• Journal of The Korean Association For Science Education
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• v.35 no.1
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• pp.73-84
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• 2015

In this research, two careers connectable with the contents of the curriculum of fifth to sixth grade elementary school students were selected among other promising future careers in biotechnology and medical engineering fields. 'Design-based promising future career STEAM program' was developed and its validity and effectiveness were verified. Reflecting recent issues, and complying with the STEAM standard (frame) instructional materials were developed through group deliberations for nine months, based on the achievement standards through an analysis of subject curriculum revised in 2009. This was prepared so that students are able to experience biotechnology and medical engineering related careers in a simulational form emphasized with creative design to make them prefer natural sciences and engineering careers and draw their interests and recognition of the relevant careers under the two disciplines. As a result of such application to STEAM Leader School students at the verification stage of the program, the contents and level of the program were verified suitable, receiving favorable reviews. And as a result of applying the developed program on other elementary school students, it was discovered that significant improvements were found in their career consciousness. Through this research, it was suggested that there is a need for a simplification of the curriculum content standards, a provision of 'standard for integration,' development of teachers' ability in reconstituting or organizing the STEAM and proceeding classes, continuous long-term support to see the effects of a policy or a program, and a reinforcement of career education integrated in the curriculum.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.6
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• pp.1-11
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• 2023

By comparing and analyzing the effects of the 2013 Suncheon Bay International Garden Expo and the 2023 Suncheon Bay International Garden Expo, designated as Korea's first national garden, this study aims to present basic data for the future operation direction and sustainability strategy. First, in both fairs, satisfaction throughout the event was high, 4.0 or higher. In particular, the satisfaction level of the 2023 Suncheon Bay International Garden Expo was higher than that of the 2013 Suncheon Bay International Garden Expo. As the longest international event held since the COVID-19 pandemic, it reflected the citizens' demand for healing and recharging in natural spaces. Second, as a result of comparing the types of perceptions that affected satisfaction, it was found that economic, environmental, and ecological types commonly affected satisfaction at the 2013 and 2023 Suncheon Bay International Garden Expo. The 2013 Suncheon Bay International Garden Expo established the brand value as an "ecological city" by creating a garden in the city center along with an ecological resource called Suncheon Bay. In addition, the 2023 Suncheon Bay International Garden Expo expanded the scope of the garden to the entire city center. It also attempted to create a city where humans and nature coexist by realizing values, such as responding to climate change and carbon neutrality. In other words, one of the ways to secure urban competitiveness is to attract corporate investment and tourists and build a differentiated brand in Suncheon by promoting the 2023 fair based on the potential ecological values of the region after the 2013 Suncheon Bay International Garden Expo. Therefore, if the Suncheon Bay International Garden Expo continues to develop environmental and ecological content and programs in line with changes in society and tries to establish itself in citizens' perception through cooperation with local governments and residents, it will be able to establish its identity and brand power.

• Korean Security Journal
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• no.22
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• pp.37-64
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• 2010

Since the September 11, 2001, the motives and objectives of terrorism that have been targeted at hard targets such as key national facilities have now shifted towards soft targets such as subways, department stores, and tourist hotels; the attacks on these soft targets are steadily increasing. Simultaneous, unconventional, and indiscriminate terrorist attacks on civilians has also increased. In November, 2010, nearly forty states of the G20 and B20 (Business 20) will join in international summits to be hosted in Seoul. This coming July, an additional 350 troops will be deployed to Afghanistan for the sustainment of public security. Such events are sensitive topics, and there is the possibility of terrorist movement. Korea has successfully hosted various international events such as the APEC and ASEM Summits, and the 2002 Korea-Japan World Cup. The experiences from these events must be applied to ensure the safety of public facilities against the dangers of terrorism. First, counter-terrorism center must be established for the long-term, above the General Officer level to ensure the safety and efficiency of multilateral, international summits, as well as promoting policies and legislation aimed at preventing terrorism. Second, a terrorist threat management system must be secured and safety measures must be emphasized. Third, a fundamental structure must be established for the prevention of terrorism on public facilities, as well as legal and government action against the new threat of IED. Fourth, the police and fire fighting networks' must have a firm rapid response posture on the scene of an attack. Fifth, the state of mentality on the recognition of terrorist threats must be changed and restructured by promoting to and educating the population. Sixth, prevention measures must be established via research and academia. Seventh, for the guarantee of security in public facilities, safety management should employ cutting edge technology such as the 3D SICS and further develop and apply such technology. All methods and resources must be fully utilized for the establishment and strengthening terrorism prevention measures.

