• Asian Pacific Journal of Cancer Prevention
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• 제16권14호
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• pp.5779-5785
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• 2015

The present study was designed to investigate cholangiocarcinoma (CCA) antibodies in hamster serum. Hamster CCA cell lines were processed using sodium dodecyl sulfate-polyacrylamide gel electrophoresis and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. A candidate biomarker was confirmed by immunoprecipitation and western blot, and was further analyzed using ELISA and sera from normal control hamsters, hamsters with opisthorchiasis and hamsters with various stages of CCA, as well as from CCA patients and healthy individuals. One candidate marker was identified as $HSP90{\alpha}$, as indicated by a high level of anti-$HSP90{\alpha}$ in hamster CCA sera. It was found that the levels of anti-$HSP90{\alpha}$ were specifically elevated in the sera of hamsters with CCA compared with other groups and progressively increased with the clinical stage. At the cut-off point of 0.4850 on the receiver operating characteristic curve, anti-$HSP90{\alpha}$ could discriminate CCA from healthy control groups with a sensitivity of 76.2%, specificity of 71.4% and total accuracy 75.5%. In the present study, we have shown that anti-$HSP90{\alpha}$ may be a potential useful serum biomarker to discriminate CCA cases from healthy persons.

• 한국통신학회논문지
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• 제31권2C호
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• pp.148-155
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• 2006

H.264/AVC 부호화 표준은 이전의 여러 부호화 표준에는 없던 새로운 부호화 도구들이 추가되었으며 이를 통해 보다 높은 압축 효율을 가진다. 추가된 여러 부호화 도구들 중 최소 4$\times$4 단위의 움직임 추정은 이전보다 인접한 블록들 사이의 움직임벡터 상관도를 높이는 결과를 가져오며, 이러한 특징은 움직임벡터 복원을 통한 에러은닉 기법에 효율적으로 사용될 수 있다. 본 논문은 옵티컬 플로워에 기반하여 움직임 벡터를 복원하는 에러은닉 방법을 제안한다. 인접한 매크로블록들 사이의 움직임벡터들 사이의 상관도가 이전의 여러 부호화 표준들에 비하여 높은 H.264 부호화 표준의 특징을 이용하여 제안하는 알고리듬은 비교적 정확한 초기값의 설정과 속도벡터를 구하기 위한 영역을 16$\times$16크기로 제한함으로써 복잡도를 경감시킨다. 실험결과 제안하는 알고리듬은 다양한 비트율 및 다양한 매크로블록 오류율에서 이전 동일 블록 복사를 수행하는 시방향 복사 방법뿐만 아니라 JM10.1에 구현되어 있는 에러은닉 기법보다 주관적 및 객관적 화질이 높은 것으로 나타난다.

• IEIE Transactions on Smart Processing and Computing
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• 제4권4호
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• pp.195-201
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• 2015

For median filtering (MF) detection in altered digital images, this paper presents a new feature vector that is formed from autoregressive (AR) coefficients via an AR model of the gradients between the neighboring row and column lines in an image. Subsequently, the defined 10-D feature vector is trained in a support vector machine (SVM) for MF detection among forged images. The MF classification is compared to the median filter residual (MFR) scheme that had the same 10-D feature vector. In the experiment, three kinds of test items are area under receiver operating characteristic (ROC) curve (AUC), classification ratio, and minimal average decision error. The performance is excellent for unaltered (ORI) or once-altered images, such as $3{\times}3$ average filtering (AVE3), QF=90 JPEG (JPG90), 90% down, and 110% up to scale (DN0.9 and Up1.1) images, versus $3{\times}3$ and $5{\times}5$ median filtering (MF3 and MF5, respectively) and MF3 and MF5 composite images (MF35). When the forged image was post-altered with AVE3, DN0.9, UP1.1 and JPG70 after MF3, MF5 and MF35, the performance of the proposed scheme is lower than the MFR scheme. In particular, the feature vector in this paper has a superior classification ratio compared to AVE3. However, in the measured performances with unaltered, once-altered and post-altered images versus MF3, MF5 and MF35, the resultant AUC by 'sensitivity' (TP: true positive rate) and '1-specificity' (FN: false negative rate) is achieved closer to 1. Thus, it is confirmed that the grade evaluation of the proposed scheme can be rated as 'Excellent (A)'.

• Nuclear Engineering and Technology
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• 제49권7호
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• pp.1423-1430
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• 2017

Detonation cell width is an important parameter in hydrogen explosion assessments. The experimental data on gas detonation are statistically analyzed to establish a universal method to numerically predict detonation cell widths. It is commonly understood that detonation cell width, ${\lambda}$, is highly correlated with the characteristic reaction zone width, ${\delta}$. Classical parametric regression methods were widely applied in earlier research to build an explicit semiempirical correlation for the ratio of ${\lambda}/{\delta}$. The obtained correlations formulate the dependency of the ratio ${\lambda}/{\delta}$ on a dimensionless effective chemical activation energy and a dimensionless temperature of the gas mixture. In this paper, support vector regression (SVR), which is based on nonparametric machine learning, is applied to achieve functions with better fitness to experimental data and more accurate predictions. Furthermore, a third parameter, dimensionless pressure, is considered as an additional independent variable. It is found that three-parameter SVR can significantly improve the performance of the fitting function. Meanwhile, SVR also provides better adaptability and the model functions can be easily renewed when experimental database is updated or new regression parameters are considered.

