• Journal of Korea Society of Industrial Information Systems
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• v.20 no.4
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• pp.39-45
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• 2015

In this paper, variable rate CDR(Clock and Data Recovery) circuit adopting blind oversampling architecture is presented. The clock recovery circuit is implemented by using wide range voltage controlled oscillator and band selection method and the data recovery circuit is designed to digital circuit used majority voting method in order to low power and small area. The designed low power variable clock and data recovery is implemented by wide range voltage controlled oscillator and digital data recovery circuit. The designed variable rate CDR is operated from 10 bps to 2 Mbps. The total power consumption is about 4.4mW at 1MHz clock. The supply voltage is 1.2V. The designed die area is $120{\mu}m{\times}75{\mu}m$ and this circuit is fabricated in $0.13{\mu}m$ CMOS process.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.3
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• pp.247-259
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• 1992

In this paper, the types of the data exchange between a cell site and a cobile phonefor the call processing on the AMPS(Advanced Mobile Phone Service) are investigated, and the circuit for processing the wideband data stream according to the data types is designed and implemented. The circuit for detecting the Busy / Idle bit which is needed for determining the channel access, the circuit for detecting the word sync and the circuit for transmitting and receiving the wideband data is designed. The 3-out-of-5 majority vote of the 5received data is performed to reduce error and an algorithm requiring a small buffer size for real time processing of voting process is proposed. The method to overcome the computational complexity and the real time constraint of the conventional BCH decoding is proposed.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.2
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• pp.87-94
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• 2016

In this paper, we discuss a gait representation based on the width of silhouette in terms of discriminative power and robustness against the noise in silhouette image for gait recognition. Its sensitivity to the noise in silhouette image are rigorously analyzed using probabilistic noisy silhouette model. In addition, we develop a gait recognition system using width representation and identify subjects using the decision level fusion based on majority voting. Experiments on CASIA gait dataset A and the SOTON gait database demonstrate the recognition performance with respect to the noise level added to the silhouette image.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.237-242
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• 2005

Predicting the cellular location of an unknown protein gives a valuable information for inferring the possible function of the protein. For more accurate prediction system, we need a good feature extraction method that transforms the raw sequence data into the numerical feature vector, minimizing information loss. In this paper, we propose new methods of extracting underlying features only from the sequence data by computing pairwise sequence alignment scores. In addition, we use composition based features to improve prediction accuracy. To construct an SVM ensemble from separately trained SVM classifiers, we propose specificity based weighted majority voting. The overall prediction accuracy evaluated by the 5-fold cross-validation reached 88.53% for the eukaryotic animal data set. By comparing the prediction accuracy of various feature extraction methods, we could get the biological insight on the location of targeting information. Our numerical experiments confirm that our new feature extraction methods are very useful for predicting subcellular localization of proteins.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.04a
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• pp.181-182
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• 2017

관성 센서 기반 행위인지는 스마트폰과 웨어러블 밴드 등의 출현으로 보다 간편한 방법으로 행위인지가 가능해졌다. 현재 대부분의 행위인지 서비스나 연구들은 단일 행위의 결론만을 도출하고 있으나, 이러한 방식은 한 행위에서 한 가지 동작밖에 취할 수 없는 경우에는 문제가 없지만 두 가지 이상의 동작이 합쳐진 경우에 어떤 행위를 최종 결론으로 도출해야 하는지에 대한 문제점을 내포한다. 따라서 본 논문에서는 이러한 문제점을 해결하기 위해 세 개의 센서 기기 (스마트폰, 스마트워치, 웨어러블 센서)를 이용한 멀티 레이블 행위인지를 제안한다. 스마트폰은 신체 전반적인 움직임 탐지를 위하여 소지위치가 정해지지 않은 비고정식 센서의 보조적인 역할을 수행한다. 스마트워치는 사용자가 주로 사용하는 손의 손목, 그리고 웨어러블 센서는 사용자의 허벅지에 부착되어 각각 상하체의 움직임을 파악한다. 이후 각 기기에서 도출된 결론에 Majority Weighted Voting 기법을 적용하여 단일 혹은 멀티 레이블의 최종 행위를 도출한다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.12B
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• pp.2016-2024
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• 2000

