• Journal of The Korean Association For Science Education
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• v.30 no.4
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• pp.472-486
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• 2010

The surveys for public awareness in relation to socio-scientific issues (SSI) have been limited to several topics such as public perception of risks about the issues and preference for some policies. To illuminate the public science culture literacy about SSI from a holistic perspective, this study aimed to develop an indicator system. For this purpose, the issue on climate change, which is currently one of the biggest issues worldwide, was adopted as a specific SSI and the framework centering on climate change was developed. Science culture literacy about SSI was defined as a lifestyle to identify SSI from various viewpoints and to cope with problems related to SSI appropriately. In the framework proposed, individual science culture indicators are divided into Potential and Activity area. The Potential consists of categories of Interest, Opinion and Understanding, whereas the Activity is composed of categories of Learning and Practice. To examine the reliability and validity of this framework statistically, the developed questionnaire was reviewed by science educators, environment experts and atmospheric scientists and was used to asked 777 secondary students. Based on the results of statistical analyses, the framework was modified and it consequently had 2 areas, 5 categories, 15 sub-categories, 34 indicators and 63 items. It is expected that the framework of science culture indicators for SSI could be used as a measurement tool for public awareness about various SSI topics.

• Cartoon and Animation Studies
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• s.24
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• pp.107-133
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• 2011

As importance of English has been getting more important with globalization, English education for preschoolers has drawn more attention from parents who were born in 1970's and 1980's. Demands for English education are very intense mainly because parent generation has experienced importance of English through own career and they have only one or two children, resulting parents' willingness to invest more on children's education. In order to response high demands for English education, Korean public education system has introduced more intense English education curriculum for younger children and put more weights on English education even for preschoolers. Even though there are numbers of studies to support effectiveness of English education for pre-school age children, adaption of English education for them without through preparation may cause unwanted results on children's learning experience. Hence, it is imperative to develop guideline for English education targeting pre-school age children based on through studies. The purpose of this paper is to justify English education for preschoolers based on various theories for language acquisition, research effectiveness of edutainment animation for English education, and provide basic guideline to develop edutainment animation in the future. To achieve this goal, this study visits how each theory emphasizes importance of language education in preschool age children and analyzes well-known edutainment animation titles by comparing them per characteristics. Furthermore, specifically from participation-inducing animation for education, each component, such as characters, story structure, & story telling methods, has been discussed. Based on the findings from this paper, basic guidelines to develop edutainment animation are developed by suggesting teaching tools for English education for preschoolers.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.3
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• pp.1178-1185
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• 2012

The 4th year medical students were randomly divided and designated as group HF and LF, representing high and low fidelity simulations respectfully. Both groups performed OSCE on 2 topics(adult intubation and IV cannulation) with each composed of the same scenario. Each scenario was developed by a faculty in charge of clinical skill education with supervision from 2 other faculty members. High fidelity simulations were designed as in-situ simulations in real OR. Low fidelity simulations had the same scenarios but the environment was simulated only with a simple task trainer in the classroom. All students participated in series of survey using a Likert scale before and after the simulations. The provided data was anlayzed with paired T-test and Mann-Whiteney test(p<0.05). The post simulations self evaluation score for group HF was lower than pre-simulation self confidence score for both topics of adult intubation and IV cannulation where as for group LF, it was lower only for adult intubation(p<0.05). In group HF, the needs for clinical training on both topics increased after the simulation. In group LF, there was no significant change of needs for clinical training between pre and post simulation survey. This suggest that fidelity may be a helpful factor to improve the motivation of the students and further study on economical aspect should be addressed.

