• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.105-122
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• 2019

Dimensionality reduction is one of the methods to handle big data in text mining. For dimensionality reduction, we should consider the density of data, which has a significant influence on the performance of sentence classification. It requires lots of computations for data of higher dimensions. Eventually, it can cause lots of computational cost and overfitting in the model. Thus, the dimension reduction process is necessary to improve the performance of the model. Diverse methods have been proposed from only lessening the noise of data like misspelling or informal text to including semantic and syntactic information. On top of it, the expression and selection of the text features have impacts on the performance of the classifier for sentence classification, which is one of the fields of Natural Language Processing. The common goal of dimension reduction is to find latent space that is representative of raw data from observation space. Existing methods utilize various algorithms for dimensionality reduction, such as feature extraction and feature selection. In addition to these algorithms, word embeddings, learning low-dimensional vector space representations of words, that can capture semantic and syntactic information from data are also utilized. For improving performance, recent studies have suggested methods that the word dictionary is modified according to the positive and negative score of pre-defined words. The basic idea of this study is that similar words have similar vector representations. Once the feature selection algorithm selects the words that are not important, we thought the words that are similar to the selected words also have no impacts on sentence classification. This study proposes two ways to achieve more accurate classification that conduct selective word elimination under specific regulations and construct word embedding based on Word2Vec embedding. To select words having low importance from the text, we use information gain algorithm to measure the importance and cosine similarity to search for similar words. First, we eliminate words that have comparatively low information gain values from the raw text and form word embedding. Second, we select words additionally that are similar to the words that have a low level of information gain values and make word embedding. In the end, these filtered text and word embedding apply to the deep learning models; Convolutional Neural Network and Attention-Based Bidirectional LSTM. This study uses customer reviews on Kindle in Amazon.com, IMDB, and Yelp as datasets, and classify each data using the deep learning models. The reviews got more than five helpful votes, and the ratio of helpful votes was over 70% classified as helpful reviews. Also, Yelp only shows the number of helpful votes. We extracted 100,000 reviews which got more than five helpful votes using a random sampling method among 750,000 reviews. The minimal preprocessing was executed to each dataset, such as removing numbers and special characters from text data. To evaluate the proposed methods, we compared the performances of Word2Vec and GloVe word embeddings, which used all the words. We showed that one of the proposed methods is better than the embeddings with all the words. By removing unimportant words, we can get better performance. However, if we removed too many words, it showed that the performance was lowered. For future research, it is required to consider diverse ways of preprocessing and the in-depth analysis for the co-occurrence of words to measure similarity values among words. Also, we only applied the proposed method with Word2Vec. Other embedding methods such as GloVe, fastText, ELMo can be applied with the proposed methods, and it is possible to identify the possible combinations between word embedding methods and elimination methods.

• Journal of the Korea Society of Computer and Information
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• v.25 no.3
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• pp.243-250
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• 2020

In this paper, we propose an effective software education scheme for universities. The key idea of this software education scheme is to analyze software curriculum of QS world university rankings Top 10, SW-oriented university, and regional main national university. And based on the results, we propose five improvements for the effective SW education method of universities. The first is to enhance the adaptability of the industry by developing courses based on the SW developer's job analysis in the curriculum development process. Second, it is necessary to strengthen the curriculum of the 4th industrial revolution core technologies(cloud computing, big data, virtual/augmented reality, Internet of things, etc.) and integrate them with various fields such as medical, bio, sensor, human, and cognitive science. Third, programming language education should be included in software convergence course after basic syntax education to implement projects in various fields. In addition, the curriculum for developing system programming developers and back-end developers should be strengthened rather than application program developers. Fourth, it offers opportunities to participate in industrial projects by reinforcing courses such as capstone design and comprehensive design, which enables product-based self-directed learning. Fifth, it is necessary to develop university-specific curriculum based on local industry by reinforcing internship or industry-academic program that can acquire skills in local industry field.

