• International Journal of Knowledge Content Development & Technology
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• v.1 no.1
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• pp.61-79
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• 2011

This study purposed to discover whether or not academic libraries reflect these changing roles. We selected K University as the research target and surveyed user satisfaction of materials, staff services, facilities, electronic devices, media, and so on. The research findings are as follows: 1) the frequency of library visits of University K was on the high side, 2) the primary purpose of using the academic library was associated with learning or reading, therefore, the most used library spaces were related to that, 3) the most used library materials were 'general books', the most unused were 'reference books', 4) the most preferred way to obtain needed materials when failing to find wanted materials was 'Contact librarian'. A similar phenomenon occurred in terms of facility use, 5) university K's users were usually satisfied with the loan policy, 6) the rate of users who don't know whether there is user education was very high, the rate of users who have no experience with user education was extremely low. These research findings can be referenced by library management to improve libraries' service quality and take advantage of complex spatial configurations.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.5
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• pp.267-278
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• 2017

As the same letter can be pronounced differently depending on word contexts, one should refer to a lexicon in order to pronounce a word correctly. Phonetic alphabets that lexicons adopt as well as pronunciations that lexicons describe for the same word can be different from lexicon to lexicon. In this paper, we use a sequence-to-sequence model that is widely used in deep learning research area in order to convert automatically from one pronunciation to another. The 12 seq2seq models are implemented based on pronunciation training data collected from 4 different lexicons. The exact accuracy of the models ranges from 74.5% to 89.6%. The aim of this study is the following two things. One is to comprehend a property of phonetic alphabets and pronunciations used in various lexicons. The other is to understand characteristics of seq2seq models by analyzing an error.

• Journal of Elementary Mathematics Education in Korea
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• v.24 no.2
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• pp.207-229
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• 2020

The study examined on the general educational system, the structure of the document of mathematical curriculum, and the characteristics of the achievement standards written in the document of France in order to compare with Korean primary mathematics education. French pupils learn about 5% more hours than Korean sixth grade pupils, and French document of mathematical curriculum describes the contents included in the documents more concretely than us. There were a large differences in the subjects both of mixed calculations and division of fractions in the area of number and operations. The study proposed the necessity for researches on the concrete description of the document of mathematical curriculum, more concrete examples to use to teach pupils on the viewpoints of school mathematics, and the learning sequences and methods of the division of fractional numbers. At last we proposed to need rethink of the importances and teaching methods of calculations.

• Proceedings of the Korea Contents Association Conference
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• 2008.05a
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• pp.668-674
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• 2008

When various kinds of contents are developed in accordance with higher rate of Internet use to have quality conditions, added values can be elevated in genuinely strong power of Internet. As soon as visiting web site on Internet, men are invited to visit corresponding information web site by a variety of techniques and colors. The visual expression is thought to be important, and color plans of web designs play an important role. This is because the color decides on images of web design to transfer sense as an important element. The paper selected colors by each type of web site and investigated color images. The purpose of the paper is to classify local web sites by each type, for instance, identity, information/community, entertainment, shopping and learning, etc and to suggest directions of color image plan by each type of web site.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.9
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• pp.349-354
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• 2019

s programming education becomes more important in recent years, it is necessary to learn how the source code written by students reflects Object-Oriented(OO) concepts. We present a tool called the Round-Trip Translator(RTT) that transforms the Unified Modeling Language(UML) class diagram and Java source code to provide a web-based environment that provides real-time synchronization of UML and source code. RTT was created by improving existing RTE and is a tool for students who are learning OO concepts to understand how their UML or source code reflects the concepts that user intended. This study compares the efficiency and user- friendliness of RTT with the existing Round-Trip Engineering-based tools. The results show that students have improved understanding of OO concepts through UML and source code translation by using the RTT. We also found out that students were satisfied with the use of the RTT, which provides more efficient and convenient user interface than the existing tools.