• Journal of The Korean Association For Science Education
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• v.22 no.4
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• pp.862-871
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• 2002

We investigated elementary students' conceptions of the simple electric circuit using a battery, a bulb and a wire, and made comparison between the cognitive conflict through peer discussion and the cognitive conflict through physical experience. Two hundred and sixty-four sixth grade students who already had learned about the electric circuit were participated. The questionnaire to investigate the student's conceptions about simple electric circuit consisted of 5 items drawing the wire connections between a battery and a bulb to light the bulb. The students in the discussion group paired randomly with student who had different conceptions, and then each pairs discussed about their ideas freely with each other. After discussion they conducted CCLT(Cognitive Conflict Level Test) which consisted of 4 factors; recognition, interest, anxiety, reappraisal. The physical experience group conducted a task in which they connected a battery and a bulb with a wire, then conducted CCLT. The sixth graders had various misconceptions. Most students were not aware of the scope of negative battery terminal and two electric terminals of a bulb. Many students emphasized the tip of a bulb and positive battery terminal. The score of CCLT in the discussion group was higher than in the physical experience group. This results showed that discussion with peers was more effective than physical experience to arouse cognitive conflict.

• Korean journal of food and cookery science
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• v.17 no.6
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• pp.542-548
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• 2001

Hazard Analysis Critical Control Point(HACCP) is becoming an important component of food safety worldwide. The aim of this study was to investigate comprehensively the education and knowledge level of food service managers on HACCP as well as applying HACCP system to industrial foodservice. Total 247 foodservice managers participated in the survey and 159 responses were used for analysis. The results were as follows: 1) 89% of foodservice managers were educated about HACCP, and 40.9% felt they did fully understand HACCP and 47.8% did half. 2) The score for the implementation of HACCP was in the order of apparatus and facility sanitation, personal sanitation, and time-temperature/etc. sanitation. 3) Foodservice managers who were taught HACCP kept a deep attention to food and personal sanitation, compared with those without education(p＜0.05). However, the education time on HACCP affected conducting safety management. The results suggest that education and understanding of HACCP are positively related, and understanding of HACCP has a positive influence on conducting safety management.

• Journal of the Korean Society of Food Science and Nutrition
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• v.43 no.6
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• pp.934-942
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• 2014

The purpose of this study was to investigate factors affecting problematic drinking by university students in the Chuncheon area. Lifelong drinking rate of subjects was 98.1%. Problematic drinking rates according to AUDIT (alcohol use disorders identification test) were as follows: 21.3% 'no problem', 58.0% 'at-risk drinking', 10.0% 'alcohol abuse' and 10.7% 'alcohol dependence'. Research has shown that problematic drinking is more prevalent among freshmen, early drinkers, those with hypochondria, and students who are less satisfied with their campus life or whose own parents are frequent drinkers. It has been shown that more serious problematic drinking is associated with higher 'positive alcohol outcome expectancies' and 'coping motives for drinking', and 'recognition level of drinking cultures' is considered less desirable. Multiple regression analysis revealed that 'coping motives for drinking' was the most significant variable affecting the problematic drinking of university students. Developing and fostering various alcohol-reducing programs that largely focus on 'coping motives for drinking' will greatly contribute to solving problematic drinking.

• Women's Studies Review
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• v.27 no.1
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• pp.73-109
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• 2010

The cultural pluralism on which more and more emphasis is put in the globalized cultural environment, takes local identity as a crucial index for the cultural exchange on the global level, but at the same time it results in transforming individual regions/places into a homogeneous space, as it forces the local identity itself to fit into the standardized global perspective. In this context I focus on two art projects that are related to 'Dongducheon', a town that houses the U. S. Second Infantry Division. These projects attract specific attention due to the fact that Dongducheon is a significant place with very 'thick' cultural identity: it reveals that modernization in Korea took place in intersection of nationalism, patriarchy and gender/sexuality postcolonial (military) culture. With these two Dongducheon related art projects (Donglyung Kim) and (Eunyoung Jeong) as excellent examples of site-specific art practice, this paper asks what it means to keep the historicity of disappearing local space/place in the global era. And how is it possible to 'represent' an extremely gendered/sexualized place like Dongducheon. This should be examined from a postcolonial feminist perspective. Since emancipation from Japanese occupation Dongducheon has been an island or an outside space in the nation-state Korea. This becomes more complicated, as now mostly women from the Philippines or former Soviet countries are working in the nightclubs in Doungducheon. and are feminist activist experiments to make the place with its residents to be seen and heard in proper a way of mourning, recognition and communication. shows the 'new' kijich'on women as those who are daring to be on an 'Odyssey' for a better life as they run everyday life in Dongducheon, working in clubs, doing laundry, bearing children, going to mass; tries to help them to be heard and felt, while it gathers sounds on the street or at mass and shows the doors or narrow alleys which lead to the their rooms. It aims to mourn the dead kijich'on women and to represent the precarious life of the present migrant kijich'on women, as it shows no faces.