• Journal of Korea Technology Innovation Society
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• v.11 no.4
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• pp.565-591
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• 2008

Using theories of sectoral innovation system and supply chain management, this paper examines the status quo of Korean IT SoC industry's innovation system by comparing it with Taiwanese one. Taiwan IT SoC industry has accomplished a rapid growth on the basis of government policies that foster domestic firms after the establishment of Hsinchu Science Park. Cooperative networks between foundries firms and fablesses have been formed within the supply chain in this process. Therefore, Taiwan industry has possessed the possibility of the coevolution in sectoral innovation system. However, Korean IT SoC industry has failed to form cooperative networks, because of weak networks between related firms. In other words, there exists an interaction failure, which is a kind of the system failure, and it means a lack of linkage between actors as a result of insufficient use of complementarities and interactive learning. Therefore, Korean industry has little possibility of the coevolution in sectoral innovation system. The cooperative networks between actors are prerequisite towards evolution of innovation system of Korean IT SoC industry. Above all, the cooperative networks between fablesses and system companies need to be strengthened within the supply chain.

• Journal of Digital Convergence
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• v.11 no.4
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• pp.409-414
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• 2013

The purpose of this study is to verify the effects of partial-cyber and full-cyber lectures and explore directions for improvement. This study compared the mean scores of course evaluation for traditional face-to-face lectures, partial-cyber lectures of blended instruction, and full-cyber lectures. Also, this study interviewed instructors of full-cyber lectures to investigate the ways to enhance the lecture quality. The findings suggest that the course evaluation scores for full-cyber university were consistently lower than those for other types of lectures for four semesters between the years of 2011 and 2012. Results also showed that mean scores of partial-cyber lectures were the same as those of face-to-face lectures. After all, class satisfaction in full-cyber courses that learning occurs in cyber space was the lowest. Instructors who taught full-cyber lectures proposed that enrollment should not be within 60 students and professional assistance should be provided for lectures exceeding 60 students. Finally, they suggested content updates through a collaborative system with professionals, instructors' efforts to enhance interaction in both online and offline contexts, and learning quantity rationalization.

• Journal of the Korea Convergence Society
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• v.9 no.1
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• pp.419-431
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• 2018

In this paper, we propose a novel method for monitoring mood trend of Twitter users by analyzing their daily tweets for a long period. Then, to more accurately understand their tweets, we analyze all types of content in tweets, i.e., texts and emoticons, and images, thus develop a multimodal sentiment analysis method. In the proposed method, two single-modal analyses first are performed to extract the users' moods hidden in texts and images: a lexicon-based and learning-based text classifier and a learning-based image classifier. Thereafter, the extracted moods from the respective analyses are combined into a tweet mood and aggregated a daily mood. As a result, the proposed method generates a user daily mood flow graph, which allows us for monitoring the mood trend of users more intuitively. For evaluation, we perform two sets of experiment. First, we collect the data sets of 40,447 data. We evaluate our method via comparing the state-of-the-art techniques. In our experiments, we demonstrate that the proposed multimodal analysis method outperforms other baselines and our own methods using text-based tweets or images only. Furthermore, to evaluate the potential of the proposed method in monitoring users' mood trend, we tested the proposed method with 40 depressive users and 40 normal users. It proves that the proposed method can be effectively used in finding depressed users.

• Journal of the Korean School Mathematics Society
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• v.14 no.4
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• pp.423-442
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• 2011

The purpose of this study was to examine the effects of tasks setting for mathematical modelling in the complex real situations. The tasks setting(MMa, MeA) in mathematical modelling was so important that we can't ignore its effects to develop meaning and integrate mathematical ideas. The experimental setting were two groups ($N_1=103$, $N_2=103$) at public high school and non-experimental setting was one group($N_3=103$). In mathematical achievement, we found meaningful improvement for MeA group on modelling tasks, but no meaningful effect on information processing tasks. The statistical method used was ACONOVA analysis. Beside their achievement, we were much concerned about their modelling approach that TSG21 had suggested in Category "Educational & cognitive Midelling". Subjects who involved in experimental works showed very interesting approach as Exploration, analysis in some situation ${\Rightarrow}$ Math. questions ${\Rightarrow}$ Setting models ${\Rightarrow}$ Problem solution ${\Rightarrow}$ Extension, generalization, but MeA group spent a lot of time on step: Exploration, analysis and MMa group on step, Setting models. Both groups integrated actively many heuristics that schoenfeld defined. Specially, Drawing and Modified Simple Strategy were the most powerful on approach step 1,2,3. It was very encouraging that those experimental setting was improved positively more than the non-experimental setting on mathematical belief and interest. In our school system, teaching math. modelling could be a answer about what kind of educational action or environment we should provide for them. That is, mathematical learning.

