• 제목/요약/키워드: Accumulation Rate Estimation

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Estimation of Nutrients Transport in Kamak Bay using the Eco-hydrodynamic Model (생태계모델을 이용한 가막만의 영양염 거동 특성 평가)

  • 김동명
    • Journal of Environmental Science International
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    • v.12 no.7
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    • pp.745-751
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    • 2003
  • The three-dimensional eco-hydrodynamic model was applied to estimate the physical process in terms of nutrients and net uptake(or regeneration) rate of nutrients in Kamak Bay for scenario analysis to find proper management plan. The estimation results of the physical process in terms of nutrients shelved that transportation of nutrients is dominant in surface level while accumulation of nutrients is dominant in bottom level. In the case of dissolved inorganic nitrogen, the results showed that the net uptake rate was 0∼60 mg/㎡/day in surface level(0∼3m), and the net regeneration rate was 0.0∼10.0 mg/㎡/day in middle level(3∼6m) and above 10mg/㎡/day in bottom level(6m∼below). In the case of dissolved inorganic phosphorus, the net uptake rate was 0.0∼3.0 mg/㎡/day in surface level, and the net regeneration rate was 0.5∼1.5 mg/㎡/day in middle level and 1.0∼3.0 mg/㎡/day in bottom level. These results indicates that net uptake and transport of nutrients are occurred predominantly at the surface level and the net generation and accumulation are dominant at bottom level. Therefore, it is important to consider the re-supplement of nutrients due to regeneration of bottom water.

Ecological modeling for estimation of a transport and distribution of COD in Kamak Bay (가막만의 COD 거동 및 분포 특성 평가를 위한 생태계 모델링)

  • Kim Dong-Myung
    • Journal of Environmental Science International
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    • v.14 no.9
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    • pp.835-842
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    • 2005
  • The three-dimensional eco-hydrodynamic model was applied to estimate the physical process in terms of COD (chemical oxygen demand) and net supply(or decomposition) rate of COD in Kamak Bay to find proper management plan for oxygen demanding organic matters. The estimation results of the physical process in terms of COD showed that transportation of COD is dominant in surface level while accumulation of COD is dominant in bottom level. In the case of surface level, the net supply rate of COD was 0 -0.50 mg/m2/day. The net decomposition rate of COD was 0 -0.04 mg/m2/day in middle level(3 -6m) and 0.05 -0.1 5 mg/m2/day in bottom level(6m -bottom). These results indicates that the biological decomposition and physical accumulation of COD are occurred predominantly at the northern part of bottom level. Therefore, it is important to consider both allochthonous and autochthonous oxygen demanding organic matters in the region.

정보통신기술의 확산과 결정요인

  • 서환주;안정화
    • Journal of Technology Innovation
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    • v.9 no.2
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    • pp.56-76
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    • 2001
  • The main purpose of this study is to analyse the digital divide and th determinants of ICT diffusion rate in Korean industries. We estimate the ICT diffusion function using the pooling data for this analysis. The results are as follows. First, the ICT capital accumulated in machinery & equipment, electrical machinery and construction industry is estimated to be 83% of total In capital stock in the 90s. Second, using the panel analysis, we find positive correlation among ICT diffusion, network effect and accumulation of human capital, which is more prominent in the service sector. Third, the estimation results show that the additional 1% increase of human capital accumulation will allow to increase the 0.69% of ICT capital intensity in Korean industries.

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Estimation of a Transport and Distribution of COD using Eco-hydrodynamic Model in Jinhae Bay (생태계 모델을 이용한 진해만의 COD의 거동과 분포특성 평가)

  • Hong, Sok-Jin;Lee, Won-Chan;Jung, Rae-Hong;Park, Sung-Eun;Jang, Ju-Hyung;Kim, Hyung-Chul;Kim, Dong-Myung
    • Journal of Environmental Science International
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    • v.16 no.12
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    • pp.1369-1382
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    • 2007
  • To find proper water quality management strategy for oxygen consumption organic matters in Jinhae bay, the physical process and net supply/decomposition in terms of COD was estimated by three-dimensional eco-hydrodynamic modeling. The estimation results of physical process in terms of COD showed that transportation of COD was dominant in loading area from land to sea, while accumulation of COD was dominant in $middle{\sim}bottom$ level. In case of surface level, the net supply rate of COD was $0{\sim}60\;mg/m^2/day$. The net decomposition rate of COD was $0{\sim}-0.05\;mg/m^2/day$($-5{\sim}-10$ m, in depth) to 2 level, and $-0.05{\sim}-0.20\;mg/m^2/day(10m{\sim})$ to bottom level. These results indicate that the biological decomposition and physical accumulation of COD are occurred for the most part of Jinhae Bay bottom. The variation of net supply or net decomposition rate of COD as reducing land based input loading is also remarkable. Therefore, it is important to consider both allochthonous and autochthonous oxygen demanding organic matters to improve the water quality of Jinhae Bay.

