• Journal of The Korean Association For Science Education
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• v.38 no.6
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• pp.865-874
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• 2018

The purpose of this study is to explore the process of inquiry problem finding in high school students' small group free-inquiry. For this purpose, 91 second grade high school students took part in small group free-inquiry. We conducted interviews with students (48 students in 15 groups) who were relatively successful in the inquiry performed for one semester (about 4 months). Based on the results of the interviews, we analyzed the characteristics of the inquiry problem finding through the steps and strategies in the inquiry problem finding process. The main results are as follows: First, in the inquiry problem finding process, steps such as selecting keyword, presenting an inconvenience, presenting a question, and finding an inquiry problem were found, and in particular, the process of selecting the keyword that correspond to the subject of inquiry, such as the material and situation of inquiry, is very important step in inquiry problem finding. Second, the strategies that students used in the process of finding inquiry problem included searching information, review of prior research, sharing of knowledge and experience, linking and extension of knowledge and experience, environmental awareness, expert consultation, discussion of suitability, elaboration, etc. Third, finding an inquiry problem was relatively easy in the inquiry for finding out problems (i.e. inconvenience) in everyday life and investigating ways to solve them. Fourth, the review of prior researches through the internet was useful in the process of selecting keyword and elaboration. Fifth, the factors that students consider when selecting one of several candidate inquiry problems are feasibility, real-life applicability, and economic condition. Sixth, the current affairs had a positive impact on the inquiry problem finding. Based on the above results, we discussed some ways to increase students' inquiry problem finding ability.

• Environmental and Resource Economics Review
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• v.28 no.1
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• pp.121-145
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• 2019

This paper investigates the relationship between the oil price and the major petroleum products prices at the trading hubs such as Singapore, North West Europe and the US New York Harbor. We focus on the lead-lag relationship between the weekly petroleum prices from 2009 to 2016 based on the vector error correction model. We find that the oil price leads the prices of petroleum products in the long term, while there is bidirectional causality in the short term. On the other hand, prices of petroleum products in regions with high import dependency, such as Europe gas oil and jet fuel price, are exogenous in the long term. We also present evidence that prices of petroleum products in region with a large global-market share lead prices in other regions. However, if the region is in an over-production situation and low industry concentration, it may lose its price leadership due to intense competition. The result in this study can provide a useful information to petroleum refining companies in forecasting fluctuations of product price, and hence in planning their regional arbitrage trading activities.

• The Journal of the Korea Contents Association
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• v.22 no.6
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• pp.295-306
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• 2022

This study examined the effects and roles of transmedia such as trailer (i.e., trailer) and webtoon OST (i.e., Original Sound Track), which have recently served as extended content in webtoons. In recent years, the number of transmedias using webtoons has increased rapidly, and production and consumption in various directions have been taking place. However, studies on whether these contents lead to positive emotions and attitudes toward webtoons are not actively conducted. Therefore, this paper examined the effect through loyalty and perceived enjoyment, and found that 'increasing immersion in content through transmedia' plays a major role as a major variable. In addition, it is determined whether these mechanisms appear differently by gender, and in the case of women, media consumption tends to be based on emotional signals compared to men, so transmedia will further increase the level of immersion, but webtoon content did not show gender effects on media consumption. This is a meaningful result that shows that in general, media consumption methods according to gender appear differently in webtoons. Therefore, based on the results, this study presented directions and implications to keep in mind when planning the production of various transmedias using webtoons.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.1860-1864
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• 2006