• The Journal of the Korea Contents Association
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• v.17 no.1
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• pp.25-38
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• 2017

This study investigates non-native speakers(NNS) of English use of backchannels with beginner-intermediate learners' use of 'uh', 'um(uhm)', 'and' and 'hm' suggesting a view as a possible pedagogical implication. The initial aim of this study was to learn this phenomenon and observe their conversation patterns to compare with previous studies. Based on the previous findings, the analyzed data using conventional Conversation Analysis (CA) methods indicate the possible presence of L1 topic markers, '-un' and '-nun' in the form of L2 backchannel tokens when uttered by beginning and intermediate level speakers of English and the presences of L2 backchannel tokens appear only in front of noun phrases. Additionally, these same words with these tokens and when translated back to Korean also require topic markers of '-un' and '-nun.' Finally, This study discusses possible pedagogical implications with the initial analysis of backchannel tokens for Korean EFL learners. In addition, the ultimate goal of this study is to refine this analysis with follow up experiments to validate this investigation into a working hypothesis generating discussions of this backchannel phenomenon from being viewed as a hindrance to as an positive influence that needs to be understood.

• Journal of Korean Academy of Nursing
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• v.30 no.1
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• pp.84-97
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• 2000

The Necessity and Purpose of the Study Recently the number of patients with chronic diseases and the aged patients is increasing steadily. Furthermore, due to the expansion of health insurance system, the number of patients hospitalized in the general hospital is increasing at a surprising speed. However, hospitals urge the early discharge of the patients for the efficiencies of hospital administration, and therefore, the number of patients who must be taken care of in their home is also increasing. Homecare nursing is one of the health care service for the patients at home who require continual attention and care, and now increasing attentions are given to it as one of the professional nursing fields. However, it was almost impossible to find a study on the actual experiences of the homecare nurses written by their own language in Korea, that it also posed a great difficulty in understanding their diverse experience. Considering these situation, this study will help understanding of them, and provide the fundamental data on their experiences for making policies to develop homecare nursing. Methods of Research Phenomenological research method was employed to analyze the lived experiences of homecare nurses fundamentally. Data collection Data were collected from August 1998 to December 1998 from ten homecare nurses who worked for patients under the homecare nursing setting as model cases designated by Seoul Nurses Association and who agreed to the purpose of this study after listening to and understanding the explanation completely. The in-depth interview was carried at the time which was convenient both for the researcher and participants for one or two hours, and recovered with the approval participants. The first interview covered diverse and broad areas like the situation of homecare nursing, and their feelings and thoughts over it, and in the second and third interviews, more specific questions are asked. Data Analysis For the phenomenological analysis, contents analysis was employed. The data collected from the participants were analyzed into the following procedures according to Van Manen 's phenomenological analysis. 1) Reserve the preconception of the researcher by restricting it inside parenthesis. 2) Make a thorough observation of the lived experiences by insight process. 3) Analyze the contents (Find out the repetitive factors) 4) Interpret the essence found. 5) State the meaning of the interpretation. Results and discussion 1. Fear and expectation for the first visit. (unfamiliarity, awkwardness, anxiety, shivering) 2. Mingle with the family (feeling friendly with the family, becoming like a family member) 3. Being proud of her own know-how (learning the know-how, organizing alternatives, building up confidence) 4. Pity for the poor. (criticizing the current government, feeling ashamed, feeling anger) 5. Difficulty of constructing cooperative system with physicians (strenuousness, frustration) 6. Helplessness due to the lack of support system (difficulty to get supplies, annoyance, embarrassment by institutional restraints) 7. Anxiousness for heavy traffic and parking (annoyance, hastiness) 8. Ethical conflicts (pity for the patients and family, skepticism about lengthening life maintenance) 9. Burden for the possible accident (pressure, anxiety, conflict, physical exhaustion) 10. Establishment of identity as a professional (fulfillment, worth, joy) 11. Being distressed at other's ignorance

