• Journal of The Korean Society of Grassland and Forage Science
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• v.41 no.2
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• pp.119-127
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• 2021

The objective of this study was to evaluate effects of feeding methods on in vitro ruminal fermentation, total gas and methane production in Hanwoo steers. Six Hanwoo steers fitted with rumen cannula (430 ± 21 kg of body weight) were randomly assigned to one of three feeding systems: 1) feeding forage 1 hour after concentrate, 2) feeding concentrate 1 hour after forage, 3) feeding mixed ration. Rumen fluid sampled from each animals was incubated 24 hours with maize or timothy substrates in in vitro. Ruminal pH was increased in feeding method 2 or maize substrate than that of other methods or timothy substrate (P < 0.001). The production of total volatile fatty acid, acetate, propionate, butyrate, and valerate were increased when steers fed diets using feeding method 1 or rumen fluid was incubated with maize substrate (P < 0.001). Increased production of total gas and methane was observed in feeding method 1 and maize substrate compared to those of other methods or timothy substrate (P < 0.001). Due to the inconsistent results between ruminal fermentation and gas production in this study, further research is required to estimate effects of feeding method on enteric fermentation and gas production in in vivo.

• The Journal of Sustainable Design and Educational Environment Research
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• v.20 no.2
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• pp.1-10
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• 2021

The results of research and analysis are as follows: First, there were 108 types of change patterns in the number of elementary school students. Second, based on the similarity of 108 types of change patterns in the number of students, a type system diagram was presented. Third, in the case of a total of 18 types of change patterns in the number of students, the number of students decreased significantly due to the establishment of additional schools on top of the existing schools. The result of a a long-term survey and analysis on the trend of increase and decrease in the number of students across the country shows an urgent need todevelop policy tasks across the entire school accommodation plan, such as the establishment of differentiated schools suitable for regional characteristics, relocation, consolidation, reorganization of school districts, remodeling, and appropriatization projects.

• Journal of Korean Home Economics Education Association
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• v.33 no.1
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• pp.101-127
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• 2021

The purpose of this study is to design and develop a teaching-learning process plan for process-based assessment, focusing on the unit related to life design in middle school home economics(HE: Home Economics part of 「Technology and Home Economics」), to propose a feedback plan after implementing it, and to evaluate the plan through participatory observation and interviews. The student reflection journals, teacher's class journals, participatory observation journals, interviews, and performance tasks, were collected and analyzed to provide foundational date to be utilized for feedback to students, and class improvement. The research results are as follows: First, the developed teaching-learning process plan consists of a total of 8 sessions, i.e. 2 sessions for each of the four learning themes, under the practical question of "What should I do to live the life I want?" The portfolio was composed of five evaluation topics and for evaluation, oral presentation, observational evaluation, self-assessment, and peer evaluation were considered. Second, during the class, feedback from teachers, feedback from fellow students, feedback through results, and a plan to record them were provided. Third, from the analysis of collected data including observation journals and interviews, it was apparent that the students recognized the necessity of process-based assessment after the class, and students acknowledged that through the process-based evaluation in which they are evaluated on the efforts they made and provided with feedbacks, they participated more in class, and it lead them to experience a sense of growth and a feeling that they took a step forward into their future. Teachers suggested that the class through feedback was suitable for the unit and the capacity of the class, but the difficulty they experienced in giving feedback was presented as a disadvantage. For the process-based assessment, follow-up research is needed on various ways to provide feedback on-line and off-line through changes in the perception of assessment.

