• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.7
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• pp.867-873
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• 2019

As of August 2019, there were 3,823 vessels under 30 tons that could be included in the category of small vessels; these account for 42.5 % of the 9,001 registered vessels in Korea. The problem is that many small vessel seafarers face many problems such as an board communication disconnection, difficulties in communication in maritime license interviews, or education related to maritime training using a large number of nonstandard terms, which are derived from foreign languages; this is leading to a decline the job skills of small vessel seafarers. Therefore, in this study, we closely analyzed the terminology of small vessel seafarers and proposed a standardization plan. In the terminology analysis, the preliminary terms of the maritime license interview and the high-frequency terms of the small vessel educational textbook were identified and the corresponding nonstandard terms were examined. Based on a survey, an expert meeting was held and incorrect Japanese notation, English notation, and the standard language for key terms were presented to analyze which questionnaire was most familiar. The ratio of the use of standard words is relatively high in the case of nautical terms, however, the wrong Japanese notation is used more for engine terms; the analysis results by age and tonnage also generally use the Japanese notation and the use frequency of English notation was determined to be low. Based on this, short- and long-term plans for the use of standard words by small vessel seafarers were proposed, including the production of a standard language dictionary for terms used by these seafarers, a promotion of the importance of using standard terms, active education through educational institutions, and the systematic preparation and implementation of Korean-language education for foreign sailors.

• Korea journal of population studies
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• v.10 no.1
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• pp.50-69
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• 1987

There are about 400, 000 Korean ethnics living in Central Asia. Most of Koreans in Central Asia are leading a stable middle class life mostly engaged in farm work. With increase of educational attainment of their children, a number of Koreans are launching into political and academic circles as well as in the cultural world or the press. In recent years, however, the countries in this area(Uzbekistan and Kazakstan) for this study advocate an ethnic united policy to stabilize the politics and society and to carry out efficient transformation from the former socialistic economy to a market oriented economy. In addition, they are trying to recover the culture and the language of each nation which has been forgotten in the assimilation of Russia policy. Koreans have difficulty in adaption to this kind of change. In fact, a number of Koreans lost traditional culture and could not speak their mother language - Korean. Although they more or less maintain national consciousness, they recognize Uzbekistan or Kazakstan as their nation politically. They associated with North Korea unilaterally before the launching of the Perestroika policy. But after the Seoul Olympics held in 1998, there was movement to know and understand South Korea. There has been increased in the investment by Korean companies in Central Asia. Now, what is an alternative idea for Korean community consciousness\ulcorner It can be summarized as follows: 1) The increase of aid to Korean education institute : Considering the last few decades of Russia's strong racial assimilation policy, which leads most Koreans to lost their language and national culture, the priority should go to Koreans education. 2) Local Korean press support : Though Korean newspaper are published and Korean broadcasting is on the air currently in Uzbekistan and Kazakstan, they are suffering from qualified staff and poor financial status. Therefore, positive support should be established for these Korean mass communication media outlets to recover their own function and expand their dissemination powers quickly. 3) Research on the actual condition for Korean Community : It is essential to directly examine the local Korean community's regional distribution, population structure, Korean group's formation and operation, social and cultural understanding, racial consciousness, hope for their mother land and much more. 4) Increase of mother land and education opportunity : To stir up national culture and national consciousness within the Korean community, it is necessary to expand continuous opportunities for mother land visits and education training for local Koreans, especially for second and third generations.

• (The) Research of the performance art and culture
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• no.43
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• pp.203-228
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• 2021

This thesis examines the play education method shown in the elementary school textbook 'Enjoy Play'. If the educational methods of the curriculum other than plays were presented in the order of 'Understanding play - Appreciation of Works - Creation of Works', the method of drama education is presented sequentially in the order of 'Understanding play - Creation of Works - Appreciation of Works' in the order of 'Understanding play - Artwork - Appreciation' have. Even if such a curriculum considers the study linked to the subject of 'Plays', students may not feel the 'burden' of 'creation', and by simplifying the understanding of 'spoken language', it is rather the characteristic of 'Korean language'. It may also make it difficult for students to feel the attraction. In addition, empathy through the conflict situation of the play or comparison with the actual conflict is mainly presented through the translation of foreign works or the expression of a fairy tale and fantastic world that is far from reality, so the burden of inferring the right life problems can be confirmed. Theatrical expressions and plays and plays learned through textbooks are partially different depending on the educational goals to be achieved. The result of this study is that the course of textbooks for elementary and upper grades may correspond to the problem of expressing 'Plays', but it is regrettable in leading students to think about ways to solve life problems in detail through 'Plays'. It is also necessary to emphasize the importance of expression that makes students realize how to express themselves autonomously in the way of expressing their feelings, but on the other hand, on the other hand, it is necessary to share empathy with feelings first, understand these feelings, Therefore, it was suggested that training to infer expressions and emotions by learning individual expressions through methods of expressing emotions and a process of educating students to voluntarily accept shared emotions are also necessary. Sharing and expressing emotional emotions through 'play', and participation through cooperation and division of labor through the process of performing.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.77-92
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• 2014

