• Korean Journal of Remote Sensing
• /
• v.33 no.5_2
• /
• pp.721-732
• /
• 2017

With the increasing socio-economic importance of rice as a global staple food, several models have been developed for rice yield estimation by combining remote sensing data with carbon cycle modelling. In this study, we aimed to estimate rice yield in Korea using such an integrative model using satellite remote sensing data in combination with a biophysical crop growth model. Specifically, daily meteorological inputs derived from MODIS (Moderate Resolution imaging Spectroradiometer) and radar satellite products were used to run a light use efficiency based crop growth model, which is based on the MODIS gross primary production (GPP) algorithm. The modelled biomass was converted to rice yield using a harvest index model. We estimated rice yield from 2003 to 2014 at the county level and evaluated the modelled yield using the official rice yield and rice straw biomass statistics of Statistics Korea (KOSTAT). The estimated rice biomass, yield, and harvest index and their spatial distributions were investigated. Annual mean rice yield at the national level showed a good agreement with the yield statistics with the yield statistics, a mean error (ME) of +0.56% and a mean absolute error (MAE) of 5.73%. The estimated county level yield resulted in small ME (+0.10~+2.00%) and MAE (2.10~11.62%),respectively. Compared to the county-level yield statistics, the rice yield was over estimated in the counties in Gangwon province and under estimated in the urban and coastal counties in the south of Chungcheong province. Compared to the rice straw statistics, the estimated rice biomass showed similar error patterns with the yield estimates. The subpixel heterogeneity of the 1 km MODIS FPAR(Fraction of absorbed Photosynthetically Active Radiation) may have attributed to these errors. In addition, the growth and harvest index models can be further developed to take account of annually varying growth conditions and growth timings.

• Journal of Distribution Science
• /
• v.14 no.1
• /
• pp.93-102
• /
• 2016

Purpose - The purpose of paper is studying the static and dynamic side for long-term memory storage properties, and increase the explanatory power regarding the long-term memory process by looking at the long-term storage attributes, Korea Composite Stock Price Index. The reason for the use of GPH statistic is to derive the modified statistic Korea's stock market, and to research a process of long-term memory. Research design, data, and methodology - Level shifts were subjected to be an empirical analysis by applying the GPH method. It has been modified by taking into account the daily log return of the Korea Composite Stock Price Index a. The Data, used for the stock market to analyze whether deciding the action by the long-term memory process, yield daily stock price index of the Korea Composite Stock Price Index and the rate of return a log. The studies were proceeded with long-term memory and long-term semiparametric method in deriving the long-term memory estimators. Chapter 2 examines the leading research, and Chapter 3 describes the long-term memory processes and estimation methods. GPH statistics induced modifications of statistics and discussed Whittle statistic. Chapter 4 used Korea Composite Stock Price Index to estimate the long-term memory process parameters. Chapter 6 presents the conclusions and implications. Results - If the price of the time series is generated by the abnormal process, it may be located in long-term memory by a time series. However, test results by price fixed GPH method is not followed by long-term memory process or fractional differential process. In the case of the time-series level shift, the present test method for a long-term memory processes has a considerable amount of bias, and there exists a structural change in the stock distribution market. This structural change has implications in level shift. Stratum level shift assays are not considered as shifted strata. They exist distinctly in the stock secondary market as bias, and are presented in the test statistic of non-long-term memory process. It also generates an error as a long-term memory that could lead to false results. Conclusions - Changes in long-term memory characteristics associated with level shift present the following two suggestions. One, if any impact outside is flowed for a long period of time, we can know that the long-term memory processes have characteristic of the average return gradually. When the investor makes an investment, the same reasoning applies to him in the light of the characteristics of the long-term memory. It is suggested that when investors make decisions on investment, it is necessary to consider the characters of the long-term storage in reference with causing investors to increase the uncertainty and potential. The other one is the thing which must be considered variously according to time-series. The research for price-earnings ratio and investment risk should be composed of the long-term memory characters, and it would have more predictability.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.33 no.4
• /
• pp.1433-1446
• /
• 2013

In this study, we proposed a methodology to develop Rating Curves for high water level using rainfall generation by the Monte Carlo Simulation (MCS) technique, optimized rainfall-runoff model, and flood routing model in an urban stream. The developed stage discharge Rating Curve based on observed data was contained flow measurement errors and uncertainties. The standard error ($S_e$) for observations was 0.056, and the random uncertainty ($2S_{mr}$) was analyzed by ${\pm}1.43%$ on average, and up to ${\pm}4.27%$. Moreover, it was found that the Rating Curve extensions by way of logarithmic and Stevens methods were overestimated to compare with the urban basin scale. Finally, we confirmed that the high water level extension by random generation of hydrological data using MCS can be reduced uncertainty of the high water level, and it will consider as a more reliable approach for high water level extension. In the near future, this results can be applied to real-time flood alert system for urban streams through construction of the high water level extension system using MCS procedures.