본 연구는 강우시 발생되는 강우유출수와 합류식하수관거월류수에 의해 하천으로 유입되는 오염부하를 저감시키기 위한 공법으로, 고수부지 및 제방사면부와 둔치부를 형상화하여 pilot를 제작하였고, 연속적으로 시운전을 한 SRTS(Stormwater Runoff Treatment System)에 관한 것이다. SRT system 내부의 사면수처리부와 평면수처리부에는 다공성 콘크리트를 충진하였다. system 상부에는 식생을 조성하여 뿌리가 수면에 닿아 영양물질을 흡수하는 목적으로 사면수처리부와 평면수처리부에 각각 정육각형과 직사각형인 식생포트를 탈.부착이 가능하도록 고안하였다. 내부에서는 토양과 수처리조 사이에 연결관을 부착하였고, 모세관현상에 의해 토양이 수분을 흡수하도록 구성하였다. pilot plant는 유입부, 사면 수처리부, 평면 수처리부, 유출부로 나누었다. 유입부는 유입펌프와 V-notch로 구성하였고, 유입펌프는 2대를 설치하여 1시간 간격으로 연속적 유입으로 유량조절이 가능하도록 상호교대 운전을 하였다. 평면 수처리부$(W(1.0m){\times}(L(2.4m){\times}H(0.6m))$는 장방형의 접촉산화조로서 하부에 슬러지 침전 및 저류를 위한 hopper를 설치하여 슬러지의 원활한 수집 및 인발이 가능하도록 하였다. 유출부는 사각weir를 설치하였다. 강우유출수의 pH는 $7.27{\sim}7.92$이고, DO농도는 $7.12{\sim}7.88mg/l$로 관측되었다. 2차처리수의 pH는 평균7.4이고 DO농도는 최저 4.5 mg/l에서 최고 8.9 mg/l로 평균 6.8 mg/l로 관측되었다. 또한 강우유출수의 유입수의 T-N, T-P 농도는 각각 $17.5{\sim}22.5mg/l,\;8.9{\sim}11.4mg/l$의 범위이고, 2차 처리수의 유입수의 T-N, T-P 농도와 유사하였다.적인 방법론을 제시할 수 있을 것으로 사료된다.첨두홍수량을 저류하기 위해서 상대적으로 넓은 저류면적이 필요한 것으로 나타난다. 대등한 수위감소값의 홍수저감효과를 발휘하기 위해서 본 연구에서는 On-Line 저류지 면적은 Off-Line 저류지에 비 두배 이상이 필요한 것으로 보여졌다.들에 관한 정보는 종종 현장관측에서 조차 무시되는 경우가 많다. 이에 본 연구에서는 수질모형의 매개변수 중 특히 수리특성에 관련된 매개변수들이 수질에 미치는 영향을 파악하는 것을 목적으로 하고 있다. 이를 위해 적용된 수질모형은 QualKo를 사용하였으며, 대상 하천은 낙동강 본류 경남구간 시점 부근인 회천 합류 전부터 낙동강 본류 경남구간 종점 부근인 밀양강 합류 전까지의 경남 오염총량관리 기본계획 시 구축된 모형 매개변수를 바탕으로 분석을 수행하였다. 일차오차분석을 이용하여 수리매개변수와 수질매개변수의 수질항목별 상대적 기여도를 파악해 본 결과, 수리매개변수는 DO, BOD, 유기질소, 유기인 모든 항목에 일정 정도의 상대적 기여도를 가지고 있는 것을 알 수 있었다. 이로부터 수질 모형의 적용 시 수리 매개변수 또한 수질 매개변수의 추정 시와 같이 보다 세심한 주의를 기울여 추정할 필요가 있을 것으로 판단된다.변화와 기흉 발생과의 인과관계를 확인하고 좀 더 구체화하기 위한 연구가 필요할 것이다.게 이루어질 수 있을 것으로 기대된다.는 초과수익률이 상승하지만, 이후로는 감소하므로, 반전거래전략을 활용하는 경우 주식투자기간은 24개월이하의 중단기가 적합함을 발견하였다. 이상의 행태적 측면과 투자성과측면의 실증결과를 통하여 한국주식시장에 있어서 시장수익률을 평균적으로 초과할 수 있는 거래전략은 존재하므로 이러한 전략을 개발 및 활용할 수 있으며, 특히, 한국주식시장에 적합한 거래전략은 반전거래전략이고, 이 전략의 유용성은 투자자가 설정한 투자기간보다 더욱 긴 분석기간의 주식가격정보에 의하여 최대한 발휘될 수 있음을 확인하

• 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.20 no.2
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• pp.39-58
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• 2014