• Asia pacific journal of information systems
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• v.24 no.4
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• pp.443-472
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• 2014

To survive in the global competitive environment, enterprise should be able to solve various problems and find the optimal solution effectively. The big-data is being perceived as a tool for solving enterprise problems effectively and improve competitiveness with its' various problem solving and advanced predictive capabilities. Due to its remarkable performance, the implementation of big data systems has been increased through many enterprises around the world. Currently the big-data is called the 'crude oil' of the 21st century and is expected to provide competitive superiority. The reason why the big data is in the limelight is because while the conventional IT technology has been falling behind much in its possibility level, the big data has gone beyond the technological possibility and has the advantage of being utilized to create new values such as business optimization and new business creation through analysis of big data. Since the big data has been introduced too hastily without considering the strategic value deduction and achievement obtained through the big data, however, there are difficulties in the strategic value deduction and data utilization that can be gained through big data. According to the survey result of 1,800 IT professionals from 18 countries world wide, the percentage of the corporation where the big data is being utilized well was only 28%, and many of them responded that they are having difficulties in strategic value deduction and operation through big data. The strategic value should be deducted and environment phases like corporate internal and external related regulations and systems should be considered in order to introduce big data, but these factors were not well being reflected. The cause of the failure turned out to be that the big data was introduced by way of the IT trend and surrounding environment, but it was introduced hastily in the situation where the introduction condition was not well arranged. The strategic value which can be obtained through big data should be clearly comprehended and systematic environment analysis is very important about applicability in order to introduce successful big data, but since the corporations are considering only partial achievements and technological phases that can be obtained through big data, the successful introduction is not being made. Previous study shows that most of big data researches are focused on big data concept, cases, and practical suggestions without empirical study. The purpose of this study is provide the theoretically and practically useful implementation framework and strategies of big data systems with conducting comprehensive literature review, finding influencing factors for successful big data systems implementation, and analysing empirical models. To do this, the elements which can affect the introduction intention of big data were deducted by reviewing the information system's successful factors, strategic value perception factors, considering factors for the information system introduction environment and big data related literature in order to comprehend the effect factors when the corporations introduce big data and structured questionnaire was developed. After that, the questionnaire and the statistical analysis were performed with the people in charge of the big data inside the corporations as objects. According to the statistical analysis, it was shown that the strategic value perception factor and the inside-industry environmental factors affected positively the introduction intention of big data. The theoretical, practical and political implications deducted from the study result is as follows. The frist theoretical implication is that this study has proposed theoretically effect factors which affect the introduction intention of big data by reviewing the strategic value perception and environmental factors and big data related precedent studies and proposed the variables and measurement items which were analyzed empirically and verified. This study has meaning in that it has measured the influence of each variable on the introduction intention by verifying the relationship between the independent variables and the dependent variables through structural equation model. Second, this study has defined the independent variable(strategic value perception, environment), dependent variable(introduction intention) and regulatory variable(type of business and corporate size) about big data introduction intention and has arranged theoretical base in studying big data related field empirically afterwards by developing measurement items which has obtained credibility and validity. Third, by verifying the strategic value perception factors and the significance about environmental factors proposed in the conventional precedent studies, this study will be able to give aid to the afterwards empirical study about effect factors on big data introduction. The operational implications are as follows. First, this study has arranged the empirical study base about big data field by investigating the cause and effect relationship about the influence of the strategic value perception factor and environmental factor on the introduction intention and proposing the measurement items which has obtained the justice, credibility and validity etc. Second, this study has proposed the study result that the strategic value perception factor affects positively the big data introduction intention and it has meaning in that the importance of the strategic value perception has been presented. Third, the study has proposed that the corporation which introduces big data should consider the big data introduction through precise analysis about industry's internal environment. Fourth, this study has proposed the point that the size and type of business of the corresponding corporation should be considered in introducing the big data by presenting the difference of the effect factors of big data introduction depending on the size and type of business of the corporation. The political implications are as follows. First, variety of utilization of big data is needed. The strategic value that big data has can be accessed in various ways in the product, service field, productivity field, decision making field etc and can be utilized in all the business fields based on that, but the parts that main domestic corporations are considering are limited to some parts of the products and service fields. Accordingly, in introducing big data, reviewing the phase about utilization in detail and design the big data system in a form which can maximize the utilization rate will be necessary. Second, the study is proposing the burden of the cost of the system introduction, difficulty in utilization in the system and lack of credibility in the supply corporations etc in the big data introduction phase by corporations. Since the world IT corporations are predominating the big data market, the big data introduction of domestic corporations can not but to be dependent on the foreign corporations. When considering that fact, that our country does not have global IT corporations even though it is world powerful IT country, the big data can be thought to be the chance to rear world level corporations. Accordingly, the government shall need to rear star corporations through active political support. Third, the corporations' internal and external professional manpower for the big data introduction and operation lacks. Big data is a system where how valuable data can be deducted utilizing data is more important than the system construction itself. For this, talent who are equipped with academic knowledge and experience in various fields like IT, statistics, strategy and management etc and manpower training should be implemented through systematic education for these talents. This study has arranged theoretical base for empirical studies about big data related fields by comprehending the main variables which affect the big data introduction intention and verifying them and is expected to be able to propose useful guidelines for the corporations and policy developers who are considering big data implementationby analyzing empirically that theoretical base.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.25-52
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• 2018

