• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.4
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• pp.350-359
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• 2013

In this paper, Inter user interference elimination algorithm based on Block Diagonal Geometric Mean Decomposition(BD-GMD) for eliminating inter user interference apply to Zero-Forcing in the Successive Signal to Leakage plus Noise Ratio(SSLNR) in Coordinated Multi-Point Coordinated Beamforming system(CoMP CB). As a result, the leakage power is eliminated. The inter user interference elimination algorithm, however, cannot guarantee the enough desired signal power therefore we perform the channel ordering to overcome this disadvantage and increase the desired signal power. The simulation results show that the proposed scheme provides the improved Bit Error Rate(BER) performance compared with existing SSLNR-Zero-Forcing-Tomlinson Harashima precoding(SSLNR-ZF-THP).

• Journal of the Korean Data and Information Science Society
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• v.7 no.1
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• pp.87-92
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• 1996

A regression model with nested erroe structure is considered. The regression model includes two error terms that are independent and normally distributed with zero means and constant variances. This error structure of the model gives correlated response variables. The distributions of variance components in the regression model with nested error structure are dervied by using theorems for quadratic forms.

• Honam Mathematical Journal
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• v.36 no.2
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• pp.291-303
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• 2014

In this paper, through a direct computation with subintervals partitioning [0, 1], we compute better a posteriori bounds for the average case error of the difference between the true value of $I(f)=\int_{0}^{1}f(x)dx$ with $f{\in}C^r$[0, 1] minus the composite trapezoidal rule and the composite trapezoidal rule minus the basic trapezoidal rule for $r{\geq}3$ by using zero mean-Gaussian.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.96-99
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• 1999

In this paper, a sliding node controller guaranteeing finite time error convergence is proposed jot uncertain systems. By using a novel sliding hyperplane, it is guaranteed that the output tracking error converges to zero in finite time.

• Journal of Energy Engineering
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• v.27 no.4
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• pp.103-110
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• 2018

In this paper, we introduce evaluation method of time series prediction model with new approach of Mean Absolute Percentage Error(hereafter MAPE) and Symmetric Mean Absolute Percentage Error(hereafter sMAPE). There are some problems using MAPE and sMAPE. First MAPE can't evaluate Zero observation of dataset. Moreover, when the observed value is very close to zero it evaluate heavier than other methods. Finally it evaluate different measure even same error between observations and predicted values. And sMAPE does different evaluations are made depending on whether the same error value is over-predicted or under-predicted. And it has different measurement according to the each sign, even if error is the same distance. These problems were solved by Maximum Mean Absolute Percentage Error(hereafter mMAPE). we used the absolute maximum of observed value as denominator instead of the observed value in MAPE, when the value is less than 1, removed denominator then solved the problem that the zero value is not defined. and were able to prevent heavier measurement problem. Also, if the absolute maximum of observed value is greater than 1, the evaluation values of mMAPE were compared with those of the other evaluations. With Beijing PM2.5 temperature data and our simulation data, we compared the evaluation values of mMAPE with other evaluations. And we proved that mMAPE can solve the problems that we mentioned.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.386-388
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• 2007

In many applications of UAVs flying in low altitude, the steady supply of accurate height measurements is very important for the UAVs to complete their mission successfully. In order to do this, a barometer or GPS height measurements are widely used. However, because these two sensors have their limitations in the application environment, a method for fusing these two measurements to produce reference heights are required. In this paper, a reference height generation filter is designed for UAV(Unmanned Air Vehicle) applications. The barometer errors originated by the change of the atmospheric environment are modeled using random walk models, and then the errors are identified and compensated through the ZSB(zero-scan-back) filter algorithm using the GPS height measurements. The performance of the proposed filter is demonstrated by realistic simulations.

• Journal of Power Electronics
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• v.14 no.6
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• pp.1334-1344
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• 2014

A novel single phase Phase-Locked Loop (PLL) is proposed in this paper to accurately and rapidly estimate the instantaneous phase angle of a grid. A conjugate rotating vector pair is proposed and defined to synthesize the single phase signal in the stationary reference frame. With this concept, the proposed PLL innovatively sets one phase input of the PARK transformation to a constant zero. By means of a proper cancellation, a zero steady state phase angle estimation error can be achieved, even under magnitude and frequency variations. The proposed PLL structure is presented together with guidelines for parameters adjustment. The performance of the proposed PLL is verified by comprehensive experiments. Satisfactory phase angle estimation can be achieved within one input signal cycle, and the estimation error can be totally eliminated in four input cycles for the most severe conditions.

• The Korean Journal of Applied Statistics
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• v.26 no.6
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• pp.923-932
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• 2013

This paper proposes a method to predict the number of foodborne disease outbreaks by microbes. The weekly data of food poisoning occurrences by microbes in Korea contain many zero-valued observations and have dependency between outbreaks. In order to model both phenomena, the number of food poisonings is predicted by an autoregressive model and the probabilities of food poisoning occurrences by microbes (given the total of food poisonings) are estimated by the baseline category logit model. The predicted number of foodborne disease outbreaks by a microbe is obtained by multiplying the predicted number of foodborne disease outbreaks and the estimated probability of the food poisoning by the corresponding microbe. The mean squared error and the mean absolute value error are evaluated to compare the performances of the proposed method and the zero-inflated model.

• The Korean Journal of Applied Statistics
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• v.19 no.3
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• pp.505-519
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• 2006

We consider zero-inflated count data, which is discrete count data but has too many zeroes compared to the Poisson distribution. Zero-inflated data can be found in various areas. Despite its increasing importance in practice, appropriate statistical inference on zero-inflated data is limited. Classical inference based on a large number theory does not fit unless the sample size is very large. And regular Poisson model shows lack of St due to many zeroes. To handle the difficulties, a mixture of distributions are considered for the zero-inflated data. Specifically, a mixture of a point mass at zero and a Poisson distribution is employed for the data. In addition, when there exist meaningful covariates selected to the response variable, loglinear link is used between the mean of the response and the covariates in the Poisson distribution part. We propose a Bayesian inference for the zero-inflated Poisson regression model by using a Markov Chain Monte Carlo method. We applied the proposed method to a Korean oral hygienic data and compared the inference results with other models. We found that the proposed method is superior in that it gives small parameter estimation error and more accurate predictions.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1832-1835
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• 1997

Off-line programming systems are widely spread in assembly lines of minute electronic products to huge offshore structures. Any OLP system has to be calibrated before the on-line robot tasks are performed because there are inherent differences between the CAD model on OLP and the real robot workspace. This paper uses simple geometric expressions to propose a calibration method applicable to an OLP for SCARA robots. A positioning task on the two-dimensional horizontal surface was used in the error analysis of a SCARA robot and the anaysis shows that the inaccuracy results from the two error sources non-zero offset angles of two rotational joints at the zero return and differences in link lengths. Pen marks on a sheet of plotting paper are used to determine the accurate data on the joint centers and link dimensions. The calculated offset angles and link lengths are fed back to the OLP for the calibration of the CAD model of the robot and task environments.