• Proceedings of the Korean Information Science Society Conference
• /
• 1998.10c
• /
• pp.482-484
• /
• 1998

Abstract : Multimedia data now one of the widely used information in all the fields as the fast developments of computer techniques have been made. Traditional database systems based on textual information have limitations when applied to multimedia information. This is because simple textual descriptions are ambiguous and inadequate for searching multimedia information for multimedia databases and digital libraries. Thus, especially for image data, which is one of the important multimedia information types, which can retrieve and browse image data on the basis of pictorial queries. Therefore, this paper presents an efficient method for describing texture information in image data.

• Proceedings of the Korean Information Science Society Conference
• /
• 2006.06b
• /
• pp.193-195
• /
• 2006

As multimedia information increases sharply, In image retrieval field the method that can analyze image data quickly and exactly is required. In the case of image data, because each data includes a lot of informations, between accuracy and speed of retrieval become trade-off. To solve these problem, feature vector extracting process that use Genetic Algorithm for implementing prompt and correct image clustering system in case of retrieval of mass image data is proposed. After extracting color and texture features, the representative feature vector among these features is extracted by using Genetic Algorithm.

• Journal of Computing Science and Engineering
• /
• v.1 no.2
• /
• pp.195-210
• /
• 2007

Dwarf is a highly compressed structure, which compresses the cube by eliminating the semantic redundancies while computing a data cube. Although it has high compression ratio, Dwarf is slower in querying and more difficult in updating due to its structure characteristics. We all know that the original intention of data cube is to speed up the query performance, so we propose two novel clustering methods for query optimization: the recursion clustering method which clusters the nodes in a recursive manner to speed up point queries and the hierarchical clustering method which clusters the nodes of the same dimension to speed up range queries. To facilitate the implementation, we design a partition strategy and a logical clustering mechanism. Experimental results show our methods can effectively improve the query performance on data cubes, and the recursion clustering method is suitable for both point queries and range queries.

• Proceedings of the Korean Information Science Society Conference
• /
• 2006.10a
• /
• pp.395-398
• /
• 2006

임베디드 시스템의 발달로 인해 기존의 컴퓨팅 패러다임(Paradigm)이 모바일이나 웨어러블 컴퓨팅 등 임베디드 환경으로 급격하게 변화하고 있다. 이렇게 컴퓨팅 패러다임이 변화해도 정보 서비스에 대한 기술이 여전히 필요하다. 네트웍 환경에서 많이 사용하고 있는 정보 서비스 기술중의 하나인 Data Distribution Service(DDS)는 간단한 통신 메커니즘을 기반으로 하면서도 높은 성능으로 정보 서비스를 제공할 수 있다. 따라서, 본 논문에서는 실시간 운영체제를 사용하는 내장형 시스템에 Data Distribution Service(DDS)를 적용하여 데이터의 수집과 전송을 효율적으로 사용하게 하였다.

• Journal of Computing Science and Engineering
• /
• v.1 no.2
• /
• pp.125-160
• /
• 2007

Data Warehousing and OLAP (On-Line Analytical Processing) have turned into the key technology for comprehensive data analysis. Originally developed for the needs of decision support in business, data warehouses have proven to be an adequate solution for a variety of non-business applications and domains, such as government, research, and medicine. Analytical power of the OLAP technology comes from its underlying multidimensional data model, which allows users to see data from different perspectives. However, this model displays a number of deficiencies when applied to non-conventional scenarios and analysis tasks. This paper presents an attempt to systematically summarize various extensions of the original multidimensional data model that have been proposed by researchers and practitioners in the recent years. Presented concepts are arranged into a formal classification consisting of fact types, factual and fact-dimensional relationships, and dimension types, supplied with explanatory examples from real-world usage scenarios. Both the static elements of the model, such as types of fact and dimension hierarchy schemes, and dynamic features, such as support for advanced operators and derived elements. We also propose a semantically rich graphical notation called X-DFM that extends the popular Dimensional Fact Model by refining and modifying the set of constructs as to make it coherent with the formal model. An evaluation of our framework against a set of common modeling requirements summarizes the contribution.