• Maritime Security
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• v.3 no.1
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• pp.141-185
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• 2021

The growing U.S.-China rivalry has placed the countries of Southeast Asia in exceedingly precarious positions. The Republic of Korea (ROK) likewise has been tasked with the challenge of "navigating the waters" between deepening geopolitical divides. It is in this context that the "New Southern Policy" (hereafter NSP) has become a key word in Korea's foreign policy circles. Through NSP, ROK aims to diversify its economic and security interests by strengthening ties with its southern partners, focusing on three key areas (termed as the "3 Ps"): People, Prosperity, and Peace. At the same time, the NSP seeks cooperation with other key diplomatic agendas such as the U.S.'s "Free and Open Indo-Pacific," rendering it crucial for the overall stability of the region. Considering such strategic significance, deeper analysis of the policy is more timely than ever. A brief assessment of the policy's outcome so far, however, reveals that relatively, the "Peace" pillar has been insufficient in achieving satisfactory outcomes. Here, this paper asks the question of: 1) How can the "Peace" pillar of South Korea's New Southern Policy be strengthened? Based on an analysis on the causes of the "Peace" pillar's weakness, this paper identifies counter-piracy cooperation as a solution. This paper then proceeds to answer the next question of: 2) How can ROK and ASEAN cooperate on counter-piracy, and how can these efforts be integrated into ROK's NSP? To answer the above question, this paper conducts in-depth case studies on ASEAN's and ROK's approaches to counter-piracy and identifies specific mechanisms of cooperation. In Chapter I, the paper begins with an overview of the NSP's strategic significance and an evaluation of its "Peace" pillar. Chapter II conducts a literature review on the causes of, and prescriptions for, the weakness of the "Peace" pillar. The paper then justifies why counter-piracy may be a solution. Chapter III examines ASEAN's and ROK's approaches to counter-piracy. By analyzing the general framework and each region's cases, the paper displays the strengths and weaknesses of each region's piracy responses. Based on this analysis, Chapter IV suggests ways to incorporate counter-piracy cooperation into the "Peace" pillar of the NSP. This research bears significance in that it identifies a specific area of cooperation (counter-piracy) to strengthen the "Peace" pillar of ROK's NSP. Such identification is based on a comprehensive study into the two parties' past and current experience in counter-piracy, making it contextual in nature. Furthermore, the study suggests practical mechanisms of cooperation, and considers ways of incorporation into the existing framework of NSP. This approach differs from existing literature that failed to generate case-specific, policy-oriented solutions. The COVID-19 pandemic has exacerbated piracy issues and deepened geopolitical divides. Turbulent seas such as these call for careful navigation. When it comes to promoting "peace," the key lies in combating the pirates that sail those very waters.

• Journal of Korean Home Economics Education Association
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• v.34 no.1
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• pp.59-80
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• 2022

The purpose of this study was to develop a workbook that can support the class and evaluation of the subject, 「Food safety and health」 and to verify its validity. The development direction of the workbook was set by analyzing the 「Food safety and health」 curriculum, dietary education materials, and previous studies related to the workbook, and the overall structure was designed by deriving the activity ideas for each area. Based on this, the draft was developed, and the draft went through several rounds of cross-review by the authors and the examination and revision by the Ministry of Food and Drug Safety, before the final edited version was developed. The workbook was finalized with corrections and enhancements based on the advice of 9 experts and 44 home economics teachers. The workbook consists of 4 areas: the 'food selection' area, with 10 learning topics and 36 lessons, the 'food poisoning and food management' area, with 10 learning topics and 36 lessons, the 'cooking' area, with 11 learning topics and 43 lessons, and the 'healthy eating' area, with 11 learning topics and 55 lessons, resulting in a total of 42 learning topics, 170 lessons. The workbook was designed to evenly cultivate practical problem-solving competency, self-reliance capacity, creative thinking capacity, and community capacity. In-depth inquiry-learning is conducted on the content, and the context is structured so that self-diagnosis can be made through evaluation. According to the validity test of the workbook, it was evaluated to be very appropriate for encouraging student-participatory classes and evaluations, and to create a class atmosphere that promotes inquiry by strengthening experiments and practices. In the current situation where the high school credit system is implemented and individual students' learning options are emphasized, the results of this study is expected to help expand the scope of home economics-based elective courses and contribute to realizing student-led classrooms with a focus on inquiry.

