• Journal of Korea Entertainment Industry Association
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• v.13 no.3
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• pp.193-202
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• 2019

This study focuses on what changes are required as to a curriculum of dance department in the university in the age of the 4th industrial revolution. By comparing and analyzing the curricula of dance department in the five universities in Seoul, five academic subjects as to curricula of dance department, which covers what to learn for dance education in the age of the 4th industrial revolution, are presented. First, dance integrative education, the integration of creativity and science education, can be referred to as a subject that stimulates ideas and creativity and raises artistic sensitivity based on STEAM. Second, the curriculum characterized by prediction of the future prospect through Big Data can be utilized well in dealing with dance performance, career path of dance-majoring people, and job creation by analyzing public opinion, evaluation, and feelings. Third, video education. Seeing the images as modern major media tends to occupy most of the expressive area of art, dance by dint of video enables existing dance work to be created as new form of art, expanding dance boundaries in academic and performing art viewpoint. Fourth, VR and AR are essential techniques in the era of smart media. Whether upcoming dance studies are in the form of performance or education or industry, for VR and AR to be digitally applied into every relevant field, keeping with the time, learning about VR and AR is indispensable. Last, the 4th industrial revolution and the curriculum of dance art are needed to foresee the changes in the 4th industrial revolution and to educate changes, development and seeking in dance curriculum.

• Journal of Korea Water Resources Association
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• v.56 no.6
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• pp.403-417
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• 2023

In this research, a methodology was developed for constructing an appropriate rainfall image database for estimating rainfall intensity based on CCTV video. The database was constructed in the Large-Scale Climate Environment Chamber of the Korea Conformity Laboratories, which can control variables with high irregularity and variability in real environments. 1,728 scenarios were designed under five different experimental conditions. 36 scenarios and a total of 97,200 frames were selected. Rain streaks were extracted using the k-nearest neighbor algorithm by calculating the difference between each image and the background. To prevent overfitting, data with pixel values greater than set threshold, compared to the average pixel value for each image, were selected. The area with maximum pixel variability was determined by shifting with every 10 pixels and set as a representative area (180×180) for the original image. After re-transforming to 120×120 size as an input data for convolutional neural networks model, image augmentation was progressed under unified shooting conditions. 92% of the data showed within the 10% absolute range of PBIAS. It is clear that the final results in this study have the potential to enhance the accuracy and efficacy of existing real-world CCTV systems with transfer learning.

• The Journal of the Korea Contents Association
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• v.14 no.4
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• pp.522-533
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• 2014

The capability of the digital communication would need to be strengthened for leveraging collaborative knowledge building and problem solving skills of the middle aged people. It was developed and implemented a smart learning model by utilizing the formative intervention based on the logic of change laboratory to target learners of 'K organization', As a results, smart learning model was composited several activities and supporting systems such as learning instructions of Smart Pad, communication games and SNS, using self-diagnosis and making posters and role-playing video by the internet applications. This research is significant that it finds efficient method to fit design of smart learning and the needs of target learners by using them as testbed which is mixed with different background and digital communication experiences.

• Journal of Digital Contents Society
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• v.8 no.3
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• pp.289-300
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• 2007

Recently, the number of People who want to study by online has been gradually increased. In addition, people's desire is increasing that represents their special knowledge and personality with new paradigm of UCC(User Created Contents). Most of the educational web-sites offer currently boring and unified educational contents without interesting objects. Therefore I want to solve these problems of existing online educational web-sites and I strongly propose the method of design to make the place educational and useful that everyone can enjoy and manifest the user's dispositions. On this study, it's possible to make pleasant environment and improve educational effects on cyber space by designing it in accordance with the individual tastes which have various design elements, beauties and facilities by the customized design method. As a result, this study proposes the model of online educational web-site having various interfaces and focusing on the customized design.

• Science of Emotion and Sensibility
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• v.20 no.2
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• pp.161-170
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• 2017

Emotion affects many parts of human life such as learning ability, behavior and judgment. It is important to understand human nature. Emotion can only be inferred from facial expressions or gestures, what it actually is. In particular, emotion is difficult to classify not only because individuals feel differently about emotion but also because visually induced emotion does not sustain during whole testing period. To solve the problem, we acquired bio-signals and extracted features from those signals, which offer objective information about emotion stimulus. The emotion pattern classifier was composed of unsupervised learning algorithm with hidden nodes and feature vectors. Restricted Boltzmann machine (RBM) based on probability estimation was used in the unsupervised learning and maps emotion features to transformed dimensions. The emotion was characterized by non-linear classifiers with hidden nodes of a multi layer neural network, named deep belief network (DBN). The accuracy of DBN (about 94 %) was better than that of back-propagation neural network (about 40 %). The DBN showed good performance as the emotion pattern classifier.

