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A Study on the Wooden Seated Vairocana Tri-kaya Buddha Images in the Daeungjeon Hall of Hwaeomsa Temple (화엄사 대웅전 목조비로자나삼신 불좌상에 대한 고찰)

  • Choe, Songeun
    • MISULJARYO - National Museum of Korea Art Journal
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    • v.100
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    • pp.140-170
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    • 2021
  • This paper investigates the Wooden Seated Tri-kaya Buddha Images(三身佛像) of Vairocana, Rushana, and Sakyamuni enshrined in Daeungjeon Hall of Hwaeomsa temple(華嚴寺) in Gurae, South Cheolla Province. They were produced in 1634 CE and placed in 1635 CE, about forty years after original images made in the Goryeo period were destroyed by the Japanese army during the war. The reconstruction of Hwaeomsa was conducted by Gakseong, one of the leading monks of Joseon Dynasty in the 17th century, who also conducted the reconstructions of many Buddhist temples after the war. In 2015, a prayer text (dated 1635) concerning the production of Hwaeomsa Tri-kaya Buddha images was found in the repository within Sakyamuni Buddha. It lists the names of participants, including royal family members (i.e., prince Yi Guang, the eighth son of King Seon-jo), and their relatives (i.e., Sin Ik-seong, son-in-law of King Seonjo), court ladies, monk-sculptors, and large numbers of monks and laymen Buddhists. A prayer text (dated 1634) listing the names of monk-sculptors written on the wooden panel inside the pedestal of Rushana Buddha was also found. A recent investigation into the repository within Rushana Buddha in 2020 CE has revealed a prayer text listing participants producing these images, similar to the former one from Sakyamuni Buddha, together with sacred relics of hoo-ryeong-tong copper bottle and a large quantity of Sutra books. These new materials opened a way to understand Hwaeomsa Trikaya images, including who made them and when they were made. The two above-mentioned prayer texts from the repository of Sakyamuni and Rushana Buddha statues, and the wooden panel inside the pedestal of Rushan Buddha tell us that eighteen monk-sculptors, including Eungwon, Cheongheon and Ingyun, who were well-known monk artisans of the 17th century, took part in the construction of these images. As a matter of fact, Cheongheon belonged to a different workshop from Eungwon and Ingyun, who were most likely teacher and disciple or senior and junior colleagues, which means that the production of Hwaeomsa Tri-kaya Buddha images was a collaboration between sculptors from two workshops. Eungwon and Ingyun seem to have belonged to the same community studying under the great Buddhist priest Seonsu, the teacher of Monk Gakseong who was in charge of the reconstruction of Haweonsa temple. Hwaeomsa Tri-kaya Buddha images show a big head, a squarish face with plump cheeks, narrow and drooping shoulders, and a short waist, which depict significant differences in body proportion to those of other Buddha statues of the first half of 17th century, which typically have wide shoulders and long waists. The body proportion shown in the Hwaeomsa images could be linked with images of late Goryeo and early Joseon period. Rushana Buddha, raising his two arms in a preaching hand gesture and wearing a crown and bracelets, shows unique iconography of the Bodhisattva form. This iconography of Rushana Buddha had appeared in a few Sutra paintings of Northern Song and Late Goryeo period of 13th and 14th century. BodhaSri-mudra of Vairocana Buddha, unlike the general type of BodhaSri-mudra that shows the right hand holding the left index finger, places his right hand upon the left hand in a fist. It is similar to that of Vairocana images of Northern and Southern Song, whose left hand is placed on the top of right hand in a fist. This type of mudra was most likely introduced during the Goryeo period. The dried lacquer Seated Vairocana image of Bulheosa Temple in Naju is datable to late Goryeo period, and exhibits similar forms of the mudra. Hwaeomsa Tri-kaya Buddha images also show new iconographic aspects, as well as traditional stylistic and iconographic features. The earth-touching (bhumisparsa) mudra of Sakymuni Buddha, putting his left thumb close to the middle finger, as if to make a preaching mudra, can be regarded as a new aspect that was influenced by the Sutra illustrations of the Ming dynasty, which were imported by the royal court of Joseon dynasty and most likely had an impact on Joseon Buddhist art from the 15th and 16th centuries. Stylistic and iconographical features of Hwaeomsa Tri-kaya Buddha images indicate that the traditional aspects of Goryeo period and new iconography of Joseon period are rendered together, side by side, in these sculptures. The coexistence of old and new aspects in one set of images could indicate that monk sculptors tried to find a new way to produce Hwaeomsa images based on the old traditional style of Goryeo period when the original Tri-kaya Buddha images were made, although some new iconography popular in Joseon period was also employed in the images. It is also probable that monk sculptors of Hwaeomsa Tri-kaya Buddha images intended to reconstruct these images following the original images of Goryeo period, which was recollected by surviving monks at Hwaeomsa, who had witnessed the original Tri-kaya Buddha images.

