• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.165-172
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• 2020

Recently, due to exponential growth of access information on the web, the importance of predicting a user's next web page use has been increasing. One of the methods that can be used for predicting user's next web page is deep learning. To predict next web page, web logs are analyzed by data preprocessing and then a user's next web page is predicted on the output of the analyzed web logs using a deep learning algorithm. In this paper, we propose a framework for web page prediction that includes methods for web log preprocessing followed by deep learning techniques for web prediction. To increase the speed of preprocessing of large web log, a Hadoop based MapReduce programming model is used. In addition, we present a web prediction system that uses an efficient deep learning technique on the output of web log preprocessing for training and prediction. Through experiment, we show the performance improvement of our proposed method over traditional methods. We also show the accuracy of our prediction.

• Journal of Korea Game Society
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• v.15 no.3
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• pp.189-200
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• 2015

These days computer graphics technology has been applied in diverse IT fields. Needs for computer graphics such as 3D Printer, Head Mount Display, VR & AR are growing rapidly. Computer graphics will be more specialized and demanding for graphics specialists will be also increased. However, serious mathematical background obstructs people to learning computer graphics. An efficient computer graphics learning system would be helpful for graphics experts training. By analyzing the graphics theory, we propose an educational software system with that students can effectively learn computer graphics. Our system focuses on theoretical objects of computer graphics and enhances accessibility and intuition using web and blocks.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.4
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• pp.23-28
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• 2022

Recently smart device(such as smart phone and tablet PC) become a role as an information gateway, using of the web news by multiple users from the web portal has been more important things. However, the quantity of creating web news on the web makes hard to catch the information which the user wants and confuse the users cause of the similar and repeated contents. In this paper, we propose the news recommend system using the document summarization based on KoBART which gives the selected news to users from the candidate news on the news portal. As a result, our proposed system shows higher performance and recommending the news efficiently by pre-training and fine-tuning the KoBART using collected news data.

• Journal of Korean Society of Water and Wastewater
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• v.21 no.3
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• pp.305-314
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• 2007

Forecasting of water quality variation is not an easy process due to the complicated nature of various water quality factors and their interrelationships. The objective of this study is to test the applicability of neural network models to the forecasting of the water quality at Dalchun station in Han River. Input data is consist of monthly data of concentration of DO, BOD, COD, SS and river flow. And this study selected optimal neural network model through changing the number of hidden layer based on input layer(n) from n to 6n. After neural network theory is applied, the models go through training, calibration and verification. The result shows that the proposed model forecast water quality of high efficiency and developed web-based water quality forecasting system after extend model

• Management & Information Systems Review
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• v.28 no.4
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• pp.1-26
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• 2009

Among food-service managers, a survey was conducted to grasp the their work-related education conditions and the demand for education program development. This study focuses on food-service managers in web-based training and analyzes the critical factors involved in their learning process in order to clarify the factors that lead to the maximization of training programs. The results of all this study process are as follows. First, the characteristics of web-based education including component of education factor, system factor, deepening learning factor have meaningful effect on commitment of the participants and education performance(except deepening learning factor to education performance). Second, the analysis that the characteristics of individuals including self-efficacy in learning, purpose-directivity factor have meaningful effects on commitment of the participants and education performance(except purpose-directivity factor to education performance). Third, commitment of the participants has meaningful effects on the education performance. Thus, it is advisable for education managers or operators to emphasize in foodservice organizations.

• Journal of Information Technology and Architecture
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• v.9 no.4
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• pp.413-422
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• 2012

Many researchers have been studied to reveal human natural language to let machine understand its meaning by text based, page rank based or more. Particularly, it has been considered that URL and HTML Tag information in web documents are attracting people' attention again to analyze huge amount of web document automatically. In this paper, we propose a STW (Semantic Term Weight) approach based on syntactic and linguistic structure of web documents in order to classify what genres are. For the evaluation, we analyzed more than 1,000 documents from 20-Genre-collection corpus for training the documents based on SVM algorithm. Afterwards, we tested KI-04 corpus to evaluate performance of our proposed method. This paper measured their accuracy by classifying them into an experiment using STW and one without u sing STW. As the results, the proposed STW based approach showed approximately 10.2% which Is higher than one without use of STW.

