• The Journal of Korean Philosophical History
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• no.25
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• pp.71-71
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• 2009

This study aims to provide a theoretical base for making a character education program on "how primary school students to cultivate their own right and good-minded characters." This study consists of three approaches: 1) an integrative approach based on the social and emotional learning, 2) development of integrative programs articulating three key domains directly and indirectly influencing students' character formation - school, family and local community(society), 3) maximum use of the educational institutes' moral education curriculums and the potential curriculums in the surrounding environment. In concrete, by specializing "social awareness and relationship skills" from various social and emotional ones, this study suggests an integrative program for the character education based on the theory of virtue in the Eastern philosophy. To develop such an Eastern philosophy-based integrative program for the cultivation of the social awareness and personal relationship skills, this study applies some virtue items of Eastern Ethics: for examples, 'rectification of the name(正名)' to improve skills for rational choice on the awareness and performance of social roles, 'empathy(忠恕)' to enhance the ability to share another person's feelings and emotions as if they were my own, 'reflect and seek in oneself(反求諸己)' to solve conflicts in peace and self-reflection, 'difficulty with countenance(色難)' to respond to others by understanding their situations and characters, 'select and follow good qualities of others and reform their bad qualities(擇其善者而從之, 其不善者而改之)' to make good results from various forms of personal relationship, and 'keep same respect as at first to old acquaintance(久而敬之)' to maintain good and emotional relationships. In particular, by underlining 'rectification of the name(正名)' and 'reflect and seek in oneself(反求諸己)', this study attempts to develop an alternative integrative program articulating three domains of school, family and local community.

• (The)Study of the Eastern Classic
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• no.73
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• pp.9-33
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• 2018

This paper examines the literary theory of Gollyun(昆侖) Choe, Changdae(崔昌大, 1669-1720). He has authored a variety of works, and his works have been recognized in many literatures. Because of this, studying his literature is a meaningful. The theory of poem creation is as follows. It is the basic poem creationism that expresses the feelings that I experienced and felt as it is. The utility is to multiply and control the artist's feelings through his poem. However, the creative theory of being the best writer is different from this. It must be premised on finding from the heart and studying various books. If these qualities was provided, the words are clear and the meaning is condensed. He distinguished between general works and the best works, and presented their own creative theory and discussed their utility. The theory of prose utility is as follows. He emphasizes the importance of communicating with contemporaries and establishing important things of the day and making them easier to understand, without specifying the morality. This is a thoroughly realistic utility theory. In the classical chinese prose's history, 'Sadal(辭達)' and 'Susa(修辭)' were issues. He transcends the recognition of 'Sadal(辭達)' and 'Susa(修辭)' as zero-sum. In addition, he gives priority to the meaning of the writer and emphasizes self-realization, which is in common with other political soron(少論) writers' theories. When creating prose, simplicity and bizarreness were issues. He emphasizes concise writing. However, it can be realized when a writer with high opinion is aware of the reason and raises the core. Through various sources, he has completely rejected Ming(明) dynasty's former and latter seven master(前後七子). However, he did not exclude their work unilaterally, and recognized the work of Chin-Han dynasty(秦漢) and Dang-Song dynasty(唐宋). This is the same as his father Choiseokjung(崔錫鼎). He recognized Chin-Han dynasty(秦漢) and Dang-Song dynasty(唐宋) equally, and sought a simplified and summarized style.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.17-32
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• 2021

Speaker recognition is generally divided into speaker identification and speaker verification. Speaker recognition plays an important function in the automatic voice system, and the importance of speaker recognition technology is becoming more prominent as the recent development of portable devices, voice technology, and audio content fields continue to expand. Previous speaker recognition studies have been conducted with the goal of automatically determining who the speaker is based on voice files and improving accuracy. Speech is an important sociolinguistic subject, and it contains very useful information that reveals the speaker's attitude, conversation intention, and personality, and this can be an important clue to speaker recognition. The final ending used in the speaker's speech determines the type of sentence or has functions and information such as the speaker's intention, psychological attitude, or relationship to the listener. The use of the terminating ending has various probabilities depending on the characteristics of the speaker, so the type and distribution of the terminating ending of a specific unidentified speaker will be helpful in recognizing the speaker. However, there have been few studies that considered speech in the existing text-based speaker recognition, and if speech information is added to the speech signal-based speaker recognition technique, the accuracy of speaker recognition can be further improved. Hence, the purpose of this paper is to propose a novel method using speech style expressed as a sentence-final ending to improve the accuracy of Korean speaker recognition. To this end, a method called sentence sequencing that generates vector values by using the type and frequency of the sentence-final ending appearing in the utterance of a specific person is proposed. To evaluate the performance of the proposed method, learning and performance evaluation were conducted with a actual drama script. The method proposed in this study can be used as a means to improve the performance of Korean speech recognition service.