Customer Behavior Prediction of Binary Classification Model Using Unstructured Information and Convolution Neural Network: The Case of Online Storefront (비정형 정보와 CNN 기법을 활용한 이진 분류 모델의 고객 행태 예측: 전자상거래 사례를 중심으로)

  • Kim, Seungsoo;Kim, Jongwoo
    • Journal of Intelligence and Information Systems
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    • v.24 no.2
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    • pp.221-241
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    • 2018
  • Deep learning is getting attention recently. The deep learning technique which had been applied in competitions of the International Conference on Image Recognition Technology(ILSVR) and AlphaGo is Convolution Neural Network(CNN). CNN is characterized in that the input image is divided into small sections to recognize the partial features and combine them to recognize as a whole. Deep learning technologies are expected to bring a lot of changes in our lives, but until now, its applications have been limited to image recognition and natural language processing. The use of deep learning techniques for business problems is still an early research stage. If their performance is proved, they can be applied to traditional business problems such as future marketing response prediction, fraud transaction detection, bankruptcy prediction, and so on. So, it is a very meaningful experiment to diagnose the possibility of solving business problems using deep learning technologies based on the case of online shopping companies which have big data, are relatively easy to identify customer behavior and has high utilization values. Especially, in online shopping companies, the competition environment is rapidly changing and becoming more intense. Therefore, analysis of customer behavior for maximizing profit is becoming more and more important for online shopping companies. In this study, we propose 'CNN model of Heterogeneous Information Integration' using CNN as a way to improve the predictive power of customer behavior in online shopping enterprises. In order to propose a model that optimizes the performance, which is a model that learns from the convolution neural network of the multi-layer perceptron structure by combining structured and unstructured information, this model uses 'heterogeneous information integration', 'unstructured information vector conversion', 'multi-layer perceptron design', and evaluate the performance of each architecture, and confirm the proposed model based on the results. In addition, the target variables for predicting customer behavior are defined as six binary classification problems: re-purchaser, churn, frequent shopper, frequent refund shopper, high amount shopper, high discount shopper. In order to verify the usefulness of the proposed model, we conducted experiments using actual data of domestic specific online shopping company. This experiment uses actual transactions, customers, and VOC data of specific online shopping company in Korea. Data extraction criteria are defined for 47,947 customers who registered at least one VOC in January 2011 (1 month). The customer profiles of these customers, as well as a total of 19 months of trading data from September 2010 to March 2012, and VOCs posted for a month are used. The experiment of this study is divided into two stages. In the first step, we evaluate three architectures that affect the performance of the proposed model and select optimal parameters. We evaluate the performance with the proposed model. Experimental results show that the proposed model, which combines both structured and unstructured information, is superior compared to NBC(Naïve Bayes classification), SVM(Support vector machine), and ANN(Artificial neural network). Therefore, it is significant that the use of unstructured information contributes to predict customer behavior, and that CNN can be applied to solve business problems as well as image recognition and natural language processing problems. It can be confirmed through experiments that CNN is more effective in understanding and interpreting the meaning of context in text VOC data. And it is significant that the empirical research based on the actual data of the e-commerce company can extract very meaningful information from the VOC data written in the text format directly by the customer in the prediction of the customer behavior. Finally, through various experiments, it is possible to say that the proposed model provides useful information for the future research related to the parameter selection and its performance.