Recently, numerous documents including unstructured data and text have been created due to the rapid increase in the usage of social media and the Internet. Each document is usually provided with a specific category for the convenience of the users. In the past, the categorization was performed manually. However, in the case of manual categorization, not only can the accuracy of the categorization be not guaranteed but the categorization also requires a large amount of time and huge costs. Many studies have been conducted towards the automatic creation of categories to solve the limitations of manual categorization. Unfortunately, most of these methods cannot be applied to categorizing complex documents with multiple topics because the methods work by assuming that one document can be categorized into one category only. In order to overcome this limitation, some studies have attempted to categorize each document into multiple categories. However, they are also limited in that their learning process involves training using a multi-categorized document set. These methods therefore cannot be applied to multi-categorization of most documents unless multi-categorized training sets are provided. To overcome the limitation of the requirement of a multi-categorized training set by traditional multi-categorization algorithms, we propose a new methodology that can extend a category of a single-categorized document to multiple categorizes by analyzing relationships among categories, topics, and documents. First, we attempt to find the relationship between documents and topics by using the result of topic analysis for single-categorized documents. Second, we construct a correspondence table between topics and categories by investigating the relationship between them. Finally, we calculate the matching scores for each document to multiple categories. The results imply that a document can be classified into a certain category if and only if the matching score is higher than the predefined threshold. For example, we can classify a certain document into three categories that have larger matching scores than the predefined threshold. The main contribution of our study is that our methodology can improve the applicability of traditional multi-category classifiers by generating multi-categorized documents from single-categorized documents. Additionally, we propose a module for verifying the accuracy of the proposed methodology. For performance evaluation, we performed intensive experiments with news articles. News articles are clearly categorized based on the theme, whereas the use of vulgar language and slang is smaller than other usual text document. We collected news articles from July 2012 to June 2013. The articles exhibit large variations in terms of the number of types of categories. This is because readers have different levels of interest in each category. Additionally, the result is also attributed to the differences in the frequency of the events in each category. In order to minimize the distortion of the result from the number of articles in different categories, we extracted 3,000 articles equally from each of the eight categories. Therefore, the total number of articles used in our experiments was 24,000. The eight categories were "IT Science," "Economy," "Society," "Life and Culture," "World," "Sports," "Entertainment," and "Politics." By using the news articles that we collected, we calculated the document/category correspondence scores by utilizing topic/category and document/topics correspondence scores. The document/category correspondence score can be said to indicate the degree of correspondence of each document to a certain category. As a result, we could present two additional categories for each of the 23,089 documents. Precision, recall, and F-score were revealed to be 0.605, 0.629, and 0.617 respectively when only the top 1 predicted category was evaluated, whereas they were revealed to be 0.838, 0.290, and 0.431 when the top 1 - 3 predicted categories were considered. It was very interesting to find a large variation between the scores of the eight categories on precision, recall, and F-score.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.1-25
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• 2020

