• Title/Summary/Keyword: Learning Contents System

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k-NN Query Optimization Scheme Based on Machine Learning Using a DNN Model (DNN 모델을 이용한 기계 학습 기반 k-최근접 질의 처리 최적화 기법)

  • We, Ji-Won;Choi, Do-Jin;Lee, Hyeon-Byeong;Lim, Jong-Tae;Lim, Hun-Jin;Bok, Kyoung-Soo;Yoo, Jae-Soo
    • The Journal of the Korea Contents Association
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    • v.20 no.10
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    • pp.715-725
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    • 2020
  • In this paper, we propose an optimization scheme for a k-Nearest Neighbor(k-NN) query, which finds k objects closest to the query in the high dimensional feature vectors. The k-NN query is converted and processed into a range query based on the range that is likely to contain k data. In this paper, we propose an optimization scheme using DNN model to derive an optimal range that can reduce processing cost and accelerate search speed. The entire system of the proposed scheme is composed of online and offline modules. In the online module, a query is actually processed when it is issued from a client. In the offline module, an optimal range is derived for the query by using the DNN model and is delivered to the online module. It is shown through various performance evaluations that the proposed scheme outperforms the existing schemes.

Instructional Design Model Development for Continuous Creativity-Personality Education based on NFTM-TRIZ (NFTM-TRIZ에 근거한 지속적인 창의·인성 교육을 위한 수업설계모형 구안)

  • Kim, Hoon-Hee
    • The Journal of the Korea Contents Association
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    • v.13 no.8
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    • pp.474-481
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    • 2013
  • The purpose of this study is that pre-service teacher are able to design creative instruction based on NFTM-TRIZ for building up their continuous creative thinking and promoting their creative instruction activities. NFTM-TRIZ is a educational technology system to form and develop creative thinking from child to adult continuously based on TRIZ theory. TRIZ is the thinking technique of creative problem solving that can be the tool of inventory solutions by finding and get over the key of contradiction that is necessary to obtain ideal final results of suggested problems. The subjects for this study were 90 pre-service teachers who are attending third and fourth graders of Teachers' College in G university and are taking 'Curriculum and Educational Evaluation'. The creativity program for this study was carried out for ten minutes at the end of lectures. The verification for this study results were performed two faces. First, pre-service teachers presented teaching and learning plan for one time used 8 Steps' Teaching and Learning Model based on NFTM-TRIZ. Second, researcher got feedback from them about this creative program.

LSTM RNN-based Korean Speech Recognition System Using CTC (CTC를 이용한 LSTM RNN 기반 한국어 음성인식 시스템)

  • Lee, Donghyun;Lim, Minkyu;Park, Hosung;Kim, Ji-Hwan
    • Journal of Digital Contents Society
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    • v.18 no.1
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    • pp.93-99
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    • 2017
  • A hybrid approach using Long Short Term Memory (LSTM) Recurrent Neural Network (RNN) has showed great improvement in speech recognition accuracy. For training acoustic model based on hybrid approach, it requires forced alignment of HMM state sequence from Gaussian Mixture Model (GMM)-Hidden Markov Model (HMM). However, high computation time for training GMM-HMM is required. This paper proposes an end-to-end approach for LSTM RNN-based Korean speech recognition to improve learning speed. A Connectionist Temporal Classification (CTC) algorithm is proposed to implement this approach. The proposed method showed almost equal performance in recognition rate, while the learning speed is 1.27 times faster.