• Journal of The Korean Association For Science Education
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• v.40 no.6
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• pp.657-670
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• 2020

The knowledge-information-processing competency is the most essential competency in a knowledge-information-based society and is the most fundamental competency in the new problem-solving ability. Data-driven science inquiry, which emphasizes how to find and solve problems using vast amounts of data and information, is a way to cultivate the problem-solving ability in a knowledge-information-based society. Therefore, this study aims to develop a teaching-learning model and strategy for data-driven science inquiry and to verify the validity of the model in terms of knowledge information processing competency. This study is developmental research. Based on literature, the initial model and strategy were developed, and the final model and teaching strategy were completed by securing external validity through on-site application and internal validity through expert advice. The development principle of the inquiry model is the literature study on science inquiry, data science, and a statistical problem-solving model based on resource-based learning theory, which is known to be effective for the knowledge-information-processing competency and critical thinking. This model is titled "Exploratory Scientific Data Analysis" The model consisted of selecting tools, collecting and analyzing data, finding problems and exploring problems. The teaching strategy is composed of seven principles necessary for each stage of the model, and is divided into instructional strategies and guidelines for environment composition. The development of the ESDA inquiry model and teaching strategy is not easy to generalize to the whole school level because the sample was not large, and research was qualitative. While this study has a limitation that a quantitative study over large number of students could not be carried out, it has significance that practical model and strategy was developed by approaching the knowledge-information-processing competency with respect of science inquiry.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.131-154
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• 2022

Recently, researches on unstructured data analysis have been actively conducted with the development of information and communication technology. In particular, topic modeling is a representative technique for discovering core topics from massive text data. In the early stages of topic modeling, most studies focused only on topic discovery. As the topic modeling field matured, studies on the change of the topic according to the change of time began to be carried out. Accordingly, interest in dynamic topic modeling that handle changes in keywords constituting the topic is also increasing. Dynamic topic modeling identifies major topics from the data of the initial period and manages the change and flow of topics in a way that utilizes topic information of the previous period to derive further topics in subsequent periods. However, it is very difficult to understand and interpret the results of dynamic topic modeling. The results of traditional dynamic topic modeling simply reveal changes in keywords and their rankings. However, this information is insufficient to represent how the meaning of the topic has changed. Therefore, in this study, we propose a method to visualize topics by period by reflecting the meaning of keywords in each topic. In addition, we propose a method that can intuitively interpret changes in topics and relationships between or among topics. The detailed method of visualizing topics by period is as follows. In the first step, dynamic topic modeling is implemented to derive the top keywords of each period and their weight from text data. In the second step, we derive vectors of top keywords of each topic from the pre-trained word embedding model. Then, we perform dimension reduction for the extracted vectors. Then, we formulate a semantic vector of each topic by calculating weight sum of keywords in each vector using topic weight of each keyword. In the third step, we visualize the semantic vector of each topic using matplotlib, and analyze the relationship between or among the topics based on the visualized result. The change of topic can be interpreted in the following manners. From the result of dynamic topic modeling, we identify rising top 5 keywords and descending top 5 keywords for each period to show the change of the topic. Existing many topic visualization studies usually visualize keywords of each topic, but our approach proposed in this study differs from previous studies in that it attempts to visualize each topic itself. To evaluate the practical applicability of the proposed methodology, we performed an experiment on 1,847 abstracts of artificial intelligence-related papers. The experiment was performed by dividing abstracts of artificial intelligence-related papers into three periods (2016-2017, 2018-2019, 2020-2021). We selected seven topics based on the consistency score, and utilized the pre-trained word embedding model of Word2vec trained with 'Wikipedia', an Internet encyclopedia. Based on the proposed methodology, we generated a semantic vector for each topic. Through this, by reflecting the meaning of keywords, we visualized and interpreted the themes by period. Through these experiments, we confirmed that the rising and descending of the topic weight of a keyword can be usefully used to interpret the semantic change of the corresponding topic and to grasp the relationship among topics. In this study, to overcome the limitations of dynamic topic modeling results, we used word embedding and dimension reduction techniques to visualize topics by era. The results of this study are meaningful in that they broadened the scope of topic understanding through the visualization of dynamic topic modeling results. In addition, the academic contribution can be acknowledged in that it laid the foundation for follow-up studies using various word embeddings and dimensionality reduction techniques to improve the performance of the proposed methodology.