• Journal of Web Engineering
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• v.21 no.2
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• pp.497-522
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• 2021

Audio event classification refers to the detection and classification of non-verbal signals, such as dog and horn sounds included in audio data, by a computer. Recently, deep neural network technology has been applied to audio event classification, exhibiting higher performance when compared to existing models. Among them, a convolutional neural network (CNN)-based training method that receives audio in the form of a spectrogram, which is a two-dimensional image, has been widely used. However, audio event classification has poor performance on test data when it is recorded by a device (unknown device) different from that used to record training data (known device). This is because the frequency range emphasized is different for each device used during recording, and the shapes of the resulting spectrograms generated by known devices and those generated by unknown devices differ. In this study, to improve the performance of the event classification system, a CNN based on the log mel-spectrogram separation technique was applied to the event classification system, and the performance of unknown devices was evaluated. The system can classify 16 types of audio signals. It receives audio data at 0.4-s length, and measures the accuracy of test data generated from unknown devices with a model trained via training data generated from known devices. The experiment showed that the performance compared to the baseline exhibited a relative improvement of up to 37.33%, from 63.63% to 73.33% based on Google Pixel, and from 47.42% to 65.12% based on the LG V50.

• Journal of Web Engineering
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• v.21 no.2
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• pp.265-284
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• 2021

In this study, an automatic end-to-end speech recognition system based on hybrid CTC-attention network for Korean language is proposed. Deep neural network/hidden Markov model (DNN/HMM)-based speech recognition system has driven dramatic improvement in this area. However, it is difficult for non-experts to develop speech recognition for new applications. End-to-end approaches have simplified speech recognition system into a single-network architecture. These approaches can develop speech recognition system that does not require expert knowledge. In this paper, we propose hybrid CTC-attention network as end-to-end speech recognition model for Korean language. This model effectively utilizes a CTC objective function during attention model training. This approach improves the performance in terms of speech recognition accuracy as well as training speed. In most languages, end-to-end speech recognition uses characters as output labels. However, for Korean, character-based end-to-end speech recognition is not an efficient approach because Korean language has 11,172 possible numbers of characters. The number is relatively large compared to other languages. For example, English has 26 characters, and Japanese has 50 characters. To address this problem, we utilize Korean 49 graphemes as output labels. Experimental result shows 10.02% character error rate (CER) when 740 hours of Korean training data are used.

• Proceedings of the Korean Society of Computer Information Conference
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• 2010.07a
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• pp.485-491
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• 2010

The arrival of the Web 2.0 age, which is characterized by such key words as participation, sharing and openness, provides a learning environment in which both instructors and students can experience interactivity. In the educational area, we are particularly witnessing a growing interest in the social software like Wiki as one of the communication tools that reflects the characteristics of Web 2.0 and focuses on the interactivity with others. Based on this background, this study aims to examine into the meanings of interactivity inherent in the Wiki-based learning by studying such cases where Wiki is being used as a learning tool. For the purpose of our study, we practiced the Wiki-based learning method on the study subjects of the 17 junior students from U- University and 18 junior students from K- University during their 2009 fall semester teacher training courses. Through a comprehensive analysis of the questionnaires, interviews, Interactivity Measurement Diagram, examinations on the Wiki uses, Daily Self-reflection Records, and any other materials collected throughout the program, we could garner the following results: First, most of the students acknowledged that the use of Wiki was a useful communication means and helped promote their interactivity during their learning activities. Second, the interactivity of the Wiki-based learning was found to be more dynamic in the team-based projects or the community-based Wiki uses than in the instructor-oriented cases. Third, the Wiki-based learning is judged effective in expanding the scope of thinking and improving the learning capabilities through the collaborative knowledge-building process. The educational employment of the social software like Wiki in this web 2.0 age has great potentials for the true establishment of the learner-oriented learning environment, which has long remained at a standstill.

• Korean Journal of Oriental Medicine
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• v.13 no.2 s.20
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• pp.127-133
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• 2007

Objectives : This study were aimed to estimate the needs for clinical research educational program development focused on oriental medicine. Methods : Department Medical Research of Korea Institute of Oriental Medicine surveyed 204 certified subjects in total by using web-based questionnaires through e-mail from Jan. 17th to Jan. 31th, 2007. Reply from 62 on-line correspondents were collected and statistically analyzed. Results : The number of clinical trial involving oriental medicine continues to increase. According to the survey, many Issues were raised as problems such as difficulty of recruitment, lack of fund and lack of stepped program. Emphasized issues were clinical research methodologies, development of protocols and case report form (CRF), and Regulations including Institutional Review Boards (IRBs) in these three consecutive education training program. Conclusion : The results of this study may contribute to the development of an educational program for oriental medicine, a program that should be taken into consideration for developing practical items, such as, problem-based learnings which reflects participants' actual needs in their works. Also this report be used for future strategy plans and execution of training program for oriental medical clinical trial.