• Journal of Industrial Convergence
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• v.17 no.3
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• pp.39-49
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• 2019

This study, as a study on building platforms for smart campus ecosystem, took an approach that reflected the needs of various stakeholders of smart campus, and focused on functions to help them strengthen their competitiveness and advance into society by focusing on the learning of the most important university student users, college life, and social connection. First, we looked at the theories related to smart campus construction through prior research, and next, through domestic and international environmental analysis and trend analysis, we designed and presented a target model for e-portfolio focusing on core competency development and support system for Industry-Academic Cooperation, and proposed the main point for continuous smart campus development model.

• Journal of the Korea Convergence Society
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• v.12 no.9
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• pp.99-111
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• 2021

This study confirms whether interaction and satisfaction between educators and learners can be repeated as artistic activities in art education and compares online and offline differences. And it suggests ways to enhance the effectiveness of online art education. As a method of research, literature analysis shall be conducted on art education, educational and social interaction, satisfaction, and behavioral intent. Two surveys were conducted on online and offline education for music and art students who completed art education lectures. As a result, 89 online and 56 offline students participated. The higher the satisfaction level of educational and social interaction in art education, the more it led to artistic activities. Educational interaction in online art education was higher, social interaction was lower, and it was different from offline.

• Communications of Mathematical Education
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• v.35 no.3
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• pp.323-340
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• 2021

The purpose of this case study is to explore the similarities revealed in the process of solving and generalizing word problems related to systems of linear equations in two variables according to covariational reasoning. As a result, student S, who reasoned with coordination of value level, had a static image of the quantities given in the situation. student D, who reasoned with smooth continuous covariation level, had a dynamic image of the quantities in the problem situation and constructed an invariant relationship between the quantities. The results of this study suggest that the activity that constructs the relationship between the quantities in solving word problems helps to strengthen the mathematical problem solving ability, and that teaching methods should be prepared to strengthen students' covariational reasoning in algebra learning.

• Journal of Internet Computing and Services
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• v.20 no.2
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• pp.93-100
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• 2019

Recently, in various business fields, companies are concentrating on providing chatbot services to various environments by adding artificial intelligence to existing messenger platforms. Organizations in the field of job placement also require chatbot services to improve the quality of employment counseling services and to solve the problem of agent management. A text-based general chatbot classifies input user sentences into learned sentences and provides appropriate answers to users. Recently, user sentences inputted to chatbots are inputted as short texts due to the activation of social network services. Therefore, performance improvement of short text classification can contribute to improvement of chatbot service performance. In this paper, we propose T-EBOW (Translation-Extended Bag Of Words), which is a method to add translation information as well as concept information of existing researches in order to strengthen the short text classification for employment chatbot. The performance evaluation results of the T-EBOW applied to the machine learning classification model are superior to those of the conventional method.

• Journal of The Korean Association of Information Education
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• v.25 no.2
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• pp.265-277
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• 2021

With the development of technology, the concept of digital literacy is expanding from the focus of function and tool utilization to the extent of communication and participation in social and cultural contexts. In particular, learners' digital literacy capabilities are more important and necessary in remote learning environments such as Corona19. In this study, we studied how to improve digital literacy education through analysis and inspection of digital literacy shown in elementary school textbooks. To this end, we analyze it through compliance consisting of 8 fundamental pieces of knowledge, 20 sub technical skills, and 10 keys of competencies that constitute digital literacy. As a result of the study, the contents of digital literacy education in elementary school textbooks were presented centered on functions and tools, and as they were biased in certain areas, they were found to be lacking in systematicity and connectivity. Therefore, it proposed the composition of the curriculum system of digital literacy through the independence of elementary informatics curriculum, the specific composition of curriculum, and the strengthening of pre-service teachers' practical skills.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.5
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• pp.619-627
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• 2021

Recent advance in low cost and light-weight drones has extended their application areas in both military and private sectors. Accordingly surveillance program against unfriendly drones has become an important issue. Drone detection and classification technique has long been emphasized in order to prevent attacks or accidents by commercial drones in urban areas. Most commercial drones have small sizes and low reflection and hence typical sensors that use acoustic, infrared, or radar signals exhibit limited performances. Recently, artificial intelligence algorithm has been actively exploited to enhance radar image identification performance. In this paper, we adopt machined learning algorithm for high resolution radar imaging in drone detection and classification applications. For this purpose, simulation is carried out against commercial drone models and compared with experimental data obtained through high resolution radar field test.