• Korean Journal of Culture and Arts Education Studies
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• v.5 no.1
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• pp.97-147
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• 2010

Under the recent trend of globalization, a new proposal on education has not been able to avoid the request for multi-cultural trend. Furthermore, education has been exposed to circumstances which are far different from the previous situations in which global cooperation and intercultural understanding have been more emphasized. 'Educational Nomadism'is a metaphor of creating new value and significance of education. In fact, transnational education which could be a crisis and opportunity at the same time has recently been the mainstream throughout the world. In terms of education, Korea has encountered base hollowing-out in which excessive dependence on the US education and autonomous education coexist. In fact, the world has spent a lot of time and money to have better educational background on a resume through redundant expense by the government and parents. Under this critical situation, it's urgent to change Korea's modern education into a creative educational system in connection with an advanced foreign educational system and further develop the advantage of Korea's education. A parent's investment in his/her child is a support to create new culture as well as an assistance for hope and better future of Korean education. A new direction of parents' education fever that has opened a door to global communitas can stir up infinite potential through which the flow of education fever can be changed to the resources of new civilization. The global cooperation and efforts for communitas means the communication with this world. Through this communication, the culture in which people are forced to zero-sum competition can leap into the education for change of civilization which creates pleasure of self sufficiency and donation.

• The Korean Nurse
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• v.20 no.4 s.112
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• pp.39-49
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• 1981

