• 한국항만학회지
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• 제15권1호
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• pp.37-46
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• 2001

Fuzzy logic control(FLC) is composed of three parts : fuzzy rule-bases, membership functions, and scaling factors. Well-defined fuzzy rule-base should contain proper physical intuition on the plant, so are needed lots of experiences of the skillful expert. When membership functions are considered, some parameters on the memberships function such as function shape, support, allocation density should be selected well. The rule of scaling factors is 'scaling'(amplifying or reducing) for both input and output signals of the FLC to fit in the membership function support and to operate the plant intentionally. To get a better performance of the FLC, it is necessary to adjust the parameters of the FLC. In general, the adaptation of the scaling factors is the most effective adjustment scheme, compared with that of the fuzzy rule-base or membership function parameters. This study proposes the adaptation scheme of the scaling factors. When the adaptation is performed on-line, the stability of the adaptive FLC should be guaranteed. The stable FLC system can be designed with stability analysis in the sense of Lyapunov stability. To adapt the scaling factors for the error signals, the concept of the conventional MRAC would be introduced into slightly modified form. A tracking accuracy of the control system would be enhanced by the modified shape and support of the membership function. The simulation is achieved on the pilot plant with the hydraulic steering control of a UCT(Unmanned Container Transporter) of which modeling dynamics have lots of severe uncertainties and modeling errors.

• 대한의용생체공학회:의공학회지
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• 제31권2호
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• pp.134-140
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• 2010

Readily available high resolution brain MRI scans allow detailed visualization of the brain structures. Researchers have focused on developing methods to quantify shape differences specific to diseased scans. We have developed a novel method to quantify shape information for a specific population based on Multidimensional scaling(MDS). MDS is a well known tool in statistics and here we apply this classical tool to quantify shape change. Distance measures are required in MDS which are computed from pair-wise image registrations of the training set. Registration step establishes spatial correspondence among scans so that they can be compared in the same spatial framework. One benefit of our method is that it is quite robust to errors in registrations. Applying our method to 13 brain MRI showed clear separation between normal and diseased (Cushing's syndrome). Intentionally perturbing the image registration results did not significantly affect the separability of two clusters. We have developed a novel method to quantify shape based on MDS, which is robust to image mis-registration.

• 대한전자공학회논문지
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• 제25권1호
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• pp.27-32
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• 1988

Electron Spectroscopy for Chemical Analysis(ESCA) allowes the determination of the elemental composition and the bonding state of the surface atomes in the interface between two materials. In the binding energies of ESCA spectrum, there are zero error, voltage scaling error and random error. Accurate analysis of the intensity energy response functions and accurate calibration of the energy scale are essential to use X-ray photoelectron spectron meter. At the results of the calibration of the ESCA spectra in the copper and cordierite (Mg2Al4Si5kO18) interfaces, the errors relative to the copper are -3.03 eV for the zero error -z,-197 ppm for the voltage scaling error -V and 6.9 meV for the random error -R. The method of the calibration is able to apply for the binding energy calibration of the another ESCA spectra.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2007년도 추계학술대회 논문집
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• pp.103-107
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• 2007

In doubly fed induction generators (DFIGs), control of rotor currents allows for adjustable speed operation, active, and reactive power control. This paper presents a DFIG control strategy that enhances the active and reactive power control with controllers that can compensate for the errors caused by current measurement path in the DFIG system. The errors can be divided into two categories: offset and scaling errors. These can induce the speed, active, and reactive power pulsations, which are one and two times the fundamental slip frequency in the DFIG. And these undesirable ripples can do the DFIG harm. In this paper, a new compensation algorithm is proposed. Therefore, the proposed algorithm has several advantages: to implement is easy; it require less computation time; it is robust with regard to the variation of the induction generator parameters. In this paper, a new algorithm is introduced by using the integral of phase currents to measure the current ripples of rotor-side converterin the DFIG system. The experiment results are shown the effectiveness of the proposed method.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2004년도 추계학술대회 논문집
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• pp.32-36
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• 2004

In order to achieve high performance vector control, it is essential to measure accurate ac current. The errors generated from current path are inevitable, and they could be divided into two categories: offset error and scaling error. The current data including these errors cause periodic speed ripples which are one and two times of stator electrical frequency respectively. Since these undesirable ripples bring about bad influences to motor driving system, a compensation algorithm must be needed in the control algorithm of the motor drive. In this paper, a new compensation algorithm is proposed. The signal of the integrator output of the d-axis current regulator is chosen and processed to compensate the current measurement errors. The compensation of the current measurement errors is easily implemented to smooth the signal of the integrator output of the d-axis current regulator by subtracting the DC offset value or rescaling the gain of the hall sensor. Therefore, the proposed algorithm has several features: the robustness of the variation of the mechanical parameters, the application of the steady and transient state, the easy implementation, and less computation time.

