• Journal of the Korea Computer Graphics Society
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• v.16 no.1
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• pp.1-7
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• 2010

With the widespread use of vision-based surveillance systems, the capability for person identification is now an essential component. However, the CCTV cameras used in surveillance systems tend to produce relatively low-resolution images, making it difficult to use face recognition techniques for person identification. Therefore, an algorithm is proposed for person identification in CCTV camera images based on the clothing. Whenever a person is authenticated at the main entrance of a building, the clothing feature of that person is extracted and added to the database. Using a given image, the clothing area is detected using background subtraction and skin color detection techniques. The clothing feature vector is then composed of textural and color features of the clothing region, where the textural feature is extracted based on a local edge histogram, while the color feature is extracted using octree-based quantization of a color map. When given a query image, the person can then be identified by finding the most similar clothing feature from the database, where the Euclidean distance is used as the similarity measure. Experimental results show an 80% success rate for person identification with the proposed algorithm, and only a 43% success rate when using face recognition.

• Journal of the Korea Society of Computer and Information
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• v.16 no.8
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• pp.29-38
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• 2011

Unlike in traditional row-oriented database systems, a column-oriented database system stores data in column-oriented and not row-oriented order. Recently, research results revealed the effectiveness of column-oriented databases for applications such as data warehouse and decision support systems that access large volumes of data in a read only manner. In this paper, we investigate the join strategies for column-oriented databases and prove the effectiveness of column-oriented databases in data warehouse systems. For unbiased comparison, the two database systems are analyzed using the star schema benchmark and the performance analysis of a star schema join query is carried out. We experimented with well-known join algorithms and considered early materialization and late materialization join strategies for column-oriented databases. The performance results confirm that star schema join queries perform better in terms of disk I/O cost in column-oriented databases than in row-oriented databases. In addition, the late materialization strategy showed more performance gain than the early materialization strategy in column-oriented databases.

• Korean Journal of Remote Sensing
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• v.31 no.6
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• pp.561-570
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• 2015

Till now, applications of many kinds of satellite images have been accentuated in the datacentric scientific studies, researches regarding system development and concerned technologies for them are on the un-matured stage. Especially, satellite image processing requires large volume data handling and specific analysis functionalities, so that practical necessity of base study for system development is emphasized on. In the view of information system, various edged trends such as web standards, cloud computing, or web framework are utilized owing to their application benefits proven and business needs. Considered these aspects, a testing implementation was carried out using OpenStack cloud computing environment and e-government framework. As for the processing functions, WPS in GeoServer, as one of OGC web standards, was applied to perform interoperable data processing scheme between two or more remote servers. Working with the server implemented, client-side was also developed using several open sources such as HTML 5, jQuery, and OpenLayers. If it is that completed further experiments onsite applications with actual multi-data sets and extension of on-demand functionalities with the result of this study, it will be referred as an example case model for complicated and complex system design and implementation which needs cloud computing, geo-spatial web standards and web framework.

• The Journal of the Korea Contents Association
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• v.8 no.12
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• pp.37-44
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• 2008

Data entered into RFID tags are used for saving costs and enhancing competitiveness in the development of applications in various industrial areas. RFID readers perform the identification and search of hundreds of objects, which are tags. RFID technology that identifies objects on request of dynamic linking and tracking is composed of application components supporting information infrastructure. Despite their many advantages, existing applications, which do not consider elements related to real.time data communication among remote RFID devices, cannot support connections among heterogeneous devices effectively. As different network devices are installed in applications separately and go through different query analysis processes, there happen the delays of monitoring or errors in data conversion. The present study implements a RFID database handling system in semantic Web environment for integrated management of information extracted from RFID tags regardless of application. Users’ RFID tags are identified by a RFID reader mounted on an application, and the data are sent to the RFID database processing system, and then the process converts the information into a semantic Web language. Data transmitted on the standardized semantic Web base are translated by a smart browser and displayed on the screen. The use of a semantic Web language enables reasoning on meaningful relations and this, in turn, makes it easy to expand the functions by adding modules.

• Journal of KIISE
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• v.44 no.10
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• pp.1112-1123
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• 2017

As content providers further offload content-centric services to the cloud, data retrieval over the cloud typically results in many redundant items because there is a prevalent near-duplication of content on the Internet. Simply fetching all data from the cloud severely degrades efficiency in terms of resource utilization and bandwidth, and data can be encrypted by multiple content providers under different keys to preserve privacy. Thus, locating near-duplicate data in a privacy-preserving way is highly dependent on the ability to deduplicate redundant search results and returns best matches without decrypting data. To this end, we propose an efficient near-duplicate detection scheme for encrypted data in the cloud. Our scheme has the following benefits. First, a single query is enough to locate near-duplicate data even if they are encrypted under different keys of multiple content providers. Second, storage, computation and communication costs are alleviated compared to existing schemes, while achieving the same level of search accuracy. Third, scalability is significantly improved as a result of a novel and efficient two-round detection to locate near-duplicate candidates over large quantities of data in the cloud. An experimental analysis with real-world data demonstrates the applicability of the proposed scheme to a practical cloud system. Last, the proposed scheme is an average of 70.6% faster than an existing scheme.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.135-135
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• 2017