기존 간호 영역 내 간호는 질적으로, 양적으로 급격히 팽창 확대되어 가고 있다. 많은 나라에서 건강관리체계가 부적절하게 분배되어 있으며 따라서 많은 사람들이 적절한 건강관리를 제공받지 못하고 있어 수준 높은 양질의 건강관리를 전체적으로 확대시키는 것이 시급하다. 혹 건강관리의 혜택을 받는다고 해도 이들 역시 보다 더 양질의 인간적인 간호를 요하고 있는 실정이다. 간호는 또한 간호영역 자체 내에서도 급격히 확대되어가고 있다. 예를들면, 미국같은 선진국가의 건강간호사(Nurse practitioner)는 간호전문직의 새로운 직종으로 건강관리체계에서 독자적인 실무자로 그 두각을 나타내고 있다. 의사의 심한 부족난으로 고심하는 발전도상에 있는 나라들에서는 간호원들에게 전통적인 간호기능 뿐 아니라 건강관리체계에서 보다 많은 역할을 수행하도록 기대하며 일선지방의 건강센터(Health center) 직종에 많은 간호원을 투입하고 있다. 가령 우리 한국정부에서 최근에 시도한 무의촌지역에서 졸업간호원들이 건강관리를 제공할 수 있도록 한 법적 조치는 이러한 구체적인 예라고 할 수 있다. 기존 간호영역내외의 이런 급격한 변화는 Melvin Toffler가 말한 대로 ''미래의 충격''을 초래하게 되었다. 따라서 이러한 역동적인 변화는 간호전문직에 대하여 몇가지 질문을 던져준다. 첫째, 미래사회에서 간호영역의 특성은 무엇인가? 둘째, 이러한 새로운 영역에서 요구되는 간호원을 길러내기 위해 간호교육자는 어떤 역할을 수행해야 하는가? 셋째 내일의 간호원을 양성하는 간호교육자를 준비시키기 위한 실질적이면서도 현실적인 전략은 무엇인가 등이다. 1. 미래사회에서 간호영역의 특성은 무엇인가? 미래의 간호원은 다음에 열거하는 여러가지 요인으로 인하여 지금까지의 것과는 판이한 환경에서 일하게 될 것이다. 1) 건강관리를 제공하는 과정에서 컴퓨터화되고 자동화된 기계 및 기구 등 새로운 기술을 많이 사용할 것이다. 2) 1차건강관리가 대부분 간호원에 의해 제공될 것이다. 3) 내일의 건강관리는 소비자 주축의 것이 될 것이다. 4) 간호영역내에 많은 새로운 전문분야들이 생길 것이다. 5) 미래의 건강관리체계는 사회적인 변화와 이의 요구에 더 민감한 반응을 하게 될 것이다. 6) 건강관리체계의 강조점이 의료진료에서 건강관리로 바뀔 것이다. 7) 건강관리체계에서의 간호원의 역할은 의료적인 진단과 치료계획의 기능에서 크게 탈피하여 병원내외에서 보다 더 독특한 실무형태로 발전될 것이다. 이러한 변화와 더불어 미래 간호영역에서 보다 효과적인 간호를 수행하기 위해 미래 간호원들은 지금까지의 간호원보다 더 광범위하고 깊은 교육과 훈련을 받아야 한다. 보다 발전된 기술환경에서 전인적인 접근을 하기위해 신체과학이나 의학뿐 아니라 행동과학 $\cdot$ 경영과학 등에 이르기까지 다양한 훈련을 받아야 할 필요가 있다. 또한 행동양상면에서 전문직인 답게 보다 진취적이고 표현적이며 자동적이고 응용과학적인 역할을 수행하도록 훈련을 받아야 한다. 그리하여 간호원은 효과적인 의사결정자$\cdot$문제해결자$\cdot$능숙한 실무자일 뿐 아니라 소비자의 건강요구를 예리하게 관찰하고 이 요구에 효과적인 존재를 발전시켜 나가는 연구자가 되어야 한다. 2. 미래의 간호교육자는 어떤 역할을 수행해야 하는가? 간호교육은 전문직으로서의 실무를 제공하기 위한 기초석이다. 이는 간호교육자야말로 미래사회에서 국민의 건강요구를 충족시키기는 능력있는 간호원을 공급하는 일에 전무해야 함을 시사해준다. 그러면 이러한 일을 달성하기 위해 간호교육자는 무엇을 해야 하는가? 우선 간호교육자는 두가지 측면에서 이 일을 수정해야 된다고 본다. 그 하나는 간호교육기관에서의 측면이고 다른 하나는 간호교육자 개인적인 측면엣서이다. 우선 간호교육기관에서 간호교육자는 1) 미래사회에서 요구되는 간호원을 교육시키기 위한 프로그램을 제공해야 한다. 2) 효과적인 교과과정의 발전과 수정보완을 계속적으로 진행시켜야 한다. 3) 잘된 교과과정에 따라 적절한 훈련을 철저히 시켜야 한다. 4) 간호교육자 자신이 미래의 예측된 현상을 오늘의 교육과정에 포함시킬 수 있는 자신감과 창의력을 가지고 모델이 되어야 한다. 5) 연구 및 학생들의 학습에 영향을 미치는 중요한 의사결정에 학생들을 참여시키도록 해야한다. 간호교육자 개인적인 측면에서는 교육자 자신들이 능력있고 신빙성있으며 간호의 이론$\cdot$실무$\cdot$연구면에 걸친 권위와 자동성$\cdot$독창성, 그리고 인간을 진정으로 이해하려는 자질을 갖추도록 계속 노력해야 한다. 3. 미래의 간호원을 양성하는 능력있는 간호교육자를 준비시키기 위한 실질적이면서도 현실적인 전략은 무엇인가? 내일의 도전을 충족시킬 수 있는 능력있는 간호교육자를 준비시키기 위한 실질적이고 현실적인 전략을 논함에 있어 우리나라의 실정을 참조하겠다. 전문직 간호교육자를 준비하는데 세가지 방법을 통해 할 수 있다고 생각한다. 첫째는 간호원 훈련수준을 전문직 실무를 수행할 수 있는 단계로 면허를 높이는 것이고, 둘째는 훈련수준을 더 향상시키기 위하여 학사 및 석사간호교육과정을 발전시키고 확대하는 것이며, 셋째는 현존하는 간호교육 프로그램의 질을 높이는 것이다. 첫째와 둘째방법은 정부의 관할이 직접 개입되는 방법이기 때문에 여기서는 생략하고 현존하는 교과과정을 발전시키고 그 질을 향상시키는 것에 대해서만 언급하고자 한다. 미래의 여러가지 도전에 부응할 수 있는 교육자를 준비시키는 교육과정의 발전을 두가지 면에서 추진시킬 수 있다고 본다. 첫째는 국제간의 교류를 통하여 idea 및 경험을 나눔으로서 교육과정의 질을 높일 수 있다. 서로 다른 나라의 간호교육자들이 정기적으로 모여 생각과 경험을 교환하고 연구하므로서 보다 체계적이고 효과적인 발전체인(chain)이 형성되는 것이다. ICN같은 국제적인 조직에 의해 이러한 모임을 시도하는 것인 가치있는 기회라고 생각한다. 국가간 또는 국제적인 간호교육자 훈련을 위한 교육과정의 교환은 한 나라안에서 그 idea를 확산시키는데 효과적인 영향을 미칠 수 있다. 충분한 간호교육전문가를 갖춘 간호교육기관이 새로운 교육과정을 개발하여 그렇지 못한 기관과의 연차적인 conference를 가지므로 확산시킬 수도 있으며 이런 방법은 경제적인 면에서도 효과적일 뿐만 아니라 그 나라 그 문화상황에 적합한 교과과정 개발에도 효과적일 수 있다. 간호교육자를 준비시키는 둘째전략은 현존간호교육자들이 간호이론과 실무$\cdot$연구를 통합하고 발전시키는데 있어서 당면하는 여러가지 요인-전인적인 간호에 적절한 과목을 이수하지 못하고 임상실무경험의 부족등-을 보충하는 방법이다. 이런 실제적인 문제를 잠정적으로 해결하기 위하여 1) 몇몇 대학에서 방학중에 계속교육 프로그램을 개발하여 현직 간호교육자들에게 필요하고 적절한 과목을 이수하도록 한다. 따라서 임상실무교육도 이때 실시할 수 있다. 2) 대학원과정 간호교육프로그램의 입학자의 자격에 2$\~$3년의 실무경험을 포함시키도록 한다. 결론적으로 교수와 학생간의 진정한 동반자관계는 자격을 구비한 능력있는 교수의 실천적인 모델을 통하여서 가능하게 이루어 질수 있다고 믿는 바이다.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.73-95
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• 2021

