• Title/Summary/Keyword: 2-period model

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Numerical Simulation of Extreme Air Pollution by Fine Particulate Matter in China in Winter 2013

  • Shimadera, Hikari;Hayami, Hiroshi;Ohara, Toshimasa;Morino, Yu;Takami, Akinori;Irei, Satoshi
    • Asian Journal of Atmospheric Environment
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    • v.8 no.1
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    • pp.25-34
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    • 2014
  • In winter 2013, extreme air pollution by fine particulate matter ($PM_{2.5}$) in China attracted much public attention. In order to simulate the $PM_{2.5}$ pollution, the Community Multiscale Air Quality model driven by the Weather Research and Forecasting model was applied to East Asia in a period from 1 January 2013 to 5 February 2013. The model generally reproduced $PM_{2.5}$ concentration in China with emission data in the year 2006. Therefore, the extreme $PM_{2.5}$ pollution seems to be mainly attributed to meteorological (weak wind and stable) conditions rather than emission increases in the past several years. The model well simulated temporal and spatial variations in $PM_{2.5}$ concentrations in Japan as well as China, indicating that the model well captured characteristics of the $PM_{2.5}$ pollutions in both areas on the windward and leeward sides in East Asia in the study period. In addition, contribution rates of four anthropogenic emission sectors (power generation, industrial, residential and transportation) in China to $PM_{2.5}$ concentration were estimated by conducting zero-out emission sensitivity runs. Among the four sectors, the residential sector had the highest contribution to $PM_{2.5}$ concentration. Therefore, the extreme $PM_{2.5}$ pollution may be also attributed to large emissions from combustion for heating in cold regions in China.

Reliability Growth Planning for a Military System Using PM2-Continuous Model (예측방법론 기반 연속형 계획 모델을 적용한 무기체계의 신뢰도 성장 계획)

  • Seo, Yangwoo;Park, Eunshim;Kim, Youngkuk;Lee, Kwanyoung;Kim, Myungsoo
    • Journal of Applied Reliability
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    • v.18 no.3
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    • pp.201-207
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    • 2018
  • Purpose: To develop the reliability growth planning for a subsystem of guided weapon system using PM2-Continuous model. Methods: The target MTBF of the subsystem is set by allocating the system target MTBF to the lower level, where ARINC method is applied. Other model parameters such as initial MTBF, management strategy ratio and average fix effectiveness factor are chosen from historical growth parameter estimates. Given the values of model parameters, the reliability growth planning curve using PM2-Continuous model is constructed and the sensitivity analyses are performed for the changes of model parameters. Results: We have developed the reliability growth plan for a subsystem of guided weapon system using PM2-Continuous model. It was found that the smaller the ratio of initial MTBF to target MTBF, the smaller the management strategy ratio, the smaller the average fix effectiveness factor, and the shorter the development test period, the higher reliability growth is required. Conclusion: The result of this study will be used as a basis for establishing the reliability growth plan, the test period setting and the budget appropriation for the similar system entering the system development stage in the future.

Comparison of Model-simulated Atmospheric Carbon Dioxide with GOSAT Retrievals

  • Shim, Chang-Sub;Nassar, Ray;Kim, Jhoon
    • Asian Journal of Atmospheric Environment
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    • v.5 no.4
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    • pp.263-277
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    • 2011
  • Global atmospheric $CO_2$ distributions were simulated with a chemical transport model (GEOS-Chem) and compared with space-borne observations of $CO_2$ column density by GOSAT from April 2009 to January 2010. The GEOS-Chem model simulated 3-D global atmospheric $CO_2$ at $2^{\circ}{\times}2.5^{\circ}$ horizontal resolution using global $CO_2$ surface sources/sinks as well as 3-D emissions from aviation and the atmospheric oxidation of other carbon species. The seasonal cycle and spatial distribution of GEOS-Chem $CO_2$ columns were generally comparable with GOSAT columns over each continent with a systematic positive bias of ~1.0%. Data from the World Data Center for Greenhouse Gases (WDCGG) from twelve ground stations spanning $90^{\circ}S-82^{\circ}N$ were also compared with the modeled data for the period of 2004-2009 inclusive. The ground-based data show high correlations with the GEOS-Chem simulation ($0.66{\leq}R^2{\leq}0.99$) but the model data have a negative bias of ~1.0%, which is primarily due to the model initial conditions. Together these two comparisons can be used to infer that GOSAT $CO_2$ retrievals underestimate $CO_2$ column concentration by ~2.0%, as demonstrated in recent validation work using other methods. We further estimated individual source/sink contributions to the global atmospheric $CO_2$ budget and trends through 7 tagged $CO_2$ tracers (fossil fuels, ocean exchanges, biomass burning, biofuel burning, net terrestrial exchange, shipping, aviation, and CO oxidation) over 2004-2009. The global $CO_2$ trend over this period (2.1 ppmv/year) has been mainly driven by fossil fuel combustion and cement production (3.2 ppmv/year), reinforcing the fact that rigorous $CO_2$ reductions from human activities are necessary in order to stabilize atmospheric $CO_2$ levels.

