• Journal of Mechanical Science and Technology
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• 제20권12호
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• pp.2043-2051
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• 2006

This paper considered identification of vibration characteristics of flexible structure with vector channel periodic lattice filter. We present an algorithm for AR coefficients for the vector-channel lattice filters, and characteristic equation and transfer function are derived from these coefficients. Vibration lattice filter is then constructed from the vector channel lattice filter, and performance of this vibration filter is tested with a test signal which is a combination of many sine waves to compare the performance of scalar and vector channel lattice. Also it is applied to the cantilever data to identify properties of the system, such as natural frequencies and damping ratios, to show its performance.

• Journal of Information Processing Systems
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• 제15권2호
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• pp.422-432
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• 2019

A hybrid kernel function of support vector machine is proposed to improve the classification performance of power quality disturbances. The kernel function mathematical model of support vector machine directly affects the classification performance. Different types of kernel functions have different generalization ability and learning ability. The single kernel function cannot have better ability both in learning and generalization. To overcome this problem, we propose a hybrid kernel function that is composed of two single kernel functions to improve both the ability in generation and learning. In simulations, we respectively used the single and multiple power quality disturbances to test classification performance of support vector machine algorithm with the proposed hybrid kernel function. Compared with other support vector machine algorithms, the improved support vector machine algorithm has better performance for the classification of power quality signals with single and multiple disturbances.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1998년도 추계종합학술대회 논문집
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• pp.507-510
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• 1998

In this paper, a novel test method is proposed to detect hard and soft fault in CMOS operational amplifiers. Proposed test method mark use of the offset character, which is one of the op-amps characteristics. During the test mode, CUT is implemented to unit gain op-amps with feedback loop. When the input is grounded, a good circuit has a small offset voltage, but a faulty circuit has a large offset voltage exceeding predefined range of tolerance. Using the proposed method, no test vector is required to be applied. Therefore the test vector generation problem is eliminated and the test time is reduced. The accuracy and effectiveness of the method is verified through HSPICE simulation.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.2594-2599
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• 2003

We consider some problems of the Modified SPRT(Sequential Probability Ratio Test) method for fault detection and isolation of inertial redundant sensor systems and propose an Advanced SPRT method to solve the problems of the Modified SPRT method. One problem of the Modified SPRT method to apply to inertial sensor system comes from the effect of inertial sensor errors such as misalignment, scale factor error and sensor bias in the parity vector, which make the Modified SPRT method hard to be applicable. The other problem is due to the correlation of parity vector components which may induce false alarm. We use a two-stage Kalman filter to remove effects of the inertial sensor errors and propose the modified parity vector and the controlled parity vector which removes the effect of correlation of parity vector components. The Advanced SPRT method is derived form the modified parity vector and the controlled parity vector. Some simulation results are presented to show the usefulness of the Advanced SPRT method to redundant inertial sensor systems.

• 전기전자학회논문지
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• 제18권3호
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• pp.305-312
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• 2014

기존의 Verilog테스트벤치로 원전용 안정등급 제어기기와 같이 복잡하고 높은 신뢰도를 요구하는 모듈의 테스트는 수작업으로만 수행된 결과를 가지고 RTL단계의 검증을 마무리하기에는 현실적으로 많은 시간과 노력이 필요하다. UVM은 기존의 테스트벤치의 한계점을 보완하는 계층적 테스트벤치의 구조를 갖고 있어 DUT의 검증을 위한 테스트개선에 대해 테스트벤치의 수정을 간편하게 할 수 있다. 비록 구축과정이 다소 복잡하긴 하지만 테스트 벤치의 컴포넌트들인 driver나 sequence 등을 사용함으로 constraint random test를 가능하게 하여 test vector 작성을 편리하게 한다. 본 논문에서는 기존의 테스트벤치와 계층적 테스트벤치인 UVM테스트벤치를 사용하여 실제 시뮬레이션 하고 커버리지를 분석하여 코드커버리지를 간편하게 향상 할 수 있음을 보였다.

