• Journal of the Korean BIBLIA Society for library and Information Science
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• v.24 no.4
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• pp.301-317
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• 2013

This study investigated general problems concerning the physical education field in the KDC 6th edition based on comparative analysis of academic characteristics and classification system, and suggested some ideas for the improvements of them. Results of this study are is summarized as follows. First, while the academic classification divided items focusing on theoretical disciplines such as physical education, sociology, or business administration, the library classification divided them into details according to sport entries. Second, We examined the classification status of the physical education field of the collection database in the National Library of Korea. The number of physical education field data was 38,585, and of them, that of books having classification codes starting with 692(physical education, sports) was 22,870. This shows that data actually have been published mainly based on academic characteristics rather than sport entries, which causes a problem due to concentration of many data on one classification code. Therefore, this study analyzed keywords around these classification codes. Third, modified classification of items was basically performed through the academic system of the physical education and the keyword analysis, and the typical KDC classification system was maintained as much as possible.

• Journal of Technology Innovation
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• v.24 no.4
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• pp.101-126
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• 2016

This paper identifies core research topics and their relationships by deriving the research topic networks in the technology management field using co-word analysis. Contrary to the conventional approach in which undirected networks are constructed based on normalized co-occurrence frequency, this study analyzes directed networks of keywords by employing the confidence index of association rule mining for pairs of keywords. Author keywords included in 2,456 articles published in nine international journals of technology management in 2011~2014 are extracted and categorized into three types: THEME, METHOD, and FIELD. One-mode networks for each type of keywords are constructed to identify core research keywords and their interrelationships with each type. We then derive the two-mode networks composed of different two types of keywords, THEME-METHOD and THEME-FIELD, to explore which methods or fields are frequently employed or studied for each theme. The findings of this study are expected to be fruitfully referred for researchers in the field of technology management to grasp research trends and set the future research directions.

• Journal of the Korean Society of Earth Science Education
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• v.10 no.3
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• pp.290-307
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• 2017

The purpose of this study is to analyze the research trends related to qualitative research on science education, to provide basic data of qualitative research on science education and to select the direction of follow-up research. The subject of the study is the level of Korean Citation Index (KCI-listed, KCI listing candidates), that can be searched by the key phrase, 'qualitative research', 'science education' in Korean language through the RISS service. In this study, the Descriptive Statistical Analysis Method is utilized to discover the number of research articles, classifying them by year and by journal. Also, the Sementic Network Analysis was conducted to the frequency of key words, Centrality Analysis throughout a variety of research articles using krkwic and Ucinet6.0. The results show that first, 138 research papers were published in 14 journals from 2005 to 2017. Second,, the analysis showed the highest frequency of appearance keyword in each article, 'elementary school teacher', 'gifted student', 'science teacher', 'class' were higher than others. third, according to the results of the whole Network Analysis, 'Analysis', 'elementary school', 'class' were analyzed as a highly influential node. And 'Comparison', 'inquiry', 'recognition', 'gifted students' were not close to the center of network. Fourth, keywords that appear in all sections are analysis, gifted students, and elementary school students, and can be analyzed continuously based on studies, lessons or recognition, and characteristics. Based on the results of this study, we explored the past and present of the study subjects related to the study of science education quality and discussed future direction of study.

• Korean Journal of Cognitive Science
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• v.21 no.1
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• pp.157-175
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• 2010

Understanding dialogue participant's emotion is important as well as decoding the explicit message in human communication. It is well known that non-verbal elements are more suitable for conveying speaker's emotions than verbal elements. Written texts, however, contain a variety of linguistic units that express emotions. This study aims at analyzing components for constructing an emotion ontology, that provides us with numerous applications in Human Language Technology. A majority of the previous work in text-based emotion processing focused on the classification of emotions, the construction of a dictionary describing emotion, and the retrieval of those lexica in texts through keyword spotting and/or syntactic parsing techniques. The retrieved or computed emotions based on that process did not show good results in terms of accuracy. Thus, more sophisticate components analysis is proposed and the linguistic factors are introduced in this study. (1) 5 linguistic types of emotion expressions are differentiated in terms of target (verbal/non-verbal) and the method (expressive/descriptive/iconic). The correlations among them as well as their correlation with the non-verbal expressive type are also determined. This characteristic is expected to guarantees more adaptability to our ontology in multi-modal environments. (2) As emotion-related components, this study proposes 24 emotion types, the 5-scale intensity (-2~+2), and the 3-scale polarity (positive/negative/neutral) which can describe a variety of emotions in more detail and in standardized way. (3) We introduce verbal expression-related components, such as 'experiencer', 'description target', 'description method' and 'linguistic features', which can classify and tag appropriately verbal expressions of emotions. (4) Adopting the linguistic tag sets proposed by ISO and TEI and providing the mapping table between our classification of emotions and Plutchik's, our ontology can be easily employed for multilingual processing.

• Therapeutic Science for Rehabilitation
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• v.4 no.2
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• pp.33-50
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• 2015

Objective : This study was conducted to determine various interventions in accordance with the recovery and cognitive processes in order to improve executive function in stroke patients through a systematic review. Methods : The literature search focused on Level I-IV studies published between January 1996 and April 2015 for 20 years in electronic databases(e.g. MEDLINE, SCOPUS, RISS). The keyword search terms were 'Stroke', 'Executive function', 'Executive function deficit', 'Occupational therapy', 'Rehabilitation', 'Remedial', 'Compensatory' and 'Education'. Result : A total of 13 articles were appraised using the hierarchy of levels of evidence-based practice and 6 Level I evidence articles, 1 Level II articles, 2 Level III articles and 4 Level IV articles. Each intervention improved executive function but was different in degree of generalization. Conclusion : Through this systematic review, we found that there are a variety of applied interventions improving executive function in stroke patients and are different in effect depending on methods of interventions. This study provided evidences to occupational therapists for the clinical practice of interventions to improve executive function in stroke patients.