• The Transactions of the Korea Information Processing Society
• /
• v.6 no.8
• /
• pp.2233-2244
• /
• 1999

It is essential to guarantee high reliability of embedded real-time systems since the failure of such systems may result in large financial damage or threaten human life. Though many researches have devoted to fault tolerant mechanisms, most of them are object-level fault tolerant mechanisms that can detect errors occurred in a single object and treat the errors in object-level. As embedded real-time systems become more complex and larger, there exist faults that cannot be detected by or tolerated with object-level fault tolerance. Hence, system-level fault tolerance is needed. System-level fault tolerance examines the status of a system whether the system is normal or not by analyzing the status of objects. When an error is detected it should be capable of locating the fault and performing an appropriate recovery and reconfiguration action. In this paper, we propose RobustRTO(Robust Real-Time Object) that provides object-level fault tolerance capability and RMO(Region Monitor real-time Object) that offers system-level fault tolerance capability. Then we show how highly dependable fault tolerant systems can be modeled by RobustRTO and RMO. The model is presented based on real-time objects.

• Journal of the Korea Convergence Society
• /
• v.6 no.5
• /
• pp.1-8
• /
• 2015

The data of fair value hierarchy is expected to contain different degree of measurement error, information asymmetry, and information risk by the level of hierarchy. Thus, this study examines how hierarchy of fair value discriminately influences on companies' cost of capital. Through regression analysis of corporations listed from 2011 to 2014, it turns out that the regression coefficient of level 1 and 2 of fair value variable vary their rank by cost of capital types, while level 3 contains the highest regression coefficient for every cost of capital variable. In addition, further study of how the relevance between cost of capital and the fair value hierarchy gets affected by market risk management level and audit quality finds no consistent results. However, by analyzing the effect of coincident interaction through the convergence of market risk management and audit quality, when audit quality and market risk management level are high, the effect of relieving cost of capital of Level 3 gets the highest. In conclusion, fair value hierarchy data seems to affect discriminately on cost of capital by involved information risk, and the information risk could decrease by the level of market risk management and audit quality.

• Atmosphere
• /
• v.16 no.1
• /
• pp.19-31
• /
• 2006

The purpose of this study is to develop the statistical model to predict sea level pressure of typhoon period in south coast of the Korean Peninsula. Seven typhoons, which struck south coast of the Korean Peninsula, are selected for this study, and the data for analysis include the central pressure and location of typhoon, and sea level pressure and location of 19 observing site. Models employed in this study are the first order regression, the second order regression and the neural network. The dependent variable of each model is a 3-hr interval sea level pressure at each station. The cause variables are the central pressure of typhoon, distance between typhoon center and observing site, and sea level pressure of 3 hrs before, whereas the indicative variable reveals whether it is before or after typhoon passing. The data are classified into two groups - one is the full data obtained during typhoon period and the other is the data that sea level pressure is less than 1000 hPa. The stepwise selection method is used in the regression model while the node number is selected in the neural network by the Schwarz's Bayesian Criterion. The performance of each model is compared in terms of the root-mean square error. It turns out that the neural network shows better performance than other models, and the case using the full data produces similar or better results than the case using the other data.