As the importance of big data and related technologies continues to grow in the industry, it has become highlighted to visualize results of processing and analyzing big data. Visualization of data delivers people effectiveness and clarity for understanding the result of analyzing. By the way, visualization has a role as the GUI (Graphical User Interface) that supports communications between people and analysis systems. Usually to make development and maintenance easier, these GUI parts should be loosely coupled from the parts of processing and analyzing data. And also to implement a loosely coupled architecture, it is necessary to adopt design patterns such as MVC (Model-View-Controller) which is designed for minimizing coupling between UI part and data processing part. On the other hand, big data can be classified as structured data and unstructured data. The visualization of structured data is relatively easy to unstructured data. For all that, as it has been spread out that the people utilize and analyze unstructured data, they usually develop the visualization system only for each project to overcome the limitation traditional visualization system for structured data. Furthermore, for text data which covers a huge part of unstructured data, visualization of data is more difficult. It results from the complexity of technology for analyzing text data as like linguistic analysis, text mining, social network analysis, and so on. And also those technologies are not standardized. This situation makes it more difficult to reuse the visualization system of a project to other projects. We assume that the reason is lack of commonality design of visualization system considering to expanse it to other system. In our research, we suggest a common information model for visualizing text data and propose a comprehensive and reusable framework, TexVizu, for visualizing text data. At first, we survey representative researches in text visualization era. And also we identify common elements for text visualization and common patterns among various cases of its. And then we review and analyze elements and patterns with three different viewpoints as structural viewpoint, interactive viewpoint, and semantic viewpoint. And then we design an integrated model of text data which represent elements for visualization. The structural viewpoint is for identifying structural element from various text documents as like title, author, body, and so on. The interactive viewpoint is for identifying the types of relations and interactions between text documents as like post, comment, reply and so on. The semantic viewpoint is for identifying semantic elements which extracted from analyzing text data linguistically and are represented as tags for classifying types of entity as like people, place or location, time, event and so on. After then we extract and choose common requirements for visualizing text data. The requirements are categorized as four types which are structure information, content information, relation information, trend information. Each type of requirements comprised with required visualization techniques, data and goal (what to know). These requirements are common and key requirement for design a framework which keep that a visualization system are loosely coupled from data processing or analyzing system. Finally we designed a common text visualization framework, TexVizu which is reusable and expansible for various visualization projects by collaborating with various Text Data Loader and Analytical Text Data Visualizer via common interfaces as like ITextDataLoader and IATDProvider. And also TexVisu is comprised with Analytical Text Data Model, Analytical Text Data Storage and Analytical Text Data Controller. In this framework, external components are the specifications of required interfaces for collaborating with this framework. As an experiment, we also adopt this framework into two text visualization systems as like a social opinion mining system and an online news analysis system.

• Korean Journal of Environment and Ecology
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• v.30 no.2
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• pp.185-198
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• 2016

Korea has put in significant efforts to increase the number of wildlife crossings between fragmented habitats to prevent loss of biodiversity and to encourage the habitat connectivity in Korea. However, there is a lack of biological data on the effect of vegetation structure in these wildlife crossings and guidelines for design and management of wildlife crossing structures in Korea. Therefore, we selected ground beetle assemblages as model organisms to compare the effect of vegetation structure in wildlife crossings, i.e. bare ground- and shrub-type corridors, in agro-forested landscapes. For this study, 4,207 ground beetles belonging to 33 species were collected through pitfall trapping along the northern forest-corridor-southern forest transects from late April to early September in 2015. Dominant species, abundance, and species richness of ground beetles were significantly higher in the shrub-type corridors than the bare ground-type corridors. Also, the species composition of bare ground-type corridor was significantly different compared to the other habitats such as shrub-type corridor and forests. Similarly, environmental variables were also influenced by vegetation management regimes or trap locations. Collectively, our study clearly indicates that the movement of forest associated ground beetles between forest patches can increase as the vegetation in wildlife crossings becomes complex. Although further studies are needed to verify this, there are indications that the current wildlife crossings that comply with the guidelines may be unfriendly to the movement of ground dwelling arthropods as well as ground beetles. To enhance the ecological function of wildlife crossings, the guidelines need to be rectified as follows: 1) Shrubs or trees should be planted along the corridor verges to provide refuge or movement paths for small mammals and ground dwelling arthropods, and 2) Open spaces should be provided in the middle of the corridors to be used as a path for the movement of large mammals.

