• Journal of Information Management
• /
• v.41 no.3
• /
• pp.191-209
• /
• 2010

A reference linking service that is connection of each other different information resource need to setup the reference database and to match identifier. CrossRef, PubMed and Web Of Science etc. the many overseas agencies developed reference linking service, that they used the automatic tools of Inera eXstyles, Parity Computings Reference Extractor etc. and setup in base DOI and PMID etc. Domestic the various agencies of KISTI(Korea Institute Science and Technology of Information), KRF(Korea Research Foundation) etc are construction reference database. But each research communities adopts a various reference bibliography writing format. As, the data base construction which is collect is confronting is many to being difficult. In this paper, We developed the Citation Matcher System. This system is automatic parsing the reference string to metadata and matching DOI, PMID and KOI as Identifier. It is improved the effectiveness of reference database setup.

• KIISE Transactions on Computing Practices
• /
• v.24 no.3
• /
• pp.138-144
• /
• 2018

A video is a vivid medium similar to human's visual-linguistic experiences, since it can inculcate a sequence of situations, actions or dialogues that can be told as a story. In this study, we propose story learning/regeneration frameworks from videos with successive event order supervision for contextual coherence. The supervision induces each episode to have a form of trajectory in the latent space, which constructs a composite representation of ordering and semantics. In this study, we incorporated the use of kids videos as a training data. Some of the advantages associated with the kids videos include omnibus style, simple/explicit storyline in short, chronological narrative order, and relatively limited number of characters and spatial environments. We build the encoder-decoder structure with successive event order embedding, and train bi-directional LSTMs as sequence models considering multi-step sequence prediction. Using a series of approximately 200 episodes of kids videos named 'Pororo the Little Penguin', we give empirical results for story regeneration tasks and SEOE. In addition, each episode shows a trajectory-like shape on the latent space of the model, which gives the geometric information for the sequence models.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.12 no.12
• /
• pp.2259-2264
• /
• 2008

Significant genes are defined as genes in which the expression level characterizes a specific experimental condition. Such genes in which the expression levels differ significantly between different groups are highly informative relevant to the studied phenomenon. In this paper, first the system can detect informative genes by similarity scale combination method being proposed in this paper after normalizing data with methods that are the most widely used among several normalization methods proposed the while. And it compare and analyze a performance of each of normalization methods with multi-perceptron neural network layer. The Result classifying in Multi-Perceptron neural network classifier for selected 200 genes using combination of PC(Pearson correlation coefficient) and ED(Euclidean distance coefficient) after Lowess normalization represented the improved classification performance of 98.84%.

• Journal of the Korean Society for information Management
• /
• v.34 no.1
• /
• pp.219-239
• /
• 2017

As IT technology develops rapidly and the personal dissemination of smart devices increases, video material is especially used as a medium of information transmission among audiovisual materials. Video as an information service content has become an indispensable element, and it has been used in various ways such as unidirectional delivery through TV, interactive service through the Internet, and audiovisual library borrowing. Especially, in the Internet environment, the information provider tries to reduce the effort and cost for the processing of the provided information in view of the video service through the smart device. In addition, users want to utilize only the desired parts because of the burden on excessive network usage, time and space constraints. Therefore, it is necessary to enhance the usability of the video by automatically classifying, summarizing, and indexing similar parts of the contents. In this paper, we propose a method of automatically segmenting the shots that make up videos by analyzing the contents and characteristics of language education videos and indexing the detailed contents information of the linguistic videos by combining visual features. The accuracy of the semantic based shot segmentation is high, and it can be effectively applied to the summary service of language education videos.

• Proceedings of the Acoustical Society of Korea Conference
• /
• autumn
• /
• pp.105-108
• /
• 1999

TTS(Text-To-Speech) 시스템 합성음성의 자연감을 개선하기 위해 하나의 언어에 대해 존재하는 운율 법칙을 정확히 구현해야 한다. 존재하는 운율 법칙을 추출하기 위해서는 방대한 분량의 언어 자료 구축이 필요하다. 그러나 이 방법은 존재하는 운율 현상이 포함된 언어자료에 대해 완벽한 운율을 파악할 수 없으므로 합성음성의 질을 좋게 할 수 없다. 본 논문은 한국어 음성의 운율을 학습하기 위해 2개의 인공 신경망을 제안한다. 하나의 신경망으로 문장의 각 음소에 대한 피치 변화를 학습시키는 것이며, 다른 하나는 에너지 변화를 학습하도록 하였다. 신경망은 BP 신경망을 이용하며 11개의 음소를 나타내기 위해 11개의 입력과, 중간 음소의 피치와 에너지 변화곡선을 근사하는 다항식 계수를 출력하도록 하였다. 신경망시스템의 학습과 평가에 앞서, 음성학적 균형잡힌 고립단어를 기반으로 의미있는 문장을 구성하였다. 문장을 남자 화자로 하여금 읽게 하고 녹음하여 음성 DB를 구축하였다. 음성 DB에 대해 각 음소의 운율 정보를 수집하여 신경망에 맞는 목표 패턴과 훈련 패턴을 작성하였다. 이 목표 패턴은 회귀분석을 통한 추세선을 이용해 피치와 에너지에 대한 2차 다항식계수로 구성하였다. 본 논문은 목표패턴에 맞는 신경망을 학습시켜 좋은 결과를 얻었다.

