• 제목/요약/키워드: Standard estimating

검색결과 614건 처리시간 0.025초

자유공간 전송방법을 이용한 마이크로파 유전특성연구 (Determination of Microwave Dielectric Properties of Grain by Free Space Transmission Method)

  • 김종헌;김기복;노상하
    • 한국전기전자재료학회:학술대회논문집
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    • 한국전기전자재료학회 1997년도 춘계학술대회 논문집
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    • pp.233-235
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    • 1997
  • A free sparse transmission method using X-band standard gain horn antenna is applied to measure the attenuation and phase shift of microwave signal through the wetted grain such as rough rice, brown rice and barley. The moisture content of grain varied from 11 to 25% based on its wetted condition. The dielectric constant and loss factor, which depend on the moisture content of the wetted grain are obtained from the measured attenuation and phase shift by vector network analyzer. The measured values of dielectric constants as a function of moisture density are compared with values of those obtained using the predicted model for estimating dielectric constants of grain.

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Performance-Based Seismic Design of Reinforced Concrete Building Structures Using Inelastic Displacements Criteria

  • Kabeyaswa, Toshimi
    • 한국지진공학회논문집
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    • 제2권3호
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    • pp.61-71
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    • 1998
  • A performance-based seismic design method for reinforced concrete building structures being developed in Japan is outlined. Technical and scientific background of the performance-based design philosophy as well as recently developed seismic design guidelines are is presented, in which maximum displacement response to design earthquake motion is used as the limit-state design criteria. A method of estimating dynamic response displacement of the structures based on static nonlinear analysis is described. A theoretical estimation of nonlinear dynamic response considering the characteristics of energy input to the system is described in detail, which may be used as the standard method in the new performance-based code. A desing philosophy not only satisfying the criteria but also evaluating seismic capacity of the structures is also introduced.

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최적 열원용량 산정을 위한 모델건물 공조부하 시뮬레이션 분석 (Thermal Load Simulation Analysis on Model Building Estimating Optimum Heat Source Capacity)

  • 박종일;김세환;이성
    • 설비공학논문집
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    • 제19권6호
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    • pp.427-433
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    • 2007
  • Generally, H.V.A.C load capacity in early planning phase can presume with maximum thermal load. Basic data can prove by air conditioning equipment system data analysis at existing building. There are poor and not reliable alternative presentation. In this paper, measured data after use H.V.A.C load calculation K-load program reply choosing standard building and variables simulation. And I founded peak load correlation graph and mode for several kinds of variable and contents of size. I wish that equipment designer is beaconed to produce optimum capacity at building as quantitative through this result.

Adaptive Q-Algorithm for Multiple Tag Identification in EPCglobal Gen-2 RFID System

  • Lim, In-Taek
    • Journal of information and communication convergence engineering
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    • 제8권3호
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    • pp.307-311
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    • 2010
  • EPCglobal Class-1 Gen-2 protocol has been proposed for UHF-band RFID systems. In Gen-2 standard, Q-algorithm was proposed to select a frame size for the next query round without estimating the number of tags. Therefore, the Q-algorithm has advantage that the reader's algorithm is simpler than other algorithms. However, it is impossible to allocate the optimized frame size. Also, the original Q-algorithm did not define an optimized parameter C for adjusting the frame size. In this paper, we propose an adaptive Q-algorithm with the different parameter $C_c$ and $C_i$ in accordance with the status of reply slot. Simulation results show that the proposed adaptive Q-algorithm outperforms the original Gen-2 Q-algorithm.

데이터 기초의 공분산 행렬로 구성된 EV 방법으로부터 다중 정현파의 주파수 추정에 관한 통계적 분석 (Statistical Analysis on Frequency Estimation of Multiple Sinusoids from EV with a Data based Covariance Matrix)

  • 안태천;탁현수;최병윤
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1992년도 하계학술대회 논문집 A
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    • pp.453-456
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    • 1992
  • A Data-based Covariance Matrix(DCM) is introduced in the Eigenvector(EV) method, among subspace methods of estimating multiple sinusoidal frequencies from finite white noisy measurements. It is shown that the EV with the DCM can obtain the true. frequencies from finite noiseless data Some asymptotic results and further improvement on the DCM are also presented mathematically. Monte-carlo simulations are statistically conducted from the view-points of means and standard deviations in the EV's of DCM and Conventional Covariance Matrix(CCM). Simulations show a great promise for using the DCM, particularly for the cases of short data records, closely spaced frequencies and high signal-to-noise ratios.