• The Journal of the Convergence on Culture Technology
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• v.8 no.1
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• pp.285-290
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• 2022

The 21st century of the 4th industrial revolution demands 'competency' as a new educational concept that is different from that required in the industrialization era. In accordance with these changes and demands of society, universities are being called for key competency-based education and innovation in education through this by breaking away from the existing methods in liberal arts and major education. At this point, universities are presenting a comprehensive reform of liberal arts education for various financial support projects. This study presents the case of University C regarding the reform of the liberal arts curriculum for the innovation of liberal arts education in universities. According to the research results, each university is reorganizing the liberal arts curriculum in a way that can suggest various key competencies according to the university's founding philosophy and induce key competencies in the aspect of liberal arts education. For the key competency-based liberal arts curriculum of University C, we proposed various subjects for insufficient key competency subjects, various micro-degrees were proposed to specialize liberal arts education, and meta-learning-related liberal arts subjects were presented to improve basic learning ability of the students.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1835-1845
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• 2021

To accurately identify black ice and warn the drivers of information in advance so they can control speed and take preventive measures. In this paper, we propose a lightweight black ice detection network based on infrared road images. A black ice recognition network model based on CNN transfer learning has been developed. Additionally, to further improve the accuracy of black ice recognition, an enhanced lightweight network based on MobileNetV2 has been developed. To reduce the amount of calculation, linear bottlenecks and inverse residuals was used, and four bottleneck groups were used. At the same time, to improve the recognition rate of the model, each bottleneck group was connected to a 3×3 convolutional layer to enhance regional feature extraction and increase the number of feature maps. Finally, a black ice recognition experiment was performed on the constructed infrared road black ice dataset. The network model proposed in this paper had an accurate recognition rate of 99.07% for black ice.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.537-543
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• 2021

The purpose of this study was to investigate the relative importance of preliminary physical education teachers between upper and lower levels. Therefore, after literature analysis and examination by experts, a model of competence should be developed by preliminary physical education teachers. Literature review was done at first to filter out the related factors from previous studies. analytic hierarchy process (AHP) was followed with other 23 experts. Results of the study is as follows: Competence for Personal Relations is placed at the top with the weight of .213, competence for Self Management follows with the weight of .203, competence for Major is placed at third with the weight of .174, competence for Studies & Liberal follows with the weight of .163, and competence for Sense of Challenge is placed with the weight of .137, competence for Creativity follows with the weight of .110.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.198-198
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• 2021

최근 자연적, 사회적, 정책적 관점에서 하천관리의 중요성이 증대되면서 국가하천 정비를 통한 하천시설 관리의 책임이 증대되고 있다. 국가하천 5대강 본류의 친수지구 이용도 변화를 살펴보면 2015년에 비해 2019년에 면적당 이용객 수가 630,813(명/km²)이 증가하였음을 알 수 있었고(국토교통부, 2020) 본 연구에서는 이용자 수 증가율이 높은 편인 한강 내 하천이용시설을 대상으로 선정하여 해당 지역을 기계학습 기반의 수위예측 알고리즘에 적용하였다. 하천이용시설은 하천이용자가 편리하게 하천을 이용하기 위하여 설치한 시설로 공원시설(강서, 난지, 양화, 망원, 여의도, 이촌, 반포, 잠원, 뚝섬, 잠실, 광나루, 구리)을 위주로 분석하였다. 해당 시설의 침수피해를 고려하기 위해 시계열 자료에 특화된 LSTM(Long Short-term Memory)기법을 활용하여 수위예측 알고리즘을 개발하였고 이를 통해 도출된 홍수 예보로 재난을 대비하고 시설물을 체계적으로 관리하는 유지관리의 효과를 분석하고자 하였다. 입력 자료(input data)는 수위 (EL.m), 팔당댐 방류량 (m³/s), 강화대교의 조위(EL.m)를 사용하였으며 수위예측 알고리즘을 통해 6시간 후 예측 수위값을 도출하여 기존 2단계(주의보, 경보)였던 홍수 예보 단계에서 4단계(관심, 보행자통제, 차량통제, 경계)로 구축하였다. 기존과 세분화된 홍수예보를 적용했을 경우의 유지관리 비용과 편익을 산정하여 하천이용시설의 경제성을 비교·분석한 결과, 유지관리 비용이 기존 대비 약 5% 이상 절감되었고 편익은 약 1.5배 이상 증가하였으며 관리등급은 평균 C등급(보통) 이상 달성하였다. 이는 수위예측 알고리즘의 적용으로 하천이용 활성화 및 투자의 효율성에 목적을 두었으며 향후 분석결과를 토대로 경제성모델을 개발하여 국가하천 내 관리그룹에 적용하면 효율적인 유지관리체계를 제시할 수 있을 것으로 기대된다.