• Proceedings of the KOSOMBE Conference
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• v.1992 no.05
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• pp.186-189
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• 1992

Adaptive fliter for noise cancellation of ECG is proposed. An adaptive noise canceller using the least mean squares algorithm is used to reduce unwanted noise. The adaptive noise canceller minimizes the mean-square error between a primary input, which is the noisy ECG, and a reference input, which is either noise that is correlated in some way with the noise in the primary input or a signal that is correlated only with ECG in the primary input.

• Journal of Korean Society for Quality Management
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• v.25 no.1
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• pp.69-79
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• 1997

We consider the semiparametric linear errors-in-variables model: yi=(${\alpha}+{\beta}ui+{\varepsilon}i$, xi=ui＋${\varepsilon}i$ i=1, …, n where (xi, yi) stands for an observation vector, (ui) denotes a set of incidental nuisance parameters, (${\alpha}$ , ${\beta}$) is a vector of regression parameters and (${\varepsilon}i$, ${\delta}i$) are mutually uncorrelated measurement errors with zero mean and finite variances but otherwise unknown distributions. On the basis of a simple small-sample low-noise a, pp.oximation, we propose a new method of comparing the mean squared errors(MSE) of the various competing estimators of the true regression parameters ((${\alpha}$ , ${\beta}$). Then we show that a class of estimators including the classical least squares estimator and the maximum likelihood estimator are consistent and first-order efficient within the class of all regular consistent estimators irrespective of type of measurement errors.

• Communications for Statistical Applications and Methods
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• v.4 no.3
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• pp.903-909
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• 1997

The ordinary least squares estimator and the corresponding pivotal statistics have been widely used for the unit test. Recently several test criteria based on maximum likelihood estimators and weighted symmetric estimator have been proposed for testing the unit root hypothesis in the autoregressive processes. Pantula at el. (1994) showed that the weighted symmetric estimator has good power properties. In this article we use an adjusted estimator for mean in the model when we use weighted symmetric estimator. A simulation study shows that for the small samples, this new test criterion has better power properties than the weighted symmetric estimator.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.5B
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• pp.830-841
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• 2000

We extend the sue of the method of least square to develop a recursive algorithm for the design of adaptive transversal filters such that, given the least-square estimate of this vector of the filter at iteration n-1, we may compute the updated estimate of this vector at iteration a upon the arrival of new data. We begin the development of the RLS algorithm by reviewing some basic relations that pertain to the method of least squares. Then, by exploiting a relation in matrix algebra known as the matrix inversion lemma, we develop the RLS algorithm. An important feature of the RLS algorithm is that it utilizes information contained in the input data, extending back to the instant of time when the algorithm is initiated. In this paper, we propose new tap weight updated RLS algorithm in adaptive transversal filter with data-recycling buffer structure. We prove that convergence speed of learning curve of RLS algorithm with data-recycling buffer is faster than it of exiting RL algorithm to mean square error versus iteration number. Also the resulting rate of convergence is typically an order of magnitude faster than the simple LMS algorithm. We show that the number of desired sample is portion to increase to converge the specified value from the three dimension simulation result of mean square error according to the degree of channel amplitude distortion and data-recycle buffer number. This improvement of convergence character in performance, is achieved at the (B+1)times of convergence speed of mean square error increase in data recycle buffer number with new proposed RLS algorithm.

• Korean Journal of Soil Science and Fertilizer
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• v.37 no.4
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• pp.259-265
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• 2004

A quicker method was developed for foliar analysis in diagnosis of nitrogen in apple trees based on multivariate calibration procedure using partial least squares regression (PLSR) and principal component regression (PCR) to establish the relationship between reflectance spectra in the near infrared region and nitrogen content of fresh- and dry-leaf. Several spectral pre-processing methods such as smoothing, mean normalization, multiplicative scatter correction (MSC) and derivatives were used to improve the robustness and performance of the calibration models. Norris first derivative with a seven point segment and a gap of six points on MSC gave the best result of partial least squares-1 PLS-1) model for dry-leaf samples with root mean square error of prediction (RMSEP) equal to $0.699g\;kg^{-1}$, and that the Savitzky-Golay first derivate with a seven point convolution and a quadratic polynomial on MSC gave the best results of PLS-1 model for fresh-samples with RMSEP of $1.202g\;kg^{-1}$. The best PCR model was obtained with Savitzky-Golay first derivative using a seven point convolution and a quadratic polynomial on mean normalization for dry leaf samples with RMSEP of $0.553g\;kg^{-1}$, and obtained with the Savitzky-Golay first derivate using a seven point convolution and a quadratic polynomial for fresh samples with RMSEP of $1.047g\;kg^{-1}$. The results indicate that nitrogen can be determined by the near infrared reflectance (NIR) technology for fresh- and dry-leaf of apple.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.5
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• pp.863-870
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• 2015

A Compensation Algorithm for The Position of the User Hands based on the Moving Mean-Shift ($CAPUH_{MMS}$) in Human Robot Interface (HRI) System running the Kinect sensor is proposed in order to improve the performance of the gesture recognition is proposed in this paper. The average error improvement ratio of the trajectories ($AEIR_{TJ}$) in left-right movements of hands for the $CAPUH_{MMS}$ is compared with other compensation algorithms such as the Compensation Algorithm based on the Compensation Algorithm based on the Kalman Filter ($CA_{KF}$) and the Compensation Algorithm based on Least-Squares Method ($CA_{LSM}$) by the developed realtime performance simulator. As a result, the $AEIR_{TJ}$ in up-down movements of hands of the $CAPUH_{MMS}$ is measured as 19.35%, it is higher value compared with that of the $CA_{KF}$ and the $CA_{LSM}$ as 13.88% and 16.68%, respectively.