• Journal of the Korean School Mathematics Society
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• v.16 no.4
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• pp.797-820
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• 2013

This study intended on analyzing the error patterns of mathematic problem posing sentences by the 100 elementary pre-teachers and discussing about the solutions. The results showed that the problem posing sentences have five error patterns: phonological error patterns, word error patterns, sentence error patterns, meaning error patterns, and notation error patterns. Divided into fourteen specific error patterns, they are as in the following. 1) Phonological error patterns are consisted of the 'ㄹ' addition error pattern and the abbreviated word error pattern. 2) Words error patterns are divided with the inappropriate usage of word error pattern and the inadequate abbreviation error pattern, which are formulized four subgroups such as the case maker, ending of the word, inappropriate usage of word, and inadequate abbreviation of article or word error pattern in detail. 3) Sentence error patterns are assumed four kinds of forms: the reference, ellipsis of sentence component, word order, and incomplete sentence error pattern. 4) Meaning error patterns are composed the logical contradiction and the ambiguous meaning. 5) Notation error patterns are formed four patterns as the spacing, punctuation, orthography of Hangul, and spelling rules of foreign words in Korean. Furthermore, the solutions for these error patterns were discussed: First, it has to be perceived the differences between spoken and written language. Second, it has to be rejected the spoken expressions in written contexts. Third, it should be focused on the learning of the basic sentence patterns during the class. Forth, it is suggested that the word meaning should have the logical development perception based on what it means. Finally, it is proposed that the system of spelling of Korean has to be learned. In addition to these suggestions, a new understanding is necessary regarding writing education for college students.

• Journal of Digital Convergence
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• v.14 no.6
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• pp.371-380
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• 2016

The aim of this case research is to describe the convergence education of Akita International University. Today, competition among universities in Korea are becoming more and more intensified, its strength is expected to continue to rise. In this situation, the Akita International University provides meaningful implications for universities in Korea. Universities in Japan are at similar situation in Korea. The unique values of Akita that we identified are twofold: The first is internationalization in education. The purpose of the internationalization is for Japanese students. For exchange students, AIU provides japan studies program and japan language program. To do this, AIU forms an international community to mingle Japanese students with foreign exchange students by living and learning together. Second thing is about international liberal arts education. The focus of international liberal arts education is that students acquire comprehensive range of skills and knowledge to build the intellectual foundation for specialist study by providing a broad range of academic disciplines. In doing so, students promotes learner autonomy. Unlike specialized education, in which students acquire an in-depth knowledge of a particular field, providing international liberal arts education is to find a field in which students want to study further. The implications and conclusions are discussed.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.9
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• pp.1-16
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• 2019

This study was carried out to develop a physics education program for foreign students of university in Korea to improve their ability to major in the field and to prevent them from becoming dropout. The subjects of the study are five Chinese students attending a natural science and engineering college. Prior to the development of the physics education program, the researchers developed basic physics textbooks for the foreign students and questionaries for diagnosis and summative evaluation, and utilized them to apply a total of seven classes. After the application of the classes, the results of the student's diagnosis and summative evaluation, the teacher's diaries, the observer's diaries, and the transcripts were analyzed by triangulation method. In addition, Nvivo12 was used for the analysis of the teacher's and observer's diaries to help with qualitative analysis. The results of the study are as follows: First, the oder and contents of physics education program for students of the natural science and engineering college were presented in detail, and basic physics textbooks and tools for diagnosis and summative assessment were developed. Second, as a result of the analysis of the diagnosis and summative assessment results of the program, the students' basic physics achievement improved by an average of 40 points due to the application of the developed program. Third, as a result of the application of the program using Nvivo12, meaningful node and actual cases were extracted. There were 10 types of nodes created such as understanding of the students, teaching method, rate of the participation, level differences, language problems, relevance to majors, curriculum and methods of education in the country of origin, cooperative learning, and interest inducement. The researcher provided suggestions on physics education methods for students of science and engineering colleges in Korea based on the related cases.

