• Journal of Korea Entertainment Industry Association
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• v.15 no.1
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• pp.117-129
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• 2021

Nowadays, the trend of early childhood education has focused on finding educational activities to enhance quality of learning with integrative, learner-centered experience by combining each subject and domain. Pre-service early childhood teacher's music drama activity is a sort of integrated education including literature, instrumental music, play, art and movement that are included in the culture and art for preschoolers to help them understand role and value of the art and directly influence personality and creativity and motive to arouse interest in various learning directly. It's expected to see that development of creative teaching plan for the music drama using piano ensemble could support basic research in integrated educational activity in the teacher training course and also, activate the music drama activity. Research findings and suggestion are as follows. First, the music drama activities are systematically and step-by-step implemented according to the audience according to the cooperative learning and creative plans of pre-service early childhood teachers. Second, if understanding characteristics of casts in the music drama and assigning their roles efficiently, it enhances approach of pre-service early childhood teacher music drama activity and activate it. Third, making music in music drama activities can be composed and arranged to suit the musical literacy and level of pre-service early childhood teacher. Fourth, pre-service early childhood teachers could have integrated experience and evaluation efficiently in the short term to use as reference for the teaching plan and data for the music drama.

• Journal of Korea Water Resources Association
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• v.55 no.12
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• pp.991-998
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• 2022

The purpose of this study is to develop GPU (Graphics Processing Unit) acceleration technique for 2-dimensional model and to assess the effectiveness for high resolution flood simulation in wide area In this study, GPU acceleration technique was implemented in the G2D (Grid based 2-Dimensional land surface flood model) model, using implicit scheme and uniform square grid, by using CUDA. The technique was applied to flood simulation in Jinju-si. The spatial resolution of the simulation domain is 10 m × 10 m, and the number of cells to calculate is 5,090,611. Flood period by typhoon Mitag, December 2019, was simulated. Rainfall radar data was applied to source term and measured discharge of Namgang-Dam (Ilryu-moon) and measured stream flow of Jinju-si (Oksan-gyo) were applied to boundary conditions. From this study, 2-dimensional flood model could be implemented to reproduce the measured water level in Nam-gang (Riv.). The results of GPU acceleration technique showed more faster flood simulation than the serial and parallel simulation using CPU (Central Processing Unit). This study can contribute to the study of developing GPU acceleration technique for 2-dimensional flood model using implicit scheme and simulating land surface flood in wide area.

• Journal of Ginseng Research
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• v.33 no.2
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• pp.115-126
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• 2009

To evaluate the efficacy and safety of red ginseng on women's health-related quality of life (QOL) and sexual function. A randomized, double-blind, placebo-controlled, crossover clinical study was performed. The main efficacy was measured using the Female Sexual Function Index (FSFl) and the 36-Item Short-Form Health Survey (SF-36). Twenty-four healthy, married women aged 30-45 years with FSFl scores below 25 were randomly divided into two groups: the red-ginseng group (N=12) and the placebo group (N=12). During the first six-week period (Study 1), each group was given red ginseng or placebo twice a day. Before the start of the second six-week period (Study 2), a crossover design was chosen with a two-week break (washout period). Interchanging the two groups after the washout period, red ginseng and placebo were given to each group. The outcomes were measured before and after each six-week period. Overall, 23 participants completed the study. In Study 1, the changes relative to the baseline in the FSFl total score were 22.50% and 22.99% for red ginseng and placebo, respectively. In Study 2, the relative changes were 8.14% for red ginseng and 6.29% for placebo. The results showed a greater improving trend in Study 1 with respect to all of the participants' sexual functions, but no significant difference was found between the groups (P=0.9567). After taking red ginseng, all the participants exhibited an improving trend in the desire domain of FSFl, but no significant difference was shown. In the measurement of SF-36, no significant difference was likewise shown. After taking red ginseng, though, all the participants exhibited an improving trend in the physical functioning (PF) domain of SF-36, with no significant difference. Moreover, there was no significant adverse event related to red ginseng. The QOL and sexual function of the study participants in the red-ginseng group were mostly improved, but no statistically significant effect of red ginseng was shown. It is supposed that this result was partly due to the affirmative impression of red ginseng in Korea. Thus, it is anticipated that a long-term clinical trial will show a significant effect of red ginseng on the QOL and sexual function.

