• Journal of the Korean Professional Engineers Association
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• v.18 no.2
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• pp.1-5
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• 1985

In the flood prediction research, it is pointed out that the difficulty of flood prediction is the frequently experienced overestimation of flood peak. That is caused by the rainfall prediction difficulty and the nonlinearity of hydrological phenomena. Even though the former reason will remain still unsolved, but the latter one can be possibly resolved the method of the AMRA (Auto Regressive Moving Average) model for each runoff component as developed by Dr. Hino and Dr. Hasebe. The principle of the method consists of separating though the numerical filters the total runoff time series into long-term, intermediate and short-term components, or ground water flow, interflow, and surface flow components. As a total system, a hydrological system is a non-linear one. However, once it is separated into two or three subsystems, each subsystem may be treated as a linear system. Also the rainfall components into each subsystem a estimated inversely from the runoff component which is separated from the observed flood. That is why flood prediction can be done without rainfall data. In the prediction of surface flow, the Kalman filter will be applicable but this paper shows only impulse function method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.1
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• pp.124-130
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• 2018

The EMG amplitude estimator, which has been investigated as an indicator of muscle force, is of high relevance not only in biomechanical studies but also more and more in clinical applications. This paper presents a new approach to estimate surface EMG amplitude by using the mean spike and mean turn amplitude(MSA and MTA) variables. Surface EMG signals, a total of 198 signals, were recorded from biceps brachii muscle over the range of 20-80%MVC isometric contraction and performance of the MSA and MTA variables applied to amplitude estimation of the EMG signals were investigated. To examine the performance, a SNR(signal-to-noise ratio) was computed from each amplitude estimate. The results of the study indicate that MSA and MTA amplitude estimations with first order whitening filter and 300[ms]-350[ms] moving average window length are optimal and show better performance(mean SNR improvement of 6%-15%) than the most frequently used variables(ARV and RMS).

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1422-1426
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• 1987

In this paper, an adaptive DPCM scheme is presented for encoding monochrome images with easy hardware implementation at a transmission rate of exactly 1 bit/pel. The system is mainly composed of a compensated mean predictor and an adaptive two-level quantizer with backward estimation. In this system, the predictor is a sort of two-dimensional ARMA predictor in which a moving-average part is added to the conventional mean predictor. The quantizer adapts to the local statistics of its input without overhead information. To reduce annoying granular noise in the reconstructed image, Lee filter is used after reconstruction in the receiver.

• Proceedings of the ESK Conference
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• 1997.04a
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• pp.107-113
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• 1997

In this paper, an interfacing method to control rehabilitation assitance system with bio-signal is proposed. Controlling with EMG signals method has certain advantage on signal-collecting, but has some drawbacks in the function resolution of EMG signals because data-processing process is not efficient. To improve function-resolution and to increase the efficiency of EMG signal interfacing with rehabilitation assistance system, Multi-layer Perception which is highly effective with static signal and hidden-Markov model for dynamic signal resolving are fused together. In proposed method. The direction and average speed of the rehabilitation assitance system are controlled by the trajectory control and estimation of the moving direction result from the fused model. From the experiment, proposed GMM and 2-level MLP hybrid-classifier yielded 8.6% perception-error rate, improving function resolution. New acceleration control method constructed with 3 nested linear filter produced continuous acceleration paths without the information of destination point. Thus, the mass output caused by non- continuous acceleration-deceleration was eliminated. In the simulation, the necessary calculation, in the case of multiplication, was reduced by 11.54%.

