• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.145-147
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• 2004

본 논문에서는 무선인터넷 환경에 적합한 개인화된 상품추천에이전트를 제안한다. 기존에 유선인터넷상의 많은 개인화 추천시스템에서는 초기 사용자 모델링을 위해 사용자에게 수많은 질의를 하고 응답을 요구하였다. 그러나 이러한 방식은 무선인터넷 환경에서 정보 전송량에 따른 높은 사용요금을 고려할 때 적용하기 힘든 방식이다. 본 제안 시스템은 사용자의 Social data률 이용하여 사용자를 비슷한 연령과 성별 그룹으로 나누고, 해당 그룹에서 구매율이 높은 상품을 우선 제시한 후, 사용자 행동을 모니터링 하여 암시적(Implicit)피드백을 통해 프로파일을 생성함으로써, 번거로운 질의-응답 과정 없이도 초기 사용자 모델링을 수행할 수 있다. 프로파일 생성 이후에는 이를 기반으로 하여 사용자몰 유사한 취향을 가진 그룹으로 다시 군집화한 후 협력적 추천을 하게 되며, 프로파일에는 해당 상품의 최종 카테고리명과 키워드를 수집함으로써, 상품의 브랜드와 규격정보를 반영한 추천이 가능하다. 또한 추천 상품과 사용자의 구매데이터와의 비교를 수행하여 사용자가 해당상품을 구매하였을 경우, 상품에 대한 취향정보는 그대로 유지하고 관련 상품을 추천하되, 구매한 상품이 중복 추천되지 않도록 하였다. 시스템 평가를 위해 프로토타입을 구현하여, 다수의 사용자에게 시스템을 이용하며 관심품목을 체크하도록 하였고. 추천횟수가 반복되며 히트율이 증가하는 결과를 통해 시스템의 학습속도와 성능을 평가하였다. 그리고 쇼핌몰에서 구매경험이 있는 사용자의 기존 구매데이터와 Social data를 이용한 초기 제시상품을 역으로 비교하여 오랜 시간과 비용 발생 없이도 초기 프로파일 생성의 유효성을 증명하였다. 포함하는 XML 질의에 대해서도 웹에서 캐쉬를 이용한 처리가 효율적임을 확인하였다.키는데 목적이 있다.RED에 비해 향상된 성능을 보여주었다.웍스 네트워크상의 다양한 디바이스들간의 네트워크 다양화와 분산화 기능을 얻을 수 있었고, 기존의 고가의 해외 솔루션인 Echelon사의 LonMaker 소프트웨어를 사용하지 않고도 국내의 순수 솔루션인 리눅스 기반의 LonWare 3.0 다중 바인딩 기능을 통해 저 비용으로 홈 네트워크 구성 관리 서버 시스템 개발에 대한 비용을 줄일 수 있다. 기대된다.e 함량이 대체로 높게 나타났다. 점미가 수가용성분에서 goucose대비 용출함량이 고르게 나타나는 경향을 보였고 흑미는 알칼리가용분에서 glucose가 상당량(0.68%) 포함되고 있음을 보여주었고 arabinose(0.68%), xylose(0.05%)도 다른 종류에 비해서 다량 함유한 것으로 나타났다. 흑미는 총식이섬유 함량이 높고 pectic substances, hemicellulose, uronic acid 함량이 높아서 콜레스테롤 저하 등의 효과가 기대되며 고섬유식품으로서 조리 특성 연구가 필요한 것으로 사료된다.리하였다. 얻어진 소견(所見)은 다음과 같았다. 1. 모년령(母年齡), 임신회수(姙娠回數), 임신기간(姙娠其間), 출산시체중등(出産時體重等)의 제요인(諸要因)은 주산기사망(周産基死亡)에 대(對)하여 통계적(統計的)으로 유의(有意)한 영향을 미치고 있어 $25{\sim}29$세(歲)의 연령군에서, 2번째 임신과 2번째의 출산에서 그리고 만삭의 임신 기간에, 출산시체중(出産時體重) $3.50{\sim}3.99kg$사이의 아

• Journal of The Korean Association For Science Education
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• v.39 no.4
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• pp.479-488
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• 2019

The purpose of this research is to derive competencies necessary for students with future convergent STEAM talents, and to explore ideal student images, teaching-learning strategies, evaluation methods, and teachers' competencies and their training methods for future schools developing students' competencies. In order to figure out the features of the future schools, 25 experts from related fields, including in-service teachers, administrators, and college students in science and technology, participated in a future workshop. According to the results, students with future convergent science and technology talents are expected to have flexible thinking and creative thinking competencies to solve problems in innovative ways rather than traditional ways. In other words, it takes the power to accept and accommodate unexpected situations and solve problems appropriately in those situations. To cultivate such competencies, therefore, future schools should also be flexible and proactive. Rigid schools delivering knowledge-based information make it impossible to cultivate flexible and creative talents. Future schools should change into leaner-centered project-based classes so that students can naturally cope with various situations and solve large and small problems, and prepare assessment systems that can provide feedback based on the student's performances rather than achievement standards.

