• The Korean Journal of Applied Statistics
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• v.31 no.4
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• pp.463-473
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• 2018

Variable selection algorithms for linear regression models of large data are considered. Many algorithms are proposed focusing on the speed and the robustness of algorithms. Among them variance inflation factor (VIF) regression is fast and accurate due to the use of a streamwise regression approach. But a VIF regression is susceptible to outliers because it estimates a model by a least-square method. A robust criterion using a weighted estimator has been proposed for the robustness of algorithm; in addition, a robust VIF regression has also been proposed for the same purpose. In this article a fast and robust variable selection method is suggested via a VIF regression with detecting and removing potential outliers. A simulation study and an analysis of a dataset are conducted to compare the suggested method with other methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2720-2736
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• 2013

Multi-view face detection has become an active area for research in the last few years. In this paper, a novel multi-view human face detection algorithm based on improved real Adaboost is presented. Real Adaboost algorithm is improved by weighted combination of weak classifiers and the approximately best combination coefficients are obtained. After that, we proved that the function of sample weight adjusting method and weak classifier training method is to guarantee the independence of weak classifiers. A coarse-to-fine hierarchical face detector combining the high efficiency of Haar feature with pose estimation phase based on our real Adaboost algorithm is proposed. This algorithm reduces training time cost greatly compared with classical real Adaboost algorithm. In addition, it speeds up strong classifier converging and reduces the number of weak classifiers. For frontal face detection, the experiments on MIT+CMU frontal face test set result a 96.4% correct rate with 528 false alarms; for multi-view face in real time test set result a 94.7 % correct rate. The experimental results verified the effectiveness of the proposed approach.

• The Korean Journal of Applied Statistics
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• v.31 no.2
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• pp.229-239
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• 2018

This paper introduces how to adopt the concept of temporal hierarchies to forecast time series data. Similarly as in hierarchical cross-sectional data, temporal hierarchies can be constructed for any time series data by means of non-overlapping temporal aggregation. Reconciliation forecasts with temporal hierarchies result in more accurate and robust forecasts when compared with the independent base and bottom-up forecasts. As an empirical example, we forecast traffic accident counts with temporal hierarchies and observe that reconciliation forecasts are superior to the base and bottom-up forecasts in terms of forecast accuracy.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.5
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• pp.425-433
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• 2002

After the removal of SA (Selective Availability), horizontal accuracy of 25m(2dRMS) is easily obtained using GPS (Global Positioning System). In this paper, the error characteristics without SA are analyzed and a navigation algorithm concerns this error characteristics is proposed to further improve the accuracy. The proposed method utilizes the relationship between elevation angle and errors that are remained after ionospheric and troposheric delay compensation. The relationship is derived from real measurements and used as a weighting matrix of weighted least squares estimator. Furthermore, a RAIM (Receiver Autonomous Integrity Monitoring) technique is included to remove abnormal measurements affected by multi-path or low SNR (Signal-to-Noise Ratio). It is shown that using the proposed method, more than 4 times accurate result, which is comparable with DGPS (Differential GPS), can be obtained from experiments with real data. Besides accuracy and reliability, the proposed method reduces large jumps in position and maintains better performance than a method using mask angle to completely remove satellites below this mask angle. Thus it is expected that the proposed method can be efficiently applied to land navigation where some satellites are blocked by building or forest.

• The Korean Journal of Applied Statistics
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• v.25 no.5
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• pp.829-835
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• 2012

When the input features are generated by factors in a classification problem, it is more meaningful to identify important factors, rather than individual features. The $F_{\infty}$-norm support vector machine(SVM) has been developed to perform automatic factor selection in classification. However, the $F_{\infty}$-norm SVM may suffer from estimation inefficiency and model selection inconsistency because it applies the same amount of shrinkage to each factor without assessing its relative importance. To overcome such a limitation, we propose the adaptive $F_{\infty}$-norm ($AF_{\infty}$-norm) SVM, which penalizes the empirical hinge loss by the sum of the adaptively weighted factor-wise $L_{\infty}$-norm penalty. The $AF_{\infty}$-norm SVM computes the weights by the 2-norm SVM estimator and can be formulated as a linear programming(LP) problem which is similar to the one of the $F_{\infty}$-norm SVM. The simulation studies show that the proposed $AF_{\infty}$-norm SVM improves upon the $F_{\infty}$-norm SVM in terms of classification accuracy and factor selection performance.

• The Korean Journal of Applied Statistics
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• v.27 no.2
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• pp.331-343
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• 2014

We propose two estimating procedures to analyze clustered interval-censored data with an informative cluster size based on a marginal model and investigate their asymptotic properties. One is an extension of Cong et al. (2007) to interval-censored data and the other uses the within-cluster resampling method proposed by Hoffman et al. (2001). Simulation results imply that the proposed estimators have a better performance in terms of bias and coverage rate of true value than an estimator with no adjustment of informative cluster size when the cluster size is related with survival time. Finally, they are applied to lymphatic filariasis data adopted from Williamson et al. (2008).

