• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.6B
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• pp.709-716
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• 2001

반복 복호 알고리듬에 의해 복호화된 터보 코드는 가산성 백색 가우시안 잡음(AWGN) 채널 환경에서 이론적으로 Shannon의 한계에 근접한 뛰어난 코딩 이득을 나타내는 것으로 보여지고 있다. 그러나, 터보 코드의 성능은 터보 부호화기에서 프레임의 크기 즉, 인터리버의 크기에 의존한다. IMT-2000과 같은 이동 통신 채널 환경에서 음성을 전송하는 경우에는 터보 코드의 프레임 크기는 매우 작다. 그리고, 그것은 터보 코드의 성능을 떨어뜨리는 직접적인 원인이 된다. 본 논문에서는 차세대 이동 통신 시스템에서 프레임 크기가 작은 음성 프레임을 이용하여 터보 코드의 성능을 검증하며, 작은 프레임 크기에 알맞은 3개의 직렬 MAP(Maximum A Posteriori probability) 복호기를 이용한 반복 복호의 터보 코드를 제안하고 부호율 1/3, 구속장의 길이 3 또는 4, 프레임 크기 24, 192 비트에 대하여 컴퓨터 모의실험을 통해 터보 코드의 성능을 분석한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2000.10b
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• pp.1095-1098
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• 2000

본 논문에서는 프레임 릴레이(Frame Relay: FR) 망과 ATM(Asynchronous Transfer Mode) 망이 연 동시 연동장치(InterWorking Unit: IWU)의 프레임에 대한 지연시간을 분석하였다. ATM과 FR 사이의 데이터 처리속도의 차이는 연동장치에서 큐 현상을 야기시키므로, 프레임이 처리되기 위해서 기다리게 된다. 본 논문에서는 지연시간을 해석적으로 분석하여 이를 시뮬레이션을 통해 검증하였다. 그 결과 FR 연결된 수가 선형적으로 증가할수록 연동장치에서 프레임의 지연시간은 지수적으로 증가함을 알 수 있었다. 따라서, 이러한 분석 결과를 통해서 FR과 ATM 사이에 있는 연동장치를 구현할 때, 전송된 프레임을 처리할 timeout의 시간을 결정하여 프레임을 재전송 할 수 있는 시간을 결정하는데 도움이 될 것으로 사료된다.

• Journal of Broadcast Engineering
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• v.8 no.4
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• pp.501-504
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• 2003

In this out watermarking method, a key is determined by quantizing the maximum motion difference between frames. We have a problem the key value for embedding and detection are different in 1 to 3% frames of all frames. This problem can be easily solved by using a new key according to bit error rate of the extracted watermark. Since the watermark is embedded in each frame nth different keys and detected In all the frames, out method is resistant against attacks such as the frame averaging and frame drop.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.4
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• pp.595-604
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• 2013

Currently, registered number of imported vehicles is increasing rapidly over the years. Accordingly, environment improvements of vehicle maintenance company for maintenance of luxury vehicle such as imported vehicle are continuously being made. In this paper, we propose a key frame extraction method based on HSV color model for smart vehicle management system implementation to offer for customer reliability of maintenance vehicle. After automatically recognize the license plates of the vehicle using vehicle license plate recognition system when the vehicle come in the car center, we check the repair history and request of the vehicle based on it. We implement mobile services which provide extracted key frame images to the user after extract key frames from vehicle repair video. In addition, we verify the superiority of key frame extraction method by applying a smart vehicle management system. Finally, we convert the RGB color to HSV color to improve the performance of proposed key frame extraction scheme. As a result, we confirmed that our scheme is more excellence about 30% in terms of recall than RGB color model from the performance evaluations.

