• Journal of Science Education
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• v.38 no.3
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• pp.718-736
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• 2014

This study was intended to determine PCK of the middle school science teachers on Mendelian genetics and factors influenced to form their PCKs. Two science teachers with biology major with a teaching experience over 5 years were chosen as the subject. Data were collected by class observation, semi-structured interview, teacher questionnaire survey, Content Representation and Pedagogical and Professional-experience Repertoire. The collected data were analyzed based on Magnusson's PCK for science teaching consisting of five components: (a) the orientation toward teaching science, (b) the knowledge of science curriculum, (c) the knowledge of students' understanding, (d) the knowledge of assessment, and (e) the knowledge and belief in the instructional strategies to teach science. Teachers could have the orientation toward teaching science served as an assisting role to support students' abilities. Both subject teachers seemed to focus on giving lectures. Their efforts to improve students' exploration methods and abilities were not expressed enough in their real classes and they found that students struggled to understand Mendelian genetics. Therefore, they should have explained them in an easier way and worked harder to make their students understood accurately and applied basic and advanced concepts of Mendelian genetics. They found students' preconception and misconception regarding Mendelian genetics and wished to enhance their learning effects by various teaching strategies such as correcting misconception, adding the history of science and simply assessing students' affirmative domains. It was also found that factors influenced to form PCK regarding Mendelian genetics by both teachers were as follows: teacher's personality and endeavor, textbooks and guidance books, schools and their circumstances, teaching experience, experience as a learner, interaction with their colleagues, and university curriculum. Both teachers said that it was important for teachers to make every efforts to give better classes.

• Korean Journal of Remote Sensing
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• v.35 no.6_4
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• pp.1319-1326
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• 2019

The KARI(Korea Aerospace Research Institute) operates the government satellite information application consultation to cope with ever-increasing demand for satellite images in the public sector, and carries out various support projects including the generation and provision of mosaic images on the Korean Peninsula every year to enhance user convenience and promote the use of satellite images. In particular, the government has wanted to increase the utilization of mosaic images on the Korean Peninsula and seek to classify and update mosaic images so that users can use them in their businesses easily. However, it is necessary to test and verify whether the classification results of the mosaic images can be utilized in the field since the original spectral information is distorted during pan-sharpening and color balancing, and there is a limitation that only R, G, and B bands are provided. Therefore, in this study, the reliability of the classification result of the mosaic image was compared to the result of KOMPSAT-3 image. The study found that the accuracy of the classification result of KOMPSAT-3 image was between 81~86% (overall accuracy is about 85%), while the accuracy of the classification result of mosaic image was between 69~72% (overall accuracy is about 72%). This phenomenon is interpreted not only because of the distortion of the original spectral information through pan-sharpening and mosaic processes, but also because NDVI and NDWI information were extracted from KOMPSAT-3 image rather than from the mosaic image, as only three color bands(R, G, B) were provided. Although it is deemed inadequate to distribute classification results extracted from mosaic images at present, it is believed that it will be necessary to explore ways to minimize the distortion of spectral information when making mosaic images and to develop classification techniques suitable for mosaic images as well as the provision of NIR band information. In addition, it is expected that the utilization of images with limited spectral information could be increased in the future if related research continues, such as the comparative analysis of classification results by geomorphological characteristics and the development of machine learning methods for image classification by objects of interest.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.18 no.3
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• pp.142-161
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• 2013

In order to enhance scientific interest and a sense of affinity about ocean, the programs of the oceanic camp 'oceanic summer school' were developed and applied to $4^{th}$ and $9^{th}$-grade elementary and middle school students for 9 years from 2004 to 2012. It was composed of oceanic training for snorkeling, a tour to oceanic institutes and museums near the camp academy place, experimental learning in oceanic-related field, field trips for ocean and earth sciences, and lectures on various subjects of ocean. We developed and implemented 9-kinds of inquiry surveys to evaluate changes in cognitive and affective characteristics, and ocean literacy of students participated at the present oceanic summer camp. Based on the statistical analysis, affective characteristics such as interest, inquisitiveness, passion, and so on, were enhanced. Analysis of ocean literacy revealed that cognitive characteristics of the students were increased by 40%. We presented parents' responses on the programs of oceanic summer school. Some students with less initial interest of ocean have positively changed to make up their minds to be a oceanographer in several years later. In light of this, the summer school can be evaluated to be successfully functioned as a long-term support system for potentially young-talented students in the field of ocean science. This study addresses that long-term implementation of the summer oceanic camp may trigger students with potential talent toward in-depth science in the near future even though it could not bring positive effect immediately. This addresses the necessity of policy supports in order that various programs like the scientific camp should be more constructively developed and executed for next-generation manpower in oceanographic fields.