• Journal of Science Education
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• v.45 no.2
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• pp.172-186
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• 2021

The purpose of this study is to analyze the science lesson plan of pre-service elementary teachers about condensation. Pre-service elementary school teachers in A national university of education was included in this study. Through the analysis of prior research and expert review, a framework for analysis of science lesson plan of pre-service elementary teachers was derived. The results of the using the analysis frame are as follows: First, the ability to apply the instructional model in the science lesson plan about condensation differences in pre-service elementary teachers need to be enhanced due to deviations, and teaching on the exact understanding of condensation-related concepts of pre-service elementary teachers is also needed. Second, there is also a deviation of pre-service elementary teachers in the beginning, development, and finishing composition of lesson course, so feedback should be supplemented. Third, in the sub-domain of lesson environment, there was a demand for specific know-how on the lesson environment. Therefore, support is needed for related PCK growth. Fourth, the sub-domain of lesson evaluation have a variety of perspectives on timing and subjects, and some missing about learning objectives in the composition of evaluation content are found to require complementary teaching. In order to improve this situation, it was found that there was a need to prepare conditions for improving science teaching professionalism of pre-service elementary teachers through in-depth discussions on the teaching methods and organization related to science education in the university of education course.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.2
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• pp.750-762
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• 2019

The importance of the call center as a contact point for the enterprise is growing. However, call centers have difficulty with their operating agents due to the agents' lack of knowledge and owing to frequent agent turnover due to downturns in the business, which causes deterioration in the quality of customer service. Therefore, through an N-bank call center case study, we developed a system to reduce the burden of keeping up business knowledge and to improve customer service quality. It is a "real-time agent advisor" system that provides agents with answers to customer questions in real time by combining AI technology for speech recognition, natural language processing, and questions & answers for existing call center information systems, such as a private branch exchange (PBX) and computer telephony integration (CTI). As a result of the case study, we confirmed that the speech recognition system for real-time call analysis and the corpus construction method improves the natural speech processing performance of the query response system. Especially with name entity recognition (NER), the accuracy of the corpus learning improved by 31%. Also, after applying the agent advisor system, the positive feedback rate of agents about the answers from the agent advisor was 93.1%, which proved the system is helpful to the agents.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.65-70
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• 2019

The purpose of this study is to understand the college students' needs for software curriculum which based on surveys from educational satisfaction of the software lecture evaluation, as well as to find out the improvement plan by applying the text content analysis method. The research method used the text content analysis program to calculate the frequency of words occurrence, key words selection, co-occurrence frequency of key words, and analyzed the text center and network analysis by using the network analysis program. As a result of this research, the decent points of the software education network are mentioned with 'lecturer' is the most frequently occurrence after then with 'kindness', 'student', 'explanation', 'coding'. The network analysis of the shortage points has been the most mention of 'lecture', 'wish to', 'student', 'lecturer', 'assignment', 'coding', 'difficult', and 'announcement' which are mentioned together. The comprehensive network analysis of both good and shortage points has compared among key words, we can figure out difference among the key words: for example, 'group activity or task', 'assignment', 'difficulty on level of lecture', and 'thinking about lecturer'. Also, from this difference, we can provide that the lack of proper role of individual staff at group activities, difficult and excessive tasks, awareness of the difficulty and necessity of software education, lack of instructor's teaching method and feedback. Therefore, it is necessary to examine not only how the grouping of software education (activities) and giving assignments (or tasks), but also how carried out group activities and tasks and monitored about the contents of lectures, teaching methods, the ratio of practice and design thinking.

• Korean Journal of Comparative Education
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• v.28 no.5
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• pp.21-46
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• 2018

This study examines the characteristics of teacher education system and professional standards of teachers in Canada through analysis of the current teacher education curriculum and salary grids of teachers in Canada. As a result, the following characteristics were found. First, contents and theories acquired during the course of teacher education are connected to the actual practice to increase the site-compatibility. Second, professional standards of teachers is rather holistic, than detailed and systematic. Based on the findings, the following implication can be drawn. To enhance the site compatibility of teachers in the Republic of Korea, it is requisite to build a persistent, and cooperative relationship among the faculty members of teacher education program, the members of the community, and supervisor teachers of practicum schools. Also, it is necessary to come up with a system that directly connects the professionalism of the teachers and the salary grids, as the salary of teachers are adjusted according to the completion of degree or courses, reflecting the professionalism.