• The Journal of Korean Institute of Next Generation Computing
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• v.14 no.6
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• pp.7-14
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• 2018

Salient information extraction from multi-view videos is a very challenging area because of inter-view, intra-view correlations, and computational complexity. There are several techniques developed for keyframes extraction from multi-view videos with very high computational complexities. In this paper, we present a keyframes extraction approach from multi-view videos using entropy and complexity information present inside frame. In first step, we extract representative shots of the whole video from each view based on structural similarity index measurement (SSIM) difference value between frames. In second step, entropy and complexity scores for all frames of shots in different views are computed. Finally, the frames with highest entropy and complexity scores are considered as keyframes. The proposed system is subjectively evaluated on available office benchmark dataset and the results are convenient in terms of accuracy and time complexity.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.4
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• pp.132-138
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• 2009

In this paper, we propose a novel approach to improve the performance of minima controlled recursive averaging (MCRA) which is based on the second-order conditional maximum a posteriori (CMAP). From an investigation of the MCRA scheme, it is discovered that the MCRA method cannot take full consideration of the inter-frame correlation of voice activity since the noise power estimate is adjusted by the speech presence probability depending on an observation of the current frame. To avoid this phenomenon, the proposed MCRA approach incorporates the second-order CMAP criterion in which the noise power estimate is obtained using the speech presence probability conditioned on both the current observation and the speech activity decisions in the previous two frames. Experimental results show that the proposed MCRA technique based on second-order conditional MAP yields better results compared to the conventional MCRA method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.2
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• pp.11-23
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• 2011

In this paper, an accurate and fully automatic video object segmentation method is proposed for video conferencing systems in which the real-time performance is required. The proposed method consists of two steps: 1) accurate object extraction on the initial frame, 2) real-time object extraction from the next frame using the result of the first step. Object extraction on the initial frame starts with generating a cumulative edge map obtained from frame differences in the beginning. This is because we can estimate the initial shape of the foreground object from the cumulative motion. This estimated shape is used to assign the seeds for both object and background, which are needed for Graph-Cut segmentation. Once the foreground object is extracted by Graph-Cut segmentation, real-time object extraction is conducted using the extracted object and the double edge map obtained from the difference between two successive frames. Experimental results show that the proposed method is suitable for real-time processing even in VGA resolution videos contrary to previous methods, being a useful tool for immersive video conferencing systems.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.6
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• pp.1148-1156
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• 2015

The maritime cognitive radio networks (MCRNs) provide the high throughput with a low communication cost because the secondary ships opportunistically access to unused licensed bands of primary ships. In the ground cognitive radio networks, the busy and idle state of a primary user during a frame is not nearly changed because the state of the primary user are slowly changed. However, the state of the primary ship in the MCRNs may be frequently changed in the frame. Therefore, this paper evaluates the throughput of a primary ship and secondary ships in the MCRNs taking the state change of a primary ship into consideration when the fusion center uses the cooperative spectrum sensing. The simulation results show that trade-off between the throughput of a primary ship and that of secondary ships according to the system parameter such as the cooperative spectrum sensing scheme, the number of secondary ships, and the target detection probability.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.18 no.2
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• pp.159-168
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• 2005

An improved stability design method for beam-columns of plane frames is proposed based on system buckling analysis and second-order elastic analysis. For this, the tangent stiffness matrix of beam-column elements is first derived using stability functions and a procedure for evaluating effective buckling lengths is reviewed using elastic system buckling analysis. And then the second-order analysis procedure is presented considering $P-\Delta$ effects and is compared with the closed-form solution through numerical examples. Design examples showing the validity of the proposed method we presented and their numerical results are compared with those obtained from the conventional stability design methods. Finally some useful conclusions are drawn.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.6
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• pp.122-128
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• 1998

This paper presents compression of image sequences based on the classification of interframe difference image blocks. classification process consists of image activity classification and energy distribution classification. In the activity classification, interframe difference image blocks are classified into activity blocks and non-activity blocks using the edge detection. In the distribution classification, activity blocks are further classified into vertical blocks, horizontal blocks, and small activity blocks using the AC energy distribution features. The RBFN, trained with numerical classification results, successfully classifies difference image blocks according to image details. Image sequence compressing based on the classification of interframe difference image blocks using the RBFN shows better compression results and less training time than the classical sorting method and the MLP network.