Efficient Object Classification Scheme for Scanned Educational Book Image (교육용 도서 영상을 위한 효과적인 객체 자동 분류 기술)

  • Choi, Young-Ju;Kim, Ji-Hae;Lee, Young-Woon;Lee, Jong-Hyeok;Hong, Gwang-Soo;Kim, Byung-Gyu
    • Journal of Digital Contents Society
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    • v.18 no.7
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    • pp.1323-1331
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    • 2017
  • Despite the fact that the copyright has grown into a large-scale business, there are many constant problems especially in image copyright. In this study, we propose an automatic object extraction and classification system for the scanned educational book image by combining document image processing and intelligent information technology like deep learning. First, the proposed technology removes noise component and then performs a visual attention assessment-based region separation. Then we carry out grouping operation based on extracted block areas and categorize each block as a picture or a character area. Finally, the caption area is extracted by searching around the classified picture area. As a result of the performance evaluation, it can be seen an average accuracy of 83% in the extraction of the image and caption area. For only image region detection, up-to 97% of accuracy is verified.

Design and Implementation of Web Based PBL System for Physical Education Science (체육교과용 웹 기반 프로젝트학습 시스템의 설계 및 구현)

  • Jang, Jong-Chul;Choi, Suk-Young;Ahn, Seong-Hun
    • The Journal of the Korea Contents Association
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    • v.6 no.12
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    • pp.216-225
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    • 2006
  • Teaching methods should focus on enabling the students to adopt an open mind towards new experiences and to be flexible to change. Moreover, their purpose lies in encouraging the students to build their ability to discern values so that they can make the right decisions when they are at a crossroad. However, traditional teaching methods were centered on textbooks and on the teachers. This type of teaching method needs to change so that the new teaching method will focus on the students themselves, taking levels of individual students into consideration to enable development of their creativity in line with the demands made during the 21st century, an era of information and globalization. Projected learning method is appropriate for the Physical Education (PE) classes where various activities aim to increase the level of cooperation among students and their investigative skills. Moreover, PE classes pay special attention to the practical aspect. Accordingly, this research makes recommendations for the class execution methods based on projected learning by improving the curriculum for the PE classes, and the effect of these methods are subject to verification.

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Development of an Engineering Education Framework for Aerodynamic Shape Optimization

  • Kwon, Hyung-Il;Kim, Saji;Lee, Hakjin;Ryu, Minseok;Kim, Taehee;Choi, Seongim
    • International Journal of Aeronautical and Space Sciences
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    • v.14 no.4
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    • pp.297-309
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    • 2013
  • Design optimization is a mathematical process to find an optimal solution through the use of formal optimization algorithms. Design plays a vital role in the engineering field; therefore, using design tools in education and research is becoming more and more important. Recently, numerical design optimization in fluid mechanics, which uses computational fluid dynamics (CFD), has numerous applications in the engineering field, because of the rapid development of high-performance computing resources. However, it is difficult to find design optimization software and contents for educational purposes in aerospace engineering. In the present study, we have developed an aerodynamic design framework specifically for an airfoil, based on the EDucation-research Integration through Simulation On the Net (EDISON) portal. The airfoil design framework is composed of three subparts: a geometry kernel, CFD flow analysis, and an optimization algorithm. Through a seamless interface among the subparts, an iterative design process is conducted. In addition, the CFD flow analysis and the design framework are provided through a web-based portal system, while the computation is taken care of by a supercomputing facility. In addition to the software development, educational contents are developed for lectures associated with design optimization in aerospace and mechanical engineering education programs. The software and content developed in this study is expected to be used as a tool for e-learning material, for education and research in universities.

A Performance Improvement of Automatic Butterfly Identification Method Using Color Intensity Entropy (영상의 색체 강도 엔트로피를 이용한 나비 종 자동 인식 향상 방법)

  • Kang, Seung-Ho;Kim, Tae-Hee
    • The Journal of the Korea Contents Association
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    • v.17 no.5
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    • pp.624-632
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    • 2017
  • Automatic butterfly identification using images is one of the interesting research fields because it helps the related researchers studying species diversity and evolutionary and development process a lot in this field. The performance of the butterfly species identification system is dependent heavily on the quality of selected features. In this paper, we propose color intensity (CI) entropy by using the distribution of color intensities in a butterfly image. We show color intensity entropy can increase the recognition rate by 10% if it is used together with previously suggested branch length similarity entropy. In addition, the performance comparison with other features such as Eigenface, 2D Fourier transform, and 2D wavelet transform is conducted against several well known machine learning methods.