A Study on the Interactive Narrative - Focusing on the analysis of VR animation <Wolves in the Walls> (인터랙티브 내러티브에 관한 연구 - VR 애니메이션 <Wolves in the Walls>의 분석을 중심으로)

  • Zhuang Sheng
    • Trans-
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    • v.15
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    • pp.25-56
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    • 2023
  • VR is a dynamic image simulation technology with very high information density. Among them, spatial depth, temporality, and realism bring an unprecedented sense of immersion to the experience. However, due to its high information density, the information contained in it is very easy to be manipulated, creating an illusion of objectivity. Users need guidance to help them interpret the high density of dynamic image information. Just like setting up navigation interfaces and interactivity in games, interactivity in virtual reality is a way to interpret virtual content. At present, domestic research on VR content is mainly focused on technology exploration and visual aesthetic experience. However, there is still a lack of research on interactive storytelling design, which is an important part of VR content creation. In order to explore a better interactive storytelling model in virtual reality content, this paper analyzes the interactive storytelling features of the VR animated version of <Wolves in the walls> through the methods of literature review and case study. We find that the following rules can be followed when creating VR content: 1. the VR environment should fully utilize the advantages of free movement for users, and users should not be viewed as mere observers. The user's sense of presence should be fully considered when designing interaction modules. Break down the "fourth wall" to encourage audience interaction in the virtual reality environment, and make the hot media of VR "cool". 2.Provide developer-driven narrative in the early stages of the work so that users are not confused about the ambiguous world situation when they first enter a virtual environment with a high degree of freedom. 1.Unlike some games that guide users through text, you can guide them through a more natural interactive approach that adds natural dialog between the user and story characters (NPC). Also, since gaze guidance is an important part of story progression, you should set up spatial scene user gaze guidance elements within it. For example, you can provide eye-following cues, motion cues, language cues, and more. By analyzing the interactive storytelling features and innovations of the VR animation <Wolves in the walls>, I hope to summarize the main elements of interactive storytelling from its content. Based on this, I hope to explore how to better showcase interactive storytelling in virtual reality content and provide thoughts on future VR content creation.

Accelerated Loarning of Latent Topic Models by Incremental EM Algorithm (점진적 EM 알고리즘에 의한 잠재토픽모델의 학습 속도 향상)

  • Chang, Jeong-Ho;Lee, Jong-Woo;Eom, Jae-Hong
    • Journal of KIISE:Software and Applications
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    • v.34 no.12
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    • pp.1045-1055
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    • 2007
  • Latent topic models are statistical models which automatically captures salient patterns or correlation among features underlying a data collection in a probabilistic way. They are gaining an increased popularity as an effective tool in the application of automatic semantic feature extraction from text corpus, multimedia data analysis including image data, and bioinformatics. Among the important issues for the effectiveness in the application of latent topic models to the massive data set is the efficient learning of the model. The paper proposes an accelerated learning technique for PLSA model, one of the popular latent topic models, by an incremental EM algorithm instead of conventional EM algorithm. The incremental EM algorithm can be characterized by the employment of a series of partial E-steps that are performed on the corresponding subsets of the entire data collection, unlike in the conventional EM algorithm where one batch E-step is done for the whole data set. By the replacement of a single batch E-M step with a series of partial E-steps and M-steps, the inference result for the previous data subset can be directly reflected to the next inference process, which can enhance the learning speed for the entire data set. The algorithm is advantageous also in that it is guaranteed to converge to a local maximum solution and can be easily implemented just with slight modification of the existing algorithm based on the conventional EM. We present the basic application of the incremental EM algorithm to the learning of PLSA and empirically evaluate the acceleration performance with several possible data partitioning methods for the practical application. The experimental results on a real-world news data set show that the proposed approach can accomplish a meaningful enhancement of the convergence rate in the learning of latent topic model. Additionally, we present an interesting result which supports a possible synergistic effect of the combination of incremental EM algorithm with parallel computing.

A Mobile Landmarks Guide : Outdoor Augmented Reality based on LOD and Contextual Device (모바일 랜드마크 가이드 : LOD와 문맥적 장치 기반의 실외 증강현실)

