• Journal of the Korea Safety Management & Science
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• v.3 no.3
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• pp.175-190
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• 2001

We propose, a new process capability index $C_{psk}$(WV) applying the weighted variance control charting method for non-normally distributed. The main idea of the weighted variance method(WVM) is to divide a skewed or asymmetric distribution into two normal distributions from its mean to create two new distributions which have the same mean but different standard deviations. In this paper we propose an example, a distributions generated from the Johnson family of distributions, to demonstrate how the weighted variance-based process capability indices perform in comparison with another two non-normal methods, namely the Clements and the Wright methods. This example shows that the weighted valiance-based indices are more consistent than the other two methods in terms of sensitivity to departure to the process mean/median from the target value for non-normal processes. Second method show using the percentage nonconforming by the Pearson, Johnson and Burr systems. This example shows a little difference between the Pearson system and Burr system, but Johnson system underestimated than the two systems for process capability.

• Journal of Korean Tunnelling and Underground Space Association
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• v.17 no.6
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• pp.615-621
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• 2015

In this paper diamond wire cutting method has been proposed to cut the rock in the tunnel face. Diamond wire saw method could cut the rock from tunnel face with very minor vibration and noise. In this study rock cutting process has been simulated with FEM method by using LS-DYNA explicit non-linear finite element code. Normal load act as an prime factor when cutting the rock surface. For observing the effect of normal load on bead, several experiments has been conducted by varying normal loads on the bead. From each experiment, cutting rate has been calculated to compare the cutting rate with different load conditions. By increasing the normal load on bead, cutting rate increases drastically.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.7 s.184
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• pp.187-193
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• 2006

This paper introduces and illustrates the results of a new method for offsetting the triangular mesh generated from multiple surfaces. The meshes generated from each surface are separated each other and normal directions are different. The face normal vectors are flipped to upward and the lower faces covered by upper faces are deleted. The virtual normal vectors are introduced and used to of feet boundary. It was shown that new method is better than previous methods in offsetting the triangular meshes generated from multiple surfaces. The introduced offset method was applied for 3-axis tool path generation system and tested by NC machining.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.7
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• pp.462-467
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• 2005

In this paper, we analyzed normal gait acceleration signal by time series analysis methods. Accelerations were measured during walking using a biaxial accelerometer. Acceleration data were acquired from normal subjects(23 men and one woman) walking on a level corridor of 20m in length with three different walking speeds. Acceleration signals were measured at a sampling frequency of 60Hz from a biaxial accelerometer mounted between L3 and L4 intervertebral area. Each step signal was analyzed using Box-Jenkins method. Most of the differenced normal step signals were modeled to AR(3) and the model didn't show difference for model's orders and coefficients with walking speed. But, tile model showed difference with acceleration signal direction - vertical and lateral. The above results suggested the proposed model could be applied to unit analysis.

• Communications for Statistical Applications and Methods
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• v.19 no.6
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• pp.793-798
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• 2012

In this paper, we propose regression methods based on the likelihood function. We assume Arnold-Beaver Skew Normal(ABSN) errors in a simple linear regression model. It was shown that the novel method performs better with an asymmetric data set compared to the usual regression model with the Gaussian errors. The utility of a novel method is demonstrated through simulation and real data sets.

• Journal of Korean Society on Water Environment
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• v.24 no.6
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• pp.676-681
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• 2008

The evaluation of the effluent water quality of sewage treatment plant is one of the most important factor in calculating total maximum daily loads (TMDLs). Current method to calculate 95% upper limit of effluent water quality of sewage treatment plant assuming normal distribution of data needs to be implemented in case of non-normal distribution. We have investigated the applicability of percentile ranking method as a non-parametric statistical analysis in case of non-normal distribution of data.

• Journal of Information Processing Systems
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• v.17 no.3
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• pp.462-472
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• 2021

With an increase in the scale of recommender systems, users' rating data tend to be extremely sparse. Some methods have been utilized to alleviate this problem; nevertheless, it has not been satisfactorily solved yet. Therefore, we propose an effective pre-rating method based on users' dichotomous preferences and average ratings fusion. First, based on a user-item ratings matrix, a new user-item preference matrix was constructed to analyze and model user preferences. The items were then divided into two categories based on a parameterized dynamic threshold. The missing ratings for items that the user was not interested in were directly filled with the lowest user rating; otherwise, fusion ratings were utilized to fill the missing ratings. Further, an optimized parameter λ was introduced to adjust their weights. Finally, we verified our method on a standard dataset. The experimental results show that our method can effectively reduce the prediction error and improve the recommendation quality. As for its application, our method is effective, but not complicated.

• 한국정보통신설비학회:학술대회논문집
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• 2009.08a
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• pp.382-386
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• 2009

Online or sequential learning is one of the most basic and powerful method to train neuron network, and it has been widely used in disease detection, weather prediction and other realistic classification problem. At present, there are many algorithms in this area, such as MRAN, GAP-RBFN, OS-ELM, SVM and SMC-RBF. Among them, SMC-RBF has the best performance; it has less number of hidden neurons, and best efficiency. However, all the existing algorithms use signal normal distribution as kernel function, which means the output of the kernel function is same at the different direction. In this paper, we use multi-variable normal distribution as kernel function, and derive EKF learning formulas for multi-variable normal distribution kernel function. From the result of the experience, we can deduct that the proposed method has better efficiency performance, and not sensitive to the data sequence.

• Journal of KSNVE
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• v.7 no.6
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• pp.975-984
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• 1997

A direct boundary element method (DBEM) is developed for thin bodies whose surfaces are rigid or compliant. The Helmholtz integral equation and its normal derivative integral equation are adoped simultaneously to calculate the pressure on both sides of the thin body, instead of the jump values across it, to account for the different surface conditions of each side. Unlike the usual assumption, the normal velocity is assumed to be discontinuous across the thin body. In this approach, only the neutral surface of the thin body has to be discretized. The method is validated by comparison with analytic and/or numerical results for acoustic scattering and radiation from several surface conditions of the thin body; the surfaces are rigid when stationary or vibrating, and part of the interior surface is lined with a sound-absoring material.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.52
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• pp.347-354
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• 1999

Statistical Process Control(SPC) which uses control charts is widely used to inspect and improve manufacturing process as a effective method. A parametric method is the most common in statistical process control. Shewhart chart was made under the assumption that measurements are independent and normal distribution. In practice, this assumption is often excluded, for example, in case of (equation omitted) chart, when the subgroup sample is small or correlation, it happens that measured data have bias or rejection of the normality test. A bootstrap method can be used in such a situation, which is calculated by resampling procedure without pre-distribution assumption. In this study, applying bootstrap percentile method to (equation omitted) chart, it is compared and evaluated standard process control limit with bootstrap percentile control limit. Also, under the normal and non-normal distributions, where parameter is 0.5, using computer simulation, it is compared standard parametric with bootstrap method which is used to decide process control limits in process quality.