• Journal of the Korean Data and Information Science Society
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• v.21 no.2
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• pp.241-250
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• 2010

Over the past few decades, several studies have been made on the modeling of circular data. But these studies focused mainly on the symmetrical cases including von Mises distribution. Recently, many studies with skew-normal distribution have been conducted in the linear case. In this paper, we dealt the problem of fitting of non-symmetrical circular data with wrapped skew-normal distribution which can be derived by using the principle of wrapping. Wrapped skew-normal distribution is very flexible to asymmetical data as well as to symmetrical data. Multi-modal data are also fitted by using the mixture of wrapped skew-normal distributions. To estimate the parameters of mixture, we suggested the EM algorithm. Finally we verified the accuracy of the suggested algorithm through simulation studies. Application with real data is also considered.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.8
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• pp.2194-2200
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• 1994

In an automotive spark ignition engine, it is important to form the proper mixture (air/fuel) on each driving condition for developing the stabilizing combustion and exhaust characteristics. Since most of supply fuel si attached on the inside wall of the intake manifold for unadequate nonuniformity of fuel distribution to each cylinder and mixture variation. Also it affects engine performance variation and causes noises and vibration. In this study, we verified the effect of the mixture variation which is caused by fuel liquid film in the intake manifold on combustion characteristics and engine performance.

• International Journal of Automotive Technology
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• v.2 no.3
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• pp.93-101
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• 2001

Distribution of fuel-air mixture has a strong influence on performance and emissions of a compressed natural gas (CNG) engine. In this paper, parametric study is performed by KIVA-3V to investigate fuel-air mixture with respect to injection timing, cycle equivalence ratio and engine speed. With open-valve injection intensive mixing during intake and compression stroke results in relatively homogeneous mixture in the cylinder. Sequential induction of fuel-air mixture and fresh air results in stratification in the cylinder among the test cases at closed-valve injection. There is close similarity in the calculated distributions of the mixture in the cylinder with different cycle equivalence ratios and engine speeds. The results are compared against pressure traces and flame images obtained in a single cylinder engine converted from a 11L six-cylinder heavy duty diesel engine.

• Journal of Korean Society for Quality Management
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• v.42 no.2
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• pp.209-219
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• 2014

Purpose: The purpose of this study is to develop the statistical test for process capability index $C_p$ based on mixture normal process. Methods: This study uses Bootstrap method to calculate the approximate P-value for various simulation conditions under mixture normal process. Results: This study indicates that our proposed method is effective way to test for process capability index $C_p$ based on mixture normal process. Conclusion: This study finds out that statistical test for process capability index $C_p$ based on mixture normal process is useful for real application.

• Journal of Positioning, Navigation, and Timing
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• v.9 no.1
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• pp.23-31
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• 2020

It is essential to estimate the vehicle localization for an autonomous safety driving. In particular, since LIDAR provides precise scan data, many studies carried out to estimate the vehicle localization using LIDAR and pre-generated map. The road marking always exists on the road because of provides driving information. Therefore, it is often used for map information. In this paper, we propose to generate the Gaussian mixture map based on road-marking information and localization method using this map. Generally, the probability distributions map stores the single Gaussian distribution for each grid. However, single resolution probability distributions map cannot express complex shapes when grid resolution is large. In addition, when grid resolution is small, map size is bigger and process time is longer. Therefore, it is difficult to apply the road marking. On the other hand, Gaussian mixture distribution can effectively express the road marking by several probability distributions. In this paper, we generate Gaussian mixture map and perform vehicle localization using Gaussian mixture map. Localization performance is analyzed through the experimental result.

