• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.153-153
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• 2022

Large-scale and accurate observations at fine spatial resolution through a means of remote sensing offer an effective tool for capturing rainfall variability over the traditional rain gauges and weather radars. Although satellite rainfall products (SRPs) derived using two major estimation approaches were evaluated worldwide, their practical applications suffered from limitations. In particular, the traditional top-down SRPs (e.g., IMERG), which are based on direct estimation of rain rate from microwave satellite observations, are mainly restricted with their coarse spatial resolution, while applications of the bottom-up approach, which allows backward estimation of rainfall from soil moisture signals, to novel high spatial resolution soil moisture satellite sensors over South Korea are not introduced. Thus, this study aims to evaluate the performances of a state-of-the-art bottom-up SRP (the self-calibrated SM2RAIN model) applied to the C-band SAR Sentinel-1, a statistically downscaled version of the conventional top-down IMERG SRP, and their integration for a targeted high spatial resolution of 0.01° (~ 1-km) over central South Korea, where the differences in climate zones (coastal region vs. mainland region) and vegetation covers (croplands vs. mixed forests) are highlighted. The results indicated that each single SRP can provide plus points in distinct climatic and vegetated conditions, while their drawbacks have existed. Superior performance was obtained by merging these individual SRPs, providing preliminary results on a complementary high spatial resolution SRP over central South Korea. This study results shed light on the further development of integration framework and a complementary high spatial resolution rainfall product from multi-satellite sensors as well as multi-observing systems (integrated gauge-radar-satellite) extending for entire South Korea, toward the demands for urban hydrology and microscale agriculture.

• Asia-Pacific Journal of Business
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• v.10 no.4
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• pp.87-118
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• 2019

The purpose of this study is to examine the effects of person-job fit, which consists of educational fit and skill fit, on employees' intrinsic job satisfaction. To the end, the 10-year balanced panel data of the Korean Labor and Income Panel Study(KLIPS) by the Korea Labor Institute (KLI) for 2008-2017 are utilized. This study analyzes 12,730 observations by 1,273 employees by using fixed effect model, random effect model, and pooled OLS estimation method. The empirical results are as follows: First, it is founded that educational fit and skill fit seem affect job satisfaction positively. Second, the negative effects of over-education are clear and the negative effects of under-education are unclear, while the effects of over-skilled and under-skilled are insignificant statistically. Third, the results imply that the size of effect of over-education on intrinsic job satisfaction is larger than that of the effect of over-skilled. Forth, it is shown that the use of fixed effect model is more effective and trustworthy than that of random effect model and pooled OLS estimation method, implying that the effect size of coefficients which are estimated by pooled OLS method and random effect model are likely over-estimated. The empirical results above imply that firms and employees should focus on solving over-education issue before all in order to enhance employees' job satisfaction and it is needed to monitor regularly whether systemic job assignment process is done based on the employees' educational attainment and skill level and to provide more chances for job re-allocation and job rotation.

• Journal of Oral Medicine and Pain
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• v.33 no.2
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• pp.167-176
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• 2008

We analyzed 121 age estimation clients who had visited oral medicine clinic, Chonbuk National University Hospital, from January 2000 to December 2007 to evaluate its characters in Jeonllabuk-do. The obtained results were as follows : 1. There was distinct difference in sex distribution(Male : 58.7%, Female : 41.3%) and more than half percent(55.4%) was over 50's. 2. The difference between registered and alleged age was the most in more than 5 years, and most of them were over 50's. 3. There were more clients who wanted to increase their age than to decrease and was no prominent difference in sex. Age estimation clients who wanted to decrease their age were predominant under 10 years old and in 20's, and those wanted to increase were predominant in 10's and over 30's. 4. The most reasons to correct age were related to welfare benefit. The purpose of age estimation was different according to each age groups; welfare benefit was the most over 50's, occupation in 40's and 50's, friendship in 30's and 40's, sibling-related in 50's, employment in 10's and 20's. 5. Age was estimated by the attrition of permanent tooth and pulp/tooth ratio from 20 years, root apex closure for 10's and calcification of permanent tooth under 10 years old. In cases that were difficult to estimate by use of the attrition of permanent tooth and pulp/tooth ratio, age was estimated by missing time of permanent tooth and the change of mandibular angle with age. 6. The estimated ages were close to alleged age in 77.7% of clients but the rest(22.3%) was close to registered age.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.2
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• pp.583-599
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• 2015

We apply the Bayesian matching pursuit (BMP) algorithm to the estimation of time-frequency selective channels in orthogonal frequency division multiplexing (OFDM) systems. By exploiting prior statistics and sparse characteristics of propagation channels, the Bayesian method provides a more accurate and efficient detection of the channel status information (CSI) than do conventional sparse channel estimation methods that are based on compressive sensing (CS) technologies. Using a reasonable approximation of the system model and a skillfully designed pilot arrangement, the proposed estimation scheme is able to address the Doppler-induced inter-carrier interference (ICI) with a relatively low complexity. Moreover, to further reduce the computational cost of the channel estimation, we make some modifications to the BMP algorithm. The modified algorithm can make good use of the group-sparse structure of doubly selective channels and thus reconstruct the CSI more efficiently than does the original BMP algorithm, which treats the sparse signals in the conventional manner and ignores the specific structure of their sparsity patterns. Numerical results demonstrate that the proposed Bayesian estimation has a good performance over rapidly time-varying channels.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1441-1461
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• 2017

