• Proceedings of the Korean Statistical Society Conference
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• 2002.11a
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• pp.265-272
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• 2002

An Integer-valued autoregressive integrated (INARI) model is introduced to eliminate stochastic trend and seasonality from time series of count data. This INARI extends the previous integer-valued ARMA model. We show that it is stationary and ergodic to establish asymptotic normality for conditional least squares estimator. Optimal estimating equations are used to reflect categorical and serial correlations arising from panel count data and variations arising from three random processes for obtaining observation into estimation. Under regularity conditions for martingale sequence, we show asymptotic normality for estimators from the estimating equations. Using cancer mortality data provided by the U.S. National Center for Health Statistics (NCHS), we apply our results to estimate the probability of cells classified by 4 causes of death and 6 age groups and to forecast death count of each cell. We also investigate impact of three random processes on estimation.

• Journal of the Korea Society for Simulation
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• v.5 no.2
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• pp.59-72
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• 1996

The purpose of this study is to make an improvement to the batch-means method, which is a procedure to construct a confidence interval(c.i.) for the steady-state process mean of a stationary simulation output process. In the batch-means method, the data in the output process are grouped into batches. The sequence of means of the data included in individual batches is called a batch-menas process and can be treated as an independently and identically distributed set of variables if each batch includes sufficiently large number of observations. The traditional batch-means method, therefore, uses a batch size as large as possible in order to. destroy the autocovariance remaining in the batch-means process. The c.i. prodedure developed and empirically tested in this study uses a small batch size which can be well fitted by a simple ARMA model, and then utilizes the dependence structure in the fitted model to correct for bias in the variance estimator of the sample mean.

• Journal of the Korean Data and Information Science Society
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• v.8 no.1
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• pp.9-20
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• 1997

Several methods are proposed for optimizing Fourier series estimators with respect to Mean Integrated Square Error metrics. Traditionally, such method have followed. one of two basic strategies; A stopping rules or the rules of determine multipliers. A central hypothesis of this study is that better estimates can be obtained by combining the two strategies. A new multiplier sequence is proposed, which used in conjunction with any of the stopping rules, is shown to improve the performance of estimator which relies solely on a stopping rule.

• ETRI Journal
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• v.39 no.1
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• pp.13-20
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• 2017

A method is proposed for scheduling sensor accesses to the shared network in a networked control system. The proposed method determines the access order in which the sensors are granted medium access through minimization of the state estimation error covariance. Solving the problem by evaluating the error covariance for each possible ordered set of sensors is not practical for large systems. Therefore, a convex optimization problem is proposed, which yields approximate yet acceptable results. A state estimator is designed for the augmented system resulting from the incorporation of the optimally chosen communication sequence in the plant dynamics. A car suspension system simulation is conducted to test the proposed method. The results show promising improvement in the state estimation performance by reducing the estimation error norm compared to round-robin scheduling.

• Genomics & Informatics
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• v.15 no.1
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• pp.38-47
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• 2017

Research into new methods for identifying highly expressed genes in anonymous genome sequences has been going on for more than 15 years. We presented here an alternative approach based on modified score of relative codon usage bias to identify highly expressed genes in crenarchaeal genomes. The proposed algorithm relies exclusively on sequence features for identifying the highly expressed genes. In this study, a comparative analysis of predicted highly expressed genes in five crenarchaeal genomes was performed using the score of Modified Relative Codon Bias Strength (MRCBS) as a numerical estimator of gene expression level. We found a systematic strong correlation between Codon Adaptation Index and MRCBS. Additionally, MRCBS correlated well with other expression measures. Our study indicates that MRCBS can consistently capture the highly expressed genes.

• Communications for Statistical Applications and Methods
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• v.8 no.1
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• pp.229-235
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• 2001

Let {X$\_$n/, n$\geq$1] be a stationary sequence of negatively associated random variables with distribution function F(x)=P(X$_1$$\leq$x). The empirical distribution function F$\_$n/(x) based on X$_1$, X$_2$,....., X$\_$n/ is proposed as an estimator for F$\_$n/(x). Strong consistency and asymptotic normality of F$\_$n/(x) are studied. We also apply these ideas to estimation of the survival function.

