• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.819-821
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• 1998

This paper deals with a method or a residual generation for fault isolation in a centrifugal pump with a water circulation system, driven by a speed controlled dc motor. It is based on parity relations derived from the moving-average model of the system and is used to identify sensor faults and two possible brush and impeller faults, where the former is dealt with additive faults, while the latter characterized as discrepancies between the nominal and actual plant parameters of the system is modelled by multiplicative faults. We will represent the propagation of this uncertainty to the model matrices by the approximate handling of partial derivatives of polynomials. With multiplicative faults, the transformation matrix implemented in the residual generator are calculated on-line. The simulation studies demonstrate that small changes of the system can be detected and diagnosed by using the method.

• Journal of international Conference on Electrical Machines and Systems
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• v.2 no.3
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• pp.342-348
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• 2013

As a number of wind power generation systems have been installed in power systems in the world, frequency fluctuations due to output power variations from wind farms have become a serious problem. Battery systems have been studied for smoothing the output variations and decreasing the resulting frequency fluctuations. Among these studies, efficient design of battery systems is one of the most important subjects from a point of view of cost. This paper presents a comparative analysis of the smoothing effect between the conventional moving average method and a new method based on frequency response analysis.

• The KSFM Journal of Fluid Machinery
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• v.7 no.5 s.26
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• pp.7-12
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• 2004

Multi-path ultrasonic flowrate measuring technology is being received much attentions from a variety of industrial fields to exactly measure the flowrate. Multi-path ultrasonic flowmeter has much advantage since it has no moving parts and little pressure loss. It offers good accuracy, repeatability, linearity and turn-down ratio can be over 1:50. The present study investigates flowrate integration errors using weighting factors. A theoretical flow model uses power law to describe a fully developed velocity profiles and wall roughness is changed. Gaussian, Chebyshev, and Tailor methods are used to integrate line-average velocities. The obtained results show that Chebyshev method in 2, 4-path arrangement and Gaussian method in 3, 5-path arrangement are not affected for wall roughness changes.

• Journal of Information Processing Systems
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• v.14 no.4
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• pp.904-915
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• 2018

We demonstrate how social media content can be used to predict the unemployment rate, a real-world indicator. We present a novel method for predicting the unemployment rate using social media analysis based on natural language processing and statistical modeling. The system collects social media contents including news articles, blogs, and tweets written in Korean, and then extracts data for modeling using part-of-speech tagging and sentiment analysis techniques. The autoregressive integrated moving average with exogenous variables (ARIMAX) and autoregressive with exogenous variables (ARX) models for unemployment rate prediction are fit using the analyzed data. The proposed method quantifies the social moods expressed in social media contents, whereas the existing methods simply present social tendencies. Our model derived a 27.9% improvement in error reduction compared to a Google Index-based model in the mean absolute percentage error metric.

• Structural Monitoring and Maintenance
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• v.6 no.3
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• pp.237-254
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• 2019

This paper presents an improved time series based damage detection approach with experimental verifications for detection, localization, and quantification of damage in shear-type structures under varying mass effects using output-only vibration data. The proposed method can be very effective for automated monitoring of buildings to develop proactive maintenance strategies. In this method, Auto-Regressive Moving Average models with eXogenous inputs (ARMAX) are built to represent the dynamic relationship of different sensor clusters. The damage features are extracted based on the relative difference of the ARMAX model coefficients to identify the existence, location and severity of damage of stiffness and mass separately. The results from a laboratory-scale shear type structure show that different damage scenarios are revealed successfully using the approach. At the end of this paper, the methodology limitations are also discussed, especially when simultaneous occurrence of mass and stiffness damage at multiple locations.

