• 제목/요약/키워드: Change rate

검색결과 9,374건 처리시간 0.041초

Estimation of Channel States for Adaptive Code Rate Change in DS-SSMA Communication Systems: Part 2. Estimation of Fading Environment

  • Youngkwon Ryn;Iickho Song;Kim, Kwang-Soon;Jinsoo Bae
    • Journal of Electrical Engineering and information Science
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    • 제1권1호
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    • pp.23-28
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    • 1996
  • In this series of two papers, adaptive code rate change schemes in DS-SSMA systems are proposed. In the proposed schemes the error correcting code rate is changed according to the channel states. Two channel states having significant effects on the bit error probability are considered: one is the effective number of users considered in Part 1, and the other is the fading environment considered in Part 2. These channel states are estimated based on retransmission requests. The criterion for the change of the code rate is to maximize the throughput under given error bound. Simulation results show that we can transmit maximum amount of information if we change the code rate based on the channel states.

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적혈구 침강속도에 대한 Westergren tube 각도, 온도 및 NaCl 농도가 미치는 영향 (The effect of Westergren tube angle, temperature and osmobility with the different percent of NaCl solution on erythrocyte sedimentation rate)

  • 김도균;김영홍;유창준
    • 대한수의학회지
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    • 제36권1호
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    • pp.75-82
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    • 1996
  • Erythrocyte sedimentation rate is influenced by plasma protein, red cell itself and physiological conditions and it is clear that the measurement of erythrocyte sedimentation rate varies with technique and various environmental factors. The effect of temperature, angle of test tube, and osmobility with different percent of NaCl solution on erythrocyte sedimentation rate on sheep was determined by modified Westergren method. In sheep, as the angle of Westergren tube was decreased from $90^{\circ}$ to $45^{\circ}$, erythrocyte sedimentation rate was increased in both diluted plasma and NaCl solutions. As temperature was increased from $4^{\circ}C$ to $20^{\circ}C$ at $45^{\circ}$ angle. erythrocyte sedimentation rate was increased. In ruminants, this modified Westergren methods, erythrocyte 1 : plasma 9 instead of erythrocyte 4 : plasma 6(whole blood), enable them to have meanings as dog therefor, using this method, clinical can determine the erythrocyte sedimentation rate of ruminants for diagnosis. Because erythrocyte sedimentation rate was changed according to the angle of Westergren tube, temperature as erythrocyte diluted with NaCl, this study detected that the change of temperature, the angle of Westergren tube could change erythrocyte sedimentation rate by effecting red cell itself. The increase of osmobility owing to change of NaCl percent resulted in the decrease of rapid erythrocyte sedimentation rate. So this fact indicate that deformibility and the change of red cell volume have meaning in the change of erythrocyte sedimentation rate.

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일별 환율데이터에 대한 시계열 모형 적합 및 비교분석 (Time Series Models for Daily Exchange Rate Data)

  • 김보미;김재희
    • 응용통계연구
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    • 제26권1호
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    • pp.1-14
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    • 2013
  • 미국 달러에 대한 한국원화의 17년간 일별 원/달러 환율 시계열 데이터에 대하여 정상 시계열 ARIMA 모형과 변동성을 포함한 시계열 모형인 ARIMA+IGARCH 모형을 적합하여 비교하고 예측을 실시하였다. 또한 환율 데이터에 구조변화가 있어 보이므로 선형구조를 포함한 구조 변화 모형과 자기상관 구조를 포함한 구조 변화 모형을 이용하여 변화점을 추정하고자 한다.

