• Journal of the Institute of Convergence Signal Processing
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• v.10 no.1
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• pp.32-39
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• 2009

In this paper, the method of region segmentation using genetic algorithm is proposed for an improvement of efficiency in moving picture coding. A genetic algorithm is the method that searches a large probing space using only a function value for a optimal combination consecutively. By progressing both motion presumption and region segmentation at once, we can assign the motion vector in a image to a small block or a pixel respectively, and transform the capacity of coding and a signal to noise rate into a problem of optimization. That is to say, there is close correlation between region segmentation and motion presumption in motion-compensated prediction coding. This is to optimize the capacity of coding and a S/N ratio. This is to arrange the motion vector in each block of picture according to the state of optimization. Therefore, we examined both the data type of genetic algorithm and the method of data processing to obtain the results of optimal region segmentation in this paper. And we confirmed the validity of a proposed method using the test pictures by means of computer simulation.

• Journal of the Korea Society of Computer and Information
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• v.19 no.11
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• pp.17-24
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• 2014

This paper proposes a fault detection method for low-speed rolling element bearings of an induction motor using acoustic emission signals and histogram modeling. The proposed method performs envelop modeling of the histogram of normalized fault signals. It then extracts and selects significant features of each fault using partial autocorrelation coefficients and distance evaluation technique, respectively. Finally, using the extracted features as inputs, the support vector regression (SVR) classifies bearing's inner, outer, and roller faults. To obtain optimal classification performance, we evaluate the proposed method with varying an adjustable parameter of the Gaussian radial basis function of SVR from 0.01 to 1.0 and the number of features from 2 to 150. Experimental results show that the proposed fault identification method using 0.64-0.65 of the adjustable parameter and 75 features achieves 91% in classification performance and outperforms conventional fault diagnosis methods as well.

• The Journal of the Acoustical Society of Korea
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• v.30 no.3
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• pp.136-141
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• 2011

In this paper, a method for measuring rhythmic similarity between two sound signals for auditory memory game is proposed. The proposed method analyzes energy fluctuation, the temporal duration of energy peak, the timbre of two signals, and detects beat positions for each signal. Then, it determines the rhythm vector after compensating a difference in tempo and the number of beats between two signals. Finally, a method for rhythmic similarity measurement is defined as a function of the dissimilarity between two rhythm vectors and a difference in the number of beats. The rhythmic similarity measured by the proposed method and that by the subjective listening test are compared, and the correlation of 0.86 between two results is achieved.

• Journal of Industrial Technology
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• v.38 no.1
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• pp.41-52
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• 2018

Recently, object detection is a critical function for any system that uses computer vision and is widely used in various fields such as video surveillance and self-driving cars. However, the conventional methods can not detect the objects clearly because of the dynamic background change in the beach. In this paper, we propose a new technique to detect humans correctly in the dynamic videos like shores. A new background modeling method that combines spatial GMM (Gaussian Mixture Model) and temporal GMM is proposed to make more correct background image. Also, the proposed method improve the accuracy of people detection by using SVM (Support Vector Machine) to classify people from the objects and KCF (Kernelized Correlation Filter) Tracker to track people continuously in the complicated environment. The experimental result shows that our method can work well for detection and tracking of objects in videos containing dynamic factors and situations.

• Journal of the Korean Society of Visualization
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• v.8 no.1
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• pp.31-38
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• 2010

An experimental study to evaluate dynamic structures of flow and turbulence characteristics in bubble-driven liquid flow in a rectangular tank with a varying flow rate of compressed air is conducted. Liquid flow fields are measured by time-resolved particle image velocimetry (PIV) with fluorescent tracer particles to eliminate diffused reflections, and by an image intensifier to acquire enhanced clean particle images. Instantaneous vector fields are investigated by using the two frame cross-correlation function and bad vectors are eliminated by magnitude difference technique. By proper orthogonal decomposition (POD) analysis, the energy distributions of spatial and temporal modes are acquired. When Reynolds number increases, bubble-induced turbulent motion becomes dominant rather than the recirculating flow near the side wall. The total kinetic energy transferred to the liquid from the rising bubbles shows a nonlinear relation regarding the energy input because of the interaction between bubbles and free surface.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.10
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• pp.543-553
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• 2020

This paper examines the effect of COVID-19 pandemic on the Philippine stock exchange, peso-dollar rate and retail price of diesel using robust least squares regression and vector autoregression (VAR). The robust least squares regression using MM-estimation method concluded that COVID-19 daily infection has negative and statistically significant effect on the Philippine stock exchange index, peso-dollar exchange rate and retail pump price of diesel. This is consistent with the results of correlation diagnostics. As for the VAR model, the lag values of the independent variable disclose significance in explaining the Philippine stock exchange index, peso-dollar exchange rate and retail pump price of diesel. Moreover, in the short run, the impulse response function confirmed relative effect of COVID-19 daily infections and the variance decomposition divulge that COVID-19 daily infections have accounted for only minor portion in explaining fluctuations of the Philippine stock exchange index, peso-dollar exchange and retail pump price of diesel. In the long term, the influence levels off. The Granger causality test suggests that COVID-19 daily infections cause changes in the Philippine stock exchange index and peso-dollar exchange rate in the short run. However, COVID-19 infection has no causal link with retail pump price of diesel.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.2
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• pp.73-78
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• 2004