• Journal of Practical Agriculture & Fisheries Research
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• v.23 no.1
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• pp.89-104
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• 2021

Based on the TF-IDF weighted value that evaluates the importance of words that play a key role, the semantic network analysis(SNA) was conducted on the self-introduction letter of freshman at Korea National College of Agriculture and Fisheries(KNCAF) in 2020. The top three words calculated by TF-IDF weights were agriculture, mathematics, study (Q. 1), clubs, plants, friends (Q. 2), friends, clubs, opinions, (Q. 3), mushrooms, insects, and fathers (Q. 4). In the relationship between words, the words with high betweenness centrality are reason, high school, attending (Q. 1), garbage, high school, school (Q. 2), importance, misunderstanding, completion (Q.3), processing, feed, and farmhouse (Q. 4). The words with high degree centrality are high school, inquiry, grades (Q. 1), garbage, cleanup, class time (Q. 2), opinion, meetings, volunteer activities (Q.3), processing, space, and practice (Q. 4). The combination of words with high frequency of simultaneous appearances, that is, high correlation, appeared as 'certification - acquisition', 'problem - solution', 'science - life', and 'misunderstanding - concession'. In cluster analysis, the number of clusters obtained by the height of cluster dendrogram was 2(Q.1), 4(Q.2, 4) and 5(Q. 3). At this time, the cohesion in Cluster was high and the heterogeneity between Clusters was clearly shown.

• Korean Security Journal
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• no.62
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• pp.35-63
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• 2020

As the frequency and intensity of catastrophic disasters increase, there is widespread public sentiment that government capacity for disaster response and recovery is fundamentally limited, and that the involvement of civil society and the private sector is ever more vital. That is, in order to strengthen national disaster response capacity, governments need to build disaster systems that are more participatory and function through the channels of civil society, rather than continuing themselves to bear sole responsibility for these "wicked problems." With the advancement of smart mobile technology and social media, government and society as a whole have been called upon to apply these new information and communication technologies to address the current shortcomings of government-led disaster management. As illustrated in such catastrophic disasters as the 2011 Tohoku earthquake and tsunami in Japan, the 2010 Haitian earthquake, and Hurricane Katrina in the United States in 2005, the realization of participatory potential of smart technologies for better disaster response has enabled citizen participation via new smart technologies during disasters and resulted in positive impact on the management of such disasters. In this context, this study focuses on the South Korean context, and aims to analyze Korean government officials' readiness for public participation using smart technologies. On this basis, it aims to offer policy suggestions aimed at promoting smart technology-enabled citizen participation. For this purpose, it proposes a particular model, termed SMART (System, Motivation, Ability, Response, and Technology).

• Korean Journal of Mineralogy and Petrology
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• v.34 no.3
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• pp.157-167
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• 2021

Lead (Pb) is one of the key trace elements, exhibiting a peculiar partitioning behavior into silicate melts in contact with minerals. Partitioning behaviors of Pb between silicate mineral and melt have been known to depend on melt composition and thus, the atomic structures of corresponding silicate liquids. Despite the importance, detailed structural studies of Pb-bearing silicate melts are still lacking due to experimental difficulties. Here, we explored the effect of lead content on the atomic structures, particularly the evolution of silicate networks in Pb-bearing sodium metasilicate ([(PbO)_x(Na₂O)_1-x]·SiO₂) glasses as a model system for trace metal bearing natural silicate melts, using ²⁹Si solid-state nuclear magnetic resonance (NMR) spectroscopy. As the PbO content increases, the ²⁹Si peak widths increase, and the maximum peak positions shift from -76.2, -77.8, -80.3, -81.5, -84.6, to -87.7 ppm with increasing PbO contents of 0, 0.25, 0.5, 0.67, 0.86, and 1, respectively. The ²⁹Si MAS NMR spectra for the glasses were simulated with Gaussian functions for Qⁿ species (SiO₄ tetrahedra with n BOs) for providing quantitative resolution. The simulation results reveal the evolution of each Qⁿ species with varying PbO content. Na-endmember Na₂SiO₃ glass consists of predominant Q² species together with equal proportions of Q¹ and Q³. As Pb replaces Na, the fraction of Q² species tends to decrease, while those for Q¹ and Q³ species increase indicating an increase in disproportionation among Qⁿ species. Simulation results on the ²⁹Si NMR spectrum showed increases in structural disorder and chemical disorder as evidenced by an increase in disproportionation factor with an increase in average cation field strengths of the network modifying cations. Changes in the topological and configurational disorder of the model silicate melt by Pb imply an intrinsic origin of macroscopic properties such as element partitioning behavior.