• The Journal of the Acoustical Society of Korea
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• v.21 no.4
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• pp.387-393
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• 2002

The enhancement technique of noise signal using mixture HFM (Midden Filter Model) are proposed. Given the parameters of the clean signal and noise, noisy signal is modeled by a linear state-space model with Markov switching parameters. Estimation of state vector is required for estimating original signal. The estimation procedure is based on mixture interacting multiple model (MIMM) and the estimator of speech is given by the weighted sum of parallel Kalman filters operating interactively. Simulation results showed that the proposed method offers performance gains relative to the previous results with slightly increased complexity.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.2
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• pp.43.5-44
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• 2021

In the local Universe, the gravitational effects of mass density fluctuations exert perturbations on galaxies' redshifts on top of Hubble's Law, called 'peculiar velocities'. These peculiar velocities provide an excellent way to test the cosmological model in the nearby Universe. In this talk, we present new cosmological constraints using peculiar velocities measured with the 2MASS Tully-Fisher survey (2MTF), 6dFGS peculiar-velocity survey (6dFGSv), the Cosmicflows-3 and Cosmicflows-4TF compilation. Firstly, the dipole and the quadrupole of the peculiar velocity field, commonly named 'bulk flow' and 'shear' respectively, enable us to test whether our cosmological model accurately describes the motion of galaxies in the nearby Universe. We develop and use a new estimators that accurately preserves the error distribution of the measurements to measure these moments. In all cases, our results are consistent with the predictions of the Λ cold dark matter model. Additionally, measurements of the growth rate of structure, fσ8 in the low-redshift Universe allow us to test different gravitational models. We developed a new estimator of the "momentum" (density weighted peculiar velocity) power spectrum and use joint measurements of the galaxy density and momentum power spectra to place new constraints on the growth rate of structure from the combined 2MTF and 6dFGSv data. We recover a constraint of fσ8=0.404+0.082-0.081 at an effective redshift zeff=0.03. This measurement is also fully consistent with the expectations of General Relativity and the Λ Cold Dark Matter cosmological model.

• Journal of Korean society of Dental Hygiene
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• v.12 no.3
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• pp.521-531
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• 2012

Objectives : The aim of this study was to evaluate the relation between the state of dental health(number of natural teeth) and nutritional status of Korean elderly using Korean Dietary Reference Intakes, which was an objective standard for nutritional intake based on database of Korea National Health and Nutrition Examination Survey, large scale of sample obtained by the government. Methods : Complex sampling procedure was used to analyze the fourth data(2007-2009) of Korea National Health and Nutrition Examination Survey. When preparing planning file, the estimator of variance as a stratification variance (variance name : kstrata), population of survey unit as a cluster variance(variance name : PSU), and previous exam and nutritional related weighted as a weighted were analyzed by considering reproduced survey and nutritional related total weighted. Complex samples chi-square test was used to estimate the relation between number of natural teeth and inadequate intake and relation factors included in the model were analyzed by complex samples logistic regression analysis. Results : The group of edentulous had a higher risk to intake less nutrient, except calcium, riboflavin and vitamin C than recommended level comparing to reference group which had natural teeth more than 20(phosphate : OR=1.763; 95% CI=1.273-2.443, thiamine : OR=1.748; 95% CI=1.276-2.395, protein : OR=1.610; 95% CI=1.213-2.138). Conclusions : The number of teeth in Korean elderly over 65 years old had a relation with nutritional status in this investigation. Especially, intake level of nutrients was different between the edentulous group and the reference group. Therefore, dental health care is needed from young and middle age to keep health dental condition for through whole life as well as old age. Although the dental condition of the aged is not good, it is evitable to educate them about the relation between dental health and nutritional ingestion to take balanced nutrition, we think.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.19 no.4 s.74
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• pp.429-440
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• 2006

This paper comprises two specific objectives. The first is to examine the applicability of ordinary kriging interpolation(OK) to the p-adaptivity of the finite element method that is based on variogram modeling. The second objective Is to present the adaptive procedure by the hierarchical p-refinement in conjunction with a posteriori error estimator using the modified S.P.R. (superconvergent patch recovery) method. The ordinary kriging method that is one of weighted interpolation techniques is applied to obtain the estimated exact solution from the stress data at the Gauss points. The weight factor is determined by experimental and theoretical variograms for interpolation of stress data apart from the conventional interpolation methods that use an equal weight factor. In the p-refinement, the analytical domain has to be refined automatically to obtain an acceptable level of accuracy by increasing the p-level non-uniformly or selectively. To verify the performance of the modified S.P.R. method, the new error estimator based on limit value has been proposed. The validity of the proposed approach has been tested with the help of some benchmark problems of linear elastic fracture mechanics such as a centrally cracked panel, a single edged crack, and a double edged crack.