• The Bulletin of The Korean Astronomical Society
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• v.36 no.2
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• pp.102.2-102.2
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• 2011

Sunspots usually appear in a group which can be classified by certain morphological criteria. In this study we examine the moments which are statistical parameters computed by summing over every pixels of contours, in order to quantify the morphological characteristics of a sunspot group. The moments can be additional characteristics to the sunspot group classification such as McIntosh classification. We are developing a program for image processing, detection of contours and computation of the moments using continuum images from SOHO/MDI. We apply the program to count the sunspot numbers from 303 continuum images in 2003. The sunspot numbers obtained by the program are compared with those by SIDC. The comparison shows that they have a good correlation (r=89%). We are extending this application to automatic sunspot classification (e.g., McIntosh classification) and flare forecasting.

• Proceedings of the KIEE Conference
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• 2001.07a
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• pp.38-40
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• 2001

Measuring technology based on the computer and software is used worldwideiy by the aids of remarkably improved digital technology and measuring devices, and the electro- magnetic interference due to high currents and high voltages is being solved by the helps of applied optic instrumentation technology. The automatic acquisition, analysis and storage system of test data is available for utilizing the numerical computation technology. The measuring accuracy and testing efficiency are thus much higher because of the developed technologies. In this paper, the construction of data acquisition system in KERI including measuring devices and its application to the short circuit test are described, and additionally the algorithm of the analyzing program for the automatic process of test data and the results of analyses are described.

• Structural Engineering and Mechanics
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• v.30 no.4
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• pp.387-402
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• 2008

The Integrated Force Method (IFM) has been developed in recent years for the analysis of civil, mechanical and aerospace engineering structures. In this method all independent or internal forces are treated as unknown variables which are calculated by simultaneously imposing equations of equilibrium and compatibility conditions. The solution by IFM needs the computation of element equilibrium and flexibility matrices from the assumed displacement, stress-resultant fields and material properties. This paper presents a general purpose code for the automatic generation of element equilibrium and flexibility matrices for plate bending elements using the Integrated Force Method. Kirchhoff and the Mindlin-Reissner plate theories have been employed in the code. Paper illustrates development of element equilibrium and flexibility matrices for the Mindlin-Reissner theory based four node quadrilateral plate bending element using the Integrated Force Method.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.9
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• pp.59-65
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• 1995

The cam is used to a main component in a variety of automatic machines and instruments. To meet the demand of a complicated operation and of reducing weight for automatic machine, Curve Blending Technology, in which each of the basic curves suitable for individual interval is connected, is used for the cam design. In the curve blending, it is necessary to select appropriate elementary curve for each interval and to confirm the dynamic continuity at connecting points between adjoining elementary curves. This paper represented the elementary curve selection method to select an appropriate curve for each interval, and executed computation for the follower displacement and angular displacement of each interval. The paper made an analysis and examine closely for elementary curves to synthesizing curve blending, and it performed dynamic conditions clearly at every points on the cam motions. Therefore the curve blending technology presented by the paper turned into easier work.

• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2807-2810
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• 2003

In this paper, we propose a fuzzy control method for improving the control performance by automatically tuning the scaling factor. The proposed method is that automatically tune the input scaling factor and the output scaling factor of fuzzy logic system through neural network. Used neural network is ADALINE (ADAptive Linear NEron) neural network with delayed input. ADALINE neural network has simple construct, superior learning capacity and small computation time. In order to verify the effectiveness of the proposed control method, we performed simulation. The results showed that the proposed control method improves considerably on the environment of the disturbance.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.1077-1080
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• 1991

It has been recognized as important subject by users that PID-Controllers widely used in industrial processes must be well-tuned, In this paper, We present an automatic tuning method for PID-Controllers which is based on discrete parameter estimation and application of conventional tuning-rules. The method is easy to implement on microprocessor because critical values are obtained by the mathematical computation. Also, it permits quick on-line tuning. Simulation results show that most processes are well tuned by the suggested tuning method in this paper.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2002.11a
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• pp.387-388
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• 2002

미국은 TMI-2 사고 이후, 방사선 비상시 신속하고 정확한 방사능 화산 및 피폭해석을 위한 프로그램을 개발하여 운영하고 있다. 이러한 피폭선량 해석 체계의 구축은 비상시 빠르게 대처하여 피해를 최대한 줄일 수 있는 재해대책을 수립하기 위하여 각 나라별로 환경에 맞게 개발되어야 한다. (중략)

• 한국정보통신설비학회:학술대회논문집
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• 2008.08a
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• pp.186-189
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• 2008

In order to estimate cell images, high-performance electron microscopes are used nowadays. In this paper, we propose a new simple, fast and efficient method for real-time automatic focusing in electron microscopes. The proposed algorithm is based on the prediction-error variance, and demonstrates its feasibility by using extensive experiments. This method is fast, easy to implement, accurate, and not demanding on computation time.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.6
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• pp.383-389
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• 2016

This paper presents a novel automatic white balance (AWB) algorithm for consumer imaging devices. While existing AWB methods require reference white patches to correct color, the proposed method performs the AWB function using only an input image in two steps: i) white point detection, and ii) color constancy gain computation. Based on the dark channel prior assumption, a white point or region can be accurately extracted, because the intensity of a sufficiently bright achromatic region is higher than that of other regions in all color channels. In order to finally correct the color, the proposed method computes color constancy gain values based on the Y component in the XYZ color space. Experimental results show that the proposed method gives better color-corrected images than recent existing methods. Moreover, the proposed method is suitable for real-time implementation, since it does not need a frame memory for iterative optimization. As a result, it can be applied to various consumer imaging devices, including mobile phone cameras, compact digital cameras, and computational cameras with coded color.

• Journal of information and communication convergence engineering
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• v.13 no.3
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• pp.145-151
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• 2015

We describe in this paper a hardware-based improvement scheme of a real-time automatic speech recognition (ASR) system with respect to speed by designing a parallel feature extraction algorithm on a Field-Programmable Gate Array (FPGA). A computationally intensive block in the algorithm is identified implemented in hardware logic on the FPGA. One such block is mel-frequency cepstrum coefficient (MFCC) algorithm used for feature extraction process. We demonstrate that the FPGA platform may perform efficient feature extraction computation in the speech recognition system as compared to the generalpurpose CPU including the ARM processor. The Xilinx Zynq-7000 System on Chip (SoC) platform is used for the MFCC implementation. From this implementation described in this paper, we confirmed that the FPGA platform is approximately 500× faster than a sequential CPU implementation and 60× faster than a sequential ARM implementation. We thus verified that a parallelized and optimized MFCC architecture on the FPGA platform may significantly improve the execution time of an ASR system, compared to the CPU and ARM platforms.