• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.04a
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• pp.340-345
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• 2014

Vibration testing is conducted for evaluate the fatigue resistance of responsible system over excitation situations and two kinds of vibration profiles, harmonic or random, are widely used in engineering fields. Harmonic excitation profile is adequate for the rotating machinery that is primarily exposed to the orderly excited force subjected for a rotating speed; Random profile is suitable for the non-stationary vibration input, that is a ground excitation for example. Recently, the sine on random (SOR) testing method was sometimes considered to represent the real excitation conditions since the measured response signals of a target system, expecially for moving mobility, shows usually a mixture of them. So, it is important to understand the accumulated fatigue damage over different excitation patterns, harmonic and/or random, to determine the efficient vibration profile of a target system. A uniaxial vibration testing with a notched simple beam was introduced to evaluate the fatigue damage for different excitation profiles and the best choice of vibration profile was concluded from those comparison of calculated fatigue damages.

• The Journal of the Acoustical Society of Korea
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• v.6 no.4
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• pp.21-30
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• 1987

Length normalization by variable frame size is proposed as a novel approach to length normalization to solve the problem that the length variation of spoken word results in a lowing of recognition accuracy. This method has the advantage of curtailment of recognition time in the recognition stage because it can reduce the number of frames constructing a word compared with length normalization by a fixed frame size. In this paper, variable frame length normalization is applied to multisection vector quantization and the efficiency of this method is estimated in the view of recognition time and accuracy through practical recognition experiments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.6
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• pp.556-565
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• 1991

Using the WDZ decomposition algorithm, a parallel algorithm is presented for solving the linear system Ax=b which has an nxn nonsingular tridiagonal matrix. For implementing this algorithm a CAM systolic arrary is proposed, and each processing element of this array has its own CAM to store the nonzero elements of the tridiagonal matrix. In order to evaluate this array the algorithm presented is compared to theis compared to the LU decomposition algorithm. It is found that the execution time of the algorithm presented is reduced to about 1/4 than that of the LU decomposition algorithm. If each computation process step can be dome in one time unit, the system of eqations is solved in a systolic fashion without central control is obtained in 2n+1 time steps.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.15 no.7
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• pp.553-564
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• 1990

The co-efficient matrix of linear second-order partial differential equations in the general form is partitioned with (n-1)x(n-1) submartices and is transformed into the block tridiagonal system. Then the cyclic odd-even reduction technique is applied to this system with the large-grain data granularity and the block cyclic reduction algorithm to solve unknown vectors of this system is created. But this block cyclic reduction technique is not suitable for the parallel processing system because of its parallelism chanigng at every computing stages. So a new algorithm for solving linear second-order partical differential equations is presentes by the block cyclic reduction technique which is modified in order to keep its parallelism constant, and to reduce gteatly its execution time. Both of these algoriths are compared and studied.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.6
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• pp.1055-1063
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• 2014

Recently, various methods have been proposed for improving the performance of the side channel analysis using the power consumption. Of those method, waveform compression method applies to reduce the noise component in pre-processing step. In this paper, we propose the new LDA(Linear Discriminant Analysis)-based signal compression method finding unique feature vector. Through experimentations, we are comparing the proposed method with the PCA(Principal Component Analysis)-based method which has known for the best performance among existing signal compression methods.

• Proceedings of the KIPE Conference
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• 2010.11a
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• pp.351-353
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• 2010

본 논문에서는 쉽고 빠르게 정확한 리튬 이온 배터리 모델을 구현할 수 있는 방법을 제시하고 있으며, 구현된 모델을 MATLAB(R)/Simulink(R)환경에서 검증한다. 모델을 구현함에 있어서 절차를 간소화하기 위해 비선형 개방 전압은 배터리 충전 및 방전 전압의 평균으로 근사하고, 배터리 내부 비선형 파라미터는 방전 초기에 발생하는 과도응답을 측정한 이산 데이터를 곡선 접합하여 구한다. 구현된 모델을 이용하여 시뮬레이션을 하고 이를 실험 데이터와 비교해본 결과, 평균 절대오차는 기존 연구보다 0.1% 낮은 0.091%로 측정되었다. 측정된 오차의 수준은 본 논문에서 제안한 방법이 파라미터 추출에 필요한 시간을 단축하고 시뮬레이션 모델을 쉽게 구현 가능하게 함에도 불구하고 여전히 리튬 이온 배터리의 출력 특성을 정확하게 예측함을 보여준다.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.1
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• pp.202-208
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• 2014

Friction force on robot systems is highly nonlinear and especially disturbs precise control of the robots at low speed. This paper deals with the dynamic friction compensation problem of a well-known one-link benchmark robot system. We consider the LuGre model because the model can successfully represent dynamic characteristics and various effects of friction phenomenon. The proposed controller is constructed as two parts. An adaptive controller based on dual observers is used to estimate and compensate the dynamic friction. In order to attenuate the friction estimation error and other disturbances, PI observer is additionally designed. Through the computer simulations with the benchmark system, this paper first examines the effects of nonlinear dynamic friction on the control performance of the benchmark robot system. Next, it is shown that the control performance against the dynamic friction is improved by using the proposed controller.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.40 no.4
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• pp.353-362
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• 2016

An accurate hysteresis model of an elastomer is important for quantifying viscoelastic energy loss. We suggest a highly nonlinear hyper-viscoelastic constitutive model of elastomers. The model captures a nonlinear viscoelastic characteristic by combining Yeoh's hyperelastic model and Hoofatt's hysteresis model used Neo-Hookean hyperelastic model. Analytical and numerical models were generated from uniaxial cyclic tests of an elastomer under a sinusoidal load with a mean strain of 150%, amplitudes of 20~80%, and frequencies of 0.02~0.2Hz. The viscoelastic model can highly capture the viscoelastic energy loss up to a strain of 230%.

• Polymer(Korea)
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• v.37 no.3
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• pp.405-410
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• 2013

The effect of styrene-ethylene/butylene-styrene (SEBS) on the blend of polyphenylene sulfide (PPS) and polyethylene terephthalate (PET) was investigated. The blends were extruded by a single screw extruder equipped with a Maddock mixing screw, and their molded properties were examined. After the binary blends were prepared on the whole compositions of PPS/PET (80/20, 60/40, 40/60, 20/80), the thermal, rheological, mechanical properties and morphology of the blends were analyzed. The results showed the significant decline in the properties of the blends owing to the incompatibility between PPS and PET phases. As a basic blend composition, the PPS/PET (40/60) blend was selected by considering cost efficiency. To this basic blend, SEBS was added as a compatibilizer. With increasing SEBS addition, the mechanical properties were improved. From the domain size reduction observed in morphology, it might be due to the enhancement of compatibility between linear PPS and PET phases by addition of SEBS.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.2 s.302
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• pp.39-48
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• 2005

This paper proposes a novel approach to recognize nine kinds of motion for a multifunction myoelectric hand, acquiring four channel EMG signals from electrodes placed on the forearm. To analyze EMG with properties of nonstationary signal, time-frequency features are extracted by wavelet packet transform. For dimensionality reduction and nonlinear mapping of the features, we also propose a feature projection composed of PCA and SOFM. The dimensionality reduction by PCA simplifies the structure of the classifier, and reduces processing time for the pattern recognition. The nonlinear mapping by SOFM transforms the PCA-reduced features to a new feature space with high class separability. Finally a multilayer neural network is employed as the pattern classifier. From experimental results, we show that the proposed method enhances the recognition accuracy, and makes it possible to implement a real-time pattern recognition.