• Korean Security Journal
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• no.52
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• pp.73-91
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• 2017

This study is based on the political and economic standpoint of each country, Use advanced equipment to prevent new terrorism from causing widespread damage, In order to establish a countermeasures against terrorism in accordance with the reality of Korea, which is effective in responding to terrorist attacks, Korea conducted a SWOT analysis of the terrorist environment and terrorist environment through specialists. First, internal strengths of Korea 's terrorist environment include stable security situation, weakness of religious and ethnic conflicts, strong regulation and control of firearms, and counter terrorism capabilities and know - how accumulated during major international events. Second, the internal weaknesses of the terrorist environment in Korea include the insecurity of the people, the instability caused by the military confrontation with North Korea, the absence of anti-terrorism law system, the difficulty of terrorism control and management by the development of the Internet and IT technology. Third, the external opportunities for Korea 's terrorist environment are as follows: ease of supplementation and learning through cases of foreign terrorism failure, ease of increase of terrorist budget and support with higher terrorism issues, strengthening of counterterrorism through military cooperation with allied nationsRespectively. Fourth, the external threats to the terrorist environment in Korea are the increase of social dissatisfaction due to the continuous influx of defectors and foreign workers, the goal of terrorism from international terrorist organizations through alliance with the United States,Increased frequency of incidents, and increased IS coverage of terrorism around the world. In addition, the SWOT in - depth interviews on the terrorist environment of the expert group were conducted to diagnose and analyze the problems, terrorism awareness and legal system in the Korean terror environment. The results of the study are summarized as follows.First, the basic law on terrorism should be enacted.Second, the establishment of an integrated anti-terrorism organization.Third, securing and nurturing specialized personnel in response to terrorism.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.43-65
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• 2010

Facing a complex environment driven by a decade, many companies are adopting new strategic frameworks such as Customer Relationship Management system to achieve sustainable profitability as well as overcome serious competition for survival. In many business areas, CRM system advanced a great deal in a matter of continuous compensating the defect and overall integration. However, pharmaceutical companies in Korea were slow to accept them for usesince they still have a tendency of holding fast to traditional way of sales and marketing based on individual networks of sales representatives. In the circumstance, this article tried to empirically address current status of CRM system as well as the effects of the system on the performance of pharmaceutical companies by applying BSC method's four perspectives, from financial, customer, learning and growth and internal process. Survey by e-mail and post to employers and employees who were working in pharma firms were undergone for the purpose. Total 113 cases among collected 140 ones were used for the statistical analysis by SPSS ver. 15 package. Reliability, Factor analysis, regression were done. This study revealed that CRM system had a significant effect on improving financial and non-financial performance of pharmaceutical companies as expected. Proposed regression model fits well and among them, CRM marketing information system shed the light on substantial impact on companies' outcome given profitability, growth and investment. Useful analytical information by CRM marketing information system appears to enable pharmaceutical firms to set up effective marketing and sales strategies, these result in favorable financial performance by enhancing values for stakeholderseventually, not to mention short-term profit and/or mid-term potential to growth. CRM system depicted its influence on not only financial performance, but also non-financial fruit of pharmaceutical companies. Further analysis for each component showed that CRM marketing information system were able to demonstrate statistically significant effect on the performance like the result of financial outcome. CRM system is believed to provide the companies with efficient way of customers managing by valuable standardized business process prompt coping with specific customers' needs. It consequently induces customer satisfaction and retentionto improve performance for long period. That is, there is a virtuous circle for creating value as the cornerstone for sustainable growth. However, the research failed to put forward to evidence to support hypothesis regarding favorable influence of CRM sales representative's records assessment system and CRM customer analysis system on the management performance. The analysis is regarded to reflect the lack of understanding of sales people and respondents between actual work duties and far-sighted goal in strategic analysis framework. Ordinary salesmen seem to dedicate short-term goal for the purpose of meeting sales target, receiving incentive bonus in a manner-of-fact style, as such, they tend to avail themselves of personal network and sales and promotional expense rather than CRM system. The study finding proposed a link between CRM information system and performance. It empirically indicated that pharmaceutical companies had been implementing CRM system as an effective strategic business framework in order for more balanced achievements based on the grounded understanding of both CRM system and integrated performance. It suggests a positive impact of supportive CRM system on firm performance, especially for pharmaceutical industry through the initial empirical evidence. Also, it brings out unmet needs for more practical system design, improvement of employees' awareness, increase of system utilization in the field. On the basis of the insight from this exploratory study, confirmatory research by more appropriate measurement tool and increased sample size should be further examined.