• 한국수자원학회논문집
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• 제41권9호
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• pp.873-884
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• 2008

본 연구에서는 서로 다른 지속기간을 가지는 강우자료간의 스케일 성질을 이용하여 확률강우량을 추정하는 방법을 알아보고, 국내 강우자료에 대해서 그 적용성을 살펴보고자 하였다. 기상청 지점중에서 기록기간이 비교적 장기간인 22개 지점에 대해서 지점빈도해석을 통한 확률강우량과 스케일 성질을 활용한 확률강우량간의 정확도를 비교해 본 결과, 시간단위자료를 사용할 경우 대부분 절대상대오차가 10 % 미만인 결과를 얻을 수 있었고, 각각의 지속 기간별로 적용가능한 재현기간을 살펴본 결과 연구에 사용된 총 14개의 재현기간 중에서 대부분 8개 이상의 재현기간에 대해서 적용이 가능한 것으로 나타났다. 적용예로서 대구지점의 지속기간 1시간 강우자료를 바탕으로 지속기간 10분${\sim}$50분까지의 확률강우량자료를 스케일 성질을 이용하여 산정한 결과 지속기간 10분을 제외하고는 모두 절대상대오차 10 % 내외의 정확도를 가지는 것으로 나타났다. 따라서 스케일 성질을 이용하여 미계측 강우지속기간의 확률강우량을 추정할 수 있을 것으로 판단된다.

• 정보보호학회논문지
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• 제33권6호
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• pp.1099-1110
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• 2023

자율주행 및 robot navigation의 인식 시스템은 성능 향상을 위해 다중 센서를 융합(Multi-Sensor Fusion)을 한 후, 객체 인식 및 추적, 차선 감지 등의 비전 작업을 한다. 현재 카메라와 라이다 센서의 융합을 기반으로 한 딥러닝 모델에 대한 연구가 활발히 이루어지고 있다. 그러나 딥러닝 모델은 입력 데이터의 변조를 통한 적대적 공격에 취약하다. 기존의 다중 센서 기반 자율주행 인식 시스템에 대한 공격은 객체 인식 모델의 신뢰 점수를 낮춰 장애물 오검출을 유도하는 데에 초점이 맞춰져 있다. 그러나 타겟 모델에만 공격이 가능하다는 한계가 있다. 센서 융합단계에 대한 공격의 경우 융합 이후의 비전 작업에 대한 오류를 연쇄적으로 유발할 수 있으며, 이러한 위험성에 대한 고려가 필요하다. 또한 시각적으로 판단하기 어려운 라이다의 포인트 클라우드 데이터에 대한 공격을 진행하여 공격 여부를 판단하기 어렵도록 한다. 본 연구에서는 이미지 스케일링 기반 카메라-라이다 융합 모델(camera-LiDAR calibration model)인 LCCNet 의 정확도를 저하시키는 공격 방법을 제안한다. 제안 방법은 입력 라이다의 포인트에 스케일링 공격을 하고자 한다. 스케일링 알고리즘과 크기별 공격 성능 실험을 진행한 결과 평균 77% 이상의 융합 오류를 유발하였다.

• 방사성폐기물학회지
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• 제2권1호
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• pp.35-40
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• 2004

Final disposal of radioactive waste generated from Nuclear Power Plant (NPP) requires the detailed information about the characteristics and the quantities of radionuclides in waste package. Most of these radionuclides are difficult to measure and expensive to assay. Thus it is suggested to the indirect method by which the concentration of the Difficult-to-Measure (DTM) nuclide is estimated using the correlations of concentration - it is called the scaling factor - between Easy-to-Measure (Key) nuclides and DTM nuclides with the measured concentration of the Key nuclide. In general, the scaling factor is determined by the log mean average (LMA) method and the regression method. However, these methods are inadequate to apply to fission product nuclides and some activation product nuclides such as 14$^{C}$ and 90$^{Sr}$ . In this study, the artificial neural network (ANN) method is suggested to improve the conventional SF determination methods - the LMA method and the regression method. The root mean squared errors (RMSE) of the ANN models are compared with those of the conventional SF determination models for 14$^{C}$ and 90$^{Sr}$ in two parts divided by a training part and a validation part. The SF determination models are arranged in the order of RMSEs as the following order: ANN model

• 한국추진공학회지
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• 제25권1호
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• pp.12-18
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• 2021

본 연구에서는 MT30 가스터빈 엔진의 성능 모델링을 수행하였다. 설계점을 결정하고, 상용 프로그램에서 제공하는 스탠다드 맵을 이용한 스케일링 기법으로 구성품 성능 맵을 생성하였다. 생성된 성능 모델로 탈-설계점 성능 해석을 수행하여 그 결과를 엔진 성능 덱 데이터와 비교하였다. 한 점 스케일링 기법으로 생성된 성능 모델이 성능 덱 데이터와 다소 오차가 있음을 확인하고, 성능 모델의 정확성을 높이기 위한 보정이 필요하다고 판단하였다. 따라서 고압 스풀 회전수에 따른 작동점(탈-설계점) 별 스케일링 계수를 구하는 방식으로 보정 성능 모델을 생성하여 탈-설계점 해석을 수행하였다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2001년도 제14회 신호처리 합동 학술대회 논문집
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• pp.107-110
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• 2001

In this paper, we propose a multiplication-free DFT kernel computation technique, whose input sequences are approximated into a ring of Algebraic Integers. This paper also gives computational examples for DFT and IDFT. And we proposes an architecture of the DFT using barrel shifts and adds. When the radix is greater than 4, the proposed method has a high Precision property without scaling errors due to twiddle factor multiplication. A possibility of higher radix system assumes that higher performance can be achievable for reducing the DFT stages in FFT.