Using Classification function to integrate Discriminant Analysis, Logistic Regression and Backpropagation Neural Networks for Interest Rates Forecasting

  • Oh, Kyong-Joo;Ingoo Han
    • 한국지능정보시스템학회:학술대회논문집
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    • 한국지능정보시스템학회 2000년도 추계정기학술대회:지능형기술과 CRM
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    • pp.417-426
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    • 2000
  • This study suggests integrated neural network models for Interest rate forecasting using change-point detection, classifiers, and classification functions based on structural change. The proposed model is composed of three phases with tee-staged learning. The first phase is to detect successive and appropriate structural changes in interest rare dataset. The second phase is to forecast change-point group with classifiers (discriminant analysis, logistic regression, and backpropagation neural networks) and their. combined classification functions. The fecal phase is to forecast the interest rate with backpropagation neural networks. We propose some classification functions to overcome the problems of two-staged learning that cannot measure the performance of the first learning. Subsequently, we compare the structured models with a neural network model alone and, in addition, determine which of classifiers and classification functions can perform better. This article then examines the predictability of the proposed classification functions for interest rate forecasting using structural change.

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Long-term Sediment Discharge Analysis in Yongdam Dam Watershed due to Climate Change

  • Felix, Micah Lourdes;Kim, Joocheol;Choi, Mikyoung;Jung, Kwansue
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2020년도 학술발표회
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    • pp.327-327
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    • 2020
  • Increase in Earth's surface temperature, higher rainfall intensity rate, and rapid changes in land cover are just some of the most evident effects of climate change. Flooding, and river sedimentation are two inevitable natural processes in our environment, and both issues poses great risks in the dam industry when not addressed properly. River sedimentation is a significant issue that causes reservoir deposition, and thus causes the dam to gradually lose its ability to store water. In this study, the long-term effects of climate change on the sediment discharge in Yongdam Dam watershed is analyzed through the utilization of SWAT, a semi-distributed watershed model. Based from the results of this study, an abrupt increase on the annual sediment inflow trend in Yongdam Dam watershed was observed; which may suggests that due to the effects of climate change, higher rainfall intensity, land use and land cover changes, the sedimentation rate also increased. An efficient sedimentation management should consider the increasing trend in sedimentation rate due to the effects of climate change.

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실질금리 결정모형에서의 구조변화분석 (Structural Change Analysis in a Real Interest Rate Model)

  • 전덕빈;박대근
    • 경영과학
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    • 제18권1호
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    • pp.119-133
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    • 2001
  • It is important to find the equilibrium level of real interest rate for it affects real and financial sector of economy. However, it is difficult to find the equilibrium level because like the most macroeconomic model the real interest model has parameter instability problem caused by structural change and it is supported by various theories and definitions. Hence, in order to cover these problems structural change detection model of real interest rate is developed to combine the real interest rate equilibrium model and the procedure to detect structural change points. 3 equations are established to find various effects of other interest-related macroeconomic variables and from each equation, structural changes are found. Those structural change points are consistent with common expectation. Oil Crisis (December, 1987), the starting point of Economic Stabilization Policy (January, 1982), the starting point of capital liberalization (January, 1988), the starting and finishing points of Interest deregulation (January, 1992 and December, 1994), Foreign Exchange Crisis (December, 1977) are detected as important points. From the equation of fisher and real effects, real interest rate level is estimated as 4.09% (October, 1988) and dependent on the underlying model, it is estimated as 0%∼13.56% (October, 1988), so it varies so much. It is expected that this result is connected to the large scale simultaneous equations to detect the parameter instability in real time, so induces the flexible economic policies.

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VAR 모형을 이용한 크기별 완도 전복가격의 선도가격 분석 (A Leading-price Analysis of Wando Abalone Producer Prices by Shell Size Using VAR Model)