• Journal of the Korean earth science society
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• v.27 no.4
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• pp.390-400
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• 2006

The purpose of this study is to propose an improvement plan based on an analysis of the current earth science teacher education curriculum in the department of education in the four fields of teaching profession theory: student-teacher practice, subject lesson education, and subject content education. The following are the conclusions and suggestions of this study. In case of teaching profession theory, too much emphasis is put on pedagogical theory over practical issues, and a problem arises upon completion. Therefore, it is sugguest that teaching profession theory might be completed before subject lesson education to ensure more authentic subjects performing teaching profession. The current term for student-teacher training is too short to understand the whole school system. Current school system does not have any off-job training course or internship system. Therefore, student-teacher training term should be increased by at least $3{\sim}6$ months to play a vital role in the current system. The credit number of subject lesson education is too small compared with subject content education. Consequently, the credit number of subject lesson education should be increased, and more professor majored in subject lesson education should be recruited. Significant deviation between the content of subject content education and that of middle school grade exists, and there is also much difference in the ratio of subject according to university. To get rid of these problems, subject content education should be connected with subject lesson education and appropriate number of credit needs to be assigned to each subject domain.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.3
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• pp.3-9
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• 2017

Recently, in 3rd Generation Partnership Project(3GPP), there is a study of the Long Term Evolution(LTE) based vehicle communication which has been actively conducted to provide a transport efficiency, telematics and infortainment. Because the vehicle communication is closely related to the safety, it requires a reliable communication. Because vehicle speed is very fast, unlike the movement of the user, radio channel is rapidly changed and generate a number of problems such as transmission quality degradation. Therefore, we have to continuously updates the channel estimates. There are five types of conventional channel estimation scheme. Least Square(LS) is obtained by pilot symbol which is known to transmitter and receiver. Decision Directed Channel Estimation(DDCE) scheme uses the data signal for channel estimation. Constructed Data Pilot(CDP) scheme uses the correlation characteristic between adjacent two data symbols. Spectral Temporal Averaging(STA) scheme uses the frequency-time domain average of the channel. Smoothing scheme reduces the peak error value of data decision. In this paper, we propose the novel channel estimation scheme in LTE based Vehicle-to-Vehicle(V2V) environment. In our Hybrid Reliable Channel Estimation(HRCE) scheme, DDCE and Smoothing schemes are combined and finally the Linear Minimum Mean Square Error(LMMSE) scheme is applied to minimize the channel estimation error. Therefore it is possible to detect the reliable data. In simulation results, overall performance can be improved in terms of Normalized Mean Square Error(NMSE) and Bit Error Rate(BER).

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.33-56
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• 2016

Many researchers have focused on developing bankruptcy prediction models using modeling techniques, such as statistical methods including multiple discriminant analysis (MDA) and logit analysis or artificial intelligence techniques containing artificial neural networks (ANN), decision trees, and support vector machines (SVM), to secure enhanced performance. Most of the bankruptcy prediction models in academic studies have used financial ratios as main input variables. The bankruptcy of firms is associated with firm's financial states and the external economic situation. However, the inclusion of qualitative information, such as the economic atmosphere, has not been actively discussed despite the fact that exploiting only financial ratios has some drawbacks. Accounting information, such as financial ratios, is based on past data, and it is usually determined one year before bankruptcy. Thus, a time lag exists between the point of closing financial statements and the point of credit evaluation. In addition, financial ratios do not contain environmental factors, such as external economic situations. Therefore, using only financial ratios may be insufficient in constructing a bankruptcy prediction model, because they essentially reflect past corporate internal accounting information while neglecting recent information. Thus, qualitative information must be added to the conventional bankruptcy prediction model to supplement accounting information. Due to the lack of an analytic mechanism for obtaining and processing qualitative information from various information sources, previous studies have only used qualitative information. However, recently, big data analytics, such as text mining techniques, have been drawing much attention in academia and industry, with an increasing amount of unstructured text data available on the web. A few previous studies have sought to adopt big data analytics in business prediction modeling. Nevertheless, the use of qualitative information on the web for business prediction modeling is still deemed to be in the primary stage, restricted to limited applications, such as stock prediction and movie revenue prediction applications. Thus, it is necessary to apply big data analytics techniques, such as text mining, to various business prediction problems, including credit risk evaluation. Analytic methods are required for processing qualitative information represented in unstructured text form due to the complexity of managing and processing unstructured text data. This study proposes a bankruptcy prediction model for Korean small- and medium-sized construction firms using both quantitative information, such as financial ratios, and qualitative information acquired from economic news articles. The performance of the proposed method depends on how well information types are transformed from qualitative into quantitative information that is suitable for incorporating into the bankruptcy prediction model. We employ big data analytics techniques, especially text mining, as a mechanism for processing qualitative information. The sentiment index is provided at the industry level by extracting from a large amount of text data to quantify the external economic atmosphere represented in the media. The proposed method involves keyword-based sentiment analysis using a domain-specific sentiment lexicon to extract sentiment from economic news articles. The generated sentiment lexicon is designed to represent sentiment for the construction business by considering the relationship between the occurring term and the actual situation with respect to the economic condition of the industry rather than the inherent semantics of the term. The experimental results proved that incorporating qualitative information based on big data analytics into the traditional bankruptcy prediction model based on accounting information is effective for enhancing the predictive performance. The sentiment variable extracted from economic news articles had an impact on corporate bankruptcy. In particular, a negative sentiment variable improved the accuracy of corporate bankruptcy prediction because the corporate bankruptcy of construction firms is sensitive to poor economic conditions. The bankruptcy prediction model using qualitative information based on big data analytics contributes to the field, in that it reflects not only relatively recent information but also environmental factors, such as external economic conditions.