• Transactions of the Korean Society of Automotive Engineers
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• v.2 no.4
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• pp.72-79
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• 1994

In an automotive spark ignition, it is important to form the proper mixture(air/fuel) on each driving condition for developing the stabilizing combustion and exhaust characteristics. Since most of supply fuel is attached on the inside wall of the intake manifold for unadequate atomization by fuel injection system, it brings a bad effect on combustion and exhaust caused by nonuniformity of fuel distribution to each cylinder and mixture variation. Also it affects engine performance variation and causes noises and vibration. In this study, we verified the effect of the mixture variation which is caused by fuel liquid film in an intake manifold on combustion characteristics and engine performance.

• Communications for Statistical Applications and Methods
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• v.16 no.2
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• pp.389-396
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• 2009

Approximations for the null distribution of a test statistic arising in multivariate analysis to test homogeneity of variances and a mixture of two beta distributions by making use of a product of beta baseline density function and a polynomial adjustment, so called beta-polynomial density approximant, are discussed. Explicit representations of density and distribution approximants of interest in each case can easily be obtained. Beta-polynomial density approximants produce good approximation over the entire range of the test statistic and also accommodate even the bimodal distribution using an artificial example of a mixture of two beta distributions.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.4
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• pp.194-202
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• 2019

Reliability analysis of the components frequently starts with the data that manufacturer provides. If enough failure data are collected from the field operations, the reliability should be recomputed and updated on the basis of the field failure data. However, when the failure time record for a component contains only a few observations, all statistical methodologies are limited. In this case, where the failure records for multiple number of identical components are available, a valid alternative is combining all the data from each component into one data set with enough sample size and utilizing the useful information in the censored data. The ROK Navy has been operating multiple Patrol Killer Guided missiles (PKGs) for several years. The Korea Multi-Function Control Console (KMFCC) is one of key components in PKG combat system. The maintenance record for the KMFCC contains less than ten failure observations and a censored datum. This paper proposes a Bayesian approach with a Dirichlet mixture model to estimate failure time density for KMFCC. Trends test for each component record indicated that null hypothesis, that failure occurrence is renewal process, is not rejected. Since the KMFCCs have been functioning under different operating environment, the failure time distribution may be a composition of a number of unknown distributions, i.e. a mixture distribution, rather than a single distribution. The Dirichlet mixture model was coded as probabilistic programming in Python using PyMC3. Then Markov Chain Monte Carlo (MCMC) sampling technique employed in PyMC3 probabilistically estimated the parameters' posterior distribution through the Dirichlet mixture model. The simulation results revealed that the mixture models provide superior fits to the combined data set over single models.

• Journal of the Korean Statistical Society
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• v.25 no.4
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• pp.545-556
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• 1996

In this paper, we introduce a new concept of partial ordering which permits us to compare pairs of the dependence structures of a new hitting times for POD multivariate vector process of interest as to their degree of POD-ness. We show that POD ordering is closed under convolution, limit in distribution, compound distribution, mixture of a certain type and convex combination. Finally, we present several examples of POD ordering processes.

• Communications for Statistical Applications and Methods
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• v.21 no.6
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• pp.501-512
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• 2014

Stylized facts on asset return are fat-tail, asymmetry, volatility clustering and structure changes. This paper simultaneously captures these characteristics by introducing a multi-regime models: Finite mixture distribution and regime switching GARCH model. Analyzing the daily KOSPI return from $4^{th}$ January 2000 to $30^{th}$ June 2014, we find that a two-component mixture of t distribution is a good candidate to describe the shape of the KOSPI return from unconditional and conditional perspectives. Empirical results suggest that the equality assumption on the shape parameter of t distribution yields better discrimination of heterogeneity component in return data. We report the strong regime-dependent characteristics in volatility dynamics with high persistence and asymmetry by employing a regime switching GJR-GARCH model with t innovation model. Compared to two sub-samples, Pre-Crisis (January 2003 ~ December 2007) and Post-Crisis (January 2010 ~ June 2014), we find that the degree of persistence in the Pre-Crisis is higher than in the Post-Crisis along with a strong asymmetry in the low-volatility (high-volatility) regime during the Pre-Crisis (Post-Crisis).