• 제목/요약/키워드: log model

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Estimations of the student numbers by nonlinear regression model (비선형 회귀모형을 이용한 학년별 학생수 추계)

  • Yoon, Yong-Hwa;Kim, Jong-Tae
    • Journal of the Korean Data and Information Science Society
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    • v.23 no.1
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    • pp.71-77
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    • 2012
  • This paper introduces the projection methods by nonlinear regression model. To predict the student numbers, a log model and an involution model as the kind of a trend-extrapolation method are used. Empirical evidence shows that a projection by log model is better than by involution model with the confidence interval estimations for the coefficients of determination.

IMM-based INS/EM-Log Integrated Underwater Navigation with Sea Current Estimation Function

  • Cho, Seong Yun;Ju, Hojin;Cha, Jaehyuck;Park, Chan Gook;Yoo, Kijeong;Park, Chanju
    • Journal of Positioning, Navigation, and Timing
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    • v.7 no.3
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    • pp.165-173
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    • 2018
  • Underwater vehicles use Inertial Navigation System (INS) with high-performance Inertial Measurement Unit (IMU) for high precision navigation. However, when underwater navigation is performed for a long time, the INS error gradually diverges, therefore, an integrated navigation method using auxiliary sensors is used to solve this problem. In terms of underwater vehicles, the vertical axis error is primarily compensated through Vertical Channel Damping (VCD) using a depth gauge, and an integrated navigation filter can be designed to perform horizontal axis error and sensor error correction using a speedometer such as Electromagnetic-Log (EM-Log). However, since EM-Log outputs the forward direction relative speed of the vehicle with respect to the sea and sea current, INS correction filter using this may cause a rather large error. Although it is possible to design proper filters if the exact model of the sea current is known, it is impossible to know the accurate model in reality. Therefore, this study proposes an INS/EM-Log integrated navigation filter with the function to estimate sea current using an Interacting Multiple Model (IMM) filters, and the performance of this filter is analyzed through a simulation performed in various environments.

An Econometric Analysis of Imported Softwood Log Markets in South Korea - on the Basis of the Lagged Dependent Variable -

  • Park, Yong Bae;Youn, Yeo-Chang
    • Journal of Korean Society of Forest Science
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    • v.98 no.2
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    • pp.148-155
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    • 2009
  • The objective of this study is to know market structures of softwood logs being imported to South Korea from log producing countries. Import demand of softwood logs imported to South Korea from America, New Zealand and Chile is fixed as a function of log prices, the lagged dependent variable and output. On the basis of the adaptive expectations model, linear regression models that the explanatory variables included and the lagged dependent variable were estimated by Seemingly Unrelated Regression Equations (SURE). The short-run and long-run own price elasticity of America's softwood log import demand is -1.738 and -4.250 respectively. Then long-run elasticity is much higher than short-run elasticity. Short-run and long-run crosselasticity of New Zealand's softwood log import demand with respect to American's softwood log import price are inelastic at 0.505 and 0.883 respectively. Short-run and long-run cross-elasticity of Chile's softwood log import demands with respect to American's softwood log import prices were highly elastic at 2.442 and 4.462 respectively. Long-run elasticity was almost twice as high as short-run elasticity.

Vector Quantization based Speech Recognition Performance Improvement using Maximum Log Likelihood in Gaussian Distribution (가우시안 분포에서 Maximum Log Likelihood를 이용한 벡터 양자화 기반 음성 인식 성능 향상)

  • Chung, Kyungyong;Oh, SangYeob
    • Journal of Digital Convergence
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    • v.16 no.11
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    • pp.335-340
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    • 2018
  • Commercialized speech recognition systems that have an accuracy recognition rates are used a learning model from a type of speaker dependent isolated data. However, it has a problem that shows a decrease in the speech recognition performance according to the quantity of data in noise environments. In this paper, we proposed the vector quantization based speech recognition performance improvement using maximum log likelihood in Gaussian distribution. The proposed method is the best learning model configuration method for increasing the accuracy of speech recognition for similar speech using the vector quantization and Maximum Log Likelihood with speech characteristic extraction method. It is used a method of extracting a speech feature based on the hidden markov model. It can improve the accuracy of inaccurate speech model for speech models been produced at the existing system with the use of the proposed system may constitute a robust model for speech recognition. The proposed method shows the improved recognition accuracy in a speech recognition system.

The Comparative Software Reliability Cost Model of Considering Shape Parameter (형상모수를 고려한 소프트웨어 신뢰성 비용 모형에 관한 비교 연구)

  • Kim, Kyung-Soo;Kim, Hee-Cheul
    • Journal of Digital Convergence
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    • v.12 no.3
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    • pp.219-226
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    • 2014
  • In this study, reliability software cost model considering shape parameter based on life distribution from the process of software product testing was studied. The shape parameter using the Erlang and Log-logistic model that is widely used in the field of reliability problems presented. The software failure model was used finite failure non-homogeneous Poisson process model, the parameters estimation using maximum likelihood estimation was conducted. In comparison result of software cost model based on the Erlang distribution and the log-logistic distribution software cost model, because Erlang model is to predict the optimal release time can be software, but the log-logistic model to predict to optimal release time can not be, Erlang distribution than the log-logistic distribution appears to be effective. In this research, software developers to identify software development cost some extent be able to help is considered.

