• Journal of KIISE
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• v.43 no.4
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• pp.419-429
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• 2016

Generating a 3D surface model from coronary artery segmentation helps to not only improve the rendering efficiency but also the diagnostic accuracy by providing physiological informations such as fractional flow reserve using computational fluid dynamics (CFD). This paper proposes a method to generate a triangular surface mesh using vessel structure information acquired with coronary artery segmentation. The marching cube algorithm is a typical method for generating a triangular surface mesh from a segmentation result as bit mask. But it is difficult for methods based on marching cube algorithm to express the lumen of thin, small and winding vessels because the algorithm only works in a three-dimensional (3D) discrete space. The proposed method generates a more accurate triangular surface mesh for each singular vessel using vessel centerlines, normal vectors and lumen diameters estimated during the process of coronary artery segmentation as the input. Then, the meshes that are overlapped due to branching are processed by mesh merging and merged into a coronary mesh.

• Journal of KIISE:Databases
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• v.31 no.4
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• pp.409-421
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• 2004

A database sharing system (DSS) couples a number of computing nodes for high performance transaction processing, and each node in DSS shares database at the disk level. In case of node failures in DSS, database recovery algorithms are required to recover the database in a consistent state. A database recovery process in DSS takes rather longer time compared with single database systems, since it should include merging of discrete log records in several nodes and perform REDO tasks using the merged lo9 records. In this paper, we propose a two version caching (2VC) algorithm that improves the cache fusion algorithm introduced in Oracle 9i Real Application Cluster (ORAC). The 2VC algorithm can achieve faster database recovery by eliminating the use of merged log records in case of single node failure. Furthermore, it can improve the performance of normal transaction processing by reducing the amount of unnecessary disk force overhead that occurs in ORAC.

• The Transactions of the Korea Information Processing Society
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• v.4 no.12
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• pp.3045-3051
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• 1997

Generally, multi-criteria decisions are made by group of people because of their complexity. In the existing fuzzy aggregation method, the operators using minimum, maximum and average are used to aggregate the viewpoints of many staffs. These methods have problems in that they do not reflect the decision situation in the decision process. In order to solve these problems we propose a new fuzzy multi-criteria decision support systems model that aids the decision maker to aggregate the viewpoints of many staffs according to the decision situation. Moreover, we design the algorithms which can be used in the fuzzy multi-criteria decision support systems and develop its prototying system.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.04a
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• pp.478-481
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• 2010

컴퓨터 비전에서 객체의 인식, 추적에 앞서 배경으로부터 전경을 분리하는 배경차감 기법과 분리된 전경에 대한 관심 영역(ROI)을 추출하는 것은 일반적인 방법이다. 하지만 전경을 정확히 분리하지 못하면 개별 객체의 관심영역(ROI) 역시 잘못 추출되는 문제가 발생된다. 본 논문에서는 정확하지 않은 전경 분리로 부터 발생되는 개별 객체에 대한 분산된 관심영역을 병합하는 방법을 제안한다. 본 방법은 배경과 분리된 전경에서 한 객체의 일정 거리 이내에 있는 다른 객체를 가상으로 병합하는 단계, 워터쉐드 분할 알고리즘을 적용하는 단계를 거쳐 다시 블럽 레이블링을 수행한다. 제안 방법을 통하여 배경 모델에서 분리된 개별 객체의 병합된 관심영역을 제공한다. 실험에서 기존의 일반적인 블럽 레이블링 방법만을 적용하여 추출한 전경영역과 제안하는 방법에 의한 전경영역을 비교하여 배경 모델에서 분리된 개별 객체의 관심영역이 효과적으로 추출되는 것을 보인다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.6B
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• pp.342-349
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• 2007

Clustering protocol of Wireless sensor networks(WSNs) not only reducing the volume of inter-node communication by the nodes's data aggreation but also extending the nodes's sleep times by cluster head's TDMA-schedule coordination. In order to extend network lifetime of WSNs, we propose ECS algorithm to select cluster-head using three variables. It consists of initial and current energy of nodes, round information and total numbers which have been selected as cluster head until current round.

