• Journal of Radiation Protection and Research
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• v.26 no.1
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• pp.19-26
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• 2001

In order to assess the atmospheric dispersion for the accidental releases of nuclear power plants, in calculating X/Q values in the XOQAR and PAVAN codes which are based on Reg. Guide 1.145, the X/Q and frequency values are plotted on log-normal paper. Starting with the highest X/Q value of this plot, the codes compare the slope of the line drawn from this point to every other point within an increment containing ten X/Q values. If there are fewer than ten values, only the number available are used. The coefficients that produce the line with the least negative slope are saved. The end point of this line is used as the next starting point, from which slopes to the points within the next increment, containing ten X/Q values, are compared. The X/Q values corresponding to the cumulative frequency values 0.5%, 5% or 50% are calculated to search for the $0{\sim}2$ hour X/Q value that tends to be a very conservative value. In this work, a fuzzy logic inference method is used for nonlinear interpolation of the X/Q values versus the cumulative frequency. The fuzzy logic inference method is known to be a food technique for nonlinear interpolation. The proposed method was applied to a potential accidential radioactive release of the Yonggwang nuclear power plant, which gives more realistic X/Q values.

• Journal of Advanced Marine Engineering and Technology
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• v.38 no.6
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• pp.710-715
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• 2014

This paper investigates the design scheme of fuzzy-based adaptive controller to give adaptability for controlling nonlinear systems. For this, a nonlinear system is linearized by the several subsystems depending on the operating point or parameter changes. Then, the sub-controller is designed by linear control scheme for each subsystem and the sub-controllers are fused with each gain of sub-controllers using fuzzy rules. The proposed method is applied to an inverted pole system which has structurally instability and nonlinearity, and simulation works are shown to illustrate the effectiveness by comparison with the interpolation-based adaptive Controller.

• Atmosphere
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• v.21 no.3
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• pp.243-256
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• 2011

This paper presents the development of new algorithm for identifying and tracking the convective cells in three dimensional reflectivity fields in Cartesian coordinates. First, the radar volume data in spherical coordinate system has been converted into Cartesian coordinate system by the bilinear interpolation. The three-dimensional convective cell has then been identified as a group of spatially consecutive grid points using reflectivity and volume thresholds. The tracking algorithm utilizes a fuzzy logic with four membership functions and their weights. The four fuzzy parameters of speed, area change ratio, reflectivity change ratio, and axis transformation ratio have been newly defined. In order to make their membership functions, the normalized frequency distributions are calculated using the pairs of manually matched cells in the consecutive radar reflectivity fields. The algorithms have been verified for two convective events in summer season. Results show that the algorithms have properly identified storm cells and tracked the same cells successively. The developed algorithms may provide useful short-term forecasting or nowcasting capability of convective storm cells and provide the statistical characteristics of severe weather.

• Journal of the Korean Society of Propulsion Engineers
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• v.10 no.3
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• pp.82-89
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• 2006

Recently operation and maintenance cost of gas turbine engines has been issued as a major parameter in terms of designing and manufacturing. Accordingly, the conception that the maintenance and repair of an engine has to be conducted in assembled condition has been spreaded out. However, it is possible only if the prediction of the engine performance is clearly identified. In this study, therefore, a diagnostic code of the engine performance has been developed by using GPA(Gas Path Analysis) and Fuzzy Logic which can analyze the engine performance and estimate the health parameters. The prediction of the quantitative performance deterioration of the established model of the turbo-shaft engine for SUAV has been achieved in a satisfied level compared to that obtained by GSP code.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.4
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• pp.264-269
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• 2008

In this paper, two neural networks as a material model, which are based on the state-space method, have been proposed. One outputs the rates of inelastic strain and material internal variables whereas the outputs of the other are the next state of the inelastic strain and material internal variables. Both the neural networks were trained using input-output data generated from Chaboche's model and successfully converged. The former neural network could reproduce the original stress-strain curve. The neural network also demonstrated its ability of interpolation by generating untrained curve. It was also found that the neural network can extrapolate in close proximity to the training data.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.4
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• pp.372-378
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• 2014

Noise in biomedical X-ray image degrades the quality so that it might causes to decrease the accuracy of diagnosis. Especially the noise reduction techniques is quite essential for low-dose biomedical X-ray images obtained from low radiation power in order to protect patients, because their noise level is usually high to well discriminate objects. This paper proposes an efficient method to remove the noise in low-dose X-ray images while preserving the edges with diverse resolutions. In the proposed method, a noisy image is at first decomposed into several images with different resolutions in pyramidal representation, then the stable map of edge confidence is obtained from each of analyzed image using a fuzzy logic-based edge detector. This map is used to adaptively determine the parameter for guided filters, which eliminate the noise while preserving edges in the corresponding image. The filtered images in the pyramid are extended and synthesized into a resulted image using interpolation technique. The superiority of proposed method compared to the median, bilateral, and guided filters has been experimentally shown in terms of noise removal and edge preserving properties.

• Journal of IKEEE
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• v.22 no.3
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• pp.680-692
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• 2018

Children's health is interesting to parents and society. A system that assists to monitor the development of their children and gives nutritional advices is an interesting of parents. In this study, we present a system that allows to track the heights and weights of a child since he/she was born up to adulthood, to predict his age of puberty, and to provide nutritional advice. Particularly, it predicts the height in near future and the adult stature for detecting the child with abnormal development. We applied Sager's model for predicting the height in near future by using interpolation and regression techniques before puberty. After determining the puberty time, we proposed a model for predicting the height. Then we applied fuzzy logic for evaluating the health status and providing nutritional advice. Our system predicted stature in near future with error bound of $1.7361{\pm}0.0397cm$ in girls and $2.4020{\pm}0.0799cm$ in boys. Our model also gave a reliable adult stature prediction with error bound of $0.3507{\pm}0.2808cm$ in girls and $1.3414{\pm}0.7024cm$ in boys. At the same time, the nutrition was provided appropriately in terms of protein, lipid, glucid. We implemented a program based on this research. Our system promises to improve the health of every child.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.1
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• pp.72-79
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• 2007

In this paper, It propose a new restoration algorithm of high resolution, which is reconstructed to high resolution image using low resolution image informations. The proposed algorithm is constructed based on super resolution theory, it is consisted of progressive steps of the integration and construction. It reduced a lot of data-processing capacity and noise with integration through sub-pixel movement and wavelet basis through a higher resolution. As a result, it is shown that the main information is maintained and the error rate is improved. Using expansion fuzzy wavelet B-spline interpolation in stage of construction, it is confirmed that we can achieve smoothing image and good resolution without blur and block.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.2
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• pp.113-118
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• 2010

This paper proposed an ECAM (Electronic cam) control system which has simple and general structure. The proposed cam controller adopted the linear and polynomial curve-fitting method to generates a smooth cam profile curve function. Smooth motion trajectory of master actuator guarantees the good performance of slave motion and has an important effect on the interpolation quality of ECAM. The auto-tuning PID velocity controller was applied to overcome the uncertainties in ECAM, and the gains of the controller are updated continuously to ensure the consistency of system performance under varying working conditions. The robustness of system against the varying load torque disturbances and noises is guaranteed by using the load torque disturbance observer to suppress the disturbance on master actuator. The velocity compensator was applied to compensate the degradation of performance of slave motion caused from the varying driving speed of master motion. The stability and validity of the proposed ECAM control system was verified by simulation results.