• Title/Summary/Keyword: Mean Power

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Estimation of wind power generation of micro wind turbine on the roof of high rise buildings in urban area (도심 고층건물 지붕에서의 소형 풍력발전기 발전량 예측)

  • Choi, Hyung-Sik;Chang, Ho-Nam
    • New & Renewable Energy
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    • v.5 no.4
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    • pp.21-27
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    • 2009
  • Potential yield of micro wind turbine on the roof of urban high rise buildings is estimated. Urban wind profile is modeled as logarithmic profile above the mean building height with roughness length 0.8, displacement 7.5 m. Mean wind velocity from the meteorological agency data at the hight of 50m is used. Wind velocity changes are simulated on the rectangular roof of 26, 45, 53 degree pitch and the circular roof by computational fluid dynamics and RNG k-$\varepsilon$ turbulence models. Wind velocity increased approximately by a factor of the order of 270 % on the 26 degree pitched roof. In the 100 m and 200 m high buildings, wind enhancement is greater at the front side than at the center of the building. In the building arrangement model wind velocity changes abruptly and it becomes wind gusts. When commercial wind turbines are installed on the building roof, average power and annual power generation enhanced by 3~4 times than normal wind velocity at 50m and 6 kw wind turbine can generate 1053 kwh per month on the 26 degree pitched roof at 50m height and sufficiently supply electrical power with 15 household for common electrical use and food waste disposer. However, power output will vary significantly by the wind conditions in the order of $\pm$ 20 %.

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Decomposition Analysis of CO2 Emissions of the Electricity Generation Sector in Korea using a Logarithmic Mean Divisia Index Method (전력산업의 온실가스 배출요인 분석 및 감축 방안 연구)

  • Cho, Yongsung
    • Journal of Climate Change Research
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    • v.8 no.4
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    • pp.357-367
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    • 2017
  • Electricity generation in Korea mainly depends on thermal power and nuclear power. Especially the coal power has led to the increase in $CO_2$ emissions. This paper intends to analyze the current status of $CO_2$ emissions from electricity generation in Korea during the period 1990~2016, and apply the logarithmic mean Divisia index (LMDI) technique to find the nature of the factors influencing the changes in $CO_2$ emissions. The main results as follows: first, $CO_2$ emission from electricity generation has increased by $165.9MtCO_2$ during the period of analysis. Coal products is the main fuel type for thermal power generation, which accounts about 73% $CO_2$ emissions from electricity generation. Secondly, the increase of real GDP is the most important contributor to increase $CO_2$ emissions from electricity generation. The carbon intensity and the electricity intensity also affected the increase in $CO_2$ emission, but the energy intensity effect and the dependency of thermal power effect play the dominant role in decreasing $CO_2$ emissions.

Statistical Convergence Properties of an Adaptive Normalized LMS Algorithm with Gaussian Signals (가우시안 신호를 갖는 적응 정규화 LMS 앨고리듬의 통계학적 수렴 성질)

  • Sung Ho CHO;Iickho SONG;Kwang Ho PARK
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.16 no.12
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    • pp.1274-1285
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    • 1991
  • This paper presents a statistical convergence analysis of the normalized least mean square(NLMS)algorithm that employs a single-pole lowpass filter, In this algorithm the lowpass filter is used to adjust its output towards the estimated value of the input signal power recursively. The estimated input signal power so obtained at each time is then used to normalize the convergence parameter. Under the assumption that the primary and reference inputs to the adaptive filter are zero mean wide sense stationary, and Gaussian random processes, and further making use of the independence assumption. we derive expressions that characterize the mean and maen squared behavior of the filter coefficients as well as the mean squared estimation error. Conditions for the mean and mean squared convergence are explored. Comparisons are also made between the performance of the NLMS algorithm and that of the popular least mean square(LMS) algorithm Finally, experimental results that show very good agreement between the analytical and emprincal results are presented.

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Tests for Mean Change with the Modified Cusum Statistics

  • Kim, Jae-Hee;Kim, Na-Yeon
    • Journal of the Korean Data and Information Science Society
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    • v.14 no.2
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    • pp.187-199
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    • 2003
  • We deal with the problem of testing a sequence of independent normal random variables with constant, known or unknown, variance for no change in mean versus alternatives with a single change-point. Various tests based on the likelihood ratio and recursive residuals, score statistics and cusums are studied. Proposed tests are modified version of Buckley's cusum statistics. A comparison study of various change-point test statistics is done by Monte Carlo simulation with S-plus software.