• Journal of Veterinary Clinics
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• v.23 no.4
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• pp.416-420
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• 2006

Compare to testing sera individually, pooled-serum testing has considered as a cost-effective method, particularly on a large population-based seroprevalence studies. This study was to determine the relationship between individual sera and pooled sera titers for detection of avian infectious bronchitis virus (IBV) and to evaluate suitability of pooled sera by comparing prevalences estimated from both samples. A total of 5,000 individual samples were collected from 500 flocks in Chungcheong, Gyunsgi, and Kangwon provinces between January 2005 and February 2006. Ten samples were randomly selected from each flock. Five-hundred pooled sera were prepared by mixing equal amount of each 10 individual serum from the original samples. IBV antibody titers were measured by hemagglutination inhibition (HI) test. The least squares regression analysis was performed to construct equation between pooled and mean individual titers. To determine whether the flock is infected 4 arbitrary criteria were used: detection of at least 1 chicken with HI titer ${\ge}$ 9 (criterion 1), detection of at least 2 samples with HI titer ${\ge}$9 (criterion 2), detection of at least 1 sample with HI titer ${\ge}$ 10 (criterion 3), and filially detection of at least 1 sample with HI titer ${\ge}$ 11 (criterion 4). The receiver operating characteristic (ROC) curve was used to examine the cut-off points of pooled titers showing optimal diagnostic accuracy. The area under the curve (AUC), sensitivities (Se), specificities (Sp), and positive (PPV) and negative (NPV) predictive values were calculated. The regression equation between pooled titers (pool) and mean individual titers (mean) was: $pool= 1.2498+0.8952{\times}mean$, with coefficient of determination of 87% (p< 0.0001). The optimal cut-off points of pooled titers were titer 8 for criterion 1 (AUC=0.975, Se=0.883, Sp=0.959, PPV=0.985, NPV=0.728), titer 8 for criterion 2 (AUC=0.969, Se=0.954, Sp=0.855, PPV=0.926, NPV=0.907), titer 9 for criterion 3 (AUC=0.970, Se=0.836, Sp=0.967, PPV=0.978, NPV=0.772), and titer 9 for criterion 4 (AUC= 0.946, Se=0.928, Sp=0.843, PPV=0.857, NPV=0.921). The difference of 'prevalence estimated by individual and pooled sample showed a minimum of 2% for criteria 2 and a maximum of 9.1:% for criteria 3. These results indicate that the use of pooled sera in HI test for screening IBV infection in laying hen flocks is considered as a cost-effective method of testing large numbers of samples with high diagnostic accuracy.

• Journal of the Korea institute for structural maintenance and inspection
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• v.15 no.2
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• pp.153-160
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• 2011

Recently there are many long span cable supported bridges like Cable Stayed Bridge and Suspension Bridge already constructed or planned. Reconsidering of proper design wind load of long span bridge is required since the meteorological value based on the data only from 1960s to 1995 has been used when we estimate the wind load for designing long span bridges. In this paper, the research area was confined to western and southern coasts where many long span bridges have constructed. The method of moment and the least-squares method were used to estimate the expected wind speeds of 100 year's return period for girder bridges and for 200 year's return period for long span bridges based on the Gumbel's distribution. As the return-period wind speed on the land face was revised because of recent high speed velocity, the revised return-period wind speed is increased by 17%. Compatibility of return-period wind speed was also evaluated using RMS (Root Mean Square) error method. Aa a result of this paper, the least-squares method is more compatible than the method of moment in the case of western and southern coasts in Korea.

• The Journal of the Acoustical Society of Korea
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• v.36 no.5
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• pp.338-344
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• 2017

In this paper, an interpolation method of HRTF (Head-Related Transfer Function) is proposed for small-sized measurement data set, especially. The proposed algorithm is based on acoustic modeling of HRTFs, and the algorithm tries to interpolate the HRTFs via estimation the model coefficients. However, the estimation of the model coefficients is hard if there is lack of measurement points, so the algorithm solves the problem by a data augmentation using the VBAP (Vector Based Amplitude Panning). Therefore, the proposed algorithm consists of two steps, which are data augmentation step based on VBAP and model coefficients estimation step by least squares method. The proposed algorithm was evaluated by a simulation with a measured data from CIPIC (Center for Image Processing and Integrated Computing) HRTF database, and the simulation results show that the proposed algorithm reduces mean-squared error by 1.5 dB ~ 4 dB than the conventional algorithms.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.44-44
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• 2017

The objective of this study was to evaluate firmness, and sweetness index (SI) of tomatoes (Lycopersicum esculentum) by using hyperspectral imaging (HSI) in the range of 1000-1400 nm. The mean spectra of the 95 matured tomato samples were extracted from the hyperspectral images, and the reference firmness and sweetness index of the same sample were measured and calibrated with their corresponding spectral data by partial least squares (PLS) regression with different preprocessing method. The results showed that the regression model developed by PLS regression based on Savitzky-Golay (S-G) second-derivative preprocessed spectra resulted in better performance for firmness, and SI of tomatoes compared to models developed by other preprocessing methods, with correlation coefficients (rpred) of 0.82, and 0.74 with standard error of prediction (SEP) of 0.86 N, and 0.63 respectively. Then, the feature wavelengths were identified using model-based variable selection method, i.e., variable important in projection (VIP), resulting from the PLS regression analyses and finally chemical images were derived by applying the respective regression coefficient on the spectral image in a pixel-wise manner. The resulting chemical images provided detailed information on firmness, and sweetness index (SI) of tomatoes. Therefore, these research demonstrated that HIS technique has a potential for rapid and non-destructive evaluation of the firmness and sweetness index of tomatoes.