• Journal of the Korean Geophysical Society
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• v.3 no.1
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• pp.57-66
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• 2000

The location and geometry of the Ulsan Fault play important roles in interpreting tectonic evolution of the southeastern part of the Korean Peninsula. Dipole-dipole electrical resistivity surveys and seismic refraction surveys were carried out in the Yaksoo area, Ulsan in order to measure the thickness of the alluvium covering the Ulsan Fault and to find associated fracture zones and possibly the location of its major fault plane. The collected data were analyzed and interpreted. Some results reported previously by others were also used in this interpretation. No low resistivity anomalies were found in the cross-sectional resistivity image of the survey line located in the east of the Dong River. In contrast, well-developed continuous low resistivity anomalies were detected in the west of the Dong River. This strongly suggests that the major fault plane of the Ulsan Fault is located under or in the west part of the Dong River. Two refraction boundaries corresponding to the underground water level and the bottom of the alluvium were found by refraction surveys carried out on the limited part of the east survey line. The thickness of the alluvium was found to be about 30 m. Small faults in the basement rock identified by reflection surveys were not detected by both resistivity and refraction seismic surveys. This might be explained by assuming that low resistivity anomaly is more closely related to the clay contents than the water contents. On the other hand, it may be resulted by the limited resolution of the resistivity and refraction surveys. Detailed study is required to clarify the reason. Resistivity survey is frequently considered to be a good exploration method to detect subsurface faults. However, it appears to be less useful than reflection seismic survey in this work. In dipole-dipole resistivity survey, the number of separation should be increased to survey deeper subsurface with the same resolution. However, signal to noise ratio decreases as the number of separation increases. In this survey area, the signal to noise ratio of up to sixteen separations was good enough based on the statistical properties of measurements.

• Cartoon and Animation Studies
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• s.22
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• pp.47-63
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• 2011

Recently, contemporary cultural contents have been shown its diversity changes followed by the birth of new media platforms with consumers' new needs in the global market. Also, developments of Internet and computer system networks are the main contributors of making this changes happened rapidly. This study aims to know that how to usefully use those new media platforms through the great example of stop-motion animation music video by analyzing its production and marketing process. The music video production had been focused to be completed with high quality by adjusting the production process economically in spite of the relatively short period(less than one month)from its crank-up to the deadline. Because the production was planned that main characters lead the whole story, the creative team had been tried to reduce the production hours by commonly use the same mold when they make original clay models by collecting the similarities of characters' appearances. By using CG technic, could overcome the visual monotonous from the similarities which inferred above. Also, the repeated rhythm in the music video, the similar scenes of backgrounds were commonly used by copy of the original scene. At the point of directing, the creative team considered both economical and art aspects for the quality work. In details, they divided the scenes into foreground and background, and removed unnecessary parts to save the production hours and budget but make depth of fields in the scenes. Except the viral marketing purposes, was searching for the methods to compensate the production cost. For this, the characters in the music video dressed the same T-shirts which are world-cup logo on, and those were designed for the sale after released the music video. Even the result of the sales was not enough to satisfied, it was estimated a great attempt to the domestic animation industry.

• Journal of Plant Biotechnology
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• v.33 no.3
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• pp.153-160
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• 2006

Brassica rape is an important species used as a vegetable, oil, and fodder worldwide. It is related phylogenically to Arabidopsis thaliana, which has already been fully sequenced as a model plant. The 'Multinational Brassica Genome Project (MBGP)'was launched by the international Brassica community with the aim of sequencing the whole genome of B. rapa in 2003 on account of its value and the fact that it has the smallest genome among the diploid Brassica. The genome study was carried out not only to know the structure of genome but also to understand the function and the evolution of the genes comprehensively. There are two mapping populations, over 1,000 molecular markers and a genetic map, 2 BAC libraries, physical map, a 22 cDHA libraries as suitable genomic materials for examining the genome of B. rapa ssp. pekinensis Chinese cabbage. As the first step for whole genome analysis, 220,000 BAC-end sequences of the KBrH and KBrB BAC library are achieved by cooperation of six countries. The results of BAC-end sequence analysis will provide a clue in understanding the structure of the genome of Brassica rapa by analyzing the gene sequence, annotation and abundant repetitive DHA. The second stage involves sequencing of the genetically mapped seed BACs and identifying the overlapping BACs for complete genome sequencing. Currently, the second stage is comprises of process genetic anchoring using communal populations and maps to identify more than 1,000 seed BACs based on a BAC-to-BAC strategy. For the initial sequencing, 629 seed BACs corresponding to the minimum tiling path onto Arabidopsis genome were selected and fully sequenced. These BACs are now anchoring to the genetic map using the development of SSR markers. This information will be useful for identifying near BAC clones with the seed BAC on a genome map. From the BAC sequences, it is revealed that the Brassica rapa genome has extensive triplication of the DNA segment coupled with variable gene losses and rearrangements within the segments. This article introduces the current status and prospective of Korea Brassica Genome Project and the bioinformatics tools possessed in each national team. In the near future, data of the genome will contribute to improving Brassicas for their economic use as well as in understanding the evolutional process.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.161-177
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• 2015