• Journal of The Korean Ophthalmological Society
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• v.54 no.9
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• pp.1445-1451
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• 2013

Purpose: To report long-term changes in the average retinal nerve fiber layer (RNFL) thickness in 2 patients who had intravitreal bevacizumab (IVB) injection for diabetic papillopathy. Case summary: A 36-year-old patient with diabetes complained of decreased visual acuity (20/200) in the right eye. The fundus examination showed optic disc swelling in both eyes. The average RNFL thickness based on optical coherence tomography (OCT) increased to $278{\mu}m$ and Goldmann perimetry showed nasal visual field defect in the right eye. The IVB was injected into the right eye. Three weeks after the IVB injection, RNFL thickness decreased to $135{\mu}m$ and visual acuity improved to 20/25 in the right eye. However, RNFL thickness increased from 126 to $207{\mu}m$ and visual acuity decreased to 20/32 in the left eye. Thus, IVB was injected into the left eye. In week 3, RNFL thickness decreased to $147{\mu}m$ and visual acuity improved to 20/20 in the left eye. At 12 months after IVB injection, RNFL thickness was $87{\mu}m$ in the right eye and $109{\mu}m$ in the left eye. A 57-year-old patient with diabetes complained of decreased visual acuity (20/200) and showed optic disc swelling in the right eye. The average RNFL thickness increased to $252{\mu}m$ and Goldmann perimetry showed an enlarged blind spot in the right eye. IVB was injected into the right eye. After 3 weeks, RNFL thickness decreased to $136{\mu}m$ and visual acuity improved to 20/70 in the right eye. Six months after IVB injection, RNFL thickness was $83{\mu}m$ in the right eye. Conclusions: Visual acuity progressively improved within 3 weeks and RNFL thickness measured by spectral domain OCT showed progressive thickness reduction in 2 cases of diabetic papillopathy patients who had IVB injections.

• Journal of The Korean Ophthalmological Society
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• v.59 no.12
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• pp.1152-1159
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• 2018

Purpose: We prospectively investigated clinical changes and long-term outcomes after administration of the drugs recommended by the Age-Related Eye Disease Study-2 to patients with intermediate age-related macular degeneration (AMD). Methods: This prospective multicenter study enrolled 79 eyes of 55 patients taking lutein and zeaxanthin. The primary endpoint was contrast sensitivity; this was checked every 12 months for a total of 36 months after treatment commenced. The secondary endpoints were visual acuity, central macular thickness, and drusen volume; the latter two parameters were assessed using spectral domain optical coherence tomography. Results: The mean patient age was $72.46{\pm}7.16years$. Contrast sensitivity gradually improved at both three and six cycles per degree. The corrected visual acuity was $0.13{\pm}0.14logMAR$ and did not change significantly over the 36 months. Neither the central macular thickness nor drusen volume changed significantly. Conclusions: Contrast sensitivity markedly improved after treatment, improving vision and patient satisfaction. Visual acuity, central retinal thickness, and drusen volume did not deteriorate. Therefore, progression of AMD and visual function deterioration were halted.