  • Zhao, Bi-Cheng;Rosli, Ahmad Nurzid;Jang, Chol-Hee;Lee, Kee-Sung;Jo, Geun-Sik
    • Journal of Intelligence and Information Systems
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    • v.18 no.1
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    • pp.1-21
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    • 2012
  • In recent years, mobile phone has experienced an extremely fast evolution. It is equipped with high-quality color displays, high resolution cameras, and real-time accelerated 3D graphics. In addition, some other features are includes GPS sensor and Digital Compass, etc. This evolution advent significantly helps the application developers to use the power of smart-phones, to create a rich environment that offers a wide range of services and exciting possibilities. To date mobile AR in outdoor research there are many popular location-based AR services, such Layar and Wikitude. These systems have big limitation the AR contents hardly overlaid on the real target. Another research is context-based AR services using image recognition and tracking. The AR contents are precisely overlaid on the real target. But the real-time performance is restricted by the retrieval time and hardly implement in large scale area. In our work, we exploit to combine advantages of location-based AR with context-based AR. The system can easily find out surrounding landmarks first and then do the recognition and tracking with them. The proposed system mainly consists of two major parts-landmark browsing module and annotation module. In landmark browsing module, user can view an augmented virtual information (information media), such as text, picture and video on their smart-phone viewfinder, when they pointing out their smart-phone to a certain building or landmark. For this, landmark recognition technique is applied in this work. SURF point-based features are used in the matching process due to their robustness. To ensure the image retrieval and matching processes is fast enough for real time tracking, we exploit the contextual device (GPS and digital compass) information. This is necessary to select the nearest and pointed orientation landmarks from the database. The queried image is only matched with this selected data. Therefore, the speed for matching will be significantly increased. Secondly is the annotation module. Instead of viewing only the augmented information media, user can create virtual annotation based on linked data. Having to know a full knowledge about the landmark, are not necessary required. They can simply look for the appropriate topic by searching it with a keyword in linked data. With this, it helps the system to find out target URI in order to generate correct AR contents. On the other hand, in order to recognize target landmarks, images of selected building or landmark are captured from different angle and distance. This procedure looks like a similar processing of building a connection between the real building and the virtual information existed in the Linked Open Data. In our experiments, search range in the database is reduced by clustering images into groups according to their coordinates. A Grid-base clustering method and user location information are used to restrict the retrieval range. Comparing the existed research using cluster and GPS information the retrieval time is around 70~80ms. Experiment results show our approach the retrieval time reduces to around 18~20ms in average. Therefore the totally processing time is reduced from 490~540ms to 438~480ms. The performance improvement will be more obvious when the database growing. It demonstrates the proposed system is efficient and robust in many cases.

Increasing Accuracy of Stock Price Pattern Prediction through Data Augmentation for Deep Learning (데이터 증강을 통한 딥러닝 기반 주가 패턴 예측 정확도 향상 방안)

  • Kim, Youngjun;Kim, Yeojeong;Lee, Insun;Lee, Hong Joo
    • The Journal of Bigdata
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    • v.4 no.2
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    • pp.1-12
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    • 2019
  • As Artificial Intelligence (AI) technology develops, it is applied to various fields such as image, voice, and text. AI has shown fine results in certain areas. Researchers have tried to predict the stock market by utilizing artificial intelligence as well. Predicting the stock market is known as one of the difficult problems since the stock market is affected by various factors such as economy and politics. In the field of AI, there are attempts to predict the ups and downs of stock price by studying stock price patterns using various machine learning techniques. This study suggest a way of predicting stock price patterns based on the Convolutional Neural Network(CNN) among machine learning techniques. CNN uses neural networks to classify images by extracting features from images through convolutional layers. Therefore, this study tries to classify candlestick images made by stock data in order to predict patterns. This study has two objectives. The first one referred as Case 1 is to predict the patterns with the images made by the same-day stock price data. The second one referred as Case 2 is to predict the next day stock price patterns with the images produced by the daily stock price data. In Case 1, data augmentation methods - random modification and Gaussian noise - are applied to generate more training data, and the generated images are put into the model to fit. Given that deep learning requires a large amount of data, this study suggests a method of data augmentation for candlestick images. Also, this study compares the accuracies of the images with Gaussian noise and different classification problems. All data in this study is collected through OpenAPI provided by DaiShin Securities. Case 1 has five different labels depending on patterns. The patterns are up with up closing, up with down closing, down with up closing, down with down closing, and staying. The images in Case 1 are created by removing the last candle(-1candle), the last two candles(-2candles), and the last three candles(-3candles) from 60 minutes, 30 minutes, 10 minutes, and 5 minutes candle charts. 60 minutes candle chart means one candle in the image has 60 minutes of information containing an open price, high price, low price, close price. Case 2 has two labels that are up and down. This study for Case 2 has generated for 60 minutes, 30 minutes, 10 minutes, and 5minutes candle charts without removing any candle. Considering the stock data, moving the candles in the images is suggested, instead of existing data augmentation techniques. How much the candles are moved is defined as the modified value. The average difference of closing prices between candles was 0.0029. Therefore, in this study, 0.003, 0.002, 0.001, 0.00025 are used for the modified value. The number of images was doubled after data augmentation. When it comes to Gaussian Noise, the mean value was 0, and the value of variance was 0.01. For both Case 1 and Case 2, the model is based on VGG-Net16 that has 16 layers. As a result, 10 minutes -1candle showed the best accuracy among 60 minutes, 30 minutes, 10 minutes, 5minutes candle charts. Thus, 10 minutes images were utilized for the rest of the experiment in Case 1. The three candles removed from the images were selected for data augmentation and application of Gaussian noise. 10 minutes -3candle resulted in 79.72% accuracy. The accuracy of the images with 0.00025 modified value and 100% changed candles was 79.92%. Applying Gaussian noise helped the accuracy to be 80.98%. According to the outcomes of Case 2, 60minutes candle charts could predict patterns of tomorrow by 82.60%. To sum up, this study is expected to contribute to further studies on the prediction of stock price patterns using images. This research provides a possible method for data augmentation of stock data.