• Proceedings of the Korea Information Processing Society Conference
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• 2001.10b
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• pp.1601-1604
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• 2001

본 논문에서는 SM 메시지(Search Message)를 이용하여 효과적인 예약 오류 최소화를 위한 새로운 RSVP(Resource Reservation Protocol) 알고기즘을 제안한다. 기존의 RFC-2205[1]에 제시된 방안은 각각의 예약 요청을 모두 유지해야하기 때문에 과도한 대역폭 낭비와 이로인한 예약 성공 횟수가 감소되는 문제점을 안고 있다. 대역폭 낭비를 줄이기위해 본 논문에서는 SM 메시지를 도입하였다. 수신자는 주기적으로 SM 메시지를 송신자로 전송하여, 전송로 상의 각 라우터의 사용가능한 대역폭을 검사하여 최소 대역폭으로 각 라우터에 블록케이드 값을 생성한다. 각 라우터에서의 병합작업시 SM 메시지를 이용하여 설정된 블록케이드 값을 기준으로 병합작업 여부를 결정한다. 이는 각각의 예약요청을 별도로 유지해야 할 필요가 없어지므로, 기존의 KRP-I 문제의 해결책인 RFC-2205보다 대역폭 낭비를 줄일수 있게되며 이로인해 예약 수락율이 증가하여 보다 많은 예약 성공 횟수를 얻을수 있게된다. 제안한 SM 알고리즘을 모의 실험 해 본 결과, 예약 수락율이 기존의 RFC-2205보다 전체적으로 약 26% 정도 향상되었다.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.1
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• pp.215-224
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• 2013

This paper proposes a robust lane detection algorithm for bumpy or slope changing roads by estimating extrinsic camera parameters, which represent the pose of the camera mounted on the car. The proposed algorithm assumes that two lanes are parallel with the predefined width. The lane detection and the extrinsic camera parameter estimation are performed simultaneously by utilizing B-snake in motion compensated and merged feature map with consecutive sequences. The experimental results show the robustness of the proposed algorithm in various road environments. Furthermore, the accuracy of extrinsic camera parameter estimation is evaluated by calculating the distance to a preceding car with the estimated parameters and comparing to the radar-measured distance.

• Journal of Internet Computing and Services
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• v.18 no.5
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• pp.47-53
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• 2017

In past few years, high-throughput sequencing, big-data generation, cloud computing, and computational biology are revolutionary. RNA sequencing is emerging as an attractive alternative to DNA microarrays. And the methods for constructing Gene Regulatory Network (GRN) from RNA-Seq are extremely lacking and urgently required. Because GRN has obtained substantial observation from genomics and bioinformatics, an elementary requirement of the GRN has been to maximize distinguishable genes. Despite of RNA sequencing techniques to generate a big amount of data, there are few computational methods to exploit the huge amount of the big data. Therefore, we have suggested a novel gene selection algorithm combining Support Vector Machines and Intensity-dependent normalization, which uses log differential expression ratio in RNAseq. It is an extended variation of support vector machine recursive feature elimination (SVM-RFE) algorithm. This algorithm accomplishes minimum relevancy with subsets of Big-Data, such as NCBI-GEO. The proposed algorithm was compared to the existing one which uses gene expression profiling DNA microarrays. It finds that the proposed algorithm have provided as convenient and quick method than previous because it uses all functions in R package and have more improvement with regard to the classification accuracy based on gene ontology and time consuming in terms of Big-Data. The comparison was performed based on the number of genes selected in RNAseq Big-Data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.11
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• pp.2187-2192
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• 2016

A data-centric routing protocol considering a data aggregation technique at relay nodes is required to increase the lifetime of wireless sensor networks. An energy-efficient data-centric routing algorithm is proposed by considering a tradeoff between acquisition time and energy consumption in the wireless sensor network. First, the proposed routing scheme decides the sink node among all sensor nodes in order to minimize the maximum distance between them. Then, the proposed routing extends its tree structure in a way to minimize the link cost between the connected nodes for reducing energy consumption while minimizing the maximum distance between sensor nodes and a sink node for rapid information gathering. Simulation results show that the proposed data-centric routing algorithm has short information acquisition time and low energy consumption; thus, it achieves high energy efficiency in the wireless sensor network compared to conventional routing algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.3C
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• pp.119-124
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• 2005

In this paper, we propose a novel algorithm for determining the variable size of locally adaptive window using region-merging method. A region including a denoising point is partitioned to disjoint sub-regions. Locally adaptive window for denoising is obtained by selecting Proper sub-lesions. In our method, nearly arbitrarily shaped window is achieved. Experimental results show that our method outperforms other critically sampled wavelet denoising scheme.