Sentiment Analysis (SA) is a Natural Language Processing (NLP) task that analyzes the sentiments consumers or the public feel about an arbitrary object from written texts. Furthermore, Aspect-Based Sentiment Analysis (ABSA) is a fine-grained analysis of the sentiments towards each aspect of an object. Since having a more practical value in terms of business, ABSA is drawing attention from both academic and industrial organizations. When there is a review that says "The restaurant is expensive but the food is really fantastic", for example, the general SA evaluates the overall sentiment towards the 'restaurant' as 'positive', while ABSA identifies the restaurant's aspect 'price' as 'negative' and 'food' aspect as 'positive'. Thus, ABSA enables a more specific and effective marketing strategy. In order to perform ABSA, it is necessary to identify what are the aspect terms or aspect categories included in the text, and judge the sentiments towards them. Accordingly, there exist four main areas in ABSA; aspect term extraction, aspect category detection, Aspect Term Sentiment Classification (ATSC), and Aspect Category Sentiment Classification (ACSC). It is usually conducted by extracting aspect terms and then performing ATSC to analyze sentiments for the given aspect terms, or by extracting aspect categories and then performing ACSC to analyze sentiments for the given aspect category. Here, an aspect category is expressed in one or more aspect terms, or indirectly inferred by other words. In the preceding example sentence, 'price' and 'food' are both aspect categories, and the aspect category 'food' is expressed by the aspect term 'food' included in the review. If the review sentence includes 'pasta', 'steak', or 'grilled chicken special', these can all be aspect terms for the aspect category 'food'. As such, an aspect category referred to by one or more specific aspect terms is called an explicit aspect. On the other hand, the aspect category like 'price', which does not have any specific aspect terms but can be indirectly guessed with an emotional word 'expensive,' is called an implicit aspect. So far, the 'aspect category' has been used to avoid confusion about 'aspect term'. From now on, we will consider 'aspect category' and 'aspect' as the same concept and use the word 'aspect' more for convenience. And one thing to note is that ATSC analyzes the sentiment towards given aspect terms, so it deals only with explicit aspects, and ACSC treats not only explicit aspects but also implicit aspects. This study seeks to find answers to the following issues ignored in the previous studies when applying the BERT pre-trained language model to ACSC and derives superior ACSC models. First, is it more effective to reflect the output vector of tokens for aspect categories than to use only the final output vector of [CLS] token as a classification vector? Second, is there any performance difference between QA (Question Answering) and NLI (Natural Language Inference) types in the sentence-pair configuration of input data? Third, is there any performance difference according to the order of sentence including aspect category in the QA or NLI type sentence-pair configuration of input data? To achieve these research objectives, we implemented 12 ACSC models and conducted experiments on 4 English benchmark datasets. As a result, ACSC models that provide performance beyond the existing studies without expanding the training dataset were derived. In addition, it was found that it is more effective to reflect the output vector of the aspect category token than to use only the output vector for the [CLS] token as a classification vector. It was also found that QA type input generally provides better performance than NLI, and the order of the sentence with the aspect category in QA type is irrelevant with performance. There may be some differences depending on the characteristics of the dataset, but when using NLI type sentence-pair input, placing the sentence containing the aspect category second seems to provide better performance. The new methodology for designing the ACSC model used in this study could be similarly applied to other studies such as ATSC.

• Journal of the Korean Society for Library and Information Science
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• v.32 no.2
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• pp.211-232
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• 1998

It is the purpose of this study to specify contents of Library and Information Science to train information professional to meet environment change of technology and system. Among them. recognizing necessity of present Artificial Intelligence and Export System (AI and ES) required by changing environment of latest Information technology, it is also the purpose of this work to figure out fundamental data and the way of solution how to introduce what contents out of AI and ES to Library and Information Science. The briefed results are as follows. 1. Due to rapid change of high Information technology and computer application it is the most important essential points, In order of Importance, in finding available network source, In indexing on-line data base, in analysing and design information system. and in computer application ability. 2. In contents of AI and ES, most Important training portion for Library and Information Science are : data base treating, thesaurus, natural language processing. and knowledge representation. 3. Library and information science professors recognize It necessary for bigger number of Library and Information Science students to be educated artificial intelligence and expert system. 4. During forthcoming age it shows more important reorganization that artificial intelligence and expert system improves information professional in reference service, cataloging, classification, information retrieval, and documentation delivery 5. According to library and information science professors more important reorganization on the subject of AI and ES, the curricular on AI and ES is, forthcoming, to be Introduced to curricular on library and information science in the nation, In order of importance, (see 1. above).

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.4
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• pp.30-39
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• 2003

In this paper, we carried out the performance evaluation of HM-Net(Hidden Markov Network) speech recognition system for Korean speech databases. We adopted to construct acoustic models using the HM-Nets modified by HMMs(Hidden Markov Models), which are widely used as the statistical modeling methods. HM-Nets are carried out the state splitting for contextual and temporal domain by PDT-SSS(Phonetic Decision Tree-based Successive State Splitting) algorithm, which is modified the original SSS algorithm. Especially it adopted the phonetic decision tree to effectively express the context information not appear in training speech data on contextual domain state splitting. In case of temporal domain state splitting, to effectively represent information of each phoneme maintenance in the state splitting is carried out, and then the optimal model network of triphone types are constructed by in the parameter. Speech recognition was performed using the one-pass Viterbi beam search algorithm with phone-pair/word-pair grammar for phoneme/word recognition, respectively and using the multi-pass search algorithm with n-gram language models for sentence recognition. The tree-structured lexicon was used in order to decrease the number of nodes by sharing the same prefixes among words. In this paper, the performance evaluation of HM-Net speech recognition system is carried out for various recognition conditions. Through the experiments, we verified that it has very superior recognition performance compared with the previous introduced recognition system.

