• Journal of Internet Computing and Services
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• v.10 no.4
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• pp.1-11
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• 2009

Recently there has arisen concern in both the database community and the graphics society about data retrieval from large motion databases because the high dimensionality of motion data implies high costs. In this circumstance, finding an effective distance measure and an efficient query processing method for such data is a challenging problem. This paper presents an elaborate motion query processing system, SMoFinder (Similar Motion Finder), which incorporates a novel kinematic distance measure and an efficient indexing strategy via adaptive frame segmentation. To this end, we regard human motions as multi-linkage kinematics and propose the weighted Minkowski distance metric. For efficient indexing, we devise a new adaptive segmentation method that chooses representative frames among similar frames and stores chosen frames instead of all frames. For efficient search, we propose a new search method that processes k-nearest neighbors queries over only representative frames. Our experimental results show that the size of motion databases is reduced greatly (${\times}1/25$) but the search capability of SMoFinder is equal to or superior to that of other systems.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.9
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• pp.401-410
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• 2016

3D registration is a computer vision technique of aligning multi-view range images with respect to a reference coordinate system. Various 3D registration algorithms have been introduced in the past few decades. Iterative Closest Point (ICP) is one of the widely used 3D registration algorithms, where various modifications are available nowadays. In the ICP-based algorithms, the closest points are considered as the corresponding points. However, this assumption fails to find matching points accurately when the initial pose between point clouds is not sufficiently close. In this paper, we propose a new method to solve this problem using the 6D distance (3D color space and 3D Euclidean distances). Moreover, a color segmentation-based adaptive sampling technique is used to reduce the computational time and improve the registration accuracy. Several experiments are performed to evaluate the proposed method. Experimental results show that the proposed method yields better performance compared to the conventional methods.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.5
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• pp.180-191
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• 2008

An Adaptive Random Testing (ART) is one of test case generation algorithms that are designed to detect common failure patterns within input domain. The ART algorithm shows better performance than that of pure Random Testing (RT). Distance-bases ART (D-ART) and Restriction Random Testing (RRT) are well known examples of ART algorithms which are reported to have good performances. But significant drawbacks are observed as quadratic runtime and non-uniform distribution of test case. They are mainly caused by a huge amount of distance computations to generate test case which are distance based method. ART through Iterative Partitioning (IP-ART) significantly reduces the amount of computation of D-ART and RRT with iterative partitioning of input domain. However, non-uniform distribution of test case still exists, which play a role of obstacle to develop a scalable algerian. In this paper we propose a new ART method which mitigates the drawback of IP-ART while achieving improved fault-detection capability. Simulation results show that the proposed one has about 9 percent of improved F-measures with respect to other algorithms.

• Proceedings of the KAIS Fall Conference
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• 2002.11a
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• pp.220-224
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• 2002

본 논문에서는 웹 서버의 부하가 급증하면서 대두된 네트워크 과부하를 해결하기 위한 방법으로 서버분산처리 방식과 RTO(retransmission time out : 재전송타임아웃)간을 조정하는 기법을 이용하였다. 부하 분산을 위한 방법으로는 기존의 NAT 기반의 가상서버 방식과 비슷하나, 기존의 가상서버에서 서버들을 선택하는 스케줄링 방법을 이용하지 않고 네트워크 주소(IP)룰 통한 서버 분산방법을 선택하였다. 이를 위해 Linux 기반의 PC에 라우터론 구축하였고 여기에 실제 IP를 할당하였으며, 라우터를 경유하여 연결된 두개의 서버에는 가상 IP를 할당 내부접속용과 외부접속용으로 나누어 서버 분산이 이루어지게끔 하였다. 이러한 서버 분산은 학교라는 즉. 웹서버의 접속이 내부접속 비율과 외부접속 비율 어느 한쪽으로도 크게 기울지 않는 네트워크 환경을 고려한 것이다. 네트워크의 성능 평가에 있어 가장 기본이 될 수 있는 응답시간은 전송거리와 트래픽량에 비례한다. 이에 외부접속용 서버와 내부접속용 서버 각각에 RTO 값을 다르게 적용시킴으로써 전체적인 Delay의 변화를 확인해 볼 수 있다. 이는 전송거리가 길 경우 생길 수 있는 패킷 손실을 고려한 것으로 패킷 손실로 인하여 재전송이 이루어질 경우 재전송 time이 RTO를 통하여 이루어지며 이러한 RTO의 적절한 값은 전체적인 응답시간에 영향을 미칠 수 있다는 것에 기인한 것으로 RTO값을 전송거리가 긴 외부접속용 서버에는 전송거리가 짧은 내부접속용 서버에 비해 길게 적응시킴으로써 전체적인 응답시간의 개선을 유도하였다

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.2
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• pp.299-306
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• 2011

In this paper, a blind adaptive equalization algorithm based on PDF-distance minimization and a set of Delta functions is introduced and its superior robustness against impulsive noise and multipath characteristics of underwater communication channels is proved. The conventional CMA based on MSE has shown to be incapable of coping with impulsive noise, and correntropy blind algorithm has also revealed to yield not satisfying performance for the mission. On the other hand, the blind adaptive equalization algorithm based on PDF-distance minimization and a set of Delta functions has been proved to solve effectively the problem of impulsive noise and multipath characteristics of underwater communication channels through theoretical and simulation analysis.