• Journal of Korea Spatial Information System Society
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• v.10 no.2
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• pp.63-79
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• 2008

With the recent development of advanced GIS and complex spatial analysis technologies, the more sophisticated technologies are being required to support the advanced knowledge for solving geographical or spatial problems in various decision support systems. In addition, necessity for research on scientific crime investigation and forensic science is increasing particularly at law enforcement agencies and investigation institutions for efficient investigation and the prevention of crimes. There are active researches on geographic profiling to predict the base location such as criminals' residence by analyzing the spatial patterns of serial crimes. However, as previous researches on geographic profiling use simply statistical methods for spatial pattern analysis and do not apply a variety of spatial and temporal analysis technologies on serial crimes, they have the low prediction accuracy. Therefore, this paper identifies the typology the spatio-temporal patterns of serial crimes according to spatial distribution of crime sites and temporal distribution on occurrence of crimes and proposes STA-BLP(Spatio-Temporal Analysis based Base Location Prediction) algorithm which predicts the base location of serial crimes more accurately based on the patterns. STA-BLP improves the prediction accuracy by considering of the anisotropic pattern of serial crimes committed by criminals who prefer specific directions on a crime trip and the learning effect of criminals through repeated movement along the same route. In addition, it can predict base location more accurately in the serial crimes from multiple bases with the local prediction for some crime sites included in a cluster and the global prediction for all crime sites. Through a variety of experiments, we proved the superiority of the STA-BLP by comparing it with previous algorithms in terms of prediction accuracy.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.1
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• pp.7-14
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• 2010

In this paper, we introduce a hierarchical internet application traffic classification system based on SVM as an alternative overcoming the uppermost limit of the conventional methodology which is using the port number or payload information. After selecting an optimal attribute subset of the bidirectional traffic flow data collected from the campus, the proposed system classifies the internet application traffic hierarchically. The system is composed of three layers: the first layer quickly determines P2P traffic and non-P2P traffic using a SVM, the second layer classifies P2P traffics into file-sharing, messenger, and TV, based on three SVDDs. The third layer makes specific classification of the entire 16 application traffics. By classifying the internet application traffic finely or coarsely, the proposed system can guarantee an efficient system resource management, a stable network environment, a seamless bandwidth, and an appropriate QoS. Also, even a new application traffic is added, it is possible to have a system incremental updating and scalability by training only a new SVDD without retraining the whole system. We validate the performance of our approach with computer experiments.

• The KIPS Transactions:PartD
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• v.12D no.4 s.100
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• pp.627-636
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• 2005

The Intelligent Web Service is proposed for the purpose of automatic discovery, invocation, composition, inter-operation, execution monitoring and recovery web service through the Semantic Web and the Agent technology. To accomplish this Intelligent Web Service, the Ontology is a necessity for reasoning and processing the knowledge by the computer. However, creating service ontology, for the intelligent web service, has two problems not only consuming a lot of time and cost depended on heuristic of service developer, but also being hard to be mapping completely between service and service ontology. Moreover, the markup language to describe the service ontology is currently hard to be learned by the service developer In a short time. This paper proposes the efficient way of designing and creating the service ontology using MDA methodology. This proposed solution reuses the creating model in terms of desiEninE and constructing Web Service Model using UML based on MDA. After converting the Platform-Independent Web Service Model to the dependent model of OWL-S which is a Service Ontology description language, it converts to OWL-S Service Ontology using XMI. This proposed solution has profits, oneis able to be easily constructed the Service Ontology by Service Developers, the other is enable to be created the both service and Service Ontology from one model. Moreover, it can be effective to reduce the time and cost as creating Service Ontology automatically from a model, and calmly dealt with a change of outer environment like as the platform change. This paper cites an instance for the validity of designing Web Service model and creating the Service Ontology, and validates whether the created Service Ontology is valid or not.