• The Journal of the Acoustical Society of Korea
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• v.38 no.5
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• pp.568-573
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• 2019

In the diagnosis of pulmonary diseases, auscultation technique is simpler than the other methods, and lung sounds can be used for predicting the types of pulmonary diseases as well as identifying patients with pulmonary diseases. Therefore, in this paper, we identify patients with pulmonary diseases and classify lung sounds according to their sound characteristics using various convolutional neural networks, and compare the classification performance of each neural network method. First, lung sounds over affected areas of the chest with pulmonary diseases are collected by using a single-channel lung sound recording device, and spectral features are extracted from the collected sounds in time domain and applied to each neural network. As classification methods, we use general, parallel, and residual convolutional neural network, and compare lung sound classification performance of each neural network through experiments.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.179-186
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• 2021

We have been developed the smart tourism app and the Instagram and YouTube contents to provide personalized tourism information and travel product information to individual tourists. In this paper, we develop a rule-based smart tourism chatbot with the khaiii (Kakao Hangul Analyzer III) morphological analyzer and Neo4J graph database. In the proposed chatbot system, we use a morpheme analyzer, a proper noun dictionary including tourist destination names, and a general noun dictionary including containing frequently used words in tourist information search to understand the intention of the user's question. The tourism knowledge base built using the Neo4J graph database provides adequate answers to tourists' questions. In this paper, the nodes of Neo4J are Area based on tourist destination address, Contents with property of tourist information, and Service including service attribute data frequently used for search. A Neo4J query is created based on the result of analyzing the intention of a tourist's question with the property of nodes and relationships in Neo4J database. An answer to the question is made by searching in the tourism knowledge base. In this paper, we create the tourism knowledge base using more than 1300 Jeju tourism information used in the smart tourism app. We plan to develop a multilingual smart tour chatbot using the named entity recognition (NER), intention classification using conditional random field(CRF), and transfer learning using the pretrained language models.

• Journal of the Korea Convergence Society
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• v.9 no.12
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• pp.39-45
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• 2018

Twitter users use 'Following', 'Retweet' and so on to find tweets that they are interested in. However, it is difficult for users to find tweets that are of interest to them on Twitter, which has more than 300 million users. In this paper, we developed a customized tweet recommendation system to resolve it. First, we gather current trends to collect tweets that are worth recommending to users and popular tweets that talk about trends. Later, to analyze users and recommend customized tweets, the users' tweets and the collected tweets are categorized. Finally, using Web service, we recommend tweets that match with user categorization and users whose interests match. Consequentially, we recommended 67.2% of proper tweet.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.331-337
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• 2014

Paradigm shift to cloud computing has increased the importance of security. Even though public cloud computing providers such as Amazon, already provides security related service like firewall and identity management services, it is not suitable to protect data in cloud environments. Because in public cloud computing environments do not allow to use client's own security solution nor equipments. In this environments, user are supposed to do something to enhance security by their hands, so the needs of visualized security management arises. To implement visualized security management, developing near realtime data handling & packet classification mechanisms are crucial. The key technical challenges in packet classification is how to classify packet in the manner of unsupervised way without human interactions. To achieve the goal, this paper presents automated packet classification mechanism based on naive-bayesian and packet Chunking techniques, which can identify signature and does machine learning by itself without human intervention.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.1
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• pp.111-116
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• 2019

The fire detectors used in the engine rooms of ships offer only a slow response to emergencies because smoke or heat must reach detectors installed on ceilings, but the air flow in engine rooms can be very fluid depending on the use of equipment. In order to overcome these disadvantages, much research on video-based fire detection has been conducted in recent years. Video-based fire detection is effective for initial detection of fire because it is not affected by air flow and transmission speed is fast. In this paper, experiments were performed using images of smoke from a smoke generator in an engine room. Data generated using LBP and GLCM operators that extract the textural features of smoke was classified using SVM, which is a machine learning classifier. Even if smoke did not rise to the ceiling, where detectors were installed, smoke detection was confirmed using the image-based technique.