• Journal of Korea Spatial Information System Society
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• v.7 no.2 s.14
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• pp.39-45
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• 2005

Nowadays, the demand of the output analyzed from the grid data have been sharply increased as the remote sensing technologies and GIS related industry have been developed. Therefore, a metadata access system which fits the requirements of the users should be developed for better managing and utilizing gridded data. In this background, this study defined a common application schema through the analysis of the metadata built by numerous institutes based on the draft metadata standards. The draft metadata standards has been proposed from the study supported by ETRI at 2003 which mainly concentrated on establishing the standards of distributing metadata for the grid data. Also, XML based integrated system was developed to access metadata maintained by SaTReC as well as SIMC to facilitate more convenient data access for the grid data users. The results of the pilot system developed from this study can be expected to contribute to build more efficient and enlarged integrated access system of metadata for grid data.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.1
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• pp.34-43
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• 2000

Replicated data that is used for fault tolerant distributed system requires replica control protocol to maintain data consistency. The one of replica control protocols is quorum consensus method which accesses replicated data by getting majority approval. If site failure or communication link failure occurs and any one can't get quorum consensus, it degrades the availability of data managed by quorum consensus protocol. So it needs for ghost to replace the failed site. Because ghost is not full replica but process which has state information using meta data, it is important to simplify meta data. In order to maintain availability and simplify meta data, we propose a method to use cohort set as ghost's meta data. The proposed method makes it possible to organize meta data in 2N+logN bits and to have higher availability than quorum consensus only with cohort set and dynamic linear voting protocol. Using Markov model we calculate proposed method's availability to analyze availability and compare it with existing protocols.

• Journal of Periodontal and Implant Science
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• v.51 no.1
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• pp.18-29
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• 2021

Purpose: The aim of this study was to compare the characteristic expression patterns of advanced periodontitis in 2 cohort data sets analyzed using different microarray platforms, and to identify differentially expressed genes (DEGs) through a meta-analysis of both data sets. Methods: Twenty-two patients for cohort 1 and 40 patients for cohort 2 were recruited with the same inclusion criteria. The 2 cohort groups were analyzed using different platforms: Illumina and Agilent. A meta-analysis was performed to increase reliability by removing statistical differences between platforms. An integrative meta-analysis based on an empirical Bayesian methodology (ComBat) was conducted. DEGs for the integrated data sets were identified using the limma package to adjust for age, sex, and platform and compared with the results for cohorts 1 and 2. Clustering and pathway analyses were also performed. Results: This study detected 557 and 246 DEGs in cohorts 1 and 2, respectively, with 146 and 42 significantly enriched gene ontology (GO) terms. Overlapping between cohorts 1 and 2 was present in 59 DEGs and 18 GO terms. However, only 6 genes from the top 30 enriched DEGs overlapped, and there were no overlapping GO terms in the top 30 enriched pathways. The integrative meta-analysis detected 34 DEGs, of which 10 overlapped in all the integrated data sets of cohorts 1 and 2. Conclusions: The characteristic expression pattern differed between periodontitis and the healthy periodontium, but the consistency between the data sets from different cohorts and metadata was too low to suggest specific biomarkers for identifying periodontitis.

• Journal of Korea Multimedia Society
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• v.23 no.8
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• pp.986-1005
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• 2020

In this paper, we propose AnoVid, an automated video annotation tool based on deep neural networks, that automatically generates various meta data for each scene or shot in a long drama video containing rich elements. To this end, a novel meta data schema for drama video is designed. Based on this schema, the AnoVid video annotation tool has a total of six deep neural network models for object detection, place recognition, time zone recognition, person recognition, activity detection, and description generation. Using these models, the AnoVid can generate rich video annotation data. In addition, AnoVid provides not only the ability to automatically generate a JSON-type video annotation data file, but also provides various visualization facilities to check the video content analysis results. Through experiments using a real drama video, "Misaeing", we show the practical effectiveness and performance of the proposed video annotation tool, AnoVid.