Nowadays, Dynamic Adaptive Streaming over HTTP (DASH) has become very popular in streaming multimedia contents. In DASH, a client estimates current network bandwidth and then determines an appropriate video quality with bitrate matching the estimated bandwidth. Thus, estimating accurately the available bandwidth is a significant premise in the quality of video streaming, especially when network traffic fluctuates substantially. To cope with this challenge, researchers have presented various filters to estimate network bandwidth adaptively. However, experiment results show that current schemes either adapt slowly to network changes or adapt fast but are very sensitive to delay jitter and produce sharply changed estimation. This paper presents a novel bandwidth estimation scheme based on Moving Average Convergence Divergence (MACD). We applied an MACD indicator and its two thresholds to classifying network states into stable state and agile state, based on the network state different filters are applied to estimate network bandwidth. In the paper, we studied the performance of various MACD indicators and the threshold values on bandwidth estimation. Then we used a DASH proxy-based environment to compare the performance of the presented scheme with current well-known schemes. The simulation results illustrate that the MACD-based bandwidth estimation scheme performs superior to existing schemes both in the speed of adaptively to network changes and in stability in bandwidth estimation.

• The Transactions of the Korean Institute of Power Electronics
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• v.26 no.1
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• pp.1-8
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• 2021

For the safe and reliable operation of lithium-ion batteries in electric vehicles or energy storage systems, having accurate information of the battery, such as the state of charge (SOC), is essential. Many different techniques of battery SOC estimation have been developed, such as the Kalman filter. However, when this filter is applied to multiple batteries, it has difficulty maintaining the accuracy of the estimation over all cells owing to the difference in parameter values of each cell. The difference in the parameter of each cell may increase as the operation time accumulates due to aging. In this paper, a novel deep neural network (DNN)-based SOC estimation method for multi-cell application is proposed. In the proposed method, DNN is implemented to determine the nonlinear relationships of the voltage and current at different SOCs and temperatures. In the training, the voltage and current data obtained at different temperatures during charge/discharge cycles are used. After the comprehensive training with the data obtained from the cycle test with a cell, the resulting algorithm is applied to estimate the SOC of other cells. Experimental results show that the mean absolute error of the estimation is 1.213% at 25℃ with the proposed DNN-based SOC estimation method.

• Journal of Korea Multimedia Society
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• v.25 no.1
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• pp.39-51
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• 2022

Image-based gender classification and age estimation of human are classic problems in computer vision. Most of researches in this field focus just only one task of either gender classification or age estimation and most of the reported methods for each task focus on accuracy performance and are not computationally light. Thus, running both tasks together simultaneously on low cost mobile or embedded systems with limited cpu processing speed and memory capacity are practically prohibited. In this paper, we propose a novel light-weight gender classification and age estimation method based on ensemble multitasking deep learning with light-weight processing neural network architecture, which processes both gender classification and age estimation simultaneously and in real-time even for embedded systems. Through experiments over various well-known datasets, it is shown that the proposed method performs comparably to the state-of-the-art gender classification and/or age estimation methods with respect to accuracy and runs fast enough (average 14fps) on a Jestson Nano embedded board.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.75-78
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• 1999

The iterative usage of soft outputs increases the performance of digital radio receiver. The feedback of reliability information reduces the channel estimation errors and increases the performance of equalization. This paper investigates the turbo equalization techniques for wireless cellular systems over continuous time varying channel. Simulation results over a GSM channel were presented.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.2
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• pp.235-243
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• 2012

In this paper, we propose a method to improve performance of pilot symbol assisted modulation(PSAM) channel estimation method for OFDM systems over frequency selective channel. When channel values are estimated, the low pilot density used for channel estimation increases not only the effective data rate but also power efficiency. Thus, the lower pilot density which is used for channel estimation is better for OFDM system. At first, we estimate the channel values which are located at the middle of adjacent pilots, and then all of the possible channel values are estiamted by using original pilot values and previously estimated pilot values. Furthermore, the error of estimated channel values is reduced by introducing guard interval which is designed acccording to maximum channel delay. Performance achieved with the proposed method is illustrated by simulation experiments in comparison with the existing methods in terms of mean squared error(MSE).

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.485-490
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• 1999

Wind vector information over the ocean is currently obtained using multiple beam scatterometer data. The scatterometers on ERS-1/2 generate wind vector information with a spatial resolution of 50km and accuracies of $\pm$2m/s in wind speed and $\pm$20$^{\circ}$ in wind direction. Synthetic aperture radar (SAR) data over the ocean have the potential of providing wind vector information independent of weather conditions with finer resolution. Finer resolution wind vector information can often be useful particularly in coastal regions where the scatterometer wind information is often corrupted because of the lower resolution system characteristics which is often contaminated by the signal returns from the coastal areas or ice in the case of arctic environments. In this paper we tested CMOD_4 and CMOD_IFR2 algorithms for extracting the wind vector from SAR data. These algorithms require precise estimation of normalized radar cross-section and wind direction from the SAR data and the local incidence angle. The CMOD series algorithms were developed for the C-band, VV-Polarized SAR data, typically for the ERS SAR data. Since RADARSAT operates at the same C-band but with HH-Polarization, the CMOD series algorithms should not be used directly. As a preliminary approach of resolving with this problem, we applied the polarization ratio between the HH and VV polarizations in the wind vectors estimation. Two test areas, one in front of Inchon and several sites around Jeju island were selected and investigated for wind vector estimation. The new results were compared with the wind vectors obtained from CMOD algorithms. The wind vector results agree well with the observed wind speed data. However the estimation of wind direction agree with the observed wind direction only when the wind speed is greater than approximately 3.0m/s.