• Structural Engineering and Mechanics
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• 제15권3호
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• pp.299-314
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• 2003

This investigation presents an efficient method for identifying modal characteristics from the measured displacement, velocity and acceleration signals of multiple channels on structural systems. A Vector Backward Auto-Regressive model (VBAR) that describes the relationship between the output information in different time steps is used to establish a backward state equation. Generally, the accuracy of the identified dynamic characteristics can be improved by increasing the order of the Auto-Regressive model (AR) in cases of measurement of data under noisy circumstances. However, a higher-order AR model also induces more numerical modes, only some of which are the system modes. The proposed VBAR model provides a clear characteristic boundary to separate the system modes from the spurious modes. A numerical example of a lumped-mass model with three DOFs was established to verify the applicability and effectiveness of the proposed method. Finally, an offshore platform model was experimentally employed as an application case to confirm the proposed VBAR method can be applied to real-world structures.

• 제어로봇시스템학회논문지
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• 제14권4호
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• pp.385-391
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• 2008

To effectively cope with a complexity of kinematic metrology due to workspace enlargement of the planar stage, the linear induction motor is suggested as its new driving source. Especially, the linear induction motor under uniform plate type of secondary doesn't inherently have a periodical force ripple which is generally shown in the brushless DC motor. But, it presents a poor transient characteristic at zero or low speed zone owing to time delay of flux settling, resulting in slow response. To improve the servo property of linear induction motor and apply successfully it to the precision stage, this paper discusses a modified vector control methodology. The controller has a novel input form, fixed d-axis current, q-axis current and forward-fed DC current, to control thrust force and normal force of the linear induction motor independently. Influence of the newly introduced input and the feasibility of controller are validated experimentally.

• 디지털콘텐츠학회 논문지
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• 제13권3호
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• pp.263-269
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• 2012

캐릭터의 그룹핑은 3D 게임에서 매우 효과적으로 게임을 즐길 수 있게 한다. 본 논문에서는 객체 특징 벡터를 이용하여 3D 게임 캐릭터를 속성에 따라 그룹핑하는 방법을 제시한다. 게임에서 움직임이 거의 없는 캐릭터(NMT)의 경우 외부가 직선에 의한 단순한 형태로 나타난다. 그러나 움직임이 많은 캐릭터(MT)는 그것과 구분된다. 이러한 특징을 가버 필터를 이용하여 추출하고 K-NN으로 그룹핑한다. 실험을 통하여 각 속성을 사용해서 그룹핑한 경우 80%를 상회하는 정확도를 얻었다. 제안한 방법은 게임 진행에서 유사한 속성을 가진 캐릭터들이 효과적으로 그룹핑되어 전략적이고 속도감 있게 플레이 할 수 있는 기능을 제공한다.

• 한국멀티미디어학회논문지
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• 제20권2호
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• pp.115-125
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• 2017

For many stroke patients undergoing rehabilitation therapy, there is a need for indicator for evaluating the body function in paretic and non-paretic regions of stroke patients quantitatively. In this paper, the function of muscles and cells in paretic and non-paretic regions of severe and mild hemiplegic stroke patients was evaluated using multi-channel bioelectrical impedance spectroscopy. The paretic and non-paretic regions of severe and mild stroke patients were quantitatively assessed by using bioelectrical impedance parameters such as prediction marker (PM), phase angle (${\theta}$), characteristic frequency ($f_c$), and bioelectrical impedance vector analysis (BIVA). The mean values of impedance vector were significantly discriminated in all comparisons (severe-paretic, severe-non-paretic, mild-paretic, and mild-non-paretic). The bioelectrical impedance parameters were proved to be a very valuable tool for quantitatively evaluating the paretic and non-paretic regions of hemiplegic stroke patients.

• 대한전기학회논문지
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• 제37권12호
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• pp.839-846
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• 1988

전기기기의 와류분포를 해석하고자 항때 자기벡터포텐셜을 이용한 2차원적 해석법을 적용하면 해석영성내의 와류의 크기는 구할수 있지만 그 분포 양상은 알 수 없다. 이러한 문제점을 해결하기 위해 전류 벡터포텐셜을 도입하여 지배방정식을 유도하였으며 이에 유한요소법을 적용하여 2차원적 와류분포해석을 시도하였다. 그리도 시간술분항의 취급에는 시간영성가중계산법을 적용하였으며 이에 따른 알고리즘을 도출하였다. 또한 위에 방법을 해석해가 좌우하는 모델 및 와류에 의해 구동토오크가 발생하는 군상적산전력계 의 알루미늄 원판에 적용하여 해석한 결과 그 타당성 및 유용성을 입증할 수 있었다.

• 센서학회지
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• 제24권1호
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• pp.47-53
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• 2015

Fall-related injuries in elderly people are a major health care problem. This paper introduces determination of fall direction before impact using support vector machine (SVM). Once a falling phase is detected, dynamic characteristic parameters measured by the accelerometer and gyroscope and then processed by a Kalman filter are used in the SVM to determine the fall directions, i.e., forward (F), backward (B), rightward (R), and leftward (L). This paper compares the determination sensitivities according to the selected parameters for the SVM (velocities, tilt angles, vs. accelerations) and sensor attachment locations (waist vs. chest) with regards to the binary classification (i.e., F vs. B and R vs. L) and the multi-class classification (i.e., F, B, R, vs. L). Based on the velocity of waist which was superior to other parameters, the SVM in the binary case achieved 100% sensitivities for both F vs. B and R vs. L, while the SVM in the multi-class case achieved the sensitivities of F 93.8%, B 91.3%, R 62.3%, and L 63.6%.