  • 남종오;심성현
    • Ocean and Polar Research
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    • 제36권4호
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    • pp.327-341
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    • 2014
  • This study aims to analyze causality among Wando abalone producer prices by size using a vector autoregressive model to expiscate the leading-price of Wando abalone in various price classes by size per kg. This study, using an analytical approach, applies a unit-root test for stability of data, a Granger causality test to learn about interaction among price classes by size for Wando abalone, and a vector autoregressive model to estimate the statistical impact among t-1 variables used in the model. As a result of our leading-price analysis of Wando abalone producer prices by shell size using a VAR model, first, DF, PP, and KPSS tests showed that the Wando abalone monthly price change rate by size differentiated by logarithm were stable. Second, the Granger causality relationship analysis showed that the price change rate for big size abalone weakly led the price change rate for the small and medium sizes of abalone. Third, the vector autoregressive model showed that three price change rates of t-1 period variables statistically, significantly impacted price change rates of own size and other sizes in t period. Fourth, the impulse response analysis indicated that the impulse responses of structural shocks for price change rate for big size abalone was relatively more powerful in its own size and in other sizes than shocks emanating from other sizes. Fifth, the variance decomposition analysis indicated that the price change rate for big size abalone was relatively more influential than the price change rates for medium and small size abalone.

기업 크기에 따른 재고자산회전 변화율의 차이 (The Difference of the Inventories Assets Turnover Change Ratio According to the Firm Size)

  • 이지혜;최영근;김판수
    • 산업경영시스템학회지
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    • 제38권2호
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    • pp.72-81
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    • 2015
  • This paper studied the differences of the inventories asset turnover change ratio and several characteristics variable between large and small manufacturing firm group. Large and small firm group were determined based on number of labors and asset size. Several characteristics variable of firms such as assets size, sales growth rate, return on assets, leverage ratio, credit rating and age of firm were used to find out the differences of firm group. As a result, the inventory asset turnover change ratio of large firm was 5.16% and that of the middle and small firm was 9.3%. For the large firm, sales growth rate, ROA and credit rating affect inventory assets turnover change ratio. For the middle and small sized firm, Assets size, sales growth rate and credit rating affect inventory assets turnover change ratio. Using this result, we can say that manufacturing company need to consider their firm size and their characteristics to make their own operation strategy of inventory.

제왕절개 분만율 공표 후 요양기관의 분만행태 변화 (Provider's Behavior Change after the Public Release of the Information on the Cesarean Section Rate)

  • 고수경;신순애;김기영;김창엽
    • 보건행정학회지
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    • 제11권3호
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    • pp.121-150
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    • 2001
  • This study was conducted to investigate provider's behavior change after releasing the information on the Cesarean section rate. Claims data filed at the National Health Insurance Corporation was used for this analysis and the focus of this study was the change of cesarean rate after the public disclosure of information. Average rates of the year 1999 and 2000 were compared, on the institutional basis, and range and coefficient of variation were estimated. For the last decade, Cesarean section rate has been increased dramatically. Clinical or demographic factors could not adequately explain the increase. Instead, nonclinical factors, such as financial incentive, physician's convenience, practice characteristics, etc., were more significant in explaining the increasing rate. Providers' behavior was significantly affected by the public release of information: after the release, average rate was decreased by 10.2%, and variations were also decreased. In particular, the extent of decrease was explained mainly by nonclinical factor rather than clinical ones. The results suggest that disseminating practice information to providers and consumers could contribute to reducing unnecessary medical service.

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Bayesian Analysis for Multiple Change-point hazard Rate Models

  • Jeong, Kwangmo
    • Communications for Statistical Applications and Methods
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    • 제6권3호
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    • pp.801-812
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    • 1999
  • Change-point hazard rate models arise for example in applying "burn-in" techniques to screen defective items and in studing times until undesirable side effects occur in clinical trials. Sometimes in screening defectives it might be sensible to model two stages of burn-in. In a clinical trial there might be an initial hazard rate for a side effect which after a period of time changes to an intermediate hazard rate before settling into a long term hazard rate. In this paper we consider the multiple change points hazard rate model. The classical approach's asymptotics can be poor for the small to all moderate sample sizes often encountered in practice. We propose a Bayesian approach avoiding asymptotics to provide more reliable inference conditional only upon the data actually observed. The Bayesian models can be fitted using simulation methods. Model comparison is made using recently developed Bayesian model selection criteria. The above methodology is applied to a generated data and to a generated data and the Lawless(1982) failure times of electrical insulation.

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