• Investigative Magnetic Resonance Imaging
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• v.20 no.4
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• pp.215-223
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• 2016

Purpose: The management of metal-induced field inhomogeneities is one of the major concerns of distortion-free magnetic resonance images near metallic implants. The recently proposed method called "Slice Encoding for Metal Artifact Correction (SEMAC)" is an effective spin echo pulse sequence of magnetic resonance imaging (MRI) near metallic implants. However, as SEMAC uses the noisy resolved data elements, SEMAC images can have a major problem for improving the signal-to-noise ratio (SNR) without compromising the correction of metal artifacts. To address that issue, this paper presents a novel reconstruction technique for providing an improvement of the SNR in SEMAC images without sacrificing the correction of metal artifacts. Materials and Methods: Low-rank approximation in each coil image is first performed to suppress the noise in the slice direction, because the signal is highly correlated between SEMAC-encoded slices. Secondly, SEMAC images are reconstructed by the best linear unbiased estimator (BLUE), also known as Gauss-Markov or weighted least squares. Noise levels and correlation in the receiver channels are considered for the sake of SNR optimization. To this end, since distorted excitation profiles are sparse, $l_1$ minimization performs well in recovering the sparse distorted excitation profiles and the sparse modeling of our approach offers excellent correction of metal-induced distortions. Results: Three images reconstructed using SEMAC, SEMAC with the conventional two-step noise reduction, and the proposed image denoising for metal MRI exploiting sparsity and low rank approximation algorithm were compared. The proposed algorithm outperformed two methods and produced 119% SNR better than SEMAC and 89% SNR better than SEMAC with the conventional two-step noise reduction. Conclusion: We successfully demonstrated that the proposed, novel algorithm for SEMAC, if compared with conventional de-noising methods, substantially improves SNR and reduces artifacts.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.10
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• pp.1845-1852
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• 2008

The key elements of inter prediction are motion estimation(ME) and motion compensation(MC). Motion estimation is to find the optimum motion vectors, not only by using a distance criteria like the SAD, but also by taking into account the resulting number of 비트s in the 비트 stream. Motion compensation is compensate for movement of blocks of current frame. Inter-prediction Encoding is always the main bottleneck in high-quality streaming applications. Therefore, in real-time streaming applications, dedicated hardware for executing Inter-prediction is required. In this paper, we studied a motion estimator(ME) for H.264/AVC. The designed motion estimator is based on 2-D systolic array and it connects processing elements for fast SAD(Sum of Absolute Difference) calculation in parallel. By providing different path for the upper and lower lesion of each reference data and adjusting the input sequence, consecutive calculation for motion estimation is executed without pipeline stall. With data reuse technique, it reduces memory access, and there is no extra delay for finding optimal partitions and motion vectors. The motion estimator supports variable-block size and takes 328 cycles for macro-block calculation. The proposed architecture is local memory-free different from paper [6] using local memory. This motion estimation encoder can be applicable to real-time video processing.

• ETRI Journal
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• v.37 no.2
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• pp.395-405
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• 2015

We address the problem of uncooperative person recognition through continuous monitoring. Multiple modalities, such as face, height, clothes color, and voice, can be used when attempting to recognize a person. In general, not all modalities are available for a given frame; furthermore, only some modalities will be useful as some frames in a video sequence are of a quality that is too low to be able to recognize a person. We propose a method that makes use of stochastic information updates of temporal modalities and environment estimators to improve person recognition performance. The environment estimators provide information on whether a given modality is reliable enough to be used in a particular instance; such indicators mean that we can easily identify and eliminate meaningless data, thus increasing the overall efficiency of the method. Our proposed method was tested using movie clips acquired under an unconstrained environment that included a wide variation of scale and rotation; illumination changes; uncontrolled distances from a camera to users (varying from 0.5 m to 5 m); and natural views of the human body with various types of noise. In this real and challenging scenario, our proposed method resulted in an outstanding performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.6
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• pp.1005-1013
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• 2015

In this paper, an uplink pilot signal structure is proposed for millimeter wave(mmWave)-based mobile wireless backhaul. For the transmit diversity of two antenna ports, uplink pilot signals generated from the Zadoff-Chu sequence can be mapped in an interleaved mode or continuous mode on the frequency axis, and channel estimation algorithms are different depending on the pilot signal mapping schemes. Through a simulation under Rayleigh fading channel assuming a subway scenario, the interleaved mapping scheme showed no performance degradation compared to the continuous mapping scheme and the implementation complexity of the uplink channel estimator was reduced due to the interleaved mapping scheme.