• Journal of the Korean Institute of Intelligent Systems
• /
• v.17 no.3
• /
• pp.355-367
• /
• 2007

This paper proposes a design method of the PI(Proportional-Integral)+D(Derivative) controller using self-tuning of the design variables and controller gains. The used fuzzy PI+D controller is the approximated conventional continuos time linear PI+D controller and the used fuzzification method is the fuzzy single tone and the adapted defuzzification method is the simplified tenter of gravity. Fuzzy estimation result would be calculated in the other function elements from the classified fuzzy variables and the result determined by the design variables decides the controller gains. As a result, the proposed method shows the capability of the high speed tuning and can be applied to the case of input variables with many fuzzy partitions and also can bring out the advantage to reduce the reconstruction(digital sampling reconstruction) error. Most simulation results show that this controller makes much bettor efficiency and improvement by using design variables and controller gains.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.12 no.3
• /
• pp.231-238
• /
• 2002

As a modeling method where the merits of fuzzy inference system and evolutionary computation are put together, evolutionary fuzzy modeling performs global approximate optimization. The paper proposes fuzzy clustering as fuzzy rule generation process which is one of the most important steps in evolutionary fuzzy modeling. With application of fuzzy clustering into the experiment or simulation results, fuzzy rules which properly describe non-linear and complex design problem can be obtained. The efficiency of evolutionary fuzzy modeling can be improved utilizing the membership degrees of data to clusters from the results of fuzzy clustering. To ensure the validity of the proposed method, the real design problem of an automotive inner trim is applied and the global approximation is achieved. Evolutionary fuzzy modeling is performed for several cases which differ in the number of clusters and the criterion of rule selection and their results are compared to prove that the proposed method can provide proper fuzzy rules for a given system and reduce computation time while maintaining the errors of modeling as a satisfactory level.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2012.05a
• /
• pp.128-132
• /
• 2012

물은 생물의 생존을 위해 필수적인 요소로 인류가 시작된 이래로 물을 효율적으로 이용하고 안전하게 관리하기 위한 노력은 계속되어 왔다. 최근 지구 온난화가 주요 원인으로 알려진 국지성 집중호우의 피해는 매우 심각하며, 이로 인해 치수에 대한 중요성은 날로 커지고 있다. 지금까지 사용해 왔던 홍수 예 경보 과정은 특정 지점의 유출량을 예측하기 위해서 강우-유출 모형을 운영하였다. 그러나 물리적 모형의 경우 운영에 필요한 매개변수의 결정과정이 복잡하고, 매개변수 결정을 위해 많은 자료를 필요로 한다. 또한 그 매개변수의 결정과정은 많은 불확실성을 포함하고 있어서 모형의 운영을 위한 전처리과정과 계산과정을 거치는 동안 발생한 오차가 누적되어 결과물 속에는 많은 오차가 포함되어 있다. 본 연구에서는 기존의 홍수 예 경보 시스템의 문제점과 불확실성을 최대한 감소시키고 더 우수한 유출량 예측을 위해 neuro-fuzzy 추론 기법을 이용한 모형인 ANFIS(Adaptive Neuro-Fuzzy Inference System)를 사용하여 하천수위를 예측하였다. ANFIS는 신경회로망과 퍼지이론을 결합한 기법으로 신경회로망의 구조와 학습 능력을 이용하여 제어환경에서 획득한 입 출력 정보로부터 언어변수의 membership 함수와 제어규칙을 제어 대상에 적합하도록 자동으로 조종하는 기법이다. 본 연구에서는 ANFIS를 사용하여 탄천 하류에 위치한 대곡교의 수위를 예측하였다. 분석을 위해 2007년부터 2011년까지의 탄천 유역의 관측 강우자료와 수위 자료 중 강우강도와 지속시간, 강우 형태에 따라 7개의 강우사상을 선정하였다. 학습자료 및 보정자료의 변화에 따른 예측 오차를 비교하여 모형의 적용성과 적정성을 평가하였다. 적용결과 입력자료 구성의 경우 해당 시간의 강우량 및 수위자료와 10분 전 강우자료를 이용한 모델이 가장 우수한 예측을 보였고, 학습자료의 경우 자료의 길이가 길고, 최대홍수량이 큰 경우 가장 우수한 예측 결과를 보였다. 본 연구의 적용결과 가장 우수한 모형의 경우 30분 예측 첨두수위 오차는 0.32%, RMSE는 0.05m 이고 예측시간이 길어짐에 따라 오차가 비선형적으로 증가하는 경향을 보였다.