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Study on the Effects of Single Fiber Tensile Properties on Bundle Tensile Properties through Estimation of HVI Bundle Modulus and Toughness

  • Koo, Hyun-Jin;Jeong, Sung Hoon;Suh, Moon W.
    • Fibers and Polymers
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    • 제2권1호
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    • pp.144-147
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    • 2001
  • The HVI properites and Mantis single fiber tensile properties were analyzed to evaluate the relationship between fiber and bundle tensile properties. For this study, a new method has been developed for estimating the modulus and toughness of cotton fiber bundles directly from the HVI tenacity-elongation curves. The single fiber tensile properties were shown to be translated well into the bundle tensile properties. The single fiber breaking elongation was found to be the most significant contributing factor to bundle tensile properties. The bundle breaking elongation and toughness were shown to increase as the single fiber breaking elongation increased. The bundle modulus increased as the single fiber breaking elongation and/or standard deviation of single fiber breaking elongation decreased.

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SLAM 기술의 과거와 현재 (Past and State-of-the-Art SLAM Technologies)

  • 송재복;황서연
    • 제어로봇시스템학회논문지
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    • 제20권3호
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    • pp.372-379
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    • 2014
  • This paper surveys past and state-of-the-art SLAM technologies. The standard methods for solving the SLAM problem are the Kalman filter, particle filter, graph, and bundle adjustment-based methods. Kalman filters such as EKF (Extended Kalman Filter) and UKF (Unscented Kalman Filter) have provided successful results for estimating the state of nonlinear systems and integrating various sensor information. However, traditional EKF-based methods suffer from the increase of computation burden as the number of features increases. To cope with this problem, particle filter-based SLAM approaches such as FastSLAM have been widely used. While particle filter-based methods can deal with a large number of features, the computation time still increases as the map grows. Graph-based SLAM methods have recently received considerable attention, and they can provide successful real-time SLAM results in large urban environments.

효율적 방재시설을 위한 정량적 위험도 분석 (An effective prevention facilities for railway tunnel design by using Quantitative Risk Analysis)

  • 권순섭;신화철;정지승;민대홍
    • 한국철도학회:학술대회논문집
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    • 한국철도학회 2007년도 춘계학술대회 논문집
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    • pp.1080-1084
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    • 2007
  • Recently, as demands of new railway and the relocation of existing line, a number of tunnel structures have been constructed. Tunnel structures contribute to minimize the cost and time of transport, but in case of railway fire accident bring serious damages of human life caused by narrowness of shelter, smoke and high temperature, difficulty in rescue. For that reason, at the beginning of plan of tunnel, the optimum design of safety facility in tunnel for minimizing the risks and satisfying the safety standard is needed. In this study, QRA(Quantitative Risk Analysis) technique is applied to design of railway tunnel for assuring the safety function and estimating the risk of safety. The case study is carried out to verify the QRA technique for railway tunnels in Iksan-Sili.

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Leave-one-out Bayesian model averaging for probabilistic ensemble forecasting

  • Kim, Yongdai;Kim, Woosung;Ohn, Ilsang;Kim, Young-Oh
    • Communications for Statistical Applications and Methods
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    • 제24권1호
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    • pp.67-80
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    • 2017
  • Over the last few decades, ensemble forecasts based on global climate models have become an important part of climate forecast due to the ability to reduce uncertainty in prediction. Moreover in ensemble forecast, assessing the prediction uncertainty is as important as estimating the optimal weights, and this is achieved through a probabilistic forecast which is based on the predictive distribution of future climate. The Bayesian model averaging has received much attention as a tool of probabilistic forecasting due to its simplicity and superior prediction. In this paper, we propose a new Bayesian model averaging method for probabilistic ensemble forecasting. The proposed method combines a deterministic ensemble forecast based on a multivariate regression approach with Bayesian model averaging. We demonstrate that the proposed method is better in prediction than the standard Bayesian model averaging approach by analyzing monthly average precipitations and temperatures for ten cities in Korea.

Chaos and Correlation Dimension

  • Kim, Hung-Soo
    • 한국수자원학회논문집
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    • 제33권S1호
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    • pp.37-47
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    • 2000
  • The method of delays is widely used for reconstruction chaotic attractors from experimental observations. Many studies have used a fixed delay time ${\tau}_d$ as the embedding dimension m is increased, but this is not necessarily the best choice for obtaining good convergence of the correlation dimension. Recently, some researchers have suggested that it is better to fix the delay time window ${\tau}_w$ instead. Unfortunately, ${\tau}_w$ cannot be estimated using either the autocorrelation function or the mutual information, and no standard procedure for estimating ${\tau}_w$ has yet emerged. However, a new technique, called the C-C method, can be used to estimate either ${\tau}_d\;or\;{\tau}_w$. Using this method, we show that, for small data sets, fixing ${\tau}_w$, rather than ${\tau}_d$, does indeed lead to a more rapid convergence of the correlation dimension as the embedding dimension m in increased.

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