• Journal of Practical Agriculture & Fisheries Research
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• v.16 no.1
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• pp.193-206
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• 2014

The objectives of the project are to increase farmers' income through GAP and to reduce the loss of agricultural produce, for which the Korean partner takes a role of transferring needed technologies to the project site. To accomplish the project plan, it is set to implement the project with six components: construction of buildings, installation of agricultural facilities, establishment of demonstration farms, dispatching experts, conducting training program in Korea and provision of equipments. The Project Management Committee and the Project Implementation Team are consisted of Korean experts and senior officials from Department of Agriculture, Myanmar that managed the project systematically to ensure the success of the project. The process of the project are; the ceremony of laying the foundation and commencing the construction of training center in April, 2012. The Ribbon Cutting Ceremony for the completion of GAP Training Center was successfully held under PMC (MOAI, GAPI/ARDC) arrangement in SAl, Naypyitaw on June 17, 2012. The Chairman of GAPI, Dr. Sang Mu Lee, Director General U Kyaw Win of DOA, officials and staff members from Korea and Myanmar, teachers and students from SAl attended the ceremony. The team carried out an inspection and fixing donors' plates on donated project machineries, agro-equipments, vehicles, computers and printer, furniture, tools and so forth. Demonstration farm for paddy rice, fruits and vegetables was laid out in April, 2012. Twenty nine Korean rice varieties and many Korean vegetable varieties were introduced into GAP Project farm to check the suitability of the varieties under Myanmar growing conditions. Paddy was cultivated three times in DAR and twice in SAl. In June 2012, vinyl houses were started to be constructed for raising seedlings and finished in December 2012. Fruit orchard for mango, longan and dragon fruit was established in June, 2012. Vegetables were grown until successful harvest and the harvested produce was used for panel testing and distribution in January 2013. Machineries for postharvest handling systems were imported in November 2012. Setting the washing line for vegetables were finished and the system as run for testing in June 2013. New water tanks, pine lines, pump house and electricity were set up in October 2013.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.38 no.4
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• pp.350-359
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• 1993

The effect of gibberellic acid ($GA_3) and abscisic acid (ABA) on KCl-enhanced proteolysis of senescing leaves of rice(Oryza sativa L. cv. Chilsung) was studied. Emphasis was given to their effects on KCI-enhanced efflux of amino acids and proteinase activity. When treated singly, $GA_3 affected leaf proteolysis little, while ABA increased proteolysis, the rate of amino acid efflux, and ribulose -1,5 -bisphosphate carboxylase / oxygenase (Rubisco)-degrading endoproteinase activity. An additive increase in all three parameters mentioned above was observed when leaves were treated with ABA and KCl. No such an additive effect was found when $GA_3 was treated with KCl. Both $GA_3 and ABA helped to alleviate the KCI-suppressed activity of Rubisco-degrading exoproteinases. The additive increase in proteolysis of rice leaves in the presence of both ABA and KCl could thus be ascribed to a further increase in the efflux of protein hydrolyzates and Rubisco-degrading endoproteinase activity. An increase in proteolysis was accompanied by a decrease in water absorption, and the combined treatment of ABA with KCl resulted in a further reduction of water absorption.

• Korean Journal of Culture and Social Issue
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• v.12 no.5_spc
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• pp.45-79
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• 2006