• Korean Association of Arts Management
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• no.55
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• pp.75-113
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• 2020

This research aims to identify current issues of arts education programs which have designed for North Korean Refugee Youth in South Korea and then navigates further steps to better serve the group. The purpose of study also pertains to the '2010 Seoul Agenda: Goals for the Development of Arts Education' announced at the Second World Conference on Arts Education, particularly, to the third Goal indicating how arts education practices can contribute to resolving social and cultural issues and promoting social cohesion and intercultural dialogues (UNESCO, 2010). This research engages with critical theory approach and adopts qualitative content analysis for collected documents and interview data. Based on the findings of this research, interview participants found its need of current arts education program for North Korean refugee youth become more value-driven and participant-centered. Currently, those programs available seem to incline to helping their adjustment to the South Korean society through arts-related activities, such as enhancing Korean language skills and learning Korean culture. Rather, it has been addressed that providing emotional and psychological supports and opportunities to search their own 'voice(s)' should be core objectives of the arts education programs. Moreover, when it is offered, arts educators and administrators need to make sure that participants can feel safe and secure as being present at the space for programs in order to express and encounter their true inner voice(s).

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.25-38
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• 2019

Selecting high-quality information that meets the interests and needs of users among the overflowing contents is becoming more important as the generation continues. In the flood of information, efforts to reflect the intention of the user in the search result better are being tried, rather than recognizing the information request as a simple string. Also, large IT companies such as Google and Microsoft focus on developing knowledge-based technologies including search engines which provide users with satisfaction and convenience. Especially, the finance is one of the fields expected to have the usefulness and potential of text data analysis because it's constantly generating new information, and the earlier the information is, the more valuable it is. Automatic knowledge extraction can be effective in areas where information flow is vast, such as financial sector, and new information continues to emerge. However, there are several practical difficulties faced by automatic knowledge extraction. First, there are difficulties in making corpus from different fields with same algorithm, and it is difficult to extract good quality triple. Second, it becomes more difficult to produce labeled text data by people if the extent and scope of knowledge increases and patterns are constantly updated. Third, performance evaluation is difficult due to the characteristics of unsupervised learning. Finally, problem definition for automatic knowledge extraction is not easy because of ambiguous conceptual characteristics of knowledge. So, in order to overcome limits described above and improve the semantic performance of stock-related information searching, this study attempts to extract the knowledge entity by using neural tensor network and evaluate the performance of them. Different from other references, the purpose of this study is to extract knowledge entity which is related to individual stock items. Various but relatively simple data processing methods are applied in the presented model to solve the problems of previous researches and to enhance the effectiveness of the model. From these processes, this study has the following three significances. First, A practical and simple automatic knowledge extraction method that can be applied. Second, the possibility of performance evaluation is presented through simple problem definition. Finally, the expressiveness of the knowledge increased by generating input data on a sentence basis without complex morphological analysis. The results of the empirical analysis and objective performance evaluation method are also presented. The empirical study to confirm the usefulness of the presented model, experts' reports about individual 30 stocks which are top 30 items based on frequency of publication from May 30, 2017 to May 21, 2018 are used. the total number of reports are 5,600, and 3,074 reports, which accounts about 55% of the total, is designated as a training set, and other 45% of reports are designated as a testing set. Before constructing the model, all reports of a training set are classified by stocks, and their entities are extracted using named entity recognition tool which is the KKMA. for each stocks, top 100 entities based on appearance frequency are selected, and become vectorized using one-hot encoding. After that, by using neural tensor network, the same number of score functions as stocks are trained. Thus, if a new entity from a testing set appears, we can try to calculate the score by putting it into every single score function, and the stock of the function with the highest score is predicted as the related item with the entity. To evaluate presented models, we confirm prediction power and determining whether the score functions are well constructed by calculating hit ratio for all reports of testing set. As a result of the empirical study, the presented model shows 69.3% hit accuracy for testing set which consists of 2,526 reports. this hit ratio is meaningfully high despite of some constraints for conducting research. Looking at the prediction performance of the model for each stocks, only 3 stocks, which are LG ELECTRONICS, KiaMtr, and Mando, show extremely low performance than average. this result maybe due to the interference effect with other similar items and generation of new knowledge. In this paper, we propose a methodology to find out key entities or their combinations which are necessary to search related information in accordance with the user's investment intention. Graph data is generated by using only the named entity recognition tool and applied to the neural tensor network without learning corpus or word vectors for the field. From the empirical test, we confirm the effectiveness of the presented model as described above. However, there also exist some limits and things to complement. Representatively, the phenomenon that the model performance is especially bad for only some stocks shows the need for further researches. Finally, through the empirical study, we confirmed that the learning method presented in this study can be used for the purpose of matching the new text information semantically with the related stocks.