• Asia pacific journal of information systems
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• v.21 no.1
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• pp.103-122
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• 2011

Recently, numerous documents have been made available electronically. Internet search engines and digital libraries commonly return query results containing hundreds or even thousands of documents. In this situation, it is virtually impossible for users to examine complete documents to determine whether they might be useful for them. For this reason, some on-line documents are accompanied by a list of keywords specified by the authors in an effort to guide the users by facilitating the filtering process. In this way, a set of keywords is often considered a condensed version of the whole document and therefore plays an important role for document retrieval, Web page retrieval, document clustering, summarization, text mining, and so on. Since many academic journals ask the authors to provide a list of five or six keywords on the first page of an article, keywords are most familiar in the context of journal articles. However, many other types of documents could not benefit from the use of keywords, including Web pages, email messages, news reports, magazine articles, and business papers. Although the potential benefit is large, the implementation itself is the obstacle; manually assigning keywords to all documents is a daunting task, or even impractical in that it is extremely tedious and time-consuming requiring a certain level of domain knowledge. Therefore, it is highly desirable to automate the keyword generation process. There are mainly two approaches to achieving this aim: keyword assignment approach and keyword extraction approach. Both approaches use machine learning methods and require, for training purposes, a set of documents with keywords already attached. In the former approach, there is a given set of vocabulary, and the aim is to match them to the texts. In other words, the keywords assignment approach seeks to select the words from a controlled vocabulary that best describes a document. Although this approach is domain dependent and is not easy to transfer and expand, it can generate implicit keywords that do not appear in a document. On the other hand, in the latter approach, the aim is to extract keywords with respect to their relevance in the text without prior vocabulary. In this approach, automatic keyword generation is treated as a classification task, and keywords are commonly extracted based on supervised learning techniques. Thus, keyword extraction algorithms classify candidate keywords in a document into positive or negative examples. Several systems such as Extractor and Kea were developed using keyword extraction approach. Most indicative words in a document are selected as keywords for that document and as a result, keywords extraction is limited to terms that appear in the document. Therefore, keywords extraction cannot generate implicit keywords that are not included in a document. According to the experiment results of Turney, about 64% to 90% of keywords assigned by the authors can be found in the full text of an article. Inversely, it also means that 10% to 36% of the keywords assigned by the authors do not appear in the article, which cannot be generated through keyword extraction algorithms. Our preliminary experiment result also shows that 37% of keywords assigned by the authors are not included in the full text. This is the reason why we have decided to adopt the keyword assignment approach. In this paper, we propose a new approach for automatic keyword assignment namely IVSM(Inverse Vector Space Model). The model is based on a vector space model. which is a conventional information retrieval model that represents documents and queries by vectors in a multidimensional space. IVSM generates an appropriate keyword set for a specific document by measuring the distance between the document and the keyword sets. The keyword assignment process of IVSM is as follows: (1) calculating the vector length of each keyword set based on each keyword weight; (2) preprocessing and parsing a target document that does not have keywords; (3) calculating the vector length of the target document based on the term frequency; (4) measuring the cosine similarity between each keyword set and the target document; and (5) generating keywords that have high similarity scores. Two keyword generation systems were implemented applying IVSM: IVSM system for Web-based community service and stand-alone IVSM system. Firstly, the IVSM system is implemented in a community service for sharing knowledge and opinions on current trends such as fashion, movies, social problems, and health information. The stand-alone IVSM system is dedicated to generating keywords for academic papers, and, indeed, it has been tested through a number of academic papers including those published by the Korean Association of Shipping and Logistics, the Korea Research Academy of Distribution Information, the Korea Logistics Society, the Korea Logistics Research Association, and the Korea Port Economic Association. We measured the performance of IVSM by the number of matches between the IVSM-generated keywords and the author-assigned keywords. According to our experiment, the precisions of IVSM applied to Web-based community service and academic journals were 0.75 and 0.71, respectively. The performance of both systems is much better than that of baseline systems that generate keywords based on simple probability. Also, IVSM shows comparable performance to Extractor that is a representative system of keyword extraction approach developed by Turney. As electronic documents increase, we expect that IVSM proposed in this paper can be applied to many electronic documents in Web-based community and digital library.

