• Journal of Korean Society of Rural Planning
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• v.20 no.2
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• pp.1-10
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• 2014

Smartphones change the picture of data and information sharing and make it possible to share various real-time flooding data and information. The vulnerability indicators of farmland inundation is needed to calculate the risk of farmland flood based on changeable hydro-meteorological data over time with morphologic characteristics of flood-damaged areas. To find related variables show the vulnerability of farmland inundation using the binary-logit model and correlation analysis and to provide vulnerability indicators were estimated by fuzzy set method. The outputs of vulnerability indicators were compared with the results of Monte Carlo simulation (MCS) for verification. From the result vulnerability indicators are applicable to mobile_based information system of farmland inundation.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.3
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• pp.330-335
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• 2004

In this paper, we propose the technique for recognizing the human emotion by using the color image. To do so, we first extract the skin color region from the color image by using HSI model. Second, we extract the face region from the color image by using Eigenface technique. Third, we find the man's feature points(eyebrows, eye, nose, mouse) from the face image and make the fuzzy model for recognizing the human emotions (surprise, anger, happiness, sadness) from the structural correlation of man's feature points. And then, we infer the human emotion from the fuzzy model. Finally, we have proven the effectiveness of the proposed method through the experimentation.

• Journal of Korean Society of Water and Wastewater
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• v.19 no.6
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• pp.738-748
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• 2005

Considering pollution source is transferred by discharge, it is very important to analyze the correlation between discharge and water quality. And temperature also influent to the water quality. In this paper, it is used water quality data that was measured DO (Dissolved Oxygen), TOC (Total Organic Carbon), TN (Total Nitrogen), TP (Total Phosphorus) at Dalchun real time monitoring stations in Namhan river. These characteristics were analyzed with the water quality of rainy and nonrainy periods. Input data of the water quality forecasting models that they were constructed by neural network and neuro-fuzzy was chosen as the reasonable data, and water quality forecasting models were applied. LMNN (Levenberg-Marquardt Neural Network), MDNN (MoDular Neural Network), and ANFIS (Adaptive Neuro-Fuzzy Inference System) models have achieved the highest overall accuracy of TOC data. LMNN and MDNN model which are applied for DO, TN, TP forecasting shows better results than ANFIS. MDNN model shows the lowest estimation error when using daily time, which is qualitative data trained with quantitative data. If some data has periodical properties, it seems effective using qualitative data to forecast.

• Journal of Advanced Navigation Technology
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• v.10 no.4
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• pp.364-370
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• 2006

In this paper, the decision method of optimal sub-band which is supposed to embedded watermark incorporating fuzzy inference into transform-based watermarking is proposed. After performing the DCT, maximum variation of human visual properties, such as text degree, contrast sensitivity function is calculated, and by using these, membership function is generated. After embedding the watermark to the selected bands obtained from fuzzy inference, performance of imperceptibility and robustness are evaluated. In order to testify the proposed scheme, such attacks as JPEG, filtering, cropping are utilized. and in addition, by using an AWGN channel of OFDM/QPSK system, PSNR as well as correlation are calculated, and finally evaluated the performance.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.4 s.304
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• pp.25-34
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• 2005

We had research to conduct interrelationships between sensors using postprocessing analysis with the Fuzzy-Kalman Filtering Auto-Correlation about Real Time Simulator data of the NaroSC LCS in case of a fully blind situation scenario. The conducted interrelations are same harmony with relations in scenario. We had analyzed signals of sensors reverse-using a optimization character of Fuzzy-Kalman Filter. As our research conclusion, We had recognized possibilities of signal processing about the KSLV-1, on-board payloads, general equipments of ground support which apply to multi sensor systems.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.423-425
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• 1998

An optical system which can autonomously form and display an impression of a picture made up by many figures has been developed. This system consists of optical fuzzy-neurons which calculate the correlation between the input picture and the reference image by incoherent optics. The calculated signal is applied to an amplifier whereby the output signal increases, then decreases according to increase of the input signal . These outputs are synthesized, and are used for changing the position where the system gaze on a part of the input picture by light beam. In this system, the light intensity used for gazing changes chaotically, The attractor drawn from the change of light intensity corresponds to the impression of the picture. This paper shows the results that are calculated by the numerical simulation. The system has been simulated to express the impression for a picture formed by 4figures.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.1
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• pp.82-88
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• 2005

The damage inspection of container surface is performed by the expert inspectors at the container terminal gate of harbor. In this paper, we substitute the expert's capability with the damage inspection system using the artificial intelligent control algorithm and vision system, so we can improve the work environment and effectively decrease the inspection time and cost. Firstly, using six CCD cameras attached to the terminal gate, whole container is partially captured according to eleven sensors aligned with the entering direction of container. Captured partial images are inspected by the fuzzy system which the expert's technology is embedded. Next, we compose partial images to be a complete container image through the correlation coefficient method. Complete container image is saved to solve future troublesome problems. In this paper, the effectiveness of the proposed system was verified through the field test.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1102-1105
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• 1993

A fuzzy expert system for prediction and mitigation of sludge bulking was developed for an activated sludge process which treats waste water from a food industry. The developed system is able not only to infer the degree of progress of sludge bulking but also to generate remedial operation guides which may be sent to the local controllers as remote set points. One of the important consequences through this study is the BI (Bulking Index) inferred by the bulking prediction expert system was found to have a close correlation with the SVI (Sludge Volume Index) which is a practical measure of degree of bulking but needs tedious chores for its measurement.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.857-860
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• 1993

In this paper, we apply the self generating neuro fuzzy model (SGNFM) to the dimension analysis of the chaotic time series. Firstly, we formulate a nonlinear time series identification problem with nonlinear autoregressive (NARMAX) model. Secondly, we propose an identification algorithm using SGNFM. We apply this method to the estimation of embedding dimension for chaotic time series, since the embedding dimension plays an essential role for the identification and the prediction of chaotic time series. In this estimation method, identification problems with gradually increasing embedding dimension are solved, and the identified result is used for computing correlation coefficients between the predicted time series and the observed one. We apply this method to the dimension estimation of a chaotic pulsation in a finger's capillary vessels.

• Nuclear Engineering and Technology
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• v.51 no.2
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• pp.453-462
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• 2019

Mental workload (MWL) is a major consideration for the user interface design in nuclear power plants (NPPs). However, each MWL evaluation method has its advantages and limitations, thus the evaluation and control methods based on multi-index methods are needed. In this study, fuzzy comprehensive evaluation (FCE) theory was adopted for assessment of interface designs in NPP based on operators' MWL. An evaluation index system and membership functions were established, and the weights were given using the combination of the variation coefficient and the entropy method. The results showed that multi-index methods such as performance measures (speed of task and error rate), subjective rating (NASA-TLX) and physiological measure (eye response) can be successfully integrated in FCE for user interface design assessment. The FCE method has a correlation coefficient compared with most of the original evaluation indices. Thus, this method might be applied for developing the tool to quickly and accurately assess the different display interfaces when considering the aspect of the operators' MWL.