An Exploration of Interaction Factors and Analysis on Interaction-Level of Synchronous Online Education in University (대학 실시간 온라인 교육에서의 상호작용 요소 탐색과 수준 분석)

  • Han, Hyeong-Jong
    • The Journal of the Korea Contents Association
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    • v.21 no.4
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    • pp.14-25
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    • 2021
  • The purpose of this study is to explore what are the interactive factors of synchronous online education in university and identify the level of interaction. This study used mixed research method. As a result of the interaction level, it was recognized that face-to-face education could be more interactive than synchronous online education. Synchronous online education could have better interactive between instructor and learner, and among learners than asynchronous online education. Factors which influencing the interaction were as follows: small group activities and scaffolding, diversification of communication channels and integration of learner's question in learning content. Detrimental elements were distance felt between instructor and learners, low intimacy among learners, content-focused lecture, restrictions on non-verbal communication, unstable systems and misusing microphones. The necessary factors to promote interaction are planning interactive class activities, etc. Based on the results, it was to suggest what kinds of efforts are needed to make interaction more effective in terms of teaching and learning method & activity, tool & system, and environment.

A Study on Asthmatic Occurrence Using Deep Learning Algorithm (딥러닝 알고리즘을 활용한 천식 환자 발생 예측에 대한 연구)

  • Sung, Tae-Eung
    • The Journal of the Korea Contents Association
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    • v.20 no.7
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    • pp.674-682
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    • 2020
  • Recently, the problem of air pollution has become a global concern due to industrialization and overcrowding. Air pollution can cause various adverse effects on human health, among which respiratory diseases such as asthma, which have been of interest in this study, can be directly affected. Previous studies have used clinical data to identify how air pollutant affect diseases such as asthma based on relatively small samples. This is high likely to result in inconsistent results for each collection samples, and has significant limitations in that research is difficult for anyone other than the medical profession. In this study, the main focus was on predicting the actual asthmatic occurrence, based on data on the atmospheric environment data released by the government and the frequency of asthma outbreaks. First of all, this study verified the significant effects of each air pollutant with a time lag on the outbreak of asthma through the time-lag Pearson Correlation Coefficient. Second, train data built on the basis of verification results are utilized in Deep Learning algorithms, and models optimized for predicting the asthmatic occurrence are designed. The average error rate of the model was about 11.86%, indicating superior performance compared to other machine learning-based algorithms. The proposed model can be used for efficiency in the national insurance system and health budget management, and can also provide efficiency in the deployment and supply of medical personnel in hospitals. And it can also contribute to the promotion of national health through early warning of the risk of outbreak by atmospheric environment for chronic asthma patients.

MBTI Personality Types of the University Students in an Area (일 지역 대학생의 성격유형)

  • Jang, Hyun-Jung
    • The Journal of the Korea Contents Association
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    • v.18 no.3
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    • pp.486-498
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    • 2018
  • This study is a descriptive research study conducted to provide useful preliminary data that is helpful for self-initiated learning through a preference trend-based learning method by analyzing the personality types of university students in an area. In this study, the self-administered MBTI form $M^{(R)}$ test was performed on 695 students of 10 departments at K University, from September 18 to 22, 2017, using an automatic scoring system. Collected data was analyzed with descriptive statistics and Chi-square test, using the SPSS Win 22.0 Program, to sort the target students into one of 16 different personality types and examine psychological function and temperament by their personality. Differences in personality type preference by gender were as follows: for judging function, the male students had a strong preference for the T type (thinking type) while the female students showed a high preference for the F type (feeling type), and in the case of the pattern of behavior and lifestyle, the male students and the female students had a strong preference for the P type (perceiving type) and the J type (judging type), respectively. In addition, there were significant differences for each major and each department in personality type, psychological function and temperament. In conclusion, personality type was found to vary by gender, major and department. It would be necessary to develop a manual for learning methods reflecting individual preference.