• Journal of the Ergonomics Society of Korea
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• v.35 no.4
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• pp.293-305
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• 2016

Objective: This study aims to measure cognitive load levels by analyzing the EEG of Koreans and foreigners, when they read a Korean text with care selected by level from the grammar and vocabulary aspects, and compare the cognitive load levels through quantitative values. The study results can be utilized as basic data for more scientific approach, when Korean texts or books are developed, and an evaluation method is built, when the foreigners encounter them for learning or an assignment. Background: Based on 2014, the number of the foreign students studying in Korea was 84,801, and they increase annually. Most of them are from Asian region, and they come to Korea to enter a university or a graduate school in Korea. Because those foreign students aim to learn within Universities in Korea, they receive Korean education from their preparation for study in Korea. To enter a university in Korea, they must acquire grade 4 or higher level in the Test of Proficiency in Korean (TOPIK), or they need to complete a certain educational program at each university's affiliated language institution. In such a program, the learners of the Korean language receive Korean education based on texts, except speaking domain, and the comprehension of texts can determine their academic achievements in studying after they enter their desired schools (Jeon, 2004). However, many foreigners, who finish a language course for the short-term, and need to start university study, cannot properly catch up with university classes requiring expertise with the vocabulary and grammar levels learned during the language course. Therefore, reading education, centered on a strategy to understand university textbooks regarded as top level reading texts to the foreigners, is necessary (Kim and Shin, 2015). This study carried out an experiment from a perspective that quantitative data on the readers of the main player of reading education and teaching materials need to be secured to back up the need for reading education for university study learners, and scientifically approach educational design. Namely, this study grasped the difficulty level of reading through the measurement of cognitive loads indicated in the reading activity of each text by dividing the difficulty of a teaching material (book) into eight levels, and the main player of reading into Koreans and foreigners. Method: To identify cognitive loads indicated upon reading Korean texts with care by Koreans and foreigners, this study recruited 16 participants (eight Koreans and eight foreigners). The foreigners were limited to the language course students studying the intermediate level Korean course at university-affiliated language institutions within Seoul Metropolitan Area. To identify cognitive load, as they read a text by level selected from the Korean books (difficulty: eight levels) published by King Sejong Institute (Sejonghakdang.org), the EEG sensor was attached to the frontal love (Fz) and occipital lobe (Oz). After the experiment, this study carried out a questionnaire survey to measure subjective evaluation, and identified the comprehension and difficulty on grammar and words. To find out the effects on schema that may affect text comprehension, this study controlled the Korean texts, and measured EEG and subjective satisfaction. Results: To identify brain's cognitive load, beta band was extracted. As a result, interactions (Fz: p =0.48; Oz: p =0.00) were revealed according to Koreans and foreigners, and difficulty of the text. The cognitive loads of Koreans, the readers whose mother tongue is Korean, were lower in reading Korean texts than those of the foreigners, and the foreigners' cognitive loads became higher gradually according to the difficulty of the texts. From the text four, which is intermediate level in difficulty, remarkable differences started to appear in comparison of the Koreans and foreigners in the beginner's level text. In the subjective evaluation, interactions were revealed according to the Koreans and foreigners and text difficulty (p =0.00), and satisfaction was lower, as the difficulty of the text became higher. Conclusion: When there was background knowledge in reading, namely schema was formed, the comprehension and satisfaction of the texts were higher, although higher levels of vocabulary and grammar were included in the texts than those of the readers. In the case of a text in which the difficulty of grammar was felt high in the subjective evaluation, foreigners' cognitive loads were also high, which shows the result of the loads' going up higher in proportion to the increase of difficulty. This means that the grammar factor functions as a stress factor to the foreigners' reading comprehension. Application: This study quantitatively evaluated the cognitive loads of Koreans and foreigners through EEG, based on readers and the text difficulty, when they read Korean texts. The results of this study can be used for making Korean teaching materials or Korean education content and topic selection for foreigners. If research scope is expanded to reading process using an eye-tracker, the reading education program and evaluation method for foreigners can be developed on the basis of quantitative values.