Enhanced Coulomb Counting Method for State-of-Charge Estimation of Lithium-ion Batteries based on Peukert's Law and Coulombic Efficiency

  • Xie, Jiale;Ma, Jiachen;Bai, Kun
    • Journal of Power Electronics
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    • v.18 no.3
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    • pp.910-922
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    • 2018
  • Conventional battery state-of-charge (SoC) estimation methods either involve sophisticated models or consume considerable computational resource. This study constructs an enhanced coulomb counting method (Ah method) for the SoC estimation of lithium-ion batteries (LiBs) by expanding the Peukert equation for the discharging process and incorporating the Coulombic efficiency for the charging process. Both the rate- and temperature-dependence of battery capacity are encompassed. An SoC mapping approach is also devised for initial SoC determination and Ah method correction. The charge counting performance at different sampling frequencies is analyzed experimentally and theoretically. To achieve a favorable compromise between sampling frequency and accumulation accuracy, a frequency-adjustable current sampling solution is developed. Experiments under the augmented urban dynamometer driving schedule cycles at different temperatures are conducted on two LiBs of different chemistries. Results verify the effectiveness and generalization ability of the proposed SoC estimation method.

Estimation of Concrete Strength Based on Artificial Intelligence Techniques (인공지능 기법에 의한 콘크리트 강도 추정)

  • 김세동;신동환;이영석;노승용;김성환
    • The Journal of the Acoustical Society of Korea
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    • v.18 no.7
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    • pp.101-111
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    • 1999
  • This paper presents concrete pattern recognition method to identify the strength of concrete by evidence accumulation with multiple parameters based on artificial intelligence techniques. At first, variance(VAR), zero-crossing(ZCR), mean frequency(MEANF), and autoregressive model coefficient(ARC) and linear cepstrum coefficient(LCC) are extracted as feature parameters from ultrasonic signal of concrete. Pattern recognition is carried out through the evidence accumulation procedure using distance measured with reference parameters. A fuzzy mapping function is designed to transform the distances for the application of the evidence accumulation method. Results(92% successful pattern recognition rate) are presented to support the feasibility of the suggested approach for concrete pattern recognition.

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Effectiveness of Sensitivity Analysis for Parameter Selection in CLIMEX Modeling of Metcalfa pruinosa Distribution

  • Byeon, Dae-hyeon;Jung, Sunghoon;Mo, Changyeun;Lee, Wang-Hee
    • Journal of Biosystems Engineering
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    • v.43 no.4
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    • pp.410-419
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    • 2018
  • Purpose: CLIMEX, a species distribution modeling tool, includes various types of parameters representing climatic conditions; the estimation of these parameters directly determines the model accuracy. In this study, we investigated the sensitivity of parameters for the climatic suitability calculated by CLIMEX for Metcalfa pruinosa in South Korea. Methods: We first changed 12 parameters and identified the three significant parameters that considerably affected the CLIMEX simulation response. Results: The result indicated that the simulation was highly sensitive to changes in lower optimal temperatures, lower soil moisture thresholds, and cold stress accumulation rate based on the sensitivity index, suggesting that these were the fundamental parameters to be used for fitting the simulation into the actual distribution. Conclusion: Sensitivity analysis is effective for estimating parameter values, and selecting the most important parameters for improving model accuracy.