• The Journal of the Korea Contents Association
• /
• v.7 no.12
• /
• pp.346-354
• /
• 2007

Interpolation methods to get the magnified image from an image with low resolution use known pixels to make an interpolated pixel. This interpolation process usually generates blurred edges and blocking effect in the result image. To improve these defects, conventional methods multiply proper weights reflecting neighborhood pixels and add the values during interpolating process. The proposed method changes input pixels in consideration of information of neighborhood pixels, gets interpolated pixels by using these values and improves the quality of interpolated image. Firstly, we compute difference values of the diagonal directions of a pixel and classify flat regions and complex regions according to these values. If the regions is complex ones, the proposed method changes an original pixel into a new value using a input pixel and a median value of it's neighbor pixels. Therefore, the proposed method applies bilinear method to the original pixels in flat regions and the changed ones in complex regions and produces the interpolated images. We evaluate the performance of the proposed method with existing methods by using PSNR and the quality of enlarged image. The results show that the proposed method improves PSNR in comparing with conventional methods and that is superior to the existing methods in terms of the quality of the interpolated image.

• Journal of the Earthquake Engineering Society of Korea
• /
• v.9 no.2 s.42
• /
• pp.37-46
• /
• 2005

To date, many viable smart base isolation systems have been proposed and investigated. In this study, a novel friction pendulum system (FPS) and an MR damper are employed as the isolator and supplemental damping device, respectively, of the smart base isolation system. A fuzzy logic controller (FLC) is used to modulate the MR damper because the FLC has an inherent robustness and ability to handle non linearities and uncertainties. A genetic algorithm (GA) is used for optimization of the FLC. The main purpose of employing a GA is to determine appropriate fuzzy control rules as well to adjust parameters of the membership functions. To this end, a GA with a local improvement mechanism is applied. This method is efficient in improving local portions of chromosomes. Neuro fuzzy models are used to represent dynamic behavior of the MR damper and FPS. Effectiveness of the proposed method for optimal design of the FLC is judged based on computed responses to several historical earthquakes. It has been shown that the proposed method can find optimal fuzzy rules and the GA optimized FLC outperforms not only a passive control strategy but also a human designed FLC and a conventional semi active control algorithm.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.18 no.4
• /
• pp.135-142
• /
• 2017

This study employs an analytical mathematical model to estimate the optimal debt ratio of Korean agricultural corporations, more sensitive to the government debt ratio policy compared to other industries, and the estimation of the optimal debt ratio based on objective data. The analytical model utilizes the equation for ROE, with the debt ratio as an independent variable, and related parameters include ROS, TAT, and NFCL. Regarding the NFCL, the optimal debt ratio standard is defined as the debt ratio that maximizes the ROE by analytical procedures such as adding an equation concerning the debt ratio and a linearity relationship to the analytical model, and from these equations, a quadratic equation with the debt ratio as an independent variable describes the ROE. This methodemploys fourteen years of corporate data. Results show that 138% of debt ratio is the optimal debt ratio to increase the ROE of the corporations, which implies that the existing debt ratio of Korean agricultural corporations is higher than optimal. Consequently, it is required for authorities to change future debt ratio policies in view that the purpose of debt ratio management is to maintain safety and increase profitability.Management should emphasize characteristics of the specific industry rather than standardized judgements based on numerical indexes.