Analysis of Domestic and Foreign Contributions using DDM in CMAQ during Particulate Matter Episode Period of February 2014 in Seoul (2014년 2월 서울의 고농도 미세먼지 기간 중에 CMAQ-DDM을 이용한 국내외 기여도 분석)

  • Kim, Jong-Hee;Choi, Dae-Ryun;Koo, Youn-Seo;Lee, Jae-Bum;Park, Hyun-Ju
    • Journal of Korean Society for Atmospheric Environment
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    • v.32 no.1
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    • pp.82-99
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    • 2016
  • This study was carried out to understand the regional contribution of Particulate Matter (PM) emissions from East Asia ($82^{\circ}{\sim}149^{\circ}E$, $18^{\circ}{\sim}53^{\circ}N$) to Seoul during high concentration period in February 2014. The Community Multi-scale Air Quality (CMAQ) version 5.0.2 with Decoupled Direct Method (DDM) was used to analyze levels of contributions over Seoul. In order to validate model performance of the CMAQ, predicted PM and its chemical species concentrations were compared to observations in China and Seoul. Model predictions could depict the daily and hourly variations of observed PM. The calculated PM concentrations, however, had a tendency of underestimation. The discrepancies are due to uncertainties of meteorological data, emission inventories and CMAQ model itself. The high PM concentration in Seoul was induced by stationary anticyclone over the West Coast of Korea during 24 to 27 February. The DDM in CMAQ was used to analyze the contributions of emissions from East Asia on Seoul during this PM episode. $PM_{10}$ concentration in Seoul is contributed by 39.77%~53.19% from China industrial and urban region, 15.37%~37.10% from South Korea, and 9.03%~18.05% North Korea. These indicate that $PM_{10}$ concentrations in Seoul during the episode period are dominated by long-range transport from China region as well as domestic sources. It was also found that the largest contribution region in China were Shandong peninsula during the PM event period.

A Study on a Modeling of the Inhibitory Reflex Mechanism of Jaw Muscle Induced by Electrical Stimulation (전기자극에 대한 턱근육의 억제반사 메카니즘의 모델링에 관한 연구)

  • 김성환;김태훈;조일준;유세근
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.52 no.9
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    • pp.560-567
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    • 2003
  • EMG recordings of the electrical activity of muscle have proved to be a valuable tool in studying muscle function and reflex activity. SP(silent period) is elicited by a electrical stimulation on the chin during isometric contraction of jaw muscle. This paper proposes a model of the inhibitory reflex mechanism of jaw muscle after electrical stimulation. The SPs of jaw muscle after a electrical stimulation to the chin were divided into SP1 and SP2. SP1 is produced by the activation of periodontal receptors. The activation of nociceptors contributes to the SP2. As a result, the EMG signal generated by a proposed a model of inhibitory reflex mechanism is similar to real both EMG signal including SP1 and SP2. The present study have shown differences of SP1 and SP2 induced by inhibitory reflex mechanism.

Drying Characteristics and Drying Model of Red Pepper (고추의 건조특성(乾燥特性)과 건조모델에 관(關)한 연구(硏究))

  • Cho, Y.J.;Koh, H.K.
    • Journal of Biosystems Engineering
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    • v.11 no.1
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    • pp.52-63
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    • 1986
  • This study was performed to find out drying characteristics and develop drying model for the design of an efficient dryer or drying system of red peper. The basic model which describes drying phenomenon of red pepper was firstly established, and drying tests were conducted at 14-different drying conditions. In this test, the effects of drying air temperature and relative humidity on the rate of drying were undertaken. Finally, a new drying model based on these experimental results was developed to describe the drying characteristics of red pepper. The results from this study may be summarized as follows. 1. Drying constant of the basic model established from Lewis' experimental model and diffusion equation was theoretically deduced as a function of moisture content and inner-temperature of red pepper. 2. From the results of drying tests, drying air temperature was found to have the greatest effect on the rate of drying. However, the effect of temperature was small for the condition of high relative humidity, and for low temperature, the effect of relative humidity was found to be large even though the range of relative humidity was low. 3. Modified Henderson equation was found to be better than Chung equation as the EMC model for the estimation of the equilibrium moisture content of red Pepper. 4. Constant-rate drying period did not exist in the red pepper drying test. And falling-rate drying period was divided into three distinct phases. Drying rate was dependent on the moisture content, the inner-temperature of red pepper and the change of physical property due to drying. 5. Drying constant increased with decrease of free moisture content, but it decreased at the end of the drying period. Also, drying constant was dependent on the drying air temperature and relative humidity. 6. The new drying model developed in this study was found to be most suitable in describing the drying characteristics of red pepper. Therefore, it may be concluded that drying time could be accurately estimated by the new drying model.