Estimating excess post-exercise oxygen consumption using multiple linear regression in healthy Korean adults: a pilot study

  • Jung, Won-Sang;Park, Hun-Young;Kim, Sung-Woo;Kim, Jisu;Hwang, Hyejung;Lim, Kiwon
    • Korean Journal of Exercise Nutrition
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    • v.25 no.1
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    • pp.35-41
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    • 2021
  • [Purpose] This pilot study aimed to develop a regression model to estimate the excess post-exercise oxygen consumption (EPOC) of Korean adults using various easy-to-measure dependent variables. [Methods] The EPOC and dependent variables for its estimation (e.g., sex, age, height, weight, body mass index, fat-free mass [FFM], fat mass, % body fat, and heart rate_sum [HR_sum]) were measured in 75 healthy adults (31 males, 44 females). Statistical analysis was performed to develop an EPOC estimation regression model using the stepwise regression method. [Results] We confirmed that FFM and HR_sum were important variables in the EPOC regression models of various exercise types. The explanatory power and standard errors of estimates (SEE) for EPOC of each exercise type were as follows: the continuous exercise (CEx) regression model was 86.3% (R2) and 85.9% (adjusted R2), and the mean SEE was 11.73 kcal, interval exercise (IEx) regression model was 83.1% (R2) and 82.6% (adjusted R2), while the mean SEE was 13.68 kcal, and the accumulation of short-duration exercise (AEx) regression models was 91.3% (R2) and 91.0% (adjusted R2), while the mean SEE was 27.71 kcal. There was no significant difference between the measured EPOC using a metabolic gas analyzer and the predicted EPOC for each exercise type. [Conclusion] This pilot study developed a regression model to estimate EPOC in healthy Korean adults. The regression model was as follows: CEx = -37.128 + 1.003 × (FFM) + 0.016 × (HR_sum), IEx = -49.265 + 1.442 × (FFM) + 0.013 × (HR_sum), and AEx = -100.942 + 2.209 × (FFM) + 0.020 × (HR_sum).

A Study on Spatial Aggregation Method for Path Travel Time Estimation using Hi-Pass DSRC System (하이패스 DSRC 기반의 경로통행시간 산정을 위한 공간적 집계방안 산정에 관한 연구)

  • Lee, Hwanpil;Shim, Sangwoo;Choi, Yuntaek;Kim, Dongin
    • International Journal of Highway Engineering
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    • v.16 no.3
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    • pp.119-129
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    • 2014
  • PURPOSES : This investigational survey is to observe a proper spatial aggregation method for path travel time estimation using the hi-pass DSRC system. METHODS : The links which connect the nodes of section detectors location are used for path travel time estimation traditionally. It makes some problem such as increasing accumulation errors and processing times. In this background, the new links composition methods for spatial aggregation are considered by using some types of nodes as IC, JC, RSE combination. Path travel times estimated by new aggregation methods are compared with PBM travel times by MAE, MAPE and statistical hypothesis tests. RESULTS : The results of minimum sample size and missing rate for 5 minutes aggregation interval are satisfied except for JC link path travel time in Seoul TG~Kuemho JC. Thus, it was additionally observed for minimum sample size satisfaction. In 15, 30 minutes and 1 hour aggregation intervals, all conditions are satisfied by the minimum sample size criteria. For accuracy test and statistical hypothesis test, it has been proved that RSE, Conzone, IC, JC links have equivalent errors and statistical characteristics. CONCLUSIONS : There are some errors between the PBM and the LBM methods that come from dropping vehicles by rest areas. Consequently, this survey result means each of links compositions are available for the estimation of path travel time when PBM vehicles are missed.

The Adjustment of Radar Precipitation Estimation Based on the Kriging Method (크리깅 방법을 기반으로 한 레이더 강우강도 오차 조정)

  • Kim, Kwang-Ho;Kim, Min-seong;Lee, Gyu-Won;Kang, Dong-Hwan;Kwon, Byung-Hyuk
    • Journal of the Korean earth science society
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    • v.34 no.1
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    • pp.13-27
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    • 2013
  • Quantitative precipitation estimation (QPE) is one of the most important elements in meteorological and hydrological applications. In this study, we adjusted the QPE from an S-band weather radar based on co-kriging method using the geostatistical structure function of error distribution of radar rainrate. In order to estimate the accurate quantitative precipitation, the error of radar rainrate which is a primary variable of co-kriging was determined by the difference of rain rates from rain gauge and radar. Also, the gauge rainfield, a secondary variable of co-kriging is derived from the ordinary kriging based on raingauge network. The error distribution of radar rain rate was produced by co-kriging with the derived theoretical variogram determined by experimental variogram. The error of radar rain rate was then applied to the radar estimated precipitation field. Locally heavy rainfall case during 6-7 July 2009 is chosen to verify this study. Correlation between adjusted one-hour radar rainfall accumulation and rain gauge rainfall accumulation improved from 0.55 to 0.84 when compared to prior adjustment of radar error with the adjustment of root mean square error from 7.45 to 3.93 mm.