본 논문에서는 결함의 영향을 받지 않고 동작할 수 있는 AVTMR(All Voting Triple Modular Redundancy) 시스템을 개발하였으며, MILSPEC-217F에 기반을 둔 고장율을 계산하여 AVTMR과 SS(Single System) 시스템을 비교 및 평가하였다. 설계된 시스템은 MC68000을 기반으로 한 3중화된 다수결 보터(Triplicated Majority Voter)를 이용하여 시스템을 개발하였다. 본 논문에서는 시스템의 신뢰도(Reliability), 가용도(Avaliability), 유지보수도(Maintainability)를 마코브 모델(Markov model)로 평가하였으며, 또한 시스템의 MTTF(Mean Time to Failure)를 계산하여 시스템의 수명을 구하였고, 설계된 AVTMR 시스템이 SS(Single System)보다 전체 시스템 평가에서 우수한 특성을 가진다는 것을 시뮬레이션을 통해 알 수 있었다. 또한, AVTMR 시스템은 결함을 허용(Fault tolerant)하는 시스템 특성을 가지기 때문에, 인간의 생명과 관련된 철도 시스템, 선박 시스템이나 항공기 시스템에 적용될 수 있다.

• Proceedings of the IEEK Conference
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• 2003.11b
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• pp.163-166
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• 2003

In conventional patchwork, the difference of the mean values of two groups is compared for watermark detection. We propose two modified patchwork schemes based on order statistics, which achieves significant improvements over conventional patchwork. First, we propose that the mean comparison is replaced by the median comparison, to get PSNR improvement due to informed watermarking. Second, we propose a majority voting scheme of a sequential comparison of pixel pairs in a sorted order, which produces significantly lower BER. The performance improvements are mathematically analyzed and tested. In experimental results, PSNR is about 5㏈～10㏈ higher in the first method and BER is about 1/5～l/2 times lower in the second method than conventional patchwork.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06a
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• pp.76-78
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• 2006

현재 심혈관 질환은 암 다음으로 높은 사망 원인으로 기록되고 있어 심혈관 질환에 대한 초기 진단은 질환의 치료에 매우 중요한 문제로 대두되고 있다. 본 논문에서는 SVM을 이용하여 심혈관질환 환자의 질환 단계를 예측하였다. 일반적으로 이진분류에 사용되는 SVM을 이용하여 정상 및 질환 $1{\sim}3$기의 총 4가지 분류가 필요한 다분류 분류문제를 처리하기 위해서 논문에서는 독립적 학습된 단일 SVM 분류기들을 결합하여 분류를 수행하는 SVM 앙상블 방법을 사용하였다. 단일 분류기의 결합은 Majority voting, 최소자승에러기반 가중치 부여, 2단계층 결합 등의 방법으로 수행하여 심혈관 질환 분류에 적합한 앙상블의 구성을 시도하였다. 실험 데이터는 (주)제노프라의 압타머 칩 데이터를 사용하였다. 서로 다른 데이터를 이용하여 학습된 이종의 SVM들을 결합한 결과 질환단계 예측에 있어서 단일 SVM을 이용하여 질환 단계를 예측하는 경우 보다 향상된 질환단계 예측 성능을 관찰할 수 있었으며, 심혈관 질환의 예측에 대해서는 단일 SVM 분류기의 2단 계층 결합법이 가장 좋은 성능을 보임을 확인하였다.

• Journal of Information Processing Systems
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• v.16 no.2
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• pp.360-376
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• 2020

Many heuristic attribute reduction algorithms have been proposed to find a single reduct that functions as the entire set of original attributes without loss of classification capability; however, the proposed reducts are not always perfect for these multiclass datasets. In this study, based on a probabilistic rough set model, we propose the class-oriented attribute reduction (COAR) algorithm, which separately finds a reduct for each target class. Thus, there is a strong dependence between a reduct and its target class. Consequently, we propose a type of ensemble constructed on a group of classifiers based on class-oriented reducts with a customized weighted majority voting strategy. We evaluated the performance of our proposed algorithm based on five real multiclass datasets. Experimental results confirm the superiority of the proposed method in terms of four general evaluation metrics.

• International Journal of Contents
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• v.11 no.3
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• pp.39-46
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• 2015

When host images are watermarked with CRT (Chinese Remainder Theorem), the watermark images are still robust in spite of the damage of the host images by maintaining the remainders in an unchanged state within some range of the changes that are incurred by the attacks. This advantage can also be attained by "zero-watermarking," which does not change the host images in any way. This paper proposes an improved zero-watermarking scheme for color images on the DCT (Discrete Cosine Transform) domain that is based on the CRT. In the scheme, RGB images are converted into YCbCr images, and one channel is used for the DCT transformation. A key is then computed from the DC and three low-frequency AC values of each DCT block using the CRT. The key finally becomes the watermark key after it is combined four times with a scrambled watermark image. When watermark images are extracted, each bit is determined by majority voting. This scheme shows that watermark images are robust against a number of common attacks such as sharpening, blurring, JPEG lossy compression, and cropping.