• The Korean Journal of Nuclear Medicine
• /
• v.32 no.3
• /
• pp.225-237
• /
• 1998

Purpose: We investigated the statistical methods to compose the functional brain map of human working memory and the principal factors that have an effect on the methods for localization. Materials and Methods: Repeated PET scans with successive four tasks, which consist of one control and three different activation tasks, were performed on six right-handed normal volunteers for 2 minutes after bolus injections of 925 MBq $H_2^{15}O$ at the intervals of 30 minutes. Image data were analyzed using SPM96 (Statistical Parametric Mapping) implemented with Matlab (Mathworks Inc., U.S.A.). Images from the same subject were spatially registered and were normalized using linear and nonlinear transformation methods. Significant difference between control and each activation state was estimated at every voxel based on the general linear model. Differences of global counts were removed using analysis of covariance (ANCOVA) with global activity as covariate. Using the mean and variance for each condition which was adjusted using ANCOVA, t-statistics was performed on every voxel To interpret the results more easily, t-values were transformed to the standard Gaussian distribution (Z-score). Results: All the subjects carried out the activation and control tests successfully. Average rate of correct answers was 95%. The numbers of activated blobs were 4 for verbal memory I, 9 for verbal memory II, 9 for visual memory, and 6 for conjunctive activation of these three tasks. The verbal working memory activates predominantly left-sided structures, and the visual memory activates the right hemisphere. Conclusion: We conclude that rCBF PET imaging and statistical parametric mapping method were useful in the localization of the brain regions for verbal and visual working memory.

• Proceedings of the Korea Society for Simulation Conference
• /
• 1999.10a
• /
• pp.169-169
• /
• 1999

최근 산업 플랜트의 공정제어 시스템은 복잡하고 대규모화되어 고장 발생시 경제적 손실과 위험성이 증폭되어 규정된 안정서와 신뢰성 확보가 필수적이라 할 수 있다. 고장검출 및 진단기법은 시스템의 신뢰성을 높이기 위한 효과적인 방안을 연구하는 것으로 현대에 들어서 많은 학자들의 관심을 끌고 있으며 실제 계통에 점차적으로 응용되고 있다. 현재까지 개발된 고장검출 및 진단기법은 사용된 프로세스 모델의 형태, 고장검출 진단 알고리즘에 따라 다양하게 분류 될 수 있으며 일반적으로 사용된 모델에 따라 크게 1) 정량적 모델에 근거한 해석적 기법, 2) 정성적 모델에 근거한 기법, 3) 지식기반 진단 기법으로 구분 할 수 있다. 이중 정량적 모델 기법은 대상계통의 수학적 모델에 근거하여 운전 데이터를 분석함으로서 고장검출 진단을 수행하는 해석적 기법으로서 근본적으로 계통의 정확한 수학적 모델을 요구하므로 불확실성을 포함한 계통 및 비선형성이 강한 계통등에는 적용이 곤란하다. 정성적 모델 및 지식기반 기법은 정량적 진단 기법과는 달리 대상 프로세스에 대한 수학적 모델 대신에 운전자의 경험과 프로세스 변수간의 상호 작용 및 고장의 전파과정, 고장원인과 증상과의 직접적인 관계에 대한 구조적 지식에 근거한 것으로 고장원인에 대한 계통의 동작을 추론 할 수 있으며, 상황 변화에 따른 영향을 예측할 수 있다. 본 논문에서는 정성적 모델 및 지식기반 기법에 근거한 고장검출 및 진단 기술을 화력 발전소 보일로 프로세스에 적용하여 정성적 시뮬레이션에 의한 설비의 고장을 조기에 발견하여 고장 파급으로 인한 발전 정지 및 설비의 손상 확대를 방지하고 고장 발생시 신속한 원인 규명 및 후속 조치관련 정보들을 운전원에게 제공할 목적으로 현재 전력원에서 개발중인 지능형 경보시스템에 대하여 기술하고자 한다.음과 같이 설명하였다. 서로 상반되는 것들이 다음과 같이 설명하였다. 서로 상반되는 것들이 부딛힘이 없이 공존하고 일상의 논리가 무시된다. 부정, 의심이 없고 확실한 것이 없다. 한 대상에 가졌던 생각이 다른 대상에 옮겨간다(displacement). 한 대상이 여러 대상이 갖고 있는 의미를 함축하고 있다(condensation). 시각적인 순서가 무시된다. 마음속의 생각과 외부의 실제적인 일을 구분하지 못한다. 시간 상의 순서가 있다가 없다가 한다. 차례로 일어나야 할 일이 동시에 한꺼번에 일어난다. 대상들이 서로 비슷해지고 동시에 있을 수 없는 대상들이 함께 나타난다. 사고의 정상적인 구조가 와해된다. Matte-Blance는 무의식에서는 여러 독립된 대상들간의 구분을 없애며, 주체와 객체를 하나로 보려는 대칭화(symmetrization)의 경향이 있기 때문에 이런 변화가 생긴다고 하였다. 또 대칭화가 진행되면 무한대의 느낌을 갖게 되어, 전지(moniscience), 전능(omnipotence), 무력감(impotence), 이상화(idealization)가 나타난다. 그러나 무의식에 대칭화만 있는 것은 아니며, 의식의 사고양식인 비대칭도 어느 정도 나타나며, 대칭화의 정도에 따라, 대상들이 잘 구분되어 있는 단계, 의식수준의 감정단계, 집단 내에서의 대칭화 단계, 집단간에서의 대칭화 단계, 구분이 없어지는 단계로 구분하였다.systems. We believe that this taxonomy is a significant contribution because it adds clarity, completeness, and "global perspective" to workflow architectural discussions. The vocabulary suggested here