• Journal of Korean society of Dental Hygiene
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• v.5 no.2
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• pp.201-218
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• 2005

The purpose of this study was to examine how dentists perceived dental coordinators including their education, hiring criteria, working condition and job. It's basically attempted to help define the job and role of 5 and to suggest how they should be nurtured. The subjects in this study were dentists at dental hospitals and clinics where dental coordinators were employed among approximately 200 dental institutions in Seoul, Cyeonggi province and Incheon. After a survey was conducted in June 2005, answer sheets from 99 respondents were analyzed. The findings of the study were as follows: 1. Regarding education for dental coordinators, 99.9% of the dentists investigated felt the need for separate education programs for dental coordinators, 42.4% knew what would-be dental coordinators learned about, and 81.8% considered it necessary for them to take intermediate or higher courses. An organization affiliated with the Korea Dental Hygienists Association was viewed as the best institute to educate dental coordinators, and educational institutes that included a department of dental hygiene was looked upon as the second best one. 68.7% believed that dental coordinators should take an official examination to test their qualifications, and concerning educational subsidy, the largest group of the dentists thought that a certain amount of subsidy should be provided. 2. As for coordinator hiring, the top priority was the impression(look) of applicants(55%), followed by adjustability to existing employees(24.5%) and professional competency(17.3%). As to the route of hiring, 41.4 percent, the largest group, reeducated some of existing employees, and dental hygienists were regarded as the best personnels to serve as a coordinator. Concerning job performance, they put the most emphasis on interpersonal relationship, which was followed by executive ability, impression and career, 58.6% the largest group, believed that dental coordinators should have a three-year or higher career to work at a dental institute. 3. As to working conditions, 75.7%, the largest group, paid dental coordinators based on their job performance, and 23.2%, the second largest group, had their pay equal to that of dental hygienists, 88.9% allowed them to determine their own retirement age. 4. In regard to their perception of dental coordinators, the largest number of the dentists considered it necessary for them to keep receiving education(4.29), and the second largest group felt that they served to enhance the image of dental institutes(4.18). The third largest group thought that they contributed to letting patients more satisfied with the quality of dental services. But they tended not to agree that their turnover rate was low(3.04), and they didn't find them to receive appropriate education, either(3.10). 5. The current major job of coordinators associated with customer services was handling appointments with customers(91.9%), treating unsatisfied customers(85.9%), and controling waiting time(84.8%). Regarding self-management, coordinators directed their energy into having good manners(89.9%), acquiring fundamental dental knowledge(84.8%), and learning how to treat customers(83.8%). Concerning hospital affairs handling, they were most responsible for information desk(87.9%), which was followed by receiving(86.9%). As a result of investigating what type of job the dentists hoped dental coordinators to fulfill in consideration of their career, their age and type of investment, the dentists wanted them the most to speak a foreign language, which belonged to the field of self-management.