• Management & Information Systems Review
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• v.36 no.5
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• pp.1-26
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• 2017

In the meantime, research on corporate informatization focuses on the completeness of information technology itself and its financial effects, so there is insufficient research on whether information technology can support business strategy. It is necessary to verify whether the management strategy implementation of the company can be led through the informatization of the enterprise and the relation between the main mechanism factors and the informatization performance. In this study, what a mechanism factor is applied in the process of result creation of informatization from three mechanism perspectives such as selecting mechanism, learning mechanism and coordinating mechanism with cases of representative domestic IT company and what an importance mechanism factors have been ascertained. This study results in 8 propositions. For a main agent of companies, securement of information capability of organizations has been selected to realize informatization results and investment of informatization has been selected to solve organizational decentralization problems as the most important factor. Additionally, as competition in the industry gets fierce, investment on informatization has been changed to a utility way of implementation of strategies and decision on investment has been made through the official process and information technology. Differentiated company capability has been made based on acquisition of technical knowledge and company information has been expanded to its whole employees through the information system. Also, informatization change management and outside subcontractor management have been acknowledged as an important adjustment factor of company. The first implication of this study is that since case studies on mechanism factors that preceding studies on informatization results did not empirically cover have directly been dealt with based on experiences of executives in charge of business and in charge of informatization, this study can provide practical views about factors that should be mainly managed for informatization results of IT companies. Secondly, since ser-M framework has been applied for IT companies for the first time, this study can academically contribute to companies in other fields about main mechanism factors for result creation of informatization based on deeper understanding and empirical cases.

• Journal of Korean Elementary Science Education
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• v.24 no.4
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• pp.391-398
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• 2005

Recent studies say that informal learning is influential to students as much as formal teaming. Nowadays we can see various informal teaming inside and outside of the country. In 2004, it was the first attempt in Korea that engineer had gone to the elementary school fur activity that included scientific experiment and engineering work with students. National Academy of Engineering of Korea (NAEK) progressed activity with companies and elementary schools for students' making sense of engineer and what they are doing. To do that, NAEK had developed the network that company could support its local school's science education circumstance by engineers' visiting program. In 2004, seventeen companies including both large and small ones took part in the program called' Korea Junior Engineering Achievement (KJEA)'. In this program, engineers played the role of teacher (we call them company teacher), elementary school teachers played the role of organizing classes as a mediator. Elementary school teachers and company teachers' recognition is very important to make students' activity meaningful. The aim of this study was to give implication for informal science education activity for which engineers visit their local school. We got the result by survey and interview of company teachers and elementary school teachers. This study's result shows that almost company teachers and school teachers were in favor of purpose of this informal science education activity and satisfied with their participation. But some company teachers were not satisfied with worksheets, materials provided and relationship between school and company). Elementary school teachers and company teachers, both of them believed students' program as the key factor of success of informal science education activity. To make informal science education grow, school administrator and teacher need to have a will to utilize the activities more actively.

• 대한공업교육학회지
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• v.44 no.2
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• pp.104-122
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• 2019

In the era of the fourth industrial revolution, maker education is drawing attention as a method of student-led education. At a time when interest in maker education is also growing in technology education, figuring out what stage of concern(SoC) a middle school technology teacher is critical to effective implementation. This study analyzed SoC in maker education by layer sampling among 400 middle school technology teachers using Concerns-based adoption model. SoC was then obtained by measuring the origin using the SoCQ and then presenting it as a SOCQ profile. Gender, training experience with two lower variables were analyzed using t verification, working cities, teaching experience with more than three lower variables were analyzed using one-way ANOVA. Studies showed that SoC in maker education of middle school technology teachers showed the most similar characteristics to that of non-users. The difference in concern depending on gender was that male teachers were more concerned in maker education than female teachers. The difference in concern depending on the working city was that teachers working in the township were more concerned in the maker education than teachers working in the large city, and the difference in concern depending on the teaching career was higher among teachers with middle experience than those with low and high experience. There was also a higher stage of concern in maker education than in teachers without training experience. Therefore, it is necessary to provide middle school technology teachers with an introduction to the maker education and various information, teaching, learning and evaluation data to enhance overall concern and to support the use and evaluation of the maker education in the classroom by providing various teacher training and consulting on the maker education in the future. Further, through further study, we should conduct study that analyzes both Stage of Concern, Level of Use and Innovation Configuration, to put in the effort for effective settlement of maker education.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.29-56
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• 2021

