• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.4
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• pp.203-212
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• 2018

Quality requirements of manufactured products or parts are given in the form of specification limits on the quality characteristics of individual units. If a product is to meet the customer's fitness for use criteria, it should be produced by a process which is stable or repeatable. In other words, it must be capable of operating with little variability around the target value or nominal value of the product's quality characteristic. In order to maintain and improve product quality, we need to apply statistical process control techniques such as histogram, check sheet, Pareto chart, cause and effect diagram, or control charts. Among those techniques, the most important one is control charting. The cumulative sum (CUSUM) control charts have been used in statistical process control (SPC) in industries for monitoring process shifts and supporting online measurement. The objective of this research is to apply Taguchi's quality loss function concept to cost based CUSUM control chart design. In this study, a modified quality loss function was developed to reflect quality loss situation where general quadratic loss curve is not appropriate. This research also provided a methodology for the design of CUSUM charts using Taguchi quality loss function concept based on the minimum cost per hour criterion. The new model differs from previous models in that the model assumes that quality loss is incurred even in the incontrol period. This model was compared with other cost based CUSUM models by Wu and Goel, According to numerical sensitivity analysis, the proposed model results in longer average run length in in-control period compared to the other two models.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.6
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• pp.425-429
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• 2009

Recently, Chen et al.'s proposed mutual authentication scheme based on the quadratic resiidue, finding the squaring root problem, for avoiding exhaustive search on the server. But, if a malicious reader sends same random value, the tag is traced by an adversary. Moreover, there is realization problem because of its limited ability to compute squaring and hash function. In this paper, we analyze Chen et al.'s scheme and its weakness. Furthermore we present an improved mutual authentication scheme based on the quadratic residue which solves the tracing problem by generating random value on the tag and uses only squaring. We also make the scheme satisfy to forward secrecy without updating and synchronizing and avoid exhaustive search.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.6
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• pp.257-266
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• 2015

There is no polynomial-time algorithm that can be obtain the optimal solution for economic load dispatch problem with non-convex fuel cost functions. Therefore, electrical field uses quadratic fuel cost function unavoidably. This paper proposes a valve-point optimization (VPO) algorithm for economic load dispatch problem with non-convex fuel cost functions. This algorithm sets the initial values to maximum powers $P_i{\leftarrow}P_i^{max}$ for each generator. It then reduces the generation power of generator i with an average power cost of $_{max}\bar{c}_i$ to a valve point power $P_{ik}$. The proposed algorithm has been found to perform better than the extant heuristic methods when applied to 13 and 40-generator benchmark data. This paper consequently proves that the optimal solution to economic load dispatch problem with non-convex fuel cost functions converges to the valve-point power of each generator.

• Computers and Concrete
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• v.26 no.1
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• pp.1-10
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• 2020

In this paper, a procedure for automated optimized design of reinforced concrete frames has been presented. The procedure consists of formulation and solution of the design problem in the form of an optimization problem. The minimization of total cost of R/C frame has been taken as the objective of optimization problem. In this research, consistent approximation method is applied to explicitly formulate constraints and objective function in terms of the design variables. In the presented method, the primary optimization problem is replaced with a sequence of explicit sub-problems. Each sub-problem is efficiently solved using the Sequential Quadratic Programming (SQP) method. The proposed method is demonstrated through a four-story frame and an eight-story frame, and the optimum results are compared with those in the available literature. It is shown that the proposed method can be easily applied to obtain rational, reliable, economical and practical designs for Reinforced Concrete Moment Resisting Frames (RCMRFs) while it is converged after a few analyses.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.1
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• pp.58-65
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• 2003

In this paper, a new model, which is a Takagi-Sugeno fuzzy model, for mobile robot is presented. A controller, consisting of two loops the one of which is the inner state feedback loop designed for stability and the outer loop is a PI controller designed for tracking the reference input, is suggested. Because the robot dynamics is nonlinear, it requires the controller to be insensitive to the nonlinear term. To achieve this objective, the model is developed by well known T-S fuzzy model. The design algorithm of inner state-feedback loop is regional pole-placement. In this paper, regions, for which poles of the inner state feedback loop are lie in, are formulated by LMI's. By solving these LMI's, we can obtain the state feedback gains for T-S fuzzy system. And this paper shows that the PI controller is equivalent to the state feedback and the cost function for reference tracking is equivalent to the LQ(linear quadratic) cost. By using these properties, it is also shown in this paper that the PI controller can be obtained by solving the LQ problem.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.51-53
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• 1993