This study uses Node2vec graph embedding method and Light GBM link prediction to explore undeveloped export candidate countries in Korea's food and beverage industry. Node2vec is the method that improves the limit of the structural equivalence representation of the network, which is known to be relatively weak compared to the existing link prediction method based on the number of common neighbors of the network. Therefore, the method is known to show excellent performance in both community detection and structural equivalence of the network. The vector value obtained by embedding the network in this way operates under the condition of a constant length from an arbitrarily designated starting point node. Therefore, it has the advantage that it is easy to apply the sequence of nodes as an input value to the model for downstream tasks such as Logistic Regression, Support Vector Machine, and Random Forest. Based on these features of the Node2vec graph embedding method, this study applied the above method to the international trade information of the Korean food and beverage industry. Through this, we intend to contribute to creating the effect of extensive margin diversification in Korea in the global value chain relationship of the industry. The optimal predictive model derived from the results of this study recorded a precision of 0.95 and a recall of 0.79, and an F1 score of 0.86, showing excellent performance. This performance was shown to be superior to that of the binary classifier based on Logistic Regression set as the baseline model. In the baseline model, a precision of 0.95 and a recall of 0.73 were recorded, and an F1 score of 0.83 was recorded. In addition, the light GBM-based optimal prediction model derived from this study showed superior performance than the link prediction model of previous studies, which is set as a benchmarking model in this study. The predictive model of the previous study recorded only a recall rate of 0.75, but the proposed model of this study showed better performance which recall rate is 0.79. The difference in the performance of the prediction results between benchmarking model and this study model is due to the model learning strategy. In this study, groups were classified by the trade value scale, and prediction models were trained differently for these groups. Specific methods are (1) a method of randomly masking and learning a model for all trades without setting specific conditions for trade value, (2) arbitrarily masking a part of the trades with an average trade value or higher and using the model method, and (3) a method of arbitrarily masking some of the trades with the top 25% or higher trade value and learning the model. As a result of the experiment, it was confirmed that the performance of the model trained by randomly masking some of the trades with the above-average trade value in this method was the best and appeared stably. It was found that most of the results of potential export candidates for Korea derived through the above model appeared appropriate through additional investigation. Combining the above, this study could suggest the practical utility of the link prediction method applying Node2vec and Light GBM. In addition, useful implications could be derived for weight update strategies that can perform better link prediction while training the model. On the other hand, this study also has policy utility because it is applied to trade transactions that have not been performed much in the research related to link prediction based on graph embedding. The results of this study support a rapid response to changes in the global value chain such as the recent US-China trade conflict or Japan's export regulations, and I think that it has sufficient usefulness as a tool for policy decision-making.