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.19 no.3
• /
• pp.301-308
• /
• 2018

This study explores an analytical mathematical model designed to estimate the optimal debt ratio of the Korean automobile industry, which has a more significant effect on the national economy than that of other industries, and attempts to estimate the optimal debt ratio based on objective data. The analytical model is based on ROA and ROE which uses the debt ratio as an independent variable and employs ROS, TAT, and NFCL as the related parameters. Regarding the NFCL, the optimal debt ratio is usually defined as the debt ratio that maximizes the ROA and ROE and is calculated using analytical procedures, such as by adding an equation that considers the debt ratio and the linearity relationship to the analytical model. This is because the optimal debt ratio can be calculated reliably by making use of an estimated value within a certain range, which is derived from more than two calculations rather than a single estimation starting from one calculation formula. In this study, for the estimation of the optimal debt ratio, the ROA and ROE are expressed as a quadratic equation with the debt ratio as the independent variable. Using this analysis procedure, the optimal debt ratio obtained using the data from the Korean automobile industry over a sixteen year period, which would optimize the profitability of the Korean automobile industry, was found to be 188% of the debt ratio in the ROA and 213% of the debt ratio in the ROE. This result was obtained by overcoming the problem of the reliability of the estimation value in spite of the limitations of the logical theory of this study, and can be interpreted as meaning that maintaining a debt ratio of 188% to 213% can enhance the profitability and reduce the risks in the Korean automobile industry. Furthermore, this indicates that the existing debt ratio of the Korean automobile industry is lower than the optimal value within the estimated range. Consequently, it is necessary for corporations to change their future debt ratio policies, given that the purpose of debt ratio management is to maintain safety and increase profitability, and to take into account the characteristics of the specific industry.

• The Journal of Korean Academy of Prosthodontics
• /
• v.53 no.2
• /
• pp.120-127
• /
• 2015

Purpose: The aim was to investigate the effect of implant thread designs on the stress dissipation of the implant. Materials and methods: The threads evaluated in this study included the V-shaped, buttress, reverse buttress, and square-shaped threads, which were of the same size (depth). Building four different implant/bone complexes each consisting of an implant with one of the 4 different threads on its cylindrical body ($4.1mm{\times}10mm$), a force of 100 N was applied onto the top of implant abutment at $30^{\circ}$ with the implant axis. In order to simulate different osseointegration stages at the implant/bone interfaces, a nonlinear contact condition was used to simulate immature osseointegration and a bonding condition for mature osseointegration states. Results: Stress distribution pattern around the implant differed depending on the osseointegration states. Stress levels as well as the differences in the stress between the analysis models (with different threads) were higher in the case of the immature osseointegration state. Both the stress levels and the differences between analysis models became lower at the completely osseointegrated state. Stress dissipation characteristics of the V-shape thread was in the middle of the four threads in both the immature and mature states of osseointegration. These results indicated that implant thread design may have biomechanical impact on the implant bed bone until the osseointegration process has been finished. Conclusion: The stress dissipation characteristics of V-shape thread was in the middle of the four threads in both the immature and mature states of osseointegration.