• 사물인터넷융복합논문지
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• 제1권1호
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• pp.33-38
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• 2015

하드웨어는 다양한 구조로 개발되고, 모듈들에 대한 시간 시뮬레이션을 할 때 각 클럭 사이클에 사용되는 변수들의 값을 확인할 필요가 있다. 본 논문은 224비트 ECDSA 하드웨어를 개발하면서 하드웨어 모듈의 시간 시뮬레이션을 위한 테스트 벡터를 제공하는 소프트웨어 생성기를 소개한다. 테스트 벡터는 GUI 형태와 텍스트 파일 형태로 제공된다.

• 전산구조공학
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• 제4권1호
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• pp.95-108
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• 1991

외연적 유한요소법은 벡터처리에 적합한 구조를 가지고 있어 벡터컴퓨터를 이용하면 기존의 스칼라 컴퓨터에서보다 휠씬 빠르게 해석을 수행할 수 있다. 본 논문에서는 memory-to-memory방식의 벡터컴퓨터에서의 외연적 유한요소법의 효율적인 벡터화 방법을 제시하였다. 먼저 벡터컴퓨터의 구조적 특성과 무관하게 적용될 수 있는 일반적인 벡터화 기법을 고찰한 후 memory-to-memory방식의 벡터컴퓨터에 적합한 벡터화 기법을 개발하였다. 개발된 벡터화 기법의 유용성을 확인하기 위해 외연적 유한요소 프로그램인 DYNA3D를 memory-to-memory방식의 벡터컴퓨터인 HDS AS/XL V50에 이식한 결과 스칼라에 비해 2.4배 이상의 성능 향상을 얻을 수 있었다.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2006년도 가을 학술발표논문집 Vol.33 No.2 (C)
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• pp.218-221
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• 2006

본 논문은 인터넷의 대표적인 문제점중의 하나인 Adult Image 분류 연구에 대해 기술한다. 특히 우리는 이러한 Adult Image를 분류하기 위한 Data Set을 5가지 타입으로 구성한다. 이러한 각 Image에 대해 Color, Gradient, Edge Direction 특성의 Feature들을 추출하고 이를 Histogram으로 구성한다. 이렇게 구성된 Histogram을 Support Vector Machine에 적용하여 Adult Image를 분류한다. 그 결과, 우리는 8250개의 Test Set에 대하여 Recall(96.53%), Precision(97.33%), False Positive(2.96%), F-Measure(96.93%)의 성능 결과를 보여준다.

• 한국데이터정보과학회:학술대회논문집
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• 한국데이터정보과학회 2005년도 춘계학술대회
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• pp.155-163
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• 2005

This paper applies Support Vector Regression (SVR) to estimate and forecast nonlinear autoregressive integrated (ARI) model of the daily exchange rates of four currencies (Swiss Francs, Indian Rupees, South Korean Won and Philippines Pesos) against U.S. dollar. The forecasting abilities of SVR are compared with linear ARI model which is estimated by OLS. Sensitivity of SVR results are also examined to kernel type and other free parameters. Empirical findings are in favor of SVR. SVR method forecasts exchange rate level better than linear ARI model and also has superior ability in forecasting the exchange rates direction in short test phase but has similar performance with OLS when forecasting the turning points in long test phase.

• 대한화학회지
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• 제58권6호
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• pp.543-552
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• 2014

A quantitative structure activity relationship (QSAR) study is performed for modeling and prediction of oral bioavailabilities of 216 diverse set of drugs. After calculation and screening of molecular descriptors, linear and nonlinear models were developed by using multiple linear regression (MLR), artificial neural network (ANN), support vector machine (SVM) and random forest (RF) techniques. Comparison between statistical parameters of these models indicates the suitability of SVM over other models. The root mean square errors of SVM model were 5.933 and 4.934 for training and test sets, respectively. Robustness and reliability of the developed SVM model was evaluated by performing of leave many out cross validation test, which produces the statistic of $Q^2_{SVM}=0.603$ and SPRESS = 7.902. Moreover, the chemical applicability domains of model were determined via leverage approach. The results of this study revealed the applicability of QSAR approach by using SVM in prediction of oral bioavailability of drugs.