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ON THE GENERAL QUADRATIC GAUSS SUMS WEIGHTED BY CHARACTER SUMS OVER A SHORT INTERVAL

  • Zhang, Tianping
    • Bulletin of the Korean Mathematical Society
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    • v.50 no.3
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    • pp.873-883
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    • 2013
  • By using the analytic methods, the mean value of the general quadratic Gauss sums weighted by the first power mean of character sums over a short interval is investigated. Several sharp asymptotic formulae are obtained, which show that these sums enjoy good distributive properties. Moreover, interesting connections among them are established.

A New Convergence Behavior of the Least Mean Fourth Adaptive Algorithm for a Multiple Sinusoidal Input

  • Lee, Kang-Seung
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.26 no.12A
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    • pp.2043-2049
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    • 2001
  • In this paper we study the convergence behavior of the least mean fourth(LMF) algorithm where the error raised to the power of four is minimized for a multiple sinusoidal input and Gaussian measurement noise. Here we newly obtain the convergence equation for the sum of the mean of the squared weight errors, which indicates that the transient behavior can differ depending on the relative sizes of the Gaussian noise and the convergence constant. It should be noted that no similar results can be expected from the previous analysis by Walach add Widrow.

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On the Robustness of Chi-square Test Procedure for a Compounded Multivariate Normal Mean

  • Kim, Hea-Jung
    • Communications for Statistical Applications and Methods
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    • v.2 no.2
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    • pp.330-335
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    • 1995
  • The rebustness of one sample Chi-square test for multivariate normal mean vector is investigated when the multivariate normal population is mixed with another multivariate normal population with differing in the mean vector. Explicit expressions for the level of significance and power of the test are derived. Some numerical results indicate that the Chi-square test procedure is quite robust against slight mixtures of multivariate normal populations differing in location parameters.

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A New Result on the Convergence Behavior of the Least Mean Fourth Algorithm for a Multiple Sinusoidal Input

  • Lee, Kang-Seung
    • The Journal of the Acoustical Society of Korea
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    • v.18 no.2E
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    • pp.3-9
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    • 1999
  • In this paper we study the convergence behavior of the least mean fourth(LMF) algorithm where the error raised to the power of four is minimized for a multiple sinusoidal input and Gaussian measurement noise. Here we newly obtain the convergence equation for the sum of the mean of the squared weight errors, which indicates that the transient behavior can differ depending on the relative sizes of the Gaussian noise and the convergence constant. It should be noted that no similar results can be expected from the previous analysis by Walach and Widrow/sup [1]/.

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Test and Estimation for Exponential Mean Change

  • Kim, Jae-Hee
    • Communications for Statistical Applications and Methods
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    • v.15 no.3
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    • pp.421-427
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    • 2008
  • This paper deals with the problem of testing for the existence of change in mean and estimating the change-point when the data are from the exponential distributions. The likelihood ratio test statistic and Gombay and Horvath (1990) test statistic are compared in a power study when there exists one change-point in the exponential means. Also the change-point estimator using the likelihood ratio and the change-point estimators based on Gombay and Horvath (1990) statistic are compared for their detecting capability via simulation.

Predicting Successful Defibrillation in Ventricular Fibrillation using Wave Analysis and Neuro-fuzzy

  • Shin Jae-Woo;Lee Hyun-Sook;Hwang Sung-Oh;Yoon Young-Ro
    • Journal of Biomedical Engineering Research
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    • v.27 no.2
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    • pp.47-52
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    • 2006
  • The purpose of this study was to predict successful defibrillation in ventricular fibrillation using parameters extracted by wave analysis method and neuro-fuzzy. Total 15 dogs were tested for predicting successful defibrillation. Feature parameters were extracted for return of spontaneous circulation (ROSC) and non-ROSC by wave analysis method, and these parameters are an irregularity factor, spectral moments, mean power of level-crossing spectrum, and mean of alpha-significant value. Additionally, two parameters by analyzing method of frequency were extracted into a mean of power spectrum and a mean frequency. Then extracted parameters were analyzed in which parameters result to have high performance of discriminating ROSC and non-ROSC by a statistical method of t-test. The average of sensitivity and specificity were 62.5% and 75.0%, respectively. The average of positive predictive factor and negative predictive factor were 61.2% and 75.8%, respectively.