Target strength estimation by tilt angle and size dependence of rockfish (Sebastes schlegeli) using ex-situ and acoustic scattering model (현수법과 모델을 이용한 조피볼락의 유영자세각과 체장에 따른 음향 후방산란강도)

  • YOON, Euna;KIM, Kiseon;LEE, Intae;JO, Hyeon-Jeong;LEE, Kyounghoon
    • Journal of the Korean Society of Fisheries and Ocean Technology
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    • v.53 no.2
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    • pp.152-159
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    • 2017
  • Rockfish was a commercially important fish specie in marine ranching areas in Korea. To estimate density and biomass of rockfish using acoustic method, target strength (TS) information is required on the species. This study measured TS dependence on tilt angle and size on 14 live rockfish individuals at 38, 70, and, 120 kHz by ex-situ measurement (tethered method) and acoustic scattering model (Krichhoff ray mode, KRM). The swimbladdered angle ranged from 18 to $30^{\circ}$ ($mean{\pm}s.d.=26{\pm}4^{\circ}$). The mean TS for all individuals was highest -35.9 dB of tilt angle $-17^{\circ}$ at 38 kHz, -35.4 dB of tilt angle $-25^{\circ}$ at 70 kHz, and -34.9 dB of tilt angle $-22^{\circ}$ at 120 kHz. The ex-situ TS-total length (TL, cm) relationships were $TS_{38kHz}=20log_{10}(TL)-67.1$, $TS_{70kHz}=20log_{10}(TL)-68.6$, and $TS_{120kHz}=20log_{10}(TL)-69.9$, respectively. The model TS-total length (TL, cm) relationships were $TS_{38kHz}=20log_{10}(TL)-66.4$, $TS_{70kHz}=20log_{10}(TL)-67.0$, $TS_{120kHz}=20log_{10}(TL)-67.0$. The two measurements between the ex-situ TS and KRM model for TS-tilt angle and fish size were found to be significantly correlated.

A study on log-density ratio in logistic regression model for binary data

  • Kahng, Myung-Wook
    • Journal of the Korean Data and Information Science Society
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    • v.22 no.1
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    • pp.107-113
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    • 2011
  • We present methods for studying the log-density ratio, which allow us to select which predictors are needed, and how they should be included in the logistic regression model. Under multivariate normal distributional assumptions, we investigate the form of the log-density ratio as a function of many predictors. The linear, quadratic and crossproduct terms are required in general. If two covariance matrices are equal, then the crossproduct and quadratic terms are not needed. If the variables are uncorrelated, we do not need the crossproduct terms, but we still need the linear and quadratic terms.

Parameter Estimation and Confidence Limits for the Log-Gumbel Distribution (대수(對數)-Gumbel 확률분포함수(確率分布函數)의 매개변수(媒介變數) 추정(推定)과 신뢰한계(信賴限界) 유도(誘導))

  • Heo, Jun Haeng
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.13 no.4
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    • pp.151-161
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    • 1993
  • The log-Gumbel distribution in real space is defined by transforming the conventional log-Gumbel distribution in log space. For this model, the parameter estimation techniques are applied based on the methods of moments, maximum likelihood and probability weighted moments. The asymptotic variances of estimator of the quantiles for each estimation method are derived to find the confidence limits for a given return period. Finally, the log-Gumbel model is applied to actual flood data to estimate the parameters, quantiles and confidence limits.

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The Comparative Study of NHPP Software Reliability Model Based on Log and Exponential Power Intensity Function (로그 및 지수파우어 강도함수를 이용한 NHPP 소프트웨어 무한고장 신뢰도 모형에 관한 비교연구)

  • Yang, Tae-Jin
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.8 no.6
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    • pp.445-452
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    • 2015
  • Software reliability in the software development process is an important issue. Software process improvement helps in finishing with reliable software product. Infinite failure NHPP software reliability models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, proposes the reliability model with log and power intensity function (log linear, log power and exponential power), which made out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on mean square error (MSE) and coefficient of determination($R^2$), for the sake of efficient model, was employed. Analysis of failure, using real data set for the sake of proposing log and power intensity function, was employed. This analysis of failure data compared with log and power intensity function. In order to insurance for the reliability of data, Laplace trend test was employed. In this study, the log type model is also efficient in terms of reliability because it (the coefficient of determination is 70% or more) in the field of the conventional model can be used as an alternative could be confirmed. From this paper, software developers have to consider the growth model by prior knowledge of the software to identify failure modes which can be able to help.

The effect of SiO2, Na2O, and CaO on the isokom temperatures in soda-lime glass (소다석회유리에서 SiO2, Na2O, CaO가 isokom 온도에 미치는 영향)

  • Kang, Seung Min;Kim, Chang-Sam
    • Journal of the Korean Crystal Growth and Crystal Technology
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    • v.32 no.1
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    • pp.12-15
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    • 2022
  • The effect of SiO2, Na2O and CaO on isokom temperatures in soda-lime glass is estimated by comparing calculated isokom temperatures using viscosity model proposed by Lakatos. The isokom temperatures at the viscosity of log η = 12.3, 10, 6.6 and 1 (Pa·s) are lowered by 6, 7, 10 and 24℃, respectively, by the substitution of SiO2 with Na2O by 1 mol%. Meanwhile, replacing 1 mol% of SiO2 with CaO raises the isokom temperatures by 3~4 and 2℃ at the viscosity of log η = 12.3 and 10 (Pa·s), respectively, but lowers the temperatures by 1 and 21℃ at the viscosity of log η = 6.6 and 1(Pa·s), respectively.