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A Study on the Background of the Rock-cut Sculpture of Two Buddhas Seated Side-by-Side in Wonpung-ri, Goesan (괴산 원풍리 마애이불병좌상의 조성 배경)

  • Jeong, Seongkwon
    • Korean Journal of Heritage: History & Science
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    • v.53 no.3
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    • pp.224-243
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    • 2020
  • The rock-cut relief of two Buddhas seated side-by-side in Wonpungri is a large Buddha sculpture in relief on the side of a cliff in Wonpung-ri, Goesan. This Buddha sculpture is from the Buddhist scripture Sutra of the Lotus. <法華經> Two seated Buddhas statues were prevalent in the Balhae Kingdom, but this was not popular in Silla and Goryeo. In the main text, the time that the two seated Buddhas in Wonpung-ri was created is identified as being during the 10th century. King Gwangjong created a Buddha statue for political purposes. The relief of two seated Buddha image carved on a cliff is located on an important traffic route over the Sobaek Mountain Range. After King Gwangjong took the throne, he paid close attention to the reigning powers of Jincheon and Cheongju because the people of Jincheon and Cheongju were engaged in a power struggle against Gwangjong. The huge relief of two seated Buddhas statue shows the authority of King Gwangjong. In particular, the people of Jincheon and Cheongju had to see this Buddha statue when crossing the Sobaek Mountain Range. The image contained in the relief of the two seated Buddhas features many characteristics of the sculpture style of the Balhae Kingdom. After the fall of Balhae, many of the Balhae people settled in Mungyeong. Balhae people from Mungyeong participated in the production of the relief of the two seated Buddhas. Through the relief of the two seated Buddhas, King Gwangjong wanted to show the people of Jincheon and Cheongju that the Balhae people were supporting him. The relief of two seated Buddhas reflects the historical situation of the King Gwangjong era in the late 10th century and the style of sculpture.

Ki Ho School of Neo-Confucianism on Yi Xue Qi Meng in Later Chosun Period (조선후기 기호성리학파의 역학계몽 이해)

  • Yi, Suhn Gyohng
    • The Journal of Korean Philosophical History
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    • no.35
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    • pp.275-308
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    • 2012
  • This article aims to investigate the studies of Yi Xue Qi Meng(易學啓蒙) performed by the researchers of Neo-Confucianism in Ki Ho region in later Chosun period. Philologically speaking, these studies were mainly performed by Han Won Jin and his colleagues. While the study of Yi Hwang(李滉)'s Qi Meng Zhuan Yi(啓蒙傳疑) performed by the researchers of Toegye(退溪) School lasts from the end of the sixteenth century to the nineteen's century, the Ki Ho(畿湖) scholars' study of Yi Xue Qi Meng are centered in the eighteenth century and hardly any significant work on this text is found before and after this century. In order to single out the distinctive features of Ki Ho School of Neo-Confucianism, this article examines three subjects the Ki Ho scholars delved into: (i) their theory of Tai Ji(太極), (ii) their theory of He-Tu(河圖) and the formation of eight trigrams, and (iii) the so-called Wu Wei Xiang De Shuo(五位相得說) discussed in one of the sections in Yi Xue Qi Meng titled the Source of He-Tu and Luo Shu[本圖書]. The Ki Ho scholars are remarkable in interpreting Tai Ji in Yi Xue Qi Meng in the context of the theory of Li-Qi and the theory of human nature. There are differences in opinion among the Ki-Ho scholars with regard to the relation between He-Tu and the formation of eight trigrams. Eventually, they withhold Zhu Xi(朱熹) and Hu Fang Ping(胡方平)'s attempt to synthesize He-Tu, the rectangular diagram of Fu Xi(伏羲)'s eight trigrams, and the circular diagram of Fu Xi's eight trigrams into one single principle. Han Won Jin tries to explain the relation between He-tu and the formation of eight trigrams in terms of the relation between He-Tu and the circular diagram, and his attempt is widely supported by his colleagues. This theory runs counter to traditional model of explaining truth. My conjecture is that such academic trend is further developed by the defenders of Practical Learning such as Hong Dae Yong(洪大容), who vigorously reject traditional system of truth and science, and that it partly explains why the study of Yi Xue Qi Meng ceases in the nineteenth century.