• Journal of Broadcast Engineering
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• v.16 no.6
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• pp.902-915
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• 2011

Recently in the area-based stereo matching field, Adaptive Support-Weight (ASW) method that weights matching cost adaptively according to the luminance intensity and the geometric difference shows promising matching performance. However, ASW requires more computational cost than other matching algorithms do and its real-time implementation becomes impractical. By applying Integral Histogram technique after approximating to the Bilateral filter equation, the computational time of ASW can be restricted in constant time regardless of the support window size. However, Integral Histogram technique causes loss of the matching accuracy during approximation process of the original ASW equation. In this paper, we propose a novel algorithm that maintains the ASW algorithm's matching accuracy while reducing the computational costs. In the proposed algorithm, we propose Sub-Block method that groups the pixels within the support area. We also propose the method adjusting the disparity search range depending on edge information. The proposed technique reduces the calculation time efficiently while improving the matching accuracy.

• Journal of Korea Multimedia Society
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• v.17 no.2
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• pp.208-217
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• 2014

This paper propose an adaptive control of symmetry contribution based generalized symmetry transform. which can be controlled symmetry contribution according to the intensity orientation of two pixels. In the proposed method, we define the C-D(convergent and divergent)plane which represents convergence and divergence region of gradient pairs. and used the gaussian phase wight function, with respect to the distance from the gradient pair to an extreme point, in calculating the symmetry contribution. The proposed method can be detect the object more efficiently by adaptive controlling the cut-off frequency of the gaussian phase wight function. To evaluate a performance of the proposed method, we compare the proposed method and conventional GST method in various images including IR image. we prove that the proposed method have better performance in object detection.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.9
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• pp.817-823
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• 2017

In the past, research has been conducted on the development of an adaptive cruise control algorithm considering fuel efficiency, and an adaptive cruise control system considering fuel efficiency have been developed. However, research on optimizing vehicle and adaptive cruise control parameters in order to maximize performances is insufficient. In this study, the design optimization of vehicle and control parameters considering fuel efficiency, trackability, ride comfort and safe distance is performed. This paper proposes performance measures of vehicle behavior and develops an adaptive cruise control system. In addition, based on the screening of vehicle parameters that significantly influence performances, kriging surrogate models are constructed through a sequential design of experiment, and kriging surrogate model-based design optimization is performed to maximize fuel efficiency and satisfy target performances.

• The Journal of the Acoustical Society of Korea
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• v.36 no.3
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• pp.151-157
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• 2017

A general linearly constrained adaptive array is proposed to improve the nulling performance. The nulling performance is examined in the array weight vector space. It is shown that the constraint plane is shifted to the origin perpendicularly by the gain factor such that the increase of the gain factor results in the decrease of the distance from the constraint plane to the origin. Thus the variation of the gain factor has an effect on the extent of orthogonality between the weight vector and the steering vectors for the interferences such that the nulling performance of the general linearly constrained adaptive array is improved by the gain factor. It is observed that the proposed adaptive array with an optimum value of the gain factor yields a better nulling performance in coherent signal environment and a similar nulling performance in noncoherent signal environment compared to the conventional linearly constrained adaptive array.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.11A
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• pp.1197-1205
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• 2007

An adaptive K-best detection scheme is proposed for MIMO systems. The proposed scheme changes the number of survivor paths, K based on the degree of the reliability of Zero-Forcing (ZF) estimates at each K-best step. The critical drawback of the fixed K-best detection is that the correct path's metric may be temporarily larger than K minimum paths metrics due to imperfect interference cancellation by the incorrect ZF estimates. Based on the observation that there are insignificant differences among path metrics (ML distances) when the ZF estimates are incorrect, we use the ratio of the minimum ML distance to the second minimum as a reliability indicator for the ZF estimates. So, we adaptively select the value of K according to the ML distance ratio. It is shown that the proposed scheme achieves the significant improvement over the conventional fixed K-best scheme. The proposed scheme effectively achieves the performance of large K-best system while maintaining the overall average computation complexity much smaller than that of large K system.