This study performs social network analysis based on consumer sentiment related to a location in Seoul using data reflecting consumers' web search activities and emotional evaluations associated with commerce. The study focuses on large commercial districts in Seoul. In addition, to consider their various aspects, social network indexes were combined with the trading area's public data to verify factors affecting the area's sales. According to R square's change, We can see that the model has a little high R square value even though it includes only the district's public data represented by static data. However, the present study confirmed that the R square of the model combined with the network index derived from the social network analysis was even improved much more. A regression analysis of the trading area's public data showed that the five factors of 'number of market district,' 'residential area per person,' 'satisfaction of residential environment,' 'rate of change of trade,' and 'survival rate over 3 years' among twenty two variables. The study confirmed a significant influence on the sales of the trading area. According to the results, 'residential area per person' has the highest standardized beta value. Therefore, 'residential area per person' has the strongest influence on commercial sales. In addition, 'residential area per person,' 'number of market district,' and 'survival rate over 3 years' were found to have positive effects on the sales of all trading area. Thus, as the number of market districts in the trading area increases, residential area per person increases, and as the survival rate over 3 years of each store in the trading area increases, sales increase. On the other hand, 'satisfaction of residential environment' and 'rate of change of trade' were found to have a negative effect on sales. In the case of 'satisfaction of residential environment,' sales increase when the satisfaction level is low. Therefore, as consumer dissatisfaction with the residential environment increases, sales increase. The 'rate of change of trade' shows that sales increase with the decreasing acceleration of transaction frequency. According to the social network analysis, of the 25 regional trading areas in Seoul, Yangcheon-gu has the highest degree of connection. In other words, it has common sentiments with many other trading areas. On the other hand, Nowon-gu and Jungrang-gu have the lowest degree of connection. In other words, they have relatively distinct sentiments from other trading areas. The social network indexes used in the combination model are 'density of ego network,' 'degree centrality,' 'closeness centrality,' 'betweenness centrality,' and 'eigenvector centrality.' The combined model analysis confirmed that the degree centrality and eigenvector centrality of the social network index have a significant influence on sales and the highest influence in the model. 'Degree centrality' has a negative effect on the sales of the districts. This implies that sales decrease when holding various sentiments of other trading area, which conflicts with general social myths. However, this result can be interpreted to mean that if a trading area has low 'degree centrality,' it delivers unique and special sentiments to consumers. The findings of this study can also be interpreted to mean that sales can be increased if the trading area increases consumer recognition by forming a unique sentiment and city atmosphere that distinguish it from other trading areas. On the other hand, 'eigenvector centrality' has the greatest effect on sales in the combined model. In addition, the results confirmed a positive effect on sales. This finding shows that sales increase when a trading area is connected to others with stronger centrality than when it has common sentiments with others. This study can be used as an empirical basis for establishing and implementing a city and trading area strategy plan considering consumers' desired sentiments. In addition, we expect to provide entrepreneurs and potential entrepreneurs entering the trading area with sentiments possessed by those in the trading area and directions into the trading area considering the district-sentiment structure.

• 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.