• Korean Medical Education Review
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• v.19 no.2
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• pp.83-89
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• 2017

The aim of this study is to examine the effect of recorded video monitoring on students' self-reflection after completing their clinical performance examination. Taking into account the particular cases involved in the examination, the present study utilized history-taking, physical examination, and patient education as bases for evaluating information-establishment ability, and asking, listening, understanding, explaining, and connectedness as the bases for evaluating patient-physician interaction ability. Student self-monitoring through recorded video feedback was carried out three days after completion of their clinical performance examination. Students self-evaluated their performance with a 10-point scale before and after self-monitoring. The results of this study show that students have a general tendency to lower their own self-evaluation scores after self-monitoring. Although there was not a statistically significant change of interrelationship in the information-establishment ability evaluation, there was a meaningful change of interrelationship in the patient-physician interaction ability evaluation after self-monitoring; specifically, in the case of acute lower abdominal pain, a high correlation was found (r=0.31, p=0.02) between the evaluation scores of standardized patients and students related to patient-physician interaction ability. This implies that self-monitoring enables the students to acquire a reflective viewpoint from which to evaluate their own performance. Therefore, it can be said that self-monitoring through recorded video feedback is a valuable method for students to use in reviewing their performance in patient-physician interactions.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.342-347
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• 2008

Face tracking and recognition are difficult problems because the face is a non-rigid object. If the system tries to track or recognize the unknown face continuously, it can be more hard problems. In this paper, we propose the method to track and to recognize the face of the unknown person on video sequences using linear combination of nonlinear manifold models that is constructed in the system. The arbitrary input face has different similarities with different persons in system according to its shape or pose. Do we can approximate the new nonlinear manifold model for the input face by estimating the similarities with other faces statistically. The approximated model is updated at each frame for the input face. Our experimental results show that the proposed method is efficient to track and recognize for the arbitrary person.

• The Bulletin of The Korean Astronomical Society
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• v.38 no.2
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• pp.98-98
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• 2013

태양의 활동영역에서 관측할 수 있는 흑점은 주로 흑점군으로 관측되며, 태양폭발현상의 발생을 예보하기 위한 중요한 관측 대상 중 하나이다. 현재 태양 폭발을 예보하는 모델들은 McIntosh 흑점군 분류법을 사용하며 통계적 모델과 기계학습 모델로 나누어진다. 컴퓨터는 흑점군의 형태학적 특성을 연속적인 값으로 계산하지만 흑점군의 형태적 다양성으로 인해 McIntosh 분류법과 일치하지 않는 경우가 있다. 이러한 이유로 컴퓨터가 계산한 흑점군의 형태학적인 특성을 예보에 직접 적용하는 것이 필요하다. 우리는 흑점군을 검출하기 위해 최소신장트리(Minimum spanning tree : MST)를 이용한 계층적 군집화 기법을 수행하였다. 그래프(Graph)이론에서 최소신장트리는 정점(Vertex)과 간선(Edge)으로 구성된 간선의 가중치의 합이 최소인 트리이다. 우리는 모든 흑점을 정점, 그들의 연결을 간선으로 적용하여 최소신장트리를 작성하였다. 또한 최소신장트리를 활용한 계층적 군집화기법은 초기값에 따른 군집화 결과의 차이가 없기 때문에 흑점군 검출에 있어서 가장 적합한 알고리즘이다. 이를 통해 흑점군의 기본적인 형태학적인 특성(개수, 면적, 면적비 등)을 계산하고 최소신장트리를 통해 가장 면적이 큰 흑점을 중심으로 트리의 깊이(Depth)와 차수(Degree)를 계산하였다. 이 방법을 2003년 SOHO/MDI의 태양 가시광 영상에 적용하여 구한 흑점군의 내부 흑점수와 면적은 NOAA에서 산출한 값들과 각각 90%, 99%의 좋은 상관관계를 가졌다. 우리는 이 연구를 통해 흑점군의 형태학적인 특성과 더불어 예보에 직접적으로 활용할 수 있는 방법을 논의하고자 한다.

• 한국정보교육학회:학술대회논문집
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• 2010.08a
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• pp.185-192
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• 2010

The purpose of this paper is to suggest design principles for videoconferencing using an English Native Speaker. For this, Design-Based Research which is emerging newly was applied. During the research period of 3 months, several English classes were recorded. After finishing each class, Korean teacher and Native teacher wrote reflective diary and a researcher implemented interviews to students who had this class. Based on these data, this class was divided into 3 steps which is consisted of before class, under class, and after class. And then a research analysed patterns of this class, errors, and interactivity etc. The result of this paper, because a Korean teacher and students in the classroom meet a Native speaker in the distance through the videoconferencing system, teachers who design this class should consider many aspects due to the complexity of this.

• Journal of Korea Multimedia Society
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• v.13 no.4
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• pp.512-525
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• 2010

A PDP(Plasma Display Panel) Frame is critical part of PDP and also produces couple hundred thousand every month. In the process of mass production, product inspection is very important process. Also to increase the reliance, inspection each part and every final product is asked quite often. Purpose of this paper is to use computer vision system to inspect the PDP parts which is Automated visual process inspection. This paper contains the system design for inspecting defects of hole, tab, stud, rivet of PDP Frame. The system also can inspect various kinds of PDP frames. Quick and accurate 100% inspection of all shapes can improve the manufacturing productivity. Inspection results can be stored in a database and analyzed to find the cause of defects. After applying the system to the industry, the result shows the possibility of fast and accuracy of the inspection.