The purpose of this paper was to review the results of the subjective well-being(swb) studies performed by Hahn and coworkers in Korean culture. As the correlates of swb, we dealt with demographic/individual difference variables, intrapersonal variables, interpersonal process variables, and Korean cultural variables. We proposed that the components of swb were consisted of quality of life(cognitive swb) and overall happy feelings about one's own life(emotional swb). It was also assumed that a measure of total swb could be calculated by summated mean of cognitive swb and emotional swb measures. The data of the swb studies were analyzed and interpreted according to the above three measures of swb. The results of a nationwide survey(Hahn, 2004) from age of 19 to 75 years ald(n=2,230) showed significant simple correlation coefficients between the following demographic/individual difference variables and swb: Gender difference in swb was found(total swb r=.08, p<.001; life satisfaction r=.10, p<.001; overall emotional swb r=.05, p<.05). Men were happier than women in terms of all three measures of swb. It was also found that women appeared to experience greater positive and negative emotions. Correlation between age and emotional swb(r=.09, p<.001) was significant, but life satisfaction was not significant(r=.04, n.s). Correlations between economic status and swb were also significant(total swb r =.23, p<.001; life satisfaction r=.15 p<.001; overall emotional swb r=.15, p<.001l). Although existence of father was negatively related to emotional swb(r=-.05, p<.05), the existence of mother was not related to any of swb measures. Similarly existence of brothers was related positively to overall emotional swb, but existence of sisters was not. Though existence of son was not related to swb, daughter contributed negatively to swb(total swb -.12, p<.01; life satisfaction -.09, p<.05; emotional swb r=-.12, p<.01). We assumed that family member-in-Iaw also contributed to swb because the extended dose social networks were important in Korean culture. The results showed that the following family member-in-law variables were related to swb: Parents-in-law(total swb r=.11, p<.01; life satisfaction r=.10, p<.01; emotional swb r=.10, p<.01), father-in-law(total swb r=.11, p<.01; life satisfaction r=.11, p<.01; emotional swb r=.06, n.s). The result suggested that especially father-in-law contributed to swb through financial and social support. Correlations between emotional experiences in everyday life and swb were also presented. The range of correlation coefficients between the positive emotion measures and swb were r=.30~.48(p<.001) when the above two measures obtained at same time. But the range decreased to r=.19~32(p<.001) when the swb measure was obtained 9 month later longitudinally. Intercorrelations between positive emotional experience; and life satisfaction were r=.37~58(p<.001) when two measures were obtained at same time. We also examined the effects of the intrapersonal cognitive responses to the most stressful life event upon swb. The results of nationwide survey(n=1,021) showed that self-disclosure(total swb r=.09, p<.010; life satisfaction r=.10, p<.01; emotional swb r=.07, p<.01), rumination(total swb r=-.17, p<.001), thought avoidance(total swb r=.12, p<.001; life satisfaction r=-.08; emotional swb r=-.12, p<.001) and suppression(total swb r=-.13, p<.001; life satisfaction r=-.08, p<.05: emotional swb r=-.13, p<.001) contributed to swb. It was also suggested that mismatch between self-guide and regulatory focus contributed negatively to emotional swb. It was also found that social comparison motives and fulfillment of the motives contributed to swb. The results of a survey research(n=363 college students) revealed that the higher the general social comparison motive, the lower the swb(total swb r=-.15, P<.01: life satisfaction r=-.17. p<.01; emotional swb r=-.10, p<.05). It was also found that satisfaction level of self-evalution motive contributed positively to swb(total swb r=-.14. p<.01: life satisfaction r=-.12, p<.05; emotional swb r=.15, p<.001). Both of self-improvement motive(r=.13, p<.05) and satisfaction level of self-improvement motive(r=.12, p<.05) contributed positively to emotional swb, respectively. The above results suggested that swb was depended upon the interaction effect of social comparison motive; and level of fulfillment of the motives. We also reported the significant multiple predictors of swb in a sample of age from 60years to 89years olds. The results of multiple regression analysis showed that the significant multiple predictors of swb were past illness(β=.174, p<.001), economic status(β=.418, p<.001), marital satisfaction(β=.0841, p<.001), satisfaction of offsprins(β=.065, p<.01), expectation level of social support from offsprings(β=-.049, p<.001), and negative emotions(β=-.454. p<.001) among 16 social psychological factors. It was also found that swb was an important multiple predictors of physical health. This finding was replicated in a longitudinal study. Both of positive and negative emotional experiences were significant multiple predictors of physical health one year later. The results of the discriminant analysis showed both of total swb and positive emotional experiences contributed to discriminate the happy and healthy olds from unhappy and unhealthy olds. We paper also examined the effects of the nonnative social behaviors upon swb in Korean culture. The main hypotheses of the study(Hahn, 2006, in press) was that the important nonnative behaviors would influence on swb through both of the mediation processes of adjustment to social relationships and psychological stress. The survey data were collected from 2,129 adults age of 19 to 75, from 7 regional areas in Korea. The results of the study revealed that almost all of correlation coefficients between 15 normative social behaviors and the above three criteria w-ere significant. The fitness test results of the covariance structural equation model showed that all of the fitness indices were satisfactory (GFI=.974, AGFI=.909, NNFI=.922, NFI=.973, CFI=.974. RMR=.049, RMSEA=.073). The results of the analysis revealed that the following five path coeffi6ents from behaviors to social adjustment were significant; behavior tor family and family members(t=5.87, p<.001), courteous behavior(t=4.39, p<.001), faithful behavior (t=2.15. p<.05). collectivistic behavior(t=8.31, p<.001). Seven path coefficients from the normative behaviors to psychological stress were significant; behavior for family and family members (t=-4.63, p<.001), faithful behavior(t=-3.86, p<.001). suppression of emotional expression(t=3.99, p<.001), trustworthy and dependable behavior(t=-2.21, p<.05), collectivistic behavior(t=3.72, p<.001), effortful and diligent behavior(t=2.94, p<.001), husbandry and saving behavior(t=3.40, p<.001). The above results suggested that four normative behaviors among seven behaviors contributed negatively to psychological stress in current Korean society. The results abo confirmed the hypothesized paths from social adjustment (t=10.40, p<.001) to swb and from psychological stress(t=-19.74, p<.001) to swb. The important results of the study were discussed in terms of the Confucian traditions and recent social changes in Korean culture. Finally limitations of this review paper were discussed and the suggestions for the future study were also proposed.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.1-20
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• 2013