• Journal of the Korea Society of Computer and Information
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• v.17 no.8
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• pp.189-201
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• 2012

The purpose of this study is to develop an effective teaching model for the "Problem solving methods and procedures" section in the revised academic high school informatics curriculum, verify its effectiveness, make the subject more effective and appealing to teachers as well as students. The model includes a middle school level informatics curriculum for the students who have yet to learn the section. This development follows the ADDIE model, and the Python programming language is adopted for the model. Using the model, classes were conducted with two groups: high school computer club students and undergraduate students majoring in computer education. Of the undergraduate students 75% responded positively to the model. This model was applied in the actual high school classroom teaching for 23 class-hours in the spring semester 2012. The Pearson correlation coefficient that verifies the correspondence between the PSI score and the informatics midterm exam grade is .247, which reflects a weak positive correlation. The result of the study showed that the developed teaching model is an effective tool in educating students about the "problem solving methods and procedures". The model is to be a cornerstone of teaching/learning plans for informatics at academic high school as well as training materials for pre-service teachers.

• Journal of the Korea Convergence Society
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• v.8 no.12
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• pp.85-92
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• 2017

As accessibility toward traditional cultural contents drops compared to its increase in production, the need for higher accessibility for continued management and research to exist. For this, this paper introduces an image classifier model for traditional images based on artificial neural networks, which converts the input image's features into a vector space and by utilizing a RNN based model it recognizes and compares the details of the input which enables the classification of traditional images. This enables the classifiers to classify similarly looking traditional images more precisely by focusing on the details. For the training of this model, a wide range of images were arranged and collected based on the format of the Korean information culture field, which contributes to other researches related to the fields of using traditional cultural images. Also, this research contributes to the further activation of demand, supply, and researches related to traditional culture.

• Journal of The Korean Association For Science Education
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• v.17 no.3
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• pp.261-271
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• 1997

This study evaluates on students' understanding and misunderstanding of homeostasis, classification of animals and plants, and food production in plants, and analyzes the teacher factor as a possible source of students' misconception. A total number of 863 students and 47 biology teachers at the middle and high school were randomly selected. Students' conceptions and misconceptions were measured with concept evaluation statements (CES) which was translated into Korean by author. The CES was developed and validated by Simson and Marek (1988). Teacher's misconceptions were investigated the way in which teachers marked students' work. The supposed answer given to the teachers to mark was based on misconceptions held by students tested in concept evaluation statements. The results of this study are as follows : 1. 0% of 7th Grade students, 4.5% of 9th Grade students and 5.4% of 11th Grade students understood homeostasis. There was a significant difference at the level of students' understanding of homeostasis according to schools and gender(P<0.05). Many students had a tendency of understanding the conception of the homeostasis by experiences and unscientific use of everyday language rather than a scientific concept. 2. 0.4% of 7th Grade students, 3.1% of 9th Grade students and 2.9% of 11th Grade students understood classification of animals and plants. There was a significant difference at the level of students' understanding of classification of animals and plants according to schools and gender(P<0.05). Students classified animals and plants through personal experiences and observations instead of trying to classify through microscopic analysis of animals and plants cell. 3. 1.2% of 7th Grade students, 10.3% of 9th Grade students and 19.4% of 11th Grade students understood food production in plants. There was a significant difference at the level of students' understanding of food production in plants according to schools and gender(P<0.05). Students had a misconception that food production in plants was done by an absorption of nutrients from soil not by photosynthesis. 4. A large proportion of teachers surveyed in this study appear to have misconceptions about homeostasis (38.1%), classification of animals and plants (34.1%), food production in plants (40.4%). The male teachers had. more misconceptions than female teachers(P<0.05). However, they didn't show any significant differences according to schools and teaching experience(P<0.05). 5. According to the investigation of teachers' perception, 29.8% of the teachers acknowledged that they might be a cause for students' misconceptions. This study shows that 38.3% of teachers did not understand the analyzed biological concepts precisely. By comparing the data of students and teachers, it turned out that teachers participate in the students' misconceptions. And teachers themselves acknowledged that students' misconceptions could be caused by them. Therefore. teachers' right understanding of fundamental biological concepts should precede to students' biology education. New training programs for biology teachers seem to be urgent.