• Korean Journal of Remote Sensing
• /
• v.18 no.1
• /
• pp.61-69
• /
• 2002

The purpose of Electro-Optical Camera (EOC), the primary payload of KOMPSAT-1, is to collect high resolution visible imagery of the Earth including Korean Peninsula. EOC images will be distributed to the public or many user groups including government, public corporations, academic or research institutes. KARI will offer the online service to the users through internet. Some application, e.g., generation of Digital Elevation Model (DEM), needs a secondary data such as satellite ephemeris data, attitude data to process the EOC imagery. EOC imagery with these ancillary information will be distributed in a file of Hierarchical Data Format (HDF) file formal. HDF is a physical file format that allows storage of many different types of scientific data including images, multidimensional data arrays, record oriented data, and point data. By the lack of public domain softwares supporting HDF file format, many public users may not access EOC data without difficulty. The purpose of this research is to develop a browsing system of EOC data for the general users not only for scientists who are the main users of HDF. The system is PC-based and huts user-friendly interface.

• Journal of KIISE:Information Networking
• /
• v.36 no.2
• /
• pp.108-117
• /
• 2009

Data aggregation is one of the well-known techniques to reduce the energy consumption for information transmission over wireless sensor networks (WSN). As the WSNs are deployed in untrusted or even hostile environments, the data aggregation becomes problematic when end-to-end data privacy including data confidentiality and integrity between sensor nodes and base station, is required. Meanwhile, data homomorphic cryptoschemes have been investigated recently and recommended to provide the end-to-end privacy in the hostile environments. In order to assure both data confidentiality and integrity for data aggregation, this paper analyzes the existing homomorphic cryptoschemes and digital signature schemes, proposes possible combinations, and evaluates their performance in terms of CPU overheads and communication costs.

• Journal of KIISE:Computer Systems and Theory
• /
• v.36 no.4
• /
• pp.283-290
• /
• 2009

The rank/select data structure is a basic tool of succinct representations for several data structures such as trees, graphs and text indexes. For a given string sequence, it is used to answer the occurrence of characters up to a certain position. In previous studies, theoretical rank/select data structures were proposed, but they didn't support practical operational time and space. In this paper, we propose a simple solution for implementing rank/select data structures efficiently. According to experiments, our methods without complex encodings achieve nH$_0$ + O(n) bits of theoretical size and perform rank/select operations faster than the original HSS data structure.

• Journal of KIISE:Information Networking
• /
• v.33 no.4
• /
• pp.324-332
• /
• 2006

A caching is a useful technique to alleviate performance degradation due to the inherent narrow bandwidth by reducing contention of broadcast requests. In this paper, we propose a caching strategy for pull-based data broadcast system which considers data popularity among clients. In addition, the proposed strategy also reflects recentness of data access based on data broadcast version. Then, we evaluate the performance of proposed strategy through a simulation approach. According to the results, the strategy considering both hit ratio and miss cost shows better performance than the traditional LRU. In addition, the strategy considering data popularity among clients shows better performance in some cases.

• Journal of KIISE:Databases
• /
• v.30 no.5
• /
• pp.521-531
• /
• 2003

Multi-level geographic data can be mainpulated by a window query such as a zoom operation. In order to handle multi-level geographic data efficiently, a spatial indexing method supporting a window query is needed. However, the conventional spatial indexing methods are not efficient to access multi-level geographic data quickly. To solve it, other a few spatial indexing methods for multi-level geographic data are known. However these methods do not support all types of multi-level geographic data. This paper presents a new efficient spatial indexing method, the MLR-tree for window query of multi-level geographic data. The MLR-tree offers both high search performance and no data redundancy. Experiments show them. Moreover, the MLR-tree supports all types of multi-level geographic data.