This paper proposes a design of the tracking controller using artificial neural network and the compare the result with a result of optimal controller. In practical use, conventional Optimal controller has some limits. First, optimal controller can be designed only for linear system. Second, for many systems state observation is difficult or sometimes impossible. But the controller using artificial neural network does not need mathmatical model of the system including state observation, so it can be used for both linear and nonlinear system with no additional cost for nonlinearity. Designed multi layer neural network controller is composed of two parts, feedforward controller gives a steady state input & feedback controller gives transient input via minimizing the quadratic cost function. From the comparison of the results of the simulation of linear & nonlinear plant, the plant controlled by using neural network controller shows the trajectory similar to that of the plant controlled by an optimal controller.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.8 s.173
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• pp.34-41
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• 2005

Generally, it is not easy to get a suitable controller for multi variable systems. If the modeling equation of the system can be found, it is possible to get LQR control as an optimal solution. This paper suggests an LQR learning method to design LQR controller without the modeling equation. The proposed algorithm uses the same cost function with error and input energy as LQR is used, and the LQR controller is trained to reduce the function. In this training process, the Jacobian matrix that informs the converging direction of the controller Is used. Jacobian means the relationship of output variations for input variations and can be approximately found by the simple experiments. In the simulations of a hydrofoil catamaran with multi variables, it can be confirmed that the training of LQR controller is possible by using the approximate Jacobian matrix instead of the modeling equation and this controller is not worse than the traditional LQR controller.

• Journal of Korean Society for Quality Management
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• v.28 no.2
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• pp.161-175
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• 2000

The problem of jointly determining the optimum process mem and screening limits for each market is considered in situations where there are several markets with different price/cost structures. Two inspection procedures are considered; an inspection based on the quality characteristic of interest, and an inspection based on a surrogate variable which is highly correlated with the quality characteristic. The quality characteristic is assumed to be a normal distribution with unknown mean and known variance. A Taguchi's quadratic loss function is utilized for developing the economic model for determining the optimum process mean and screening limits. A numerical example is given.

• Journal of Korean Society of Forest Science
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• v.79 no.1
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• pp.1-15
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• 1990

In this study the stem analysis program, which can be operated with personal computer was developed to reduce time and cost of calculation, and to increase accuracy of analysis. The stem analysis method used in this program was compared with other methods. The results obtained were as follows : The value, 1/100mm measured from the latest annual ring measurement machine (Jahrringme${\beta}$geraete Johan Type II) was automatically inputed to the computer and saved into given file name. Turbo Pascal program was written to do this. The measured data was analyzed by stem analysis calculation program written by Fortran-77. Volume and height increments were approximated by spline function, and diameter of the stem disk was calculated by quadratic mean method. The increment values calculated by the programs were printed annually and in every five-year. Stem analysis diagram and several increment graphs were also easily printed. The result compared between those analysis methods showed that quadratic mean could reduce the error caused from eccentric pith. When the stem taper curve method, approximated by spline function, was used in the calculation of tree height and volume, increments would be more exactly calculated.

• Journal of Advanced Navigation Technology
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• v.25 no.6
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• pp.543-549
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• 2021

In this paper, a robust transfer alignment method is proposed for a strapdown inertial navigation system(SDINS) with norm-bounded parametric uncertainties. The uncertainties are described by the energy bound constraint, i.e., sum quadratic constraint(SQC). It is shown that the SQC can be coverted into an indefinite quadratic cost function in the Krein space. Krein space Kalman filter is designed by modifying the measurement matrix and the variance of measurement noises in the conventional Kalman filter. Since the proposed Krein space Kalman filter has the same recursive structure as a conventional Kalman filter, the proposed filter can easily be designed. The simulation results show that the proposed filter achieves robustness against measurement time delay and high dynamic environment of the vehicle.