• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.367-368
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• 2007

In this paper, we propose a new de-noising algorithm for 2 dimensional image using discrete wavelet transform. The proposed algorithm consists of edge detection in spatial domain, zero-tree estimation, subband estimation, and shrinkage algorithm. The results from it shows that the denoised image which Is damaged by 20% gaussian noise has 28dB quality for the original one.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• fall
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• pp.168-171
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• 2021

최근 시맨틱 웹은 Linked Open Data (LOD)의 사용으로 웹 분야에서 주목을 받고 있다. 이에 LOD 등을 중심으로 검색 고도화 연구가 활발히 수행되고 있다. 그러나 LOD 클라우드를 이용한 효율적인 검색 방법이나 활용 방안을 위한 깊이 있는 연구는 상대적으로 매우 부족한 상황이다. 따라서 본 논문에서는 LOD 클라우드를 효율적으로 구성하기 위한 인덱스 구조를 제안하고자 HYBRID R*-tree 인덱스 구조와 단일 인덱스 구조의 성능을 비교하여 평가한다.

• Journal of the Korean Institute of Gas
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• v.1 no.1
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• pp.56-63
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• 1997

This paper presents a hybrid network model(HY-PIPENET) implementing a minimum cost spanning tree(MCST) network algorithm to be able to determine optimum path and constrained derivative(CD) method to select optimum Pipe diameter. The HY-PIPENET has been validated with the published data of 6-node/7-pipe network. Networking system and also this system has been optimized with MCST-CD method. As a result, it was found that the gas can be sufficiently supplied at the lower pressure with the smaller diameters of pipe compared to the original system in 6-node/7-pipe network. Hence, the construction cost was reduced about $40\%$ in the optimized system. The hybrid networking model has been also applied to a complicated domestic gas pipeline network in metropolitan area, Korea. In this simulation, parametric study was peformed to understand the role of each individual parameter such as source pressure, flow rate, and pipe diameter on the optimized network. From the results of these simulations, we have proposed the optimized network as tree-type structure with optimum pipe diameter and source pressure in metropolitan area, Korea, however, this proposed system does not consider the environmental problems or safety concerns.

• Journal of Korean Society of Forest Science
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• v.69 no.1
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• pp.19-27
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• 1985

Introgressive hybridization of Pinus densiflora in Korea was investigated by examining the position of resin ducts in 4,992 trees from 67 populations. Judging that P. densiflora has only external resin ducts, P. thunbergii only medial resin ducts, and any tree which has even one needle with external and medial resin ducts is hybrid, hybrids are found at all populations investigated. As variation in position of resin ducts was found among needles on a tree, the number of needles investigated from a tree affects judgment of the tree's hybridity. Therefore, hybridity seems to be judged by many traits rather than by the single trait, position of resin ducts. Seed production by artificial pollination between P. densiflora and P. thunbergii was very poor, i.e. one full seed from five female flowers or from two mature cones. This poor seed production, in addition to the low hybrid vigor, if any, seems to make the artificial pollination between the two species for mass-production of seeds for planting impractical.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.12
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• pp.471-480
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• 2016

Recently, the damage of cyber attack toward infra-system, national defence and security system is gradually increasing. In this situation, military recognizes the importance of cyber warfare, and they establish a cyber system in preparation, regardless of the existence of threaten. Thus, the study of Intrusion Detection System(IDS) that plays an important role in network defence system is required. IDS is divided into misuse and anomaly detection methods. Recent studies attempt to combine those two methods to maximize advantagesand to minimize disadvantages both of misuse and anomaly. The combination is called Hybrid IDS. Previous studies would not be inappropriate for near real-time network environments because they have computational complexity problems. It leads to the need of the study considering the structure of IDS that have high detection rate and low computational cost. In this paper, we proposed a Hybrid IDS which combines C4.5 decision tree(misuse detection method) and Weighted K-means algorithm (anomaly detection method) hierarchically. It can detect malicious network packets effectively with low complexity by applying mutual information and genetic algorithm based efficient feature selection technique. Also we construct upgraded the the hierarchical structure of IDS reusing feature weights in anomaly detection section. It is validated that proposed Hybrid IDS ensures high detection accuracy (98.68%) and performance at experiment section.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.580-586
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• 2021

The CAT methodology is a numerical analysis technique using CAE. Recently, a methodology of applying artificial intelligence techniques to a simulation has been studied. A previous study compared the deformation results according to the injection molding process using a machine learning technique. Although MLP has excellent prediction performance, it lacks an explanation of the decision process and is like a black box. In this study, data was generated using Autodesk Moldflow 2018, an injection molding analysis software. Several Machine Learning Algorithms models were developed using RapidMiner version 9.5, a machine learning platform software, and the root mean square error was compared. The decision-tree showed better prediction performance than other machine learning techniques with the RMSE values. The classification criterion can be increased according to the Maximal Depth that determines the size of the Decision-tree, but the complexity also increases. The simulation showed that by selecting an intermediate value that satisfies the constraint based on the changed position, there was 7.7% improvement compared to the previous simulation.

