• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.12
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• pp.2346-2351
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• 2011

This paper presents the intelligent external noise analysis method for nonlinear maneuvering target. After recognizing maneuvering pattern of the target by the proposed method, we track the state of the target. The external noise can be divided into mere noise and acceleration using only the measurement. divided noise passes through the filtering step and acceleration is punched into dynamic model to compensate expected states. The acceleration is the most deterministic factor to the maneuvering. By dividing, approximating, and compensating the acceleration, we can reduce the tracking error effectively. We use the fuzzy c-means (FCM) clustering as the method to divide external noise. FCM can separate the acceleration from the noise without criteria. It makes the criteria with the data made by measurement at every sampling time. So it can show the adaptive tracking result. The proposed method proceeds the tracking target simultaneously with the learning process. Thus it can apply to the online system. The proposed method shows the remarkable tracking result on the linear and nonlinear maneuvering. Finally, some examples are provided to show the feasibility of the proposed algorithm.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.31 no.6
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• pp.61-71
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• 2003

In the study of control technique for a turbojet engine model, the Takagi-Sugeno fuzzy logic controller has been designed based on the model identification by the well designed PI controlled system through T-S neuro-fuzzy inference system. To enhance this designed controller, those procedures are proposed that certainty factors are adopted to each rule of objective groups which are classified by the fuzzy C-Means algorithm and the satisfaction degrees are matched to meet the objectives. This proposed technique shows its feasibility by upgrading performances of the previously well-designed T-S fuzzy controller.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.12
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• pp.2520-2528
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• 2009

In this paper, we proposed tracking detection methodology using information granulation-based fuzzy radial basis function neural networks (IG-FRBFNN). According to IEC 60112, tracking device is manufactured and utilized for experiment. We consider 12 features that can be used to decide whether tracking phenomenon happened or not. These features are considered by signal processing methods such as filtering, Fast Fourier Transform(FFT) and Wavelet. Such some effective features are used as the inputs of the IG-FRBFNN, the tracking phenomenon is confirmed by using the IG-FRBFNN. The learning of the premise and the consequent part of rules in the IG-FRBFNN is carried out by Fuzzy C-Means (FCM) clustering algorithm and weighted least squares method (WLSE), respectively. Also, Hierarchical Fair Competition-based Parallel Genetic Algorithm (HFC-PGA) is exploited to optimize the IG-FRBFNN. Effective features to be selected and the number of fuzzy rules, the order of polynomial of fuzzy rules, the fuzzification coefficient used in FCM are optimized by the HFC-PGA. Tracking inference engine is implemented by using the LabVIEW and loaded into embedded system. We show the superb performance and feasibility of the tracking detection system through some experiments.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.818-823
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• 2005

Creep damage is one of the mosl important characteristics for the stability of high temperature structures such as huge energy converting facilities. Creep failure of Type 316LN stainless steel is highly correlated to generation and growth of the voids. In this paper, in order to investigate the correlation of creep rupture time and ultrasonic parameters (group velocity, angular velocity), creep-damaged Type 316LN specimens and measurements for the ultrasonic parameters were made. However, bi-directional measurements were applied along the load direction and the perpendicular direction to the load line by means of the contact type probe of which the central frequencies are 10MHz, 15MHz and 20MHz. Analyzing the angular velocities of the ultrasonic signals obtained from the load direction, it was confirmed that the angular velocities were declined as the creep time passed when 15MHz and 20MHz probes were used. Also, the group velocities were declined for all three frequencies as the creep time increased. Thus, positive feasibility for the creep damage evaluation by means of the angular and group velocities was confirmed. Moreover, result of analysis for the ultrasonic signal which was obtained from the perpendicular direction upon the angular and group velocities indicated little variation for both of the angular and group velocities. Therefore, the creep damage is likely to represent anisotropic itself.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.5
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• pp.1085-1092
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• 2017

In this paper, we propose a wind forecasting method that reflects wind characteristics to improve the accuracy of wind power prediction. The proposed method consists of extracting wind characteristics and predicting power generation. The part that extracts the characteristics of the wind uses correlation analysis of power generation amount, wind direction and wind speed. Based on the correlation between the wind direction and the wind speed, the feature vector is extracted by clustering using the K-means method. In the prediction part, machine learning is performed using the SVR that generalizes the SVM so that an arbitrary real value can be predicted. Machine learning was compared with the proposed method which reflects the characteristics of wind and the conventional method which does not reflect wind characteristics. To verify the accuracy and feasibility of the proposed method, we used the data collected from three different locations of Jeju Island wind farm. Experimental results show that the error of the proposed method is better than that of general wind power generation.