With the rapid evolution of technology, the size, number, and the type of databases has increased concomitantly, so data mining approaches face many challenging applications from databases. One such application is discovery of fraud patterns from agricultural product wholesale transaction instances. The agricultural product wholesale market in Korea is huge, and vast numbers of transactions have been made every day. The demand for agricultural products continues to grow, and the use of electronic auction systems raises the efficiency of operations of wholesale market. Certainly, the number of unusual transactions is also assumed to be increased in proportion to the trading amount, where an unusual transaction is often the first sign of fraud. However, it is very difficult to identify and detect these transactions and the corresponding fraud occurred in agricultural product wholesale market because the types of fraud are more intelligent than ever before. The fraud can be detected by verifying the overall transaction records manually, but it requires significant amount of human resources, and ultimately is not a practical approach. Frauds also can be revealed by victim's report or complaint. But there are usually no victims in the agricultural product wholesale frauds because they are committed by collusion of an auction company and an intermediary wholesaler. Nevertheless, it is required to monitor transaction records continuously and to make an effort to prevent any fraud, because the fraud not only disturbs the fair trade order of the market but also reduces the credibility of the market rapidly. Applying data mining to such an environment is very useful since it can discover unknown fraud patterns or features from a large volume of transaction data properly. The objective of this research is to empirically investigate the factors necessary to detect fraud transactions in an agricultural product wholesale market by developing a data mining based fraud detection model. One of major frauds is the phantom transaction, which is a colluding transaction by the seller(auction company or forwarder) and buyer(intermediary wholesaler) to commit the fraud transaction. They pretend to fulfill the transaction by recording false data in the online transaction processing system without actually selling products, and the seller receives money from the buyer. This leads to the overstatement of sales performance and illegal money transfers, which reduces the credibility of market. This paper reviews the environment of wholesale market such as types of transactions, roles of participants of the market, and various types and characteristics of frauds, and introduces the whole process of developing the phantom transaction detection model. The process consists of the following 4 modules: (1) Data cleaning and standardization (2) Statistical data analysis such as distribution and correlation analysis, (3) Construction of classification model using decision-tree induction approach, (4) Verification of the model in terms of hit ratio. We collected real data from 6 associations of agricultural producers in metropolitan markets. Final model with a decision-tree induction approach revealed that monthly average trading price of item offered by forwarders is a key variable in detecting the phantom transaction. The verification procedure also confirmed the suitability of the results. However, even though the performance of the results of this research is satisfactory, sensitive issues are still remained for improving classification accuracy and conciseness of rules. One such issue is the robustness of data mining model. Data mining is very much data-oriented, so data mining models tend to be very sensitive to changes of data or situations. Thus, it is evident that this non-robustness of data mining model requires continuous remodeling as data or situation changes. We hope that this paper suggest valuable guideline to organizations and companies that consider introducing or constructing a fraud detection model in the future.

• Journal of Internet Computing and Services
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• v.24 no.2
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• pp.19-26
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• 2023

Humans have adapted and evolved to natural light. However, as humans stay in indoor longer in modern times, the problem of biorhythm disturbance has been induced. To solve this problem, research is being conducted on lighting that reproduces the correlated color temperature(CCT) of natural light that varies from sunrise to sunset. In order to reproduce the CCT of natural light, multiple LED light sources with different CCTs are used to produce lighting, and then a control index DB is constructed by measuring and collecting the light characteristics of the combination of input currents for each light source in hundreds to thousands of steps, and then using it to control the lighting through the light characteristic matching method. The problem with this control method is that the more detailed the steps of the combination of input currents, the more time and economic costs are incurred. In this paper, an LED lighting control method that applies interpolation and combination calculation based on the minimum spectral power distribution information for each light source is proposed to reproduce the CCT of natural light. First, five minimum SPD information for each channel was measured and collected for the LED lighting, which consisted of light source channels with different CCTs and implemented input current control function of a 256-steps for each channel. Interpolation calculation was performed to generate SPD of 256 steps for each channel for the minimum SPD information, and SPD for all control combinations of LED lighting was generated through combination calculation of SPD for each channel. Illuminance and CCT were calculated through the generated SPD, a control index DB was constructed, and the CCT of natural light was reproduced through a matching technique. In the performance evaluation, the CCT for natural light was provided within the range of an average error rate of 0.18% while meeting the recommended indoor illumination standard.