Open Digital Textbook for Smart Education (스마트교육을 위한 오픈 디지털교과서)

  • Koo, Young-Il;Park, Choong-Shik
    • Journal of Intelligence and Information Systems
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    • v.19 no.2
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    • pp.177-189
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    • 2013
  • In Smart Education, the roles of digital textbook is very important as face-to-face media to learners. The standardization of digital textbook will promote the industrialization of digital textbook for contents providers and distributers as well as learner and instructors. In this study, the following three objectives-oriented digital textbooks are looking for ways to standardize. (1) digital textbooks should undertake the role of the media for blended learning which supports on-off classes, should be operating on common EPUB viewer without special dedicated viewer, should utilize the existing framework of the e-learning learning contents and learning management. The reason to consider the EPUB as the standard for digital textbooks is that digital textbooks don't need to specify antoher standard for the form of books, and can take advantage od industrial base with EPUB standards-rich content and distribution structure (2) digital textbooks should provide a low-cost open market service that are currently available as the standard open software (3) To provide appropriate learning feedback information to students, digital textbooks should provide a foundation which accumulates and manages all the learning activity information according to standard infrastructure for educational Big Data processing. In this study, the digital textbook in a smart education environment was referred to open digital textbook. The components of open digital textbooks service framework are (1) digital textbook terminals such as smart pad, smart TVs, smart phones, PC, etc., (2) digital textbooks platform to show and perform digital contents on digital textbook terminals, (3) learning contents repository, which exist on the cloud, maintains accredited learning, (4) App Store providing and distributing secondary learning contents and learning tools by learning contents developing companies, and (5) LMS as a learning support/management tool which on-site class teacher use for creating classroom instruction materials. In addition, locating all of the hardware and software implement a smart education service within the cloud must have take advantage of the cloud computing for efficient management and reducing expense. The open digital textbooks of smart education is consdered as providing e-book style interface of LMS to learners. In open digital textbooks, the representation of text, image, audio, video, equations, etc. is basic function. But painting, writing, problem solving, etc are beyond the capabilities of a simple e-book. The Communication of teacher-to-student, learner-to-learnert, tems-to-team is required by using the open digital textbook. To represent student demographics, portfolio information, and class information, the standard used in e-learning is desirable. To process learner tracking information about the activities of the learner for LMS(Learning Management System), open digital textbook must have the recording function and the commnincating function with LMS. DRM is a function for protecting various copyright. Currently DRMs of e-boook are controlled by the corresponding book viewer. If open digital textbook admitt DRM that is used in a variety of different DRM standards of various e-book viewer, the implementation of redundant features can be avoided. Security/privacy functions are required to protect information about the study or instruction from a third party UDL (Universal Design for Learning) is learning support function for those with disabilities have difficulty in learning courses. The open digital textbook, which is based on E-book standard EPUB 3.0, must (1) record the learning activity log information, and (2) communicate with the server to support the learning activity. While the recording function and the communication function, which is not determined on current standards, is implemented as a JavaScript and is utilized in the current EPUB 3.0 viewer, ths strategy of proposing such recording and communication functions as the next generation of e-book standard, or special standard (EPUB 3.0 for education) is needed. Future research in this study will implement open source program with the proposed open digital textbook standard and present a new educational services including Big Data analysis.