• Journal of Fashion Business
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• v.24 no.6
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• pp.63-79
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• 2020

This study analyze consumers' unconscious visual attention to color and images of internet shopping malls by using eye-tracking method. Twenty-nine participants, including 15 females and 14 males, participated. The average ages of the male and female participants were 27.3 years and 27.7 years, respectively. Ten images of five layouts (multi-composition images, single-model images, gender-composed images, videos, and moving banner images) of internet shopping malls were shown on an eye-tracker computer screen. Quantitative analyses of the eye-tracking responses were conducted. SPSS was used to analyze the descriptive characteristics and to conduct an independent-sample t-test, along with an ANOVA. The data analysis showed that the image area generally had the shortest time to first fixation (TFF), the longest duration of fixation (DOF), the highest number of fixations (NOF), and the highest numbers of revisits(NOR).Notably, visual attention towards female models was high among various images. The results can be used to improve credibility and design online shopping layout with a scientific evidence that helps consumers through their purchase decisions.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.3
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• pp.1-10
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• 2022

This research proposes a novel trading method based on sample entropy for the FTSE China A50 Index. The approach is used to determine the points at which the index should be bought and sold for various holding durations. The findings are then compared to three other trading strategies: buying and holding the index for the entire time period, using the Relative Strength Index (RSI), and using the Moving Average Convergence Divergence (MACD) as buying/selling signaling tools. The unique entropy trading method, which used 90-day holding periods and was called StEn(90), produced the highest cumulative return: 25.66 percent. Regular buy and hold, RSI, and MACD were all outperformed by this strategy. In fact, when applied to the same time periods, RSI and MACD had negative returns for the FTSE China A50 Index. Regular purchase and hold yielded a 6% positive return, whereas RSI yielded a 28.56 percent negative return and MACD yielded a 33.33 percent negative return.

• Journal of Electrical Engineering and information Science
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• v.1 no.2
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• pp.45-51
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• 1996

This paper presents a neural network approach for on-line estimation of partial discharge(PD) location using advanced correlation technique in power transformer. Ultrasonic sensors detect ultrasonic signals generated by a PD and the proposed method calculates time difference between the ultrasonic signals at each sensor pair using the cross-correlation technique applied by moving average and the Hamming window. The neural network takes distance difference as inputs converted from time difference, and estimates the PD location. Case studies showed that the proposed method using advanced correlation technique and a neural network estimated the PD location better than conventional methods.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.39 no.8
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• pp.14-25
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• 2002

In this paper, we propose a modified AFC algorithm which is suitable for the implementation of WCDMA reverse link receiver modem. To reduce the complexity, the modified CP-FDD algorithm named 'Normalized CP-FDD' is applied to the AFC loop. The proposed FDD algorithm overcomes the conventional CP-FDD's sensitivity to the variance of input signal amplitude and increases the linear range of S -curve. Therefore, offset frequency estimation using the proposed scheme can be more stable than the conventional method. Unlike IS-95, since pilot symbol in WCDMA is not transmitted continuously, we introduce a moving average filter at the FDD input to increase the number of cross-product. So, tracking speed and stability are improved. For more rapid frequency acquisition and tracking, we adopt a multi-stage tracking mode. Using NCO having ROM table structure, the frequency offset is compensated. We applied the proposed algorithm in the implementation of WCDMA base station modem successfully.

• Journal of Korea Multimedia Society
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• v.10 no.11
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• pp.1530-1537
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• 2007

In this paper, we implemented a speech emotion recognition system that can distinguish human emotional states from recorded speech captured by a single microphone and classify them into four categories: neutrality, happiness, sadness and anger. In general, a speech recorded with a microphone contains background noises due to the speaker environment and the microphone characteristic, which can result in serious system performance degradation. In order to minimize the effect of these noises and to improve the system performance, a MA(Moving Average) filter with a relatively simple structure and low computational complexity was adopted. Then a SFS(Sequential Forward Selection) feature optimization method was implemented to further improve and stabilize the system performance. For speech emotion classification, a SVM pattern classifier is used. The experimental results indicate the emotional classification performance around 65% in the computer simulation and 62% on the ARM platform.