM has adopted the One-Against-One (OAO) approach, which is known as the most accurate approach among the various MSVM approaches. Although there are some limitations, the final experimental results demonstrate that the proposed model, GA-MSVM, performs at a significantly higher level than all comparative models.