Recently, various types of products have been launched with the rapid growth of the e-commerce market. As a result, many users face information overload problems, which is time-consuming in the purchasing decision-making process. Therefore, the importance of a personalized recommendation service that can provide customized products and services to users is emerging. For example, global companies such as Netflix, Amazon, and Google have introduced personalized recommendation services to support users' purchasing decisions. Accordingly, the user's information search cost can reduce which can positively affect the company's sales increase. The existing personalized recommendation service research applied Collaborative Filtering (CF) technique predicts user preference mainly use quantified information. However, the recommendation performance may have decreased if only use quantitative information. To improve the problems of such existing studies, many studies using reviews to enhance recommendation performance. However, reviews contain factors that hinder purchasing decisions, such as advertising content, false comments, meaningless or irrelevant content. When providing recommendation service uses a review that includes these factors can lead to decrease recommendation performance. Therefore, we proposed a novel recommendation methodology through CNN-based review usefulness score prediction to improve these problems. The results show that the proposed methodology has better prediction performance than the recommendation method considering all existing preference ratings. In addition, the results suggest that can enhance the performance of traditional CF when the information on review usefulness reflects in the personalized recommendation service.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.1-17
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• 2019

Because stock price forecasting is an important issue both academically and practically, research in stock price prediction has been actively conducted. The stock price forecasting research is classified into using structured data and using unstructured data. With structured data such as historical stock price and financial statements, past studies usually used technical analysis approach and fundamental analysis. In the big data era, the amount of information has rapidly increased, and the artificial intelligence methodology that can find meaning by quantifying string information, which is an unstructured data that takes up a large amount of information, has developed rapidly. With these developments, many attempts with unstructured data are being made to predict stock prices through online news by applying text mining to stock price forecasts. The stock price prediction methodology adopted in many papers is to forecast stock prices with the news of the target companies to be forecasted. However, according to previous research, not only news of a target company affects its stock price, but news of companies that are related to the company can also affect the stock price. However, finding a highly relevant company is not easy because of the market-wide impact and random signs. Thus, existing studies have found highly relevant companies based primarily on pre-determined international industry classification standards. However, according to recent research, global industry classification standard has different homogeneity within the sectors, and it leads to a limitation that forecasting stock prices by taking them all together without considering only relevant companies can adversely affect predictive performance. To overcome the limitation, we first used random matrix theory with text mining for stock prediction. Wherever the dimension of data is large, the classical limit theorems are no longer suitable, because the statistical efficiency will be reduced. Therefore, a simple correlation analysis in the financial market does not mean the true correlation. To solve the issue, we adopt random matrix theory, which is mainly used in econophysics, to remove market-wide effects and random signals and find a true correlation between companies. With the true correlation, we perform cluster analysis to find relevant companies. Also, based on the clustering analysis, we used multiple kernel learning algorithm, which is an ensemble of support vector machine to incorporate the effects of the target firm and its relevant firms simultaneously. Each kernel was assigned to predict stock prices with features of financial news of the target firm and its relevant firms. The results of this study are as follows. The results of this paper are as follows. (1) Following the existing research flow, we confirmed that it is an effective way to forecast stock prices using news from relevant companies. (2) When looking for a relevant company, looking for it in the wrong way can lower AI prediction performance. (3) The proposed approach with random matrix theory shows better performance than previous studies if cluster analysis is performed based on the true correlation by removing market-wide effects and random signals. The contribution of this study is as follows. First, this study shows that random matrix theory, which is used mainly in economic physics, can be combined with artificial intelligence to produce good methodologies. This suggests that it is important not only to develop AI algorithms but also to adopt physics theory. This extends the existing research that presented the methodology by integrating artificial intelligence with complex system theory through transfer entropy. Second, this study stressed that finding the right companies in the stock market is an important issue. This suggests that it is not only important to study artificial intelligence algorithms, but how to theoretically adjust the input values. Third, we confirmed that firms classified as Global Industrial Classification Standard (GICS) might have low relevance and suggested it is necessary to theoretically define the relevance rather than simply finding it in the GICS.