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Information Flow Effect Between the Stock Market and Bond Market (주식시장과 채권시장간의 정보 이전효과)

  • Choi, Cha-Soon
    • Journal of Convergence for Information Technology
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    • v.10 no.3
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    • pp.67-75
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    • 2020
  • This paper investigated the information spillover effect between stock market and bond market with the KOSPI daily index and MMF yield data. The overall analysis period is from May 2, 1997 to August 30, 2019. The empirical analysis was conducted by dividing the period from May 2, 1997 to December 30, 2008 before the global financial crisis, and from December 30, 2008 to August 30, 2019 after the global financial crisis, and the overall analysis period. The analysis shows that the EGARCH model considering asymmetric variability is suitable. The price spillover effect and volatility spillover effect existed in both directions between the stock market and the bond market, and the price transfer effect was greater in the period before the global financial crisis than in the period after the global financial crisis. Asymmetric volatility in information between stock and bond markets appears to exist in both markets.

Operational Hydrological Forecast for the Nakdong River Basin Using HSPF Watershed Model (HSPF 유역모델을 이용한 낙동강유역 실시간 수문 유출 예측)

  • Shin, Changmin;Na, Eunye;Lee, Eunjeong;Kim, Dukgil;Min, Joong-Hyuk
    • Journal of Korean Society on Water Environment
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    • v.29 no.2
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    • pp.212-222
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    • 2013
  • A watershed model was constructed using Hydrological Simulation Program Fortran to quantitatively predict the stream flows at major tributaries of Nakdong River basin, Korea. The entire basin was divided into 32 segments to effectively account for spatial variations in meteorological data and land segment parameter values of each tributary. The model was calibrated at ten tributaries including main stream of the river for a three-year period (2008 to 2010). The deviation values (Dv) of runoff volumes for operational stream flow forecasting for a six month period (2012.1.2 to 2012.6.29) at the ten tributaries ranged from -38.1 to 23.6%, which is on average 7.8% higher than those of runoff volumes for model calibration (-12.5 to 8.2%). The increased prediction errors were mainly from the uncertainties of numerical weather prediction modeling; nevertheless the stream flow forecasting results presented in this study were in a good agreement with the measured data.

Stock market stability index via linear and neural network autoregressive model (선형 및 신경망 자기회귀모형을 이용한 주식시장 불안정성지수 개발)

  • Oh, Kyung-Joo;Kim, Tae-Yoon;Jung, Ki-Woong;Kim, Chi-Ho
    • Journal of the Korean Data and Information Science Society
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    • v.22 no.2
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    • pp.335-351
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    • 2011
  • In order to resolve data scarcity problem related to crisis, Oh and Kim (2007) proposed to use stability oriented approach which focuses a base period of financial market, fits asymptotic stationary autoregressive model to the base period and then compares the fitted model with the current market situation. Based on such approach, they developed financial market instability index. However, since neural network, their major tool, depends on the base period too heavily, their instability index tends to suffer from inaccuracy. In this study, we consider linear asymptotic stationary autoregressive model and neural network to fit the base period and produce two instability indexes independently. Then the two indexes are combined into one integrated instability index via newly proposed combining method. It turns out that the combined instability performs reliably well.

Comparison of Mortality Estimate and Prediction by the Period of Time Series Data Used (시계열 적용기간에 따른 사망력 추정 및 예측결과 비교 - LC모형과 LC 코호트효과 확장모형을 중심으로 -)

  • Jung, Kyunam;Baek, Jeeseon;Kim, Donguk
    • The Korean Journal of Applied Statistics
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    • v.26 no.6
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    • pp.1019-1032
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    • 2013
  • The accurate prediction of future mortality is an important issue due to recent rapid increases in life expectancy. An accurate estimation and prediction of mortality is important to future welfare policies. The optimal selection of a mortality model is important to estimate and predict mortality; however, the period of time series data used is also an important issue. It is essential to understand that the time series data for mortality is short in Korea and the data before 1982 is incomplete. This paper divides the time series of Korean mortality into two sets to compare the parameter estimates of the LC model and LC model with a cohort effect by the period of data used. A modeling and prediction of the mortality index and cohort effect index as well as the evaluation of future life expectancy is conducted. Finally, some suggestions are proposed for the future prediction of mortality.