• Journal of Science Education
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• v.42 no.3
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• pp.334-351
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• 2018

Teacher's gaze empathy for students in science class is considered to be effective in enhancing the learning effect. Thus, studies on gaze empathy have been conducted, but most of the studies are just to reveal the characteristics of gaze. Therefore, it is necessary to deal with a research to raise the level of science teacher's gaze empathy. The purpose of this study is to develop an instruction consulting strategy based on eye tracking for improving science teachers' gaze empathy. In this study, we selected and analyzed relevant literature on teacher's gaze empathy. We also designed a consulting strategy and then revised the design through expert reviews on validity and reliability. The developed consulting strategy was aimed to improve science teacher's gaze empathy and set quantitative goal based on eye tracking. The consulting strategy consisted of six steps: preparation for consulting, measurement and analysis of teacher's gaze empathy, instruction and feedback of gaze empathy, training for improving gaze empathy, evaluation of consulting result, and completion of the consulting. In addition, the consultation was completed or repeated again through the measurement and evaluation of gaze empathy using eye tracking. The developed consulting strategy has a value in that it provides an alternative with quantitative diagnosis and prescription for improving gaze empathy. The strategy can contribute to enhance teacher professional competency through the analysis of teaching behavior.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.6
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• pp.33-45
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• 2020

This paper aims to look at the perspective that the latest cutting-edge technologies are predicting individual diseases in the actual medical environment in a situation where various types of wearable devices are rapidly increasing and used in the healthcare domain. Through the process of collecting, processing, and transmitting data by merging clinical data, genetic data, and life log data through a user-participating wearable device, it presents the process of connecting the learning model and the feedback model in the environment of the Deep Neural Network. In the case of the actual field that has undergone clinical trial procedures of medical IT occurring in such a high-tech medical field, the effect of a specific gene caused by metabolic syndrome on the disease is measured, and clinical information and life log data are merged to process different heterogeneous data. That is, it proves the objective suitability and certainty of the deep neural network of heterogeneous data, and through this, the performance evaluation according to the noise in the actual deep learning environment is performed. In the case of the automatic encoder, we proved that the accuracy and predicted value varying per 1,000 EPOCH are linearly changed several times with the increasing value of the variable.

• Journal of Korea Entertainment Industry Association
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• v.14 no.8
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• pp.501-511
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• 2020

This study investigated and analyzed the contents of writing learning, self-evaluation of writing ability, recognition of writing ability, and recognition of writing education direction to J university students in order to analyze the perception of writing of university students and find ways to improve writing education. Through this, the improvement plan of writing education was discussed. As a result of researching and analyzing the perceptions of university students, college students perceived writing ability as important, and they wanted practical writing classes that received feedback and wrote actual writing rather than theoretical classes. In addition, it was found that they wanted to develop their ability to construct and develop the contents of the article. In order to make writing education a practical competency for college students, theoretical lectures are important, but it is necessary to give enough time and opportunity to write in practice, and to develop customized practical writing. Also, it is necessary to make writing class that students can participate through various teaching methods, and to make writing ability lead to practical competence even after graduation through the method of university graduation certification requirements. This study is meaningful in that it can seek the direction of university writing education through the recognition of college students related to writing.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.6
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• pp.1137-1144
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• 2022

In this study, an artificial intelligence(AI) was developed to help with facial expression practice in order to express emotions. The developed AI used multimodal inputs consisting of sentences and facial images for deep neural networks (DNNs). The DNNs calculated similarities between the emotions predicted by the sentences and the emotions predicted by facial images. The user practiced facial expressions based on the situation given by sentences, and the AI provided the user with numerical feedback based on the similarity between the emotion predicted by sentence and the emotion predicted by facial expression. ResNet34 structure was trained on FER2013 public data to predict emotions from facial images. To predict emotions in sentences, KoBERT model was trained in transfer learning manner using the conversational speech dataset for emotion classification opened to the public by AIHub. The DNN that predicts emotions from the facial images demonstrated 65% accuracy, which is comparable to human emotional classification ability. The DNN that predicts emotions from the sentences achieved 90% accuracy. The performance of the developed AI was evaluated through experiments with changing facial expressions in which an ordinary person was participated.