By modeling the block matching algorithm as a function of the correlation of image blocks, we derive search patterns for fast block matching motion estimation. The proposed approach provides an analytical support lot the diamond-shape search pattern, which is widely used in fast block matching algorithms. We also propose a new fast motion estimation algorithm using adaptive search patterns and statistical properties of the object displacement. In order to select an appropriate search pattern, we exploit the relationship between the motion vector and the block differences. By changing the search pattern adaptively, we improve motion prediction accuracy while reducing required computational complexity compared to other fast block matching algorithms.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.28 no.4
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• pp.121-132
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• 2023

Marine heatwaves (MHWs), referring to anomalously high sea surface temperatures, have drawn significant attention from marine scientists due to their broad impacts on the surface marine ecosystem, fisheries, weather patterns, and various human activities. In this study, we examined the impact of the distribution of Changjiang diluted water (CDW), a significant factor causing oceanic property changes in the East China Sea (ECS) during the summer, on MHWs. The surface salinity distribution in the ECS indicates that from June to August, the eastern extension of the CDW influences areas as far as Jeju Island and the Korea Strait. In September, however, the CDW tends to reside in the Changjiang estuary. Through the Empirical Orthogonal Function analysis of the cumulative intensity of MHWs during the summer, we extracted the loading vector of the first mode and its principal component time series to conduct a correlation analysis with the distribution of the CDW. The results revealed a strong negative spatial correlation between areas of the CDW and regions with high cumulative intensity of MHWs, indicating that the reinforcement of stratification due to low-salinity water can increase the intensity and duration of MHWs. This study suggests that the CDW may still influence the spatial distribution of MHWs in the region, highlighting the importance of oceanic environmental factors in the occurrence of MHWs in the waters surrounding the Korean Peninsula.

• Journal of Plant Biotechnology
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• v.3 no.1
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• pp.7-12
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• 2001

An antiserum against the carrot HSP17 (17 KDa heat shock protein) was raised using the HSP17 purified after being expressed in a recombinant E.coli in order to develop an assay system for thermotolerance in crops. The DCHsp17.7 including the coding sequence corresponding to a carrot HSP17 protein was recombined within pET-32(b) vector and achieved a maximum expression in 4 hours after an induction in E.coli. The purified DCHsp17.7 was used as an antigen to generate the corresponding antibody. The polyclonal antiserum was confirmed for it's specificity only to the low molecular weight (1mw) HSP. Besides, the possibilities to use the antiserum to interact with 1mwHSPs from other plants such as rice, cucumber, tomato, and hot pepper were examined to be plausible. To reveal any specific correlation between the amounts of 1mwHSP expressed upon HS conditions and an acquisition of thermotolerance two different approaches have been applied. first, it has been shown that only the pre-HS conditions inducing the synthesis of HSP17 allowed for the seedlings to achieve an thermotolerance and to survive the following lethal condition. Second, a western analysis using 15 different collected lines of hot peppers was performed to distinguish each other in terms of the amount of 1mwHSP. The results indicated that all 14 hot pepper lines were able to synthesize HSPs in response to an exposure to HS conditions and the amounts of the proteins synthesized at different HS temperatures were variable among the lines. There are several different patterns of 1mwHSP synthesized as a function of temperature increase observed and their correlation to physiological aspects of thermotolerance remains to be analyzed.

• Nuclear Engineering and Technology
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• v.52 no.4
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• pp.846-855
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• 2020

A loose part monitoring system is used to detect unexpected loose parts in a reactor coolant system in a nuclear power plant. It is still necessary to develop a new methodology for the localization and mass estimation of loose parts owing to the high estimation error of conventional methods. In addition, model-based diagnostics recently emphasized the importance of a model describing the behavior of a mechanical system or component. The purpose of this study is to propose a new localization and mass-estimation method based on finite element analysis (FEA) and optimization technique. First, an FEA model to simulate the propagation behavior of the bending wave generated by a metal sphere impact is validated by performing an impact test and a corresponding FEA and optimization for a downsized steam-generator structure. Second, a novel methodology based on FEA and optimization technique was proposed to estimate the impact location and mass of a loose part at the same time. The usefulness of the methodology was then validated through a series of FEAs and some blind tests. A new feature vector, the cross-correlation function, was also proposed to predict the impact location and mass of a loose part, and its usefulness was then validated. It is expected that the proposed methodology can be utilized in model-based diagnostics for the estimation of impact parameters such as the mass, velocity, and impact location of a loose part. In addition, the FEA-based model can be used to optimize the sensor position to improve the collected data quality in the site of nuclear power plants.