• Nuclear Engineering and Technology
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• v.55 no.9
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• pp.3260-3267
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• 2023

Zr-Nb alloy have been widely used as fuel rods in nuclear power plants. However, from the Fukushima nuclear accident, the weakness of the rod was revealed under harsh conditions, and research on the safety of these types of rods was conducted after the disaster. The method of depositing chromium onto the existing Zr-Nb alloy fuel rods is being considered as a means by which to compensate for the weakness of Zr-Nb alloy rods because chromium is strong against oxidation at high temperatures and has high strength. In order to secure these advantages, it is important to maintain the Cr thickness of the rods and properly inspect the rods before and during their use in power generation. Eddy current testing is a typical means of evaluating the thickness of thin metals and detecting surface defects. Depending on the size and shape of the inspected object, various eddy current sensors can be applied. In particular, because pancake sensors can be manufactured in very small sizes, they can be used for inspections even in narrow spaces, such as a nuclear fuel assembly. In this study, an eddy current technique was developed to confirm the feasibility of Cr coating thickness evaluations. After determining the design parameters of the pancake sensor by means of a FEM simulation, a FPCB pancake sensor was manufactured and the optimal frequency was selected by measuring minute changes in the Cr-coating thickness using the developed sensor.

• Journal of Korea Technology Innovation Society
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• v.17 no.1
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• pp.45-67
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• 2014

National Innovative Capability (NIC) is an important decisive factor where economic growth is concerned. As such, it is very important to measure and manage NIC. The composite index approach is one of the widely used approaches to measuring NIC, but there have been insufficient reviews of its feasibility and reliability. This paper conducted an analysis of the feasibility and reliability of the report on the last three years (i.e. 2011 through 2013) of the Innovation Union Scoreboard (IUS) of the EU, which is the most representative means of measuring NIC. It turned out that its reliability meets the recommended criteria as a result of Chronbach's alpha-based test of the models of IUS-related composite index. However, neither the absolute fit index nor the incremental fit index was found to meet the recommended criteria in a construct validity analysis. It also turned out that predictive validity is very low as a result of panel linear regression analysis of sectors and items of IUS-related composite index. This paper presents a number of considerations to be made when measuring national innovative capability using the composite index approach, as well as major policy suggestions based on the results of the analysis.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.1816-1824
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• 2011

Recently, with traffic SOC investment policy changing from road-centered to railway-centered according to environment-friendly and sustainable development, issues regarding overlapping and overinvestment of traffic facility have been raised. Regarding investment of various traffic facilities of which departure and destination are similar to each other, academia, civic organizations, government, etc. are recognizing problems including overlapping investment of budget, environmental destruction, etc., but not suggesting definite solutions. Objective transportation network analysis is required because various positive effects including solutions of delay/congestion may occur due to provision of alternative way and distribution of the amount of traffic when accidents occur, as well as negative effects suggested by some of civic organizations in various transportation facility investment of similar departure and destination. Hereupon, this study tries to suggest a tool that can objectively evaluate interrelations of transportation network by applying multi-criteria analysis including economic feasibility regarding analysis of interconnections between and within means of transportation.

• The Journal of Sustainable Design and Educational Environment Research
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• v.13 no.2
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• pp.1-12
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• 2014

A school building complex means building both the learning spaces of students and convenience space of community within school lands. The projects have has a positive effect on saving the national budget as well as expanding the learning spaces. The absence of standard agreement contracted through discussion of participants, however, has made many problems in the operated projects. Through analysis on the previous researches and conference, the paper finds main problems discussed in the operating step. And, the feasibility study is carried out in order to analyze the appropriateness of on the existing agreements on the problems. Finally, the paper presents the standard agreement for the school building complex projects. The practitioners can prevent the existing problems from new projects through using the proposed agreement. Furthermore, it is expected that the school building complex projects will be activated.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2498-2501
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• 2003

In this paper, we present a wavelet neural network (WNN) approach to the solution of the path tracking problem for mobile robots that possess complexity, nonlinearity and noise. First, we discuss a WNN based control system where the control signals are directly obtained by minimizing the difference between the reference track and the pose of a mobile robot. This compact network structure is helpful to determine the number of hidden nodes and the initial value of weights. Then, the data with various noises provided by odometric and external sensors are here fused together by means of an Extended Kalman Filter (EKF) approach for the pose estimation problem of mobile robots. This control process is a dynamic on-line process that uses the wavelet neural network trained via the gradient-descent method with estimates from EKF. Finally, we verify the effectiveness and feasibility of the proposed control system through simulations.