• Quality Improvement in Health Care
• /
• v.7 no.1
• /
• pp.106-116
• /
• 2000

Background : Severance Hospital is an university hospital which has 1,580 beds. A LAN system was installed in the Medical Record Department in 1992 and discharge abstract data have been added to the discharge abstract database(DB) The previous work flow in the Medical Record Department had 5 levels: 1) chart collection from wards, 2) assembling, 3) abstracting data from medical record on worksheet by 2 RRAs, 4) checking deficiencies and coding diagnosis and procedures by 4 RRAs, 5) inputting the data into the discharge abstract data base by 1 RRA. The average processing time took 19.3 days from the patient discharge date. It had the production of monthly statistical report delayed. Besides, it caused the users in the hospital to complain. Methods : A CQI team was organized to find a way to shorten the processing time less than 10 days. The team identified the factors making the processing time long and integrated three levels from the 3rd level into one. Each of 7 RRAs performed the integrated level on her workstation instead of taking one of three separate levels. The comparison of processing time before and after the changes was made with 3'846 discharges of April, 1999 and 4,189 discharges of August, 1999. Results : The average processing time was shortened from 19.3 days to 8.7 days. Especially the integrated level took only 3.6 days, compared with 12.3 days before the change. The percentage of finishing up the whole processing within 10 days from discharge was increased up to 77.6%, which was 2.4% before the integration. The prevalence of error in data input was not increased in the new method. Conclusions : The integrated processing method has the following advantages: 1) the expedition of production of monthly statistical report, 2) the increase of utilizing rate of dischare abstract data by Billing Dept, Emergency Room, QI Dept., etc., 3) the improvement of intradepartmental work follow, 4) the enhancement of medical record quality by checking the deficiencies earlier than before.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.52 no.5
• /
• pp.23-32
• /
• 2015

The advanced receiver which can manage inter-cell interference is required to cope with the explosively increasing mobile data traffic. 3rd Generation Partnership Project (3GPP) has discussed network assisted interference cancellation and suppression (NAICS) to improve signal-to-noise-plus-interference ratio (SINR) and receiver performance by suppression or cancellation of interference signal from inter-cells. In this paper, we propose the novel hybrid receiver Full Suppression Cancellation (FSC) to reduce the interference from neighbor cell in backhaul system. The proposed receiver can suppress and cancel the interference by combining Interference Rejection Combining (IRC) with Successive Interference Cancellation (SIC). We perform the system level simulation based on 20MHz bandwidth of 3GPP LTE-Advanced system. Simulation results show that the proposed receiver can improve error rate and throughput of conventional system.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.49 no.9
• /
• pp.244-250
• /
• 2012

This paper describes a 4-Gb/s receiver circuit for a low-swing ground-referenced differential signaling system. The receiver employs a common-gate level-shifter and a continuous linear equalizer which compensates inter-symbol-interference (ISI) and improves voltage and timing margins. A bias circuit maintains the bias current of the level-shifter when the common level of the input signal changes. The receiver is implemented with a low-power 65-nm CMOS technology. When 4-Gb/s 400mVp-p signals are transmitted to the receiver through the channel with the attenuation of -19.7dB, the timing margin based on bit error rate (BER) of $10^{-11}$ is 0.48UI and the power consumption is as low as 0.30mW/Gb/s.

• Journal of Biomedical Engineering Research
• /
• v.41 no.2
• /
• pp.84-93
• /
• 2020

Despite of a lot of studies about proprioception tests, there are little study results to investigate the relationship between the functional movement and proprioception level. In this study, we tried to perform quantitative analysis for the effect of ankle joint proprioception level on the one leg standing postural control ability. Nine healthy people volunteered for this study. Force and position aspects of proprioception were evaluated using the electromyography system (EMG) and mobile clinometer application, respectively. The center of pressure (COP) trajectories, measured by a pressure mat sensor, were used for quantitative analysis of balance for each subject. We computed indices and errors of force and position aspects of proprioception from the EMG and ankle angle. Mean velocity of total and anterior-posterior direction (Vm and Vm_ap), root mean squared distance in anterior-posterior direction (RDap), travel length (L), and area (A) of COP trajectories were also calculated as indices of postural control ability of subjects. Two aspects of proprioception showed the low correlation from each other as previous studies. However, the EMG error of gastrocnemius lateral activation showed a high correlation coefficient with COP variables such as Vm (ρ=0.817, p=0.007), Vm_ap (ρ=0.883, p=0.002), RDap (ρ=0.854, p=0.003), L (ρ=0.817, 0.007) and A (ρ=0.700, p=0.036). Within our knowledge, this is almost the first study that investigated the relationship between proprioception level and functional movement. These study results could support that the ankle joint proprioception facilitation exercise would have positive effects on functional balance rehabilitation interventions.