Nowadays, social network is a huge communication platform for providing people to connect with one another and to bring users together to share common interests, experiences, and their daily activities. Users spend hours per day in maintaining personal information and interacting with other people via posting, commenting, messaging, games, social events, and applications. Due to the growth of user's distributed information in social network, there is a great potential to utilize the social data to enhance the quality of recommender system. There are some researches focusing on social network analysis that investigate how social network can be used in recommendation domain. Among these researches, we are interested in taking advantages of the interaction between a user and others in social network that can be determined and known as social relationship. Furthermore, mostly user's decisions before purchasing some products depend on suggestion of people who have either the same preferences or closer relationship. For this reason, we believe that user's relationship in social network can provide an effective way to increase the quality in prediction user's interests of recommender system. Therefore, social relationship between users encountered from social network is a common factor to improve the way of predicting user's preferences in the conventional approach. Recommender system is dramatically increasing in popularity and currently being used by many e-commerce sites such as Amazon.com, Last.fm, eBay.com, etc. Collaborative filtering (CF) method is one of the essential and powerful techniques in recommender system for suggesting the appropriate items to user by learning user's preferences. CF method focuses on user data and generates automatic prediction about user's interests by gathering information from users who share similar background and preferences. Specifically, the intension of CF method is to find users who have similar preferences and to suggest target user items that were mostly preferred by those nearest neighbor users. There are two basic units that need to be considered by CF method, the user and the item. Each user needs to provide his rating value on items i.e. movies, products, books, etc to indicate their interests on those items. In addition, CF uses the user-rating matrix to find a group of users who have similar rating with target user. Then, it predicts unknown rating value for items that target user has not rated. Currently, CF has been successfully implemented in both information filtering and e-commerce applications. However, it remains some important challenges such as cold start, data sparsity, and scalability reflected on quality and accuracy of prediction. In order to overcome these challenges, many researchers have proposed various kinds of CF method such as hybrid CF, trust-based CF, social network-based CF, etc. In the purpose of improving the recommendation performance and prediction accuracy of standard CF, in this paper we propose a method which integrates traditional CF technique with social relationship between users discovered from user's behavior in social network i.e. Facebook. We identify user's relationship from behavior of user such as posts and comments interacted with friends in Facebook. We believe that social relationship implicitly inferred from user's behavior can be likely applied to compensate the limitation of conventional approach. Therefore, we extract posts and comments of each user by using Facebook Graph API and calculate feature score among each term to obtain feature vector for computing similarity of user. Then, we combine the result with similarity value computed using traditional CF technique. Finally, our system provides a list of recommended items according to neighbor users who have the biggest total similarity value to the target user. In order to verify and evaluate our proposed method we have performed an experiment on data collected from our Movies Rating System. Prediction accuracy evaluation is conducted to demonstrate how much our algorithm gives the correctness of recommendation to user in terms of MAE. Then, the evaluation of performance is made to show the effectiveness of our method in terms of precision, recall, and F1-measure. Evaluation on coverage is also included in our experiment to see the ability of generating recommendation. The experimental results show that our proposed method outperform and more accurate in suggesting items to users with better performance. The effectiveness of user's behavior in social network particularly shows the significant improvement by up to 6% on recommendation accuracy. Moreover, experiment of recommendation performance shows that incorporating social relationship observed from user's behavior into CF is beneficial and useful to generate recommendation with 7% improvement of performance compared with benchmark methods. Finally, we confirm that interaction between users in social network is able to enhance the accuracy and give better recommendation in conventional approach.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.167-181
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• 2018

