• Journal of Biomedical Engineering Research
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• v.42 no.3
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• pp.100-106
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• 2021

Measuring Intima-media thickness (IMT) with ultrasound images can help early detection of coronary artery disease. As a result, numerous machine learning studies have been conducted to measure IMT. However, most of these studies require several steps of pre-treatment to extract the boundary, and some require manual intervention, so they are not suitable for on-site treatment in urgent situations. in this paper, we propose to use deep learning networks U-Net, Attention U-Net, and Pretrained U-Net to automatically segment the intima-media complex. This study also applied the HE, HS, and CLAHE preprocessing technique to wireless portable ultrasound diagnostic device images. As a result, The average dice coefficient of HE applied Models is 71% and CLAHE applied Models is 70%, while the HS applied Models have improved as 72% dice coefficient. Among them, Pretrained U-Net showed the highest performance with an average of 74%. When comparing this with the mean value of IMT measured by Conventional wired ultrasound equipment, the highest correlation coefficient value was shown in the HS applied pretrained U-Net.

• Smart Media Journal
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• v.10 no.4
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• pp.21-27
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• 2021

Recently, the importance of counseling is increasing due to the Corona Blue caused by COVID-19. Also, with the increase of non-face-to-face services, researches on chatbots that have changed the counseling media are being actively conducted. In non-face-to-face counseling through chatbot, it is most important to accurately understand the client's emotions. However, since there is a limit to recognizing emotions only in sentences written by the client, it is necessary to recognize the dimensional emotions embedded in the sentences for more accurate emotion recognition. Therefore, in this paper, the vector and sentence VAD (Valence, Arousal, Dominance) generated by learning the Word2Vec model after correcting the original data according to the characteristics of the data are learned using a deep learning algorithm to learn the multi-dimensional We propose an emotion recognition model. As a result of comparing three deep learning models as a method to verify the usefulness of the proposed model, R-squared showed the best performance with 0.8484 when the attention model is used.

• Journal of the Korea Society of Computer and Information
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• v.28 no.3
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• pp.67-73
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• 2023

Under the influence of COVID-19, as a measure of social distancing for about two years and one month, non-face-to-face services using ICT element technology are expanding not only to the education sector but to all fields. In particular, as educational programs using the Metaverse platform spread to various fields, educators, and learners have more learning experiences using Edutech, but problems through non-face-to-face learning such as reduced immersion or concentration in education are raising In this paper, to overcome the problems raised through non-face-to-face learning and develop metaverse immersive media digital contents to improve the educational environment, we utilize VR (Virtual Reality) based on an immersive metaverse to provide education / Training contents and the educational environment was established. In this paper, we presented a system to increase immersion and concentration in educational contents in a virtual environment using HMD (Head Mounted Display) for learners who are put into military education/training. Immersion was further improved.

• Journal of Internet Computing and Services
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• v.9 no.6
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• pp.141-153
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• 2008

E-learning is a new paradigm of education using Internet media. E-learning is rapidly expanding, since it is not restricted by time and space. However, due to the lack of standardization in e-learning, learning contents are developed redundantly. SCORM has been proposed to address this standardization problems. The mere learning contents are shared, the higher the reusability of contents becomes. Therefore, it is needed to develop methods or tools to help educators or content producers to create a learning course easily. In this paper, we propose an association method that could help educators or content producers to efficiently generate learning courses for a subject. The association method, a learning course generation method suggested by this paper, makes use of existing learning courses and learning contents to create new learning courses suitable to a subject. The association method analyzes statistical information of leaning objects derived from existing learning courses and measures coherence between learning objects to create a learning course. The association method suggested by this paper not only supports educators or content producers for easy generation of learning course but also offers a guideline for developing learning courses.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.12
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• pp.5486-5492
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• 2011

This paper presents a model of ubiquitous learning environment system based on the concepts of ubiquitous computing technology that enables learning to take place anywhere at anytime. This ubiquitous learning environment is described as an environment-friendly learning scheme that supports students' learning using digital media in geographically distributed environments. The u-learning model is a web-based e-learning system that could enable learners to acquire knowledge and skills through interaction between them and the ubiquitous learning environment. Education is happening all around the student but the student may not even be conscious of the learning process. Source data is present in the embedded objects and students do not have to do anything in order to learn. The communication between devices and the embedded computers in the environment allows learners to learn in an environment of their interest while they are moving, hence, attaching them to their learning environment.

• Journal of Korean Library and Information Science Society
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• v.48 no.3
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• pp.131-152
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• 2017

The purpose of this study was to investigate the relationship between media richness, media usefulness, media experience and media decision in order to identify factors that determine the media of school library in solving performance evaluation tasks. For this purpose, 132 primary and middle school students were surveyed and their structural equation was set up by hypothesis setting, validity test, and causal model. As a result, it was confirmed that media experience of school library is a major factor in media decision. Also, media richness and media experience appeared to influence media decision through media usefulness. The analysis implies that school library is centered on teaching - learning process and evaluation, so information literacy education should be carried out in school curriculum and school library is required to provide students experience on media as the center of school education.

• Journal of the Korean Society for Library and Information Science
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• v.39 no.4
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• pp.163-175
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• 2005

I identified constructivism's teaching-learning theory as a modern ideal method of education on this paper. And I explained how school media center relate with constructivism on educational method and educational environment. I suggested what is the points of development of school media center under the educational method of constructivism. And then by doing so I strived for contribution to the solution of problems of school education in Korea.

• International journal of advanced smart convergence
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• v.2 no.2
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• pp.7-9
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• 2013

Current physics-based simulation is an important tool in the fluid animation. However some problems require a new change to current research trends which depend only on the simulation. The ultimate goal of this project is to obtain information of flow example, analyze an example through machine learning and the novel fluid animation reconfigure without physical simulation.

• Broadcasting and Media Magazine
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• v.22 no.1
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• pp.91-102
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• 2017

비디오 정보를 자동으로 학습하고 관련 문제를 해결하기 위해서는, 비디오의 기본 구성요소인 영상, 음성, 언어 정보의 학습을 기반으로 고차원의 추상적 개념을 파악하는 기술이 필수적이다. 최근 딥러닝이 실용적인 수준으로 이러한 기술을 가능하게 함에 따라, 보다 도전적인 비디오 스토리 분석과 이해 문제 해결을 시도할 수 있게 되었다. 본 고에서는 비디오의 요소별 분석에 적용 가능한 최신 딥러닝 기술을 소개하고, 딥러닝 기술을 핵심으로 한 TV 드라마의 스토리 분석 사례를 살펴본다.

• Smart Media Journal
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• v.2 no.4
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• pp.20-26
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• 2013

This paper presents an approach to Mongolian car plate recognition using artificial neural network. Our proposed method consists of two steps: detection and recognition. In detection step, we implement Flood fill algorithm. In recognition step we proceed to segment the plate for each Cyrillic character, and use an Artificial Neural Network (ANN) machine - learning algorithm to recognize the character. We have learned the theory of ANN and implemented it without using any library. A total of 150 vehicles images obtained from community entrance gates have been tested. The recognition algorithm shows an accuracy rate of 89.75%.