• The KIPS Transactions:PartD
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• v.13D no.5 s.108
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• pp.633-640
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• 2006

Spatial clustering, which groups similar objects based on their distance, connectivity, or their relative density in space, is an important component of spatial data mining. Density-based and grid-based clustering are two main clustering approaches. The former is famous for its capability of discovering clusters of various shapes and eliminating noises, while the latter is well known for its high speed. Clustering large data sets has always been a serious challenge for clustering algorithms, because huge data set would make the clustering process extremely costly. In this paper, we propose an enhanced Density-Grid based Clustering algorithm for Large spatial database by setting a default number of intervals and removing the outliers effectively with the help of a proper measurement to identify areas of high density in the input data space. We use a density threshold DT to recognize dense cells before neighbor dense cells are combined to form clusters. When proposed algorithm is performed on large dataset, a proper granularity of each dimension in data space and a density threshold for recognizing dense areas can improve the performance of this algorithm. We combine grid-based and density-based methods together to not only increase the efficiency but also find clusters with arbitrary shape. Synthetic datasets are used for experimental evaluation which shows that proposed method has high performance and accuracy in the experiments.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.13-18
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• 1999

Land cover map of 30 arc-second grid by NOAA AVHRR data for the whole Asia was produced by the authors as the project of the Asian Association on Remote Sensing(AARS). Land cover change monitoring of continental scale by satellite data needs preprocessing to remove undesirable factors due to noises, atmosphere, or the effect by solar zenith angle. The paper describes the method to remove these factors. The most important thing for better mapping/monitoring in the future is the accumulation of ground truth data by many land cover related researchers. The project of the development of Global Land Cover Ground Truth Database(GLCGT-DB) is proposed.

• Journal of Electrical Engineering and Technology
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• v.7 no.3
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• pp.376-383
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• 2012

A number of scientific researches are currently being conducted on the potential health hazards of power frequency electric and magnetic field (EMF). There exists a non-objective and psychological belief that they are harmful, although no scientific and objective proof of such exists. This possible health risk from ELF magnetic field (MF) exposure, especially for children under 17 years of age, is currently one of Korea's most highly contested social issues. Therefore, to assess the magnetic field exposure levels of those children in their general living environments, the personal MF exposure levels of 436 subjects were measured for about 6 years using government funding. Using the measured database, estimation formulas were developed to predict personal MF exposure levels. These formulas can serve as valuable tools in estimating 24-hour personal MF exposure levels without directly measuring the exposure. Three types of estimation formulas were developed by applying evolutionary computation methods such as genetic algorithm (GA) and genetic programming (GP). After tuning the database, the final three formulas with the smallest estimation error were selected, where the target estimation error was approximately 0.03 ${\mu}T$. The seven parameters of each of these three formulas are gender (G), age (A), house type (H), house size (HS), distance between the subject's residence and a power line (RD), power line voltage class (KV), and the usage conditions of electric appliances (RULE).

• Nuclear Engineering and Technology
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• v.40 no.1
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• pp.21-36
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• 2008

High bum-up fuel technology has been developed through a national R&D program, which covers key technology areas such as claddings, $UO_2$ pellets, spacer grids, performance code, and fuel assembly tests. New cladding alloys were developed through alloy designs, tube fabrication, out-of-pile test and in-reactor test. The new Zr-Nb tubes are found to be much better in their corrosion resistance and creep strength than the Zircaloy-4 tube, owing to an optimized composition and heat treatment of the new Zr-Nb alloys. A new fabrication technology for large grain $UO_2$ pellets was developed using various uranium oxide seeds and a micro-doping of Al. The uranium oxide seeds, which were added to $UO_2$ powder, were prepared by oxidizing and heat-treating scrap $UO_2$ pellets. A $UO_2$ pellet containing tungsten channels was fabricated for a thermal conductivity enhancement. For the fuel performance analysis, new high burnup models were developed and implemented in a code. This code was verified by an international database and our own database. The developed spacer grid has two features of contoured contact spring and hybrid mixing vanes. Mechanical and hydraulic tests showed that the spacer grid is superior in its rodsupporting, wear resistance and CHF performance. Finally, fuel assembly test technology was also developed. Facilities for mechanical and thermal hydraulic tests were constructed and are now in operation. Several achievements are to be utilized soon by the Korea Nuclear Fuel and thereby contribute to the economy and safety of PWR fuel in Korea