• The Journal of the Korea Contents Association
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• v.20 no.2
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• pp.162-171
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• 2020

The purpose of this study is to examine the social perception of disaster safety education for young children based on Textom big data and to explore the direction of young children's disaster safety education. Researchers collected and analyzed online text data using the keywords 'young children+disaster+safety education' from portal websites from 2014 to 2017. The raw data were then subjected to first and second data refinement process. Based on the frequency analysis results, 50 keywords were selected, and the selected keywords were converted into matrix data for network analysis. The results of the study are: first, the most frequently appeared keyword together with young children's disaster safety education was 'education', followed by 'experience', 'kindergarten', 'prevention', and 'school.' Second, keywords with high centrality in the analysis of centrality also were 'education', 'experience', and 'prevention'. In addition, keywords like 'prevention', 'life', and 'evacuation' appear higher in connection-centricity than frequency ranking, which means that the degree of connection between the words is high. These results suggest that young children need education in during early childhood in order to improve their disaster safety skills, and disaster safety education should be accomplished through 'prevention' and 'experience' in early childhood education institutions.

• The KIPS Transactions:PartD
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• v.9D no.6
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• pp.1055-1062
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• 2002

Recently, the lesson plan document that is imported in the educational area is not provided to the educational information systematically, and the teachers are not easy to compose the lessen plan documentation. So, it needs additional time and effort to develope the lesson plan documents. Because of increasing the distributing network. web-based lesson plan system is required to all of the education area. Therefore, we need to compose the lesson plan that is possible to obtain the various teacher's requirement by providing creation, retrival, and reusability of document using the standard XML on web. In this paper, we developed the system for creating the common DTD (Document Type Definition), providing the standard XML document through the common DTD over the lesson plan analysis. In this system, it provides the editor to compose the lesson plan and supports the searching function to improvement of reusability on the existing lesson plan. We design the searching functions such as the structure base, facet and keyword. The composed lesson plans are interoperated with Database. Consequently, we can share the information on web by composing the lesson plan using the XML and save the time and cost by directly writing the lesson plan on web. We can also provide the improved learning environment.

• The Journal of Society for e-Business Studies
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• v.21 no.3
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• pp.15-28
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• 2016

This paper proposes a system recommending spatial information what user wants with collecting and analyzing tweets around the user's location by using the GPS information acquired in mobile. This system has built an emotion dictionary and then derive the recommendation score of morphological analyzed tweets to provide not just simple information but recommendation through the emotion analysis information. The system also calculates distance between the recommended tweets and user's latitude-longitude coordinates and the results showed the close order. This paper evaluates the result of the emotion analysis in a total of 10 areas with two keyword 'Restaurants' and 'Performance.' In the result, the number of tweets containing the words positive or negative are 122 of the total 210. In addition, 65 tweets classified as positive or negative by analyzing emotions after a morphological analysis and only 46 tweets contained the meaning of the positive or negative actually. This result shows the system detected tweets containing the emotional element with recall of 38% and performed emotion analysis with precision of 71%.

• Korean Journal of Construction Engineering and Management
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• v.9 no.4
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• pp.193-205
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• 2008

Quality is an important keyword representing the corporate competitiveness and image in today' s construction industry. Especially in concrete construction, any problems or defects in fresh concrete can significantly degrade the entire quality and performance of the facility built. Thus, adequate quality inspection and testing must be exercised over the fresh concrete, if concrete with the required strength, durability and appearance is to be obtained. The testing of concrete delivered to the construction job site involves testing of fresh concrete and performing strength tests on hardened concrete. The principal tests conducted on fresh concrete include the slump test and tests for air and salt content. The temperature of fresh concrete should be checked out hot or cold weather concreting. The 7-day and 28-day strength of hardened concrete are also determined by compression tests on usually cylinder samples. However, it is very complex and time-consuming process requiring a lot of efforts to document those on-site concrete testing results and to accumulate their historical data. The primary objective of this study is to suggest a unique PDA and web-based system which enables an on-site quality manager to effectively conduct the concrete inspection and testing, automatically document and accumulate the collected historical data, and promptly obtain the approval from supervisors. Finally, it is anticipated that the effective use of the proposed PDA and web-based system would be able to improve reliability of the concrete quality inspection and testing data as well as significantly reduce the approval process.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.10
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• pp.447-454
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• 2015

This paper proposes geographical name denoising by machine learning of event detection based on twitter. Recently, the increasing number of smart phone users are leading the growing user of SNS. Especially, the functions of short message (less than 140 words) and follow service make twitter has the power of conveying and diffusing the information more quickly. These characteristics and mobile optimised feature make twitter has fast information conveying speed, which can play a role of conveying disasters or events. Related research used the individuals of twitter user as the sensor of event detection to detect events that occur in reality. This research employed geographical name as the keyword by using the characteristic that an event occurs in a specific place. However, it ignored the denoising of relationship between geographical name and homograph, it became an important factor to lower the accuracy of event detection. In this paper, we used removing and forecasting, these two method to applied denoising technique. First after processing the filtering step by using noise related database building, we have determined the existence of geographical name by using the Naive Bayesian classification. Finally by using the experimental data, we earned the probability value of machine learning. On the basis of forecast technique which is proposed in this paper, the reliability of the need for denoising technique has turned out to be 89.6%.