• Journal of applied mathematics & informatics
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• v.7 no.2
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• pp.629-640
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• 2000

this paper present an efficient line-drawing algorithm that reduces the amount of space required, Because of its efficiency , this line-drawing algorithm is faster than the Bresenham algorithm or the recursive bisection method. this efficiency was achieved through a new data structure; namely , the modified segment tree (MST). Using the modified segment tree and the distribution rule suggested in this paper, we dra lines without generating the recursive calls used in [3] and without creating the binary operation used in [4]. we also show that line accuracy improves in proportion to the display resolution . In practice, we can significantly improve the algorithm's performance with respect to time and space, This improvement offer an increase in speed, specially with lines at or near horizontal, diagonal. or vertical ; that is, this algorithm requires the time complexity of (n) and the space complexity O(2k+1), where n is the number of pixels and k is a level of the modified segment tree.

• Journal of the Korean Data and Information Science Society
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• v.17 no.2
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• pp.455-465
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• 2006

Data mining is the method to find useful information for large amounts of data in database. It is used to find hidden knowledge by massive data, unexpectedly pattern, and relation to new rule. The methods of data mining are decision tree, association rules, clustering, neural network and so on. We analyze industrial waste database using data mining technique. We use k-means algorithm for clustering and C5.0 algorithm for decision tree and Apriori algorithm for association rule. We can use these outputs for environmental preservation and environmental improvement.

• Textile Coloration and Finishing
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• v.15 no.6
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• pp.47-54
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• 2003

To be dyed with cationic Berberine, the cotton fiber was modified with reactive anionic agent. The Berberine, a natural cationic colorant of pure yellow, is the major component of Amur Cork tree extract and also can be employed as a natural antimicrobial agent due to its characteristic of cationic quaternary ammonium salt. By LC/MS analysis, it became obvious that the Berberine was contained in Amur Cork tree extract as a major color component. The adsorption of the Berberine on the cotton fabrics pretreated with the anionic agent was greatly increased comparing to that of untreated fabric. Because the anionic agent was colorless, it did not cause unintended color change of the dyeings. The dyed fabric with the Berberine has strong antimicrobial activity showing 99.5% of reduction of bacteria against Staphylococcu aureus.

• Journal of Information Technology Services
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• v.12 no.3
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• pp.331-343
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• 2013

In RFID systems, the anti-collision algorithm is being improved to recognize Tag's ID within recognition area of the reader quickly and efficiently. This paper focuses on Tag collision. Many studies have been carried out to resolve Tag collision. This paper proposes a new N-ary Query Tree Algorithm to resolve more than Tag collision simultaneously, according to the value of m(2 ~ 6). This algorithm can identify more tags than existing methods by treating a maximum 6 bit collision, regardless of the continuation/non-continuation Tag's ID patterns. So, it extracts maximumly different $2^6$ bit patterns per single prefix in recognition process. The performance of N-ary Query Tree Algorithm is evaluated by theoretical analysis and simulation program.

• Proceedings of the Korea Multimedia Society Conference
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• 2002.05d
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• pp.710-714
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• 2002

학생은 미래뿐만 아니라 현재의 소비자로서 합리적인 의사결정을 통한 소비문화가 요구된다. 하지만 학생의 소비문화와 학교의 소비교육, 가정교육은 문제점을 안고 있다. 학생들은 물건의 필요성이나 용도, 금전상황, 가정상황 등을 전체적으로 고려하여 구매하기보다는 비계획적이고, 즉흥적이다. 학교에서는 교사들이 학생의 소비행위를 한 눈에 파악하여 교육적으로 피드백하기가 쉽지 않다. 가정에서는 학생들의 소비행위에 대한 의사소통의 길이 부족하다. 이에 본 연구는 소비의사결정 5단계와 Decision-Tree의 교육적인 면을 고려하여 합리적 소비 의사결정을 위한 6단계(문제정의, 정보탐색, 대안평가, 가치확립, 구매경험, 구매평가)를 새롭게 제안하고, 소비교실, 용돈 의사결정, 설문모듈을 통해 6단계를 체험하는 시스템을 설계하였다. 제안한 모델은 교사와 학생, 학부모 모두가 참여하여 학생의 계획적이고 합리적인 소비 의사결정 능력을 신장시키는데 도움을 줄 것이다.

• 한국데이터정보과학회:학술대회논문집
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• 2006.04a
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• pp.241-251
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• 2006

Data mining is the method to find useful information for large amounts of data in database It is used to find hidden knowledge by massive data, unexpectedly pattern, relation to new rule. The methods of data mining are decision tree, association rules, clustering, neural network and so on. We analyze industrial waste database using data mining technique. We use k-means algorithm for clustering and C5.0 algorithm for decision tree and Apriori algorithm for association rule. We can use these analysis outputs for environmental preservation and environmental improvement.

• Journal of the Korean Wood Science and Technology
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• v.29 no.3
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• pp.21-26
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• 2001

Acquisition of precise information on drying characteristics of wood is indispensable for the improvement of drying schedules and wood quality. Recognition of the exact moisture content at which drying defects such as checks occur during drying with given drying conditions may be essential to reduce drying losses. In this study an image-processing system was combined with a laboratory-scale wood dry kiln for experiments and the surface of tree disk of black locust (Robinia pseudoacacia L.) was monitored to investigate the behavior of check formation over all the drying process. This system showed good potential for improving drying schedules and wood product quality.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.195-198
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• 2002

We propose an efficient mixture Gaussian synthesis method for decision tree based state tying that produces better context-dependent models in a short period of training time. This method makes it possible to handle mixture Gaussian HMMs in decision tree based state tying algorithm, and provides higher recognition performance compared to the conventional HMM training procedure using decision tree based state tying on single Gaussian GMMs. This method also reduces the steps of HMM training procedure. We applied this method to training of PBS, and we expect to achieve a little point improvement in phoneme accuarcy and reduction in training time.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.2
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• pp.67-73
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• 2023

Tree routing is one of appropriate routing schemes in wireless sensor network because the complexity of this approach is relatively low. But, congestion at a specific node may happen because a parent node toward a sink node is usually selected in one hop way, specially where large number of node are deployed. As feasible solution for this problem, multiple paths and sinks schemes can be applied. However, the performance of these schemes are not proved and analyzed yet. In this paper, we conduct diverse simulaton scenarios performance evaluation for these cases to identify the improvement and analyze the impact of schemes. The performance is measured in the aspects of packet transmission rate, throughput, and end-to-end delay as a function of amount of network traffic.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.17 no.2
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• pp.117-128
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• 1999

A Simple tree-structured line simplification method, which exactly follows the Douglas-Peucker algorithm, has a strength for its simplification index to be involved into the hierarchical data structures. However, the hierarchy of simplification index, which is the core in a simple tree method, may not be always guaranteed. It is validated that the local property of line features in such global approaches as Douglas-Peucker algorithm is apt to be neglected and the construction of hierarchy with no thought of locality may entangle the hierarchy. This study designed a new approach, CALS(Convex hull Applied Line Simplification), a) to search critical points of line feature with convex hull search technique, b) to construct the hierarchical data structure based on these critical points, c) to simplify the line feature using multiple trees. CALS improved the spatial accuracy as compared with a simple tree method. Especially CALS was excellent in case of line features having the great extent of sinuosity.