• Journal of KIISE:Computing Practices and Letters
• /
• v.8 no.6
• /
• pp.679-691
• /
• 2002

Volume visualization is an important subarea of scientific visualization, and is concerned with techniques that are effectively used in generating meaningful and visual information from abstract and complex volume datasets, defined in three- or higher-dimensional space. It has been increasingly important in various fields including meteorology, medical science, and computational fluid dynamics, and so on. On the other hand, virtual reality is a research field focusing on various techniques that aid gaining experiences in virtual worlds with visual, auditory and tactile senses. In this paper, we have developed a visualization system for CAVE, an immersive 3D virtual environment system, which generates stereoscopic images from huge human volume datasets in real-time using an improved volume visualization technique. In order to complement the 3D texture-mapping based volume rendering methods, that easily slow down as data sizes increase, our system utilizes an image-based rendering technique to guarantee real-time performance. The system has been designed to offer a variety of user interface functionality for effective visualization. In this article, we present detailed description on our real-time stereoscopic visualization system, and show how the Visible Korean Human dataset is effectively visualized on CAVE.

• Journal of Navigation and Port Research
• /
• v.29 no.10 s.106
• /
• pp.883-890
• /
• 2005

Database Integration problems has been recognized as a critical issue for effective logistics service in logistics environment. However, researches related to effective methodology for this have been studied theoretically in the DB schema integration, are insufficient in the side of the system realization. The aim of this paper is to present a schema integration technique to integrate DB using XML( eXtensible Markup Language) in the part of practical DB integration, a quantitative methodology for the identification of conflict that is a representative problem on database integration. To achieve this aim, we extracted the entity name and attribute name from DB schema and suggested a quantitative methodology to easily fine name conflict that frequently give raise to a trouble when schema integration, based on the level of semantic similarity between attributes and entities.

• The Korean Journal of Applied Statistics
• /
• v.29 no.6
• /
• pp.1007-1023
• /
• 2016

This paper explores the conditions and potential of newly designed and tried methodology of big data analysis that apply to Korean history subject matter. In order to advance them, we need to pay more attention to quantitative analysis methodologies over pre-existing qualitative analysis. To obtain our new challenge, I propose 'digital history' methods along with associated disciplines such as linguistics and computer science, data science and statistics, and visualization techniques. As one example, I apply interdisciplinary convergence approaches to the principle and mechanism of elite reproduction during the Korean medieval age. I propose how to compensate for a lack of historical material by applying a semi-supervised learning method, how to create a database that utilizes text-mining techniques, how to analyze quantitative data with statistical methods, and how to indicate analytical outcomes with intuitive visualization.

• Journal of Korean Society of Transportation
• /
• v.27 no.1
• /
• pp.27-34
• /
• 2009

The operational effect of traffic signal control improvement was evaluated using the Two-Fluid Model. The parameters engaged in the Two-Fluid Model becomes food indicators to measure the quality of traffic flow due to the improvement of traffic signal operation. A series of experiment were conduced for the 31 signalized intersections in Uijeongbu City. To estimate the parameters in the Two-Fluid Model the trajectory informations of individual vehicles were collected using the CORSIM and Run Time Extension. The test results showed 35 percent decrease of average minimum trip time per unit distance. One of the parameters in the Two-Fluid Model is a measure of the resistance of the network to the degraded operation with the increased demand. The test result showed 28 percent decrease of this parameter. In spite of the simulation results of the arterial flow, it was concluded that the Two-Fluid Model is useful tool to evaluate the improvement of the traffic signal control system from the macroscopic aspect.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2005.10a
• /
• pp.353-360
• /
• 2005

Database Integration problems has been recognized as a critical issue for effective logistics service in logistics environment. However, researches related to effective methodology for this have been studied theoretically in the DB schema integration, are insufficient in the side of the system realization. The aim of this paper is to present a schema integration technique to integrate DB using XML(eXtensible Markup Language) in the part of practical DB integration, a quantitative methodology for the identification of conflict that is a representative problem on database integration. To achieve this aim, we extracted the entity name and attribute name from DB schema and suggested a quantitative methodology to easily fine name conflict that frequently give raise to a trouble when schema integration, based on the level of semantic similarity between attributes and entities.