• Journal of the Korea Society of Computer and Information
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• v.21 no.10
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• pp.55-62
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• 2016

In this paper, we present indoor localization technologies using the bluetooth signal categorizing them into proximity based, triangulation based and fingerprinting based technologies. Then we provide localization accuracy improvement algorithms such as moving average, K-means, particle filter, and K-Nearest neighbor algorithms. We define important performance issues for indoor localization technologies and analyze recent technologies according to the performance issues. Finally we provide experimental results for correlation between RSSI and distance. We believe that this paper provide wise view and necessary information for recent localization technologies using the bluetooth signal.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.917-922
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• 2003

In this paper, a high speed rotating arc sensor for automatic fillet welding is introduced. In order to track the welding seam, The high speed rotating arc sensor is used. The welding tip of a high speed rotating arc sensor rotates about 3000 rpm using DC motor. The rotating torch is driven by gear between welding torch body and wire guide. The welding current is measured by using the current sensor and rot at ing position sensor. To realize the welding seam tracking algorithm with accuracy, a software filter algorithm using the moving average method is applied to the measured welding current in the microprocessor. The welding mobile robot with two wheels and two sliders is developed for fillet welding. The welding mobile robot can control its traveling direction and turn itself around the corner. The effectiveness is proven through the experimental results conducted with varied fillet tracking patterns.

• Journal of Biomedical Engineering Research
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• v.15 no.4
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• pp.455-464
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• 1994

The intelligent trajectory control method that controls moving direction and average velocity for a prosthetic arm is proposed by pattern recognition and force estimations using EMG signals. Also, we propose the real time trajectory planning method which generates continuous accelleration paths using 3 stage linear filters to minimize the impact to human body induced by arm motions and to reduce the muscle fatigue. We use combination of MLP and fuzzy filter for pattern recognition to estimate the direction of a muscle and Hogan's method for the force estimation. EMG signals are acquired by using a amputation simulator and 2 dimensional joystick motion. The simulation results of proposed prosthetic arm control system using the EMG signals show that the arm is effectively followed the desired trajectory depended on estimated force and direction of muscle movements.

• Transactions of the Korean Society of Automotive Engineers
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• v.1 no.3
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• pp.55-62
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• 1993

Autoregressive moving average(ARMA) model which is a time domain parametric modeling method is implemented for modeling and reproducing characteristics of exhaust noise of an automobile in various RPM range. Experiments have been carried out using 9 set of exhaust noise signals measured at 1,000-3,000 RPM range. Characteristics of sampled signals were estimated using ARMA modeling and Akaike's FPE(final prediction error) criterion to define exact model structure and for model validation. The digital filter consisted of the esitmated ARMA(70,1) model parameters was programed to reproduce exhaust noise. The spectral analysis of reproduced noise is very close to original. The results show that our approaching technique for reproducing acoustic characteristics is valid and feasible to apply in the field of noise quality control.

• Journal of Welding and Joining
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• v.19 no.2
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• pp.208-214
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• 2001

In this study, we constructed a visual sensor system for weld seam tracking in real time in GMA welding. A sensor part consists of a CCD camera, a band-pass filter, a diode laser system with a cylindrical lens, and a vision board for inter frame process. We used a commercialized robot system which includes a GMA welding machine. To extract the weld seam we used a inter frame process in vision board from that we could remove the noise due to the spatters and fume in the image. Since the image was very reasonable by using the inter frame p개cess, we could use the simplest way to extract the weld seam from the image, such as first differential and central difference method. Also we used a moving average method to the successive position data or weld seam for reducing the data fluctuation. In experiment the developed robot system with visual sensor could be able to track a most popular weld seam. such as a fillet-joint, a V-groove, and a lap-joint of which weld seam include planar and height directional variation.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.04a
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• pp.883-886
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• 2016

본 논문에서는 장기투약자의 복약 관리 시스템 개발의 기초 연구로 Textile proximity pressure sensor를 개발하였고, 약통의 무게 감지를 통하여 약의 복용 여부를 판별하는 연구를 수행하였다. 실험은 총 2가지로, 약의 개수에 따른 baseline검출 실험과 약 한알의 무게 도출 실험을 수행하였다. 잡음을 제거하기 위해 5 point의 이동평균필터(MAF: Moving average filter)를 적용하였다. 본 논문을 통해 얻은 결과는 차후 장기 투약이 필요한 환자로 하여금 규칙적으로 약을 복용하도록 하여 만성질환의 완치율을 높이는 데 기여할 수 있을 것으로 판단된다.