• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.207-210
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• 2002

This paper is concerned with the experiments on the active vibration control of a plate with piezoceramic sensors and actuators. The natural frequencies of the composite plate featured by a piezo-film sensor and piezo-ceramic actuator are calculated by using the modal analysis method. Modal coordinates are introduced to obtain the state equations of the structural system. Six natural frequencies were considered in the modelling, because robust control theory which has inherent robustness to structured uncertainty is adopted to suppress the transients vibrations of a glass fiber reinforced(GFR) composite beam. A robust controller satisfying the nominal performance and robust performance is designed using robust theory based on the structured singular value. Simulations were carried out with the designed controller and effectiveness of the robust control strategy was verified by results.

• Proceedings of the Korea Concrete Institute Conference
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• 1989.10a
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• pp.69-72
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• 1989

It is widely recognized that the strength of reinforced concrete members has characteristics of random variations due to the variability of the mechanical properties of concrete and steel, the dimensional error as well as incorrect placement of reinforcing bars. In those sources of randomness, variations in concrete strength may be the one affecting the strength of R.C. members most. The concrete strength is usually assumed to have large uncertainty due to the variations in many factors, such as material properties, proportions of the concrete mix, methods of mixing, transporting, placing and curing, etc. In this study, the random characteristics inherent in the strength of field-cast concrete have been examined based on the data collected by testing standard cylinders made of field-cast concrete and cured under in-situ condition.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.117-120
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• 2001

In this work, we propose a new method of extracting and weighting representative keywords(RKs) from a few documents that might interest a user. In order to extract RKs, we first extract candidate terms and then choose a number of terms called initial representative keywords (IRKS) from them through fuzzy inference. Then, by expanding and reweighting IRKS using term co-occurrence similarity, the final RKs are obtained. Performance of our approach is heavily influenced by effectiveness of selection method of IRKS so that we choose fuzzy inference because it is more effective in handling the uncertainty inherent in selecting representative keywords of documents. The problem addressed in this paper can be viewed as the one of calculating center of document vectors. So, to show the usefulness of our approach, we compare with two famous methods - Rocchio and Widrow-Hoff - on a number of documents collections. The results show that our approach outperforms the other approaches.

• Journal of Korea Technology Innovation Society
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• v.8 no.1
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• pp.29-50
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• 2005

Real options provide a new and productive way to view corporate r&d investment decisions. DCF approach is well established and beloved of financial executives, but is known to systematically underestimate investment value under significant uncertainty. Though real options are not inherent in a r&d investment, they can be used to compute the investment value including managerial flexibility like option value. In this paper, we explain how the interval of option value in black-scholes model can be estimated using simulation. We also present a process framework for interval estimation of volatility and efficient of period of investment value. In such a setting, we can obtain the appropriate interval estimation of the expanded investment value.

• Journal of the Korean Operations Research and Management Science Society
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• v.27 no.3
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• pp.145-156
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• 2002

Business managers are often required to use LP problems to deal with uncertainty inherent in decision making due to rapid changes in today＇s business environments. Uncertain parameters can be easily formulated in the two-stage stochastic LP problems. However, since solution methods are complex and time-consuming, a common approach has been to use modified formulations to provide upper and lower bounds on the two-stage stochastic LP problem. One approach is to use an expected value problem, which provides upper and lower bounds. Another approach is to use “walt-and-see” problem to provide upper and lower bounds. The objective of this paper is to propose a modified approach of “wait-and-see” problem to provide an upper bound and to compare the relative error of optimal value with various upper and lower bounds. A computing experiment is implemented to show the relative error of optimal value with various upper and lower bounds and computing times.

• Journal of Welding and Joining
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• v.18 no.3
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• pp.122-130
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• 2000

Due to the inherent dimensional uncertainty, the tolerances accumulate in the assembly of plasma cutting torch. Tolerance accumulation has serious effect on the performance of the plasma torch. This study proposes a statistical tolerance propagation model, which is based on matrix transform. This model can predict the final tolerance distributions of the completed plasma torch assembly with the prescribed statistical tolerance distribution of each part to be assembled. Verification of the proposed model was performed by making use of Monte Carlo simulation. Monte Carlo simulation generates a large number of discrete plasma torch assembly instances and randomly selects a point within the tolerance region with the prescribed statistical distribution. Monte Carlo simulation results show good agreement with that of the proposed model. This results are promising in that we can predict the final tolerance distributions in advance before assembly process of plasma torch thus provide great benefit at the assembly design stage of plasma torch.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.3
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• pp.149-156
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• 2000

Time delay observer (TDO), thanks to the time delay control (TDC) concept, requires little knowledge of a plant model, and hence is easy to design, robust to parameter variation and computationally efficient, yet can reconstruct states rather reliable for nonlinear plant. In this paper, we propose an improved version of TDO that solves two problems inherent in TDO as follows: TDO displays large reconstruction errors due to low-frequency uncertainty and has some restrictions on selecting its gains. By introducing a low pass filter and a state associated with it, we obtain an enhanced time delay observer (ETDO). This observer turns out to have smaller reconstruction errors than those of TDO and not to have any restriction on selecting its gains, thereby solving the problems. Through performance comparison by transfer function and simulation, we validate the analysis results of two observers (TDO and ETDO) and evaluate the performances. Finally, through experiments on BLDC motor system, the analysis results are clearly conformed.

• International journal of advanced smart convergence
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• v.9 no.3
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• pp.42-48
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• 2020

These days people are overwhelmed by information on the Internet thus searching for useful information becomes burdensome, often failing to acquire some in a reasonable time. Recommender systems are indispensable to fulfill such user needs through many practical commercial sites. This study proposes a novel similarity measure for user-based collaborative filtering which is a most popular technique for recommender systems. Compared to existing similarity measures, the main advantages of the suggested measure are that it takes all the ratings given by users into account for computing similarity, thus relieving the inherent data sparsity problem and that it reflects the uncertainty or vagueness of user ratings through fuzzy logic. Performance of the proposed measure is examined by conducting extensive experiments. It is found that it demonstrates superiority over previous relevant measures in terms of major quality metrics.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.1 no.1
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• pp.29-34
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• 2001

This paper is devoted to investigating direct adaptive neural control of nonlinear systems with uncertain or unknown dynamic models. In the direct adaptive neural networks control area, theoretical issues of the existing backpropagation-based adaptive neural networks control schemes. The major contribution is proposing the variable index control approach, which is of great significance in the control field, and applying it to derive new stable robust adaptive neural network control schemes. This new schemes possess inherent robustness to system model uncertainty, which is not required to satisfy any matching condition. To demonstrate the feasibility of the proposed leaning algorithms and direct adaptive neural networks control schemes, intensive computer simulations were conducted based on the flexible joint robot systems and functions.

• Korean Journal of Optics and Photonics
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• v.5 no.2
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• pp.191-197
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• 1994

We investigated the properties of various methods of 3 dimensional profilometry to choose the phase shifting technique for the reconstruction of the shape of a given specimen. The pattern was generated by a Twyman-Green interferometer and a PZT was used to shift the fringes on the target surface. The shape was calculated with Hariharan algorithm within the uncertainty of a scaling factor. The optical noise inherent in the laser source was observed to influence the final outcome to a great extent and the need for an exact calibration was noted. noted.