• The Journal of Society for e-Business Studies
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• v.7 no.1
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• pp.141-152
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• 2002

Data dictionary is a collection of meta-data, which describes data produced and consumed while performing business processes. Data dictionary is an essential element for business process standardization and automation, and has a fundamental role in ERP application management and customization. Also, data dictionary facilitates B2B processes by enabling painless integration of business processes between various enterprises. We implemented data dictionary support in SEA＋, a component- based scalable ERP system developed in ETRI, and found out that it's a plausible feature of business information system. We discovered that data dictionary promotes semantic, not syntactic, data management, which can make it possible to leverage viability of the tool in the coming age of more meta-data oriented computing world. We envision that business data dictionary is a firm foundation of adapting business knowledge, applications and processes into the semantic web based enterprise infra-structure.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.148-153
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• 2022

In keeping with the fourth industrial revolution, IoT-based environments are being implemented everywhere, and as a result, there is an increasing number of cases in which various types of sensed data are utilized efficiently. In particular, the number of multimedia application cases using smart devices is increasing, and there is an increasing number of cases in which large amounts of data are used as fast and convenient as small amounts of data. Given the increasing size of files used in smart devices, the study designed a modified Htree based on journaling meta data management in Ext4-based smart devices and analyzed performance through experiments of various methods. Performance evaluation analysis using IOZone and Hdread shows that the data size of 100Mbyte compared to the data input / output of existing htree is 10% or more, and that of the super large capacity file of 500Mbyte or more is 5% or more.

• The Journal of Bigdata
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• v.4 no.2
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• pp.93-103
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• 2019

In this paper, we introduce a big data platform and a metadata management technique for fishery science R & D information. The big data platform collects and integrates various types of fisheries science R & D information and suggests how to build it in the form of a data lake. In addition to existing data collected and accumulated in the field of fisheries science, we also propose to build a big data platform that supports diverse analysis by collecting unstructured big data such as satellite image data, research reports, and research data. Next, by collecting and managing metadata during data extraction, preprocessing and storage, systematic management of fisheries science big data is possible. By establishing metadata in a standard form along with the construction of a big data platform, it is meaningful to suggest a systematic and continuous big data management method throughout the data lifecycle such as data collection, storage, utilization and distribution.

• The Transactions of the Korea Information Processing Society
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• v.6 no.8
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• pp.2031-2041
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• 1999

In this paper, we present the HVIS (Hybrid Video Information System) which bolsters up meaning retrieval of all the various users by integrating feature-based retrieval and annotation-based retrieval of unformatted formed and massive video data. HVIS divides a set of video into video document, sequence, scene and object to model the metadata and suggests the Two layered Hybrid Object-oriented Metadata Model(THOMM) which is composed of raw-data layer for physical video stream, metadata layer to support annotation-based retrieval, content-based retrieval, and similarity retrieval. Grounded on this model, we presents the video query language which make the annotation-based query, content-based query and similar query possible and Video Query Processor to process the query and query processing algorithm. Specially, We present the similarity expression to appear degree of similarity which considers interesting of user. The proposed system is implemented with Visual C++, ActiveX and ORACLE.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.12
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• pp.2212-2220
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• 2006

Recently enterprises introduce EAI systems and legacy business which already obtained for data integration among legacy systems. EAI systems in cooperative transaction environment can be expected efficient retrieval as sharing and integrating. However existing legacy systems have to introduce particular EAI solution because it is difficult to adjust standard technology to EAI due to be managed independently without considering interoperability. For solving these problems we use metadata registry using data integration. Various types, semantic specification data heterogeneity and heterogeneity of systems, however, are occurred. Therefore retrieval system based on XMDR(extended Meta-Data Registry) for data interoperability in the web environment are proposed in this paper.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.3
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• pp.586-593
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• 2009

As most of the data configuration at distributed environment has a tree structure following the hierarchical classification, relative data retrieve is limited. Among these data, the data stored in a database has a problem in integration and efficient retrieve. Accordingly, we suggest the system that uses XMDR for distributed database integration and links XMDR to TopicMap for efficient retrieve of knowledge expressed hierarchically. We proposes a plan for efficient integration retrieve through using the XMDR which is composed of Meta Semantic Ontology, Instance Semantic Ontology and meta location, solves data heterogeneity and metadata heterogeneity problem and integrates them, and replaces the occurrence of the TopicMap with the Meta Location of the XMDR, which expresses the resource location of TopicMap by linking Meta Semantic Ontology and Instance Semantic Ontology of XMDR to the TopicMap.