• Journal of the Korea Society of Computer and Information
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• v.10 no.6 s.38
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• pp.195-208
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• 2005

Recently, amount of the data such as sequences is being increased rapidly due to deploying computational technique and advance of experiment tools in the biological areas. In bioinformatics, it is very significant to extract the knowledge from such huge biological data. Sequence comparisons are most frequently used to predict the function of the genes or proteins. However it takes so much time to process the persistently increasing data In this paper, we propose hardware-based grid, CGRID(Chungbuk National University GRID), to improve performance and complement existing middleware-only approach and apply it in the sequence comparison. Hardware-based approach is easy to construct, maintain, and manage the grid as not requiring the software installation individually for every node. We reduce orthologous database construction time from 33 weeks to just a week. Furthermore, CGRID guarantees that the performance increases proportionally as adding the nodes.

• Journal of KIISE
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• v.44 no.6
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• pp.613-620
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• 2017

Skyline queries are used extensively to solve various problems, such as in decision-making, because they find data that meet a variety of user criteria. Recent research has focused on skyline queries by using the MapReduce framework for large database processing, mainly in terms of applying existing index structures to MapReduce. In a skyline, data closer to the origin dominate more area. However, the existing index structure does not reflect such characteristics of the skyline. In this paper, we propose a grid-block structure that groups grid cells to match the characteristics of a skyline, and a two-level grid-block structure that can be used even when there are no data close to the origin. We also propose an efficient skyline-query algorithm that uses the two-level grid-block structure.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.10
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• pp.75-81
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• 2005

Jettison, grid and CTS test are widely used for the store and stage separation studies. This is an introductory paper on the experimental methodology and typical results of grid and CTS test used for the Korean 3-stage sounding rocket development. Thirteen separation trajectories were evaluated in the ONERA S2MA wind tunnel at Mach numbers of 2.0 and 2.8. The test result was applied as the basic database for the design of optimized separation device.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2007.02a
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• pp.48-52
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• 2007

As huge amount of literature including biological data is being generated after post genome era, it becomes difficult for researcher to find useful knowledge from the biological databases. Bio-text mining and related natural language processing technique are the key issues in the intelligent knowledge retrieval from the biological databases. We propose a bio-text mining technique for the biologists who find Knowledge from the huge literature. At first, web robot is used to extract and transform related literature from remote databases. To improve retrieval speed, we generate an inverted file for keywords in the literature. Then, text mining system is used for extracting given knowledge patterns and keywords. Finally, we construct a grid computing environment to guarantee processing speed in the text mining even for huge literature databases. In the real experiment for 10,000 bio-literatures, the system shows 95% precision and 98% recall.

• ETRI Journal
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• v.38 no.6
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• pp.1197-1206
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• 2016

Performing continuous skyline queries of dynamic data sets is now more challenging as the sizes of data sets increase and as they become more volatile due to the increase in dynamic updates. Although previous work proposed support for such queries, their efficiency was restricted to small data sets or uniformly distributed data sets. In a production database with many concurrent queries, the execution of continuous skyline queries impacts query performance due to update requirements to acquire exclusive locks, possibly blocking other query threads. Thus, the computational costs increase. In order to minimize computational requirements, we propose a method based on a multi-layer grid structure. First, relational data object, elements of an initial data set, are processed to obtain the corresponding multi-layer grid structure and the skyline influence regions over the data. Then, the dynamic data are processed only when they are identified within the skyline influence regions. Therefore, a large amount of computation can be pruned by adopting the proposed multi-layer grid structure. Using a variety of datasets, the performance evaluation confirms the efficiency of the proposed method.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.6
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• pp.1593-1603
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• 2016

In the smart grid environment, there are various security threats. In particular, exposure of smart meter data can lead to serious privacy violation. In this paper, we propose a method for de-identification method of metering data. The proposed method is to de-identify the time data and the numeric data, respectively. Therefore, it can't analyze the pattern information from the metering data. In addition, there is an advantage that the query is available, such as the range of search in the database for statistical analysis.