• Journal of agriculture & life science
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• v.45 no.6
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• pp.41-46
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• 2011

In this study, in addition to the green tea-wood fiber hybrid composite boards of previous researches, to make effective use of saw dust of domestic cypress tree with functionalities and application as interior materials, eco-friendly hybrid composite boards were manufactured from wood fiber, green tea and saw dust of cypress tree. We investigated the effect of the component ratio of saw dust and green tea on static bending strength performances. Static bending MOE (modulus of elasticity) was within 0.956~1.18GPa, and showed the highest value in wood fiber : green tea : saw dust = 50 : 40 : 10 of the component ratio, and had the lowest value in 50 : 30 : 20 of component ratio. These values were 2.0~3.1times lower than those of green tea-wood fiber hybrid composite boards reported in the previous researches. The bending MOR (modulus of rupture) showed 8.99~11.5MPa, the change of the bending MOR with component ratio of the factors was the same as that of bending MOE. These values had 1.9~3.5 times lower value than those of green tea-wood fiber hybrid composite boards, and showed the slightly lower values than the MOR of particle boards (PB) and medium density fiberboards (MDF) prescribed in Korean Industrial Standard. Therefore, it is considered that these hybrid composite boards need to improve strength performances by component ratio change, hybrid composite with other materials and adhesive change etc. in order to industrialize the hybrid composite boards.

• Journal of KIISE:Software and Applications
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• v.36 no.7
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• pp.560-570
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• 2009

RFID, Radio Frequency Identification, is a technology of automated identification replacing bar-code. RFID technology has advantages that it recognizes fast and it is strong to contamination using wireless communication. However, there are difficult problems that should be solved for popularization of RFID. Among of these, tag anti-collision problem is dealed in this paper. It affected the performance of RFID system directly. This paper analyzes conventional algorithms and proposes new algorithms of tag anti-collision. The algorithm proposed was composed of appropriate properties to each phase of distribution and recognition as hybrid between ALOHA-based algorithm and QT-based algorithm. At phase of distribution, the number of tags recognizing at a frame was reduced using ALOHA-based algorithm. It addressed the delay problem because of deep depth of tree. At phase of recognition, it solved ALOHA-based chronic problem that couldn't recognize all the tags sometimes. Moreover, QTR algorithm that recognize by reversed tag IDs was adopted for the performance. The FQTR algorithm proposed in this paper showed brilliant performance as compared with convention algorithms by simulation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37B no.10
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• pp.859-876
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• 2012

Since the existing protocols separated mobility management part and routing protocol part in their design and used a flooding, they suffer from the high control overhead, thereby limiting performance. In this paper, we use a tree-based mobility management method and present a simple and efficient routing protocol that exploits the topology information which is built additionally through mobility management. Thus, the mobility management and the routing protocol closely cooperate to optimize control overhead. Furthermore, we use a progressive path discovery method to alleviate traffic congestion around IG and a unicast-based broadcast method to increase the reliability of message delivery and to judge link validity promptly. The proposed protocol reduces control overhead greatly and works in a stable manner even with the large number of nodes and high mobility. This was proven by comparing with the AODV protocol that employs the hybrid mobility management protocol.

• Journal of KIISE:Software and Applications
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• v.34 no.1
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• pp.30-39
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• 2007

The existing content-based spam mail filtering algorithms have difficulties in filtering spam mails when e-mails contain images but little text. In this thesis we propose an efficient spam mail classification algorithm that utilizes the link structure of e-mails. We compute the number of hyperlinks in an e-mail and the in-link frequencies of the web pages hyperlinked in the e-mail. Using these two features we classify spam mails and legitimate mails based on the decision tree trained for spam mail classification. We also suggest a hybrid system combining three different algorithms by majority voting: the link structure analysis algorithm, a modified link structure analysis algorithm, in which only the host part of the hyperlinked pages of an e-mail is used for link structure analysis, and the content-based method using SVM (support vector machines). The experimental results show that the link structure analysis algorithm slightly outperforms the existing content-based method with the accuracy of 94.8%. Moreover, the hybrid system achieves the accuracy of 97.0%, which is a significant performance improvement over the existing method.