The Gramene database (http://www.gramene.org) is a powerful online resource for agricultural researchers, plant breeders and educators that provides easy access to reference data, visualizations and analytical tools for conducting cross-species comparisons. Learn the benefits of using Gramene to enrich your lectures, accelerate your research goals, and respond to your organismal community needs. Gramene's genomes portal hosts browsers for 44 complete reference genomes, including crops and model organisms, each displaying functional annotations, gene-trees with orthologous and paralogous gene classification, and whole-genome alignments. SNP and structural diversity data, available for 11 species, are displayed in the context of gene annotation, protein domains and functional consequences on transcript structure (e.g., missense variant). Browsers from multiple species can be viewed simultaneously with links to community-driven organismal databases. Thus, while hosting the underlying data for comparative studies, the portal also provides unified access to diverse plant community resources, and the ability for communities to upload and display private data sets in multiple standard formats. Our BioMart data mining interface enable complex queries and bulk download of sequence, annotation, homology and variation data. Gramene's pathway portal, the Plant Reactome, hosts over 240 pathways curated in rice and inferred in 66 additional plant species by orthology projection. Users may compare pathways across species, query and visualize curated expression data from EMBL-EBI's Expression Atlas in the context of pathways, analyze genome-scale expression data, and conduct pathway enrichment analysis. Our integrated search database and modern user interface leverage these diverse annotations to facilitate finding genes through selecting auto-suggested filters with interactive views of the results.

• The Journal of the Korea Contents Association
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• v.8 no.11
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• pp.412-425
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• 2008

One of the important elements for improving academic achievement of learners in education through e-learning is to support learners to study by finding questions they want with providing various evaluation questions. However, most of question retrieval systems usually depend on keyword search based on only a syntactical analysis and/or a hierarchical browsing system classified by the topics of subjects. In such a system it is not easy to find integrative questions associated with each other. In order to improve this problem, in this paper we proposed a question management and retrieval system which allows users to easily manage questions and also to effectively find questions for study on the Web. Then, we implemented a system that gives to access questions for the domain of C language programming. The system makes it possible to easily search questions related to not only a single theme but also questions integrated by interrelationship between topics and questions. This is done by supporting to be able to retrieve questions according to conceptual interrelationships between questions from user query. Consequently, it is expected that the proposed system will provide learners to understand the basic theories and the concepts of the subjects as well as to improve the ability of comprehensive knowledge utilization and problem-solving.

• Journal of KIISE:Databases
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• v.30 no.5
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• pp.476-493
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• 2003

Data broadcast is an effective data transmission method from a data base server to numerous mobile clients due to the restrictions on mobile environment such as low wireless communication bandwidth and energy shortage of mobile devices. There are various broadcast methods based on clients' data access frequencies or semantic relationship of data. The broadcast schedule based only on the access frequencies does not consider semantic relations of data, so that when a client needs to access a series of semantically related data, the client has to listen to the wireless channel for a long time. On the other hand, the broadcast schedule based only on semantic relationship of data makes data access time longer when clients highly request specific data which are not semantically related but frequently accessed. In this paper, we present an efficient data broadcast method based on not only data access frequencies but also semantic relationship to improve mobile clients' query response time. The new hybrid broadcast method we propose creates a data broadcast schedule according to the data access frequencies and then the schedule is adjusted to reflect semantic relationship of data. We show our method is efficient by experimental performance analysis.

• Journal of Advanced Navigation Technology
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• v.15 no.6
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• pp.1015-1024
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• 2011

Mobile P2P protocols in ad-hoc networks have gained large attention recently. Although there has been much research on P2P algorithms for wired networks, existing P2P protocols are not suitable for mobile ad-hoc networks because they do not consider mobility of peers. This study proposes a new cluster-based P2P protocol for ad hoc networks which utilizes peer mobility. In typical cluster-based P2P algorithms, each cluster has a super peer and other peers of the cluster register their file list to the super peer. High mobility peers would cause a lot of file list registration traffic because they hand-off between clusters frequently. In the proposed scheme, while peers with low mobility behave in the same way as the peers of the typical cluster-based P2P schemes, peers with high mobility behave differently. They inform their entrance to the cluster region to the super peer but they do not register their file list to the super peer. When a peer wishes to find a file, it first searches the registered file list of the super peer and if fails, query message is broadcasted. We perform mathematical modeling, analysis and optimization of the proposed scheme regarding P2P traffic and associated routing traffic. Numerical results show that the proposed scheme performs much better than or similar to the typical cluster-based P2P scheme and flooding based Gnutella.

• Horticultural Science & Technology
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• v.29 no.6
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• pp.633-640
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• 2011

Brassica rapa is an A genome model species for Brassica crop genetics, genomics, and breeding. With the completion of sequencing the B. rapa genome, functional analysis of the genome is forthcoming issue. The expressed sequence tags are fundamental resources supporting annotation and functional analysis of the genome including identification of tissue-specific genes and promoters. As of July 2011, 147,217 ESTs from 39 cDNA libraries of B. rapa are reported in the public database. However, little information can be retrieved from the sequences due to lack of organized databases. To leverage the sequence information and to maximize the use of publicly-available EST collections, the Brassica rapa tissue-specific EST database (BrTED) is developed. BrTED includes sequence information of 23,962 unigenes assembled by StackPack program. The unigene set is used as a query unit for various analyses such as BLAST against TAIR gene model, functional annotation using MIPS and UniProt, gene ontology analysis, and prediction of tissue-specific unigene sets based on statistics test. The database is composed of two main units, EST sequence processing and information retrieving unit and tissue-specific expression profile analysis unit. Information and data in both units are tightly inter-connected to each other using a web based browsing system. RT-PCR evaluation of 29 selected unigene sets successfully amplified amplicons from the target tissues of B. rapa. BrTED provided here allows the user to identify and analyze the expression of genes of interest and aid efforts to interpret the B. rapa genome through functional genomics. In addition, it can be used as a public resource in providing reference information to study the genus Brassica and other closely related crop crucifer plants.