Over the past decade, deep learning has been in spotlight among various machine learning algorithms. In particular, CNN(Convolutional Neural Network), which is known as the effective solution for recognizing and classifying images or voices, has been popularly applied to classification and prediction problems. In this study, we investigate the way to apply CNN in business problem solving. Specifically, this study propose to apply CNN to stock market prediction, one of the most challenging tasks in the machine learning research. As mentioned, CNN has strength in interpreting images. Thus, the model proposed in this study adopts CNN as the binary classifier that predicts stock market direction (upward or downward) by using time series graphs as its inputs. That is, our proposal is to build a machine learning algorithm that mimics an experts called 'technical analysts' who examine the graph of past price movement, and predict future financial price movements. Our proposed model named 'CNN-FG(Convolutional Neural Network using Fluctuation Graph)' consists of five steps. In the first step, it divides the dataset into the intervals of 5 days. And then, it creates time series graphs for the divided dataset in step 2. The size of the image in which the graph is drawn is $40(pixels){\times}40(pixels)$, and the graph of each independent variable was drawn using different colors. In step 3, the model converts the images into the matrices. Each image is converted into the combination of three matrices in order to express the value of the color using R(red), G(green), and B(blue) scale. In the next step, it splits the dataset of the graph images into training and validation datasets. We used 80% of the total dataset as the training dataset, and the remaining 20% as the validation dataset. And then, CNN classifiers are trained using the images of training dataset in the final step. Regarding the parameters of CNN-FG, we adopted two convolution filters ($5{\times}5{\times}6$ and $5{\times}5{\times}9$) in the convolution layer. In the pooling layer, $2{\times}2$ max pooling filter was used. The numbers of the nodes in two hidden layers were set to, respectively, 900 and 32, and the number of the nodes in the output layer was set to 2(one is for the prediction of upward trend, and the other one is for downward trend). Activation functions for the convolution layer and the hidden layer were set to ReLU(Rectified Linear Unit), and one for the output layer set to Softmax function. To validate our model - CNN-FG, we applied it to the prediction of KOSPI200 for 2,026 days in eight years (from 2009 to 2016). To match the proportions of the two groups in the independent variable (i.e. tomorrow's stock market movement), we selected 1,950 samples by applying random sampling. Finally, we built the training dataset using 80% of the total dataset (1,560 samples), and the validation dataset using 20% (390 samples). The dependent variables of the experimental dataset included twelve technical indicators popularly been used in the previous studies. They include Stochastic %K, Stochastic %D, Momentum, ROC(rate of change), LW %R(Larry William's %R), A/D oscillator(accumulation/distribution oscillator), OSCP(price oscillator), CCI(commodity channel index), and so on. To confirm the superiority of CNN-FG, we compared its prediction accuracy with the ones of other classification models. Experimental results showed that CNN-FG outperforms LOGIT(logistic regression), ANN(artificial neural network), and SVM(support vector machine) with the statistical significance. These empirical results imply that converting time series business data into graphs and building CNN-based classification models using these graphs can be effective from the perspective of prediction accuracy. Thus, this paper sheds a light on how to apply deep learning techniques to the domain of business problem solving.