• Communications for Statistical Applications and Methods
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• v.2 no.2
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• pp.358-365
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• 1995

This paper presents another system of multi-level skip-lot sampling plan, which can directly retum to normal inspection from any skpping inspection level when a sudden shift for the worse in the process mean occurs. All the other properties of the proposed sampling plan are similar to those of the Choi's(1993) plan. The formula of the poerating characteristic function for the proposed n-level skip-lot sampling plan is derived. Sone poerating characteristic properties for the proposed plan are graphically compared with those of the Choi's plan.

• Journal of the Korean Statistical Society
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• v.33 no.3
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• pp.283-298
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• 2004

We present a trial solution approach to GI/M/l queues with generalized vacations. Specific types of generalized vacations we consider are N -policy and a combination of N-policy and exponential multiple vacations. Discussions about how to find trial solutions are given.

• Journal of Korean Society for Quality Management
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• v.13 no.1
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• pp.31-40
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• 1985

In this paper, statistical estimation of the parameters of the bivariate exponential distribution are studied. Bayes estimators of the parameters are obtained and compared with the maximum likelihood estimators which are introduced by Freund. We know that the method of moments estimators coincide with the maximum likelihood estimators and Bayes estimators are more efficient than the maximum likelihood estimators in moderate samples. The asymptotic distributions of the maximum likelihood estimators and the estimator of mean time to system failure are obtained.

• Communications for Statistical Applications and Methods
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• v.6 no.3
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• pp.871-880
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• 1999

The main purpose of queueing theory is to find the optimal solution for maintaining systems such as service facilities. Analyzing the overfolw process provides an important information for the solution in queueing systems with finite capacity. In this thesis we approximate the expected time until the first overflow in M/G/1/K/N queueing systems. Results will be applied to approximate the expected time until the first reduction of source population system. Simulation results show that our approximation is applicable to real situations.

• Communications for Statistical Applications and Methods
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• v.11 no.3
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• pp.553-562
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• 2004

In this short communication we discuss the bias problems of CART in split variable selection and suggest a method to reduce the variable selection bias. Penalties proportional to the number of categories or distinct values are applied to the splitting criteria of CART. The results of empirical comparisons show that the proposed modification of CART reduces the bias in variable selection.

• The Journal of Korea Robotics Society
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• v.16 no.2
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• pp.103-111
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• 2021

This study addresses a low-cost lidar sensor-based glass feature extraction method for an accurate map representation using statistical moments, i.e. the mean and variance. Since the low-cost lidar sensor produces range-only data without intensity and multi-echo data, there are some difficulties in detecting glass-like objects. In this study, a principle that an incidence angle of a ray emitted from the lidar with respect to a glass surface is close to zero degrees is concerned for glass detection. Besides, all sensor data are preprocessed and clustered, which is represented using statistical moments as glass feature candidates. Glass features are selected among the candidates according to several conditions based on the principle and geometric relation in the global coordinate system. The accumulated glass features are classified according to the distance, which is lastly represented on the map. Several experiments were conducted in glass environments. The results showed that the proposed method accurately extracted and represented glass windows using proper parameters. The parameters were empirically designed and carefully analyzed. In future work, we will implement and perform the conventional SLAM algorithms combined with our glass feature extraction method in glass environments.

• Textile Coloration and Finishing
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• v.18 no.4
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• pp.43-48
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• 2006

A phthalocyanine reactive dye was applied to nylon fibers to study the effects of the temperature and pH on % exhaustion and fixation. In addition, appropriate predictable empirical models, relatively new approaches in dyeing process, were developed incorporating interactions effects of temperature and pH for predicting the both % exhaustion and fixation. The significance of the mathematical model developed was ascertained using Excel regression (solver) analysis module. A very high correlation coefficient was obtained ($R^2=0.9895$ for % exhaustion, $R^2=0.9932$ for fixation) for the model which shows prominent prediction capacity of the model for the unknown conditions. The predictable polynomial equations developed from the Experimental results were thoroughly analyzed by ANOVA (Analysis of Variance) statistical concepts.

• Textile Coloration and Finishing
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• v.20 no.2
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• pp.19-28
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• 2008

The objective of this study was to apply the statistical technique known as design of experiments to optimize the % exhaustion variables for phthalocyanine dyeing of nylon fiber. In this study, a three-factor Central Composite Rotatable Design (CCRD) was used to establish the optimum conditions for the phthalocyanine reactive dyeing of nylon fiber. Temperature, pH and liquor ratio were considered as the variable of interest. Acidic solution with higher temperature and lower liquor ratio were found to be suitable conditions for higher % exhaustion. These three variables were used as independent variables, whose effects on % exhaustion were evaluated. Significant polynomial regression models describing the changes on % exhaustion and % fixation with respect to independent variables were established with coefficient of determination, R2, greater than 0.90. Close agreement between experimental and predicted yields was obtained. Optimum conditions were obtained using surface plots and Monte Carlo simulation techniques where maximum dyeing efficiency is achieved. The significant level of both the main effects and interaction was observed by analysis of variance (ANOVA) approach. Based on the statistical analysis, the results have provided much valuable information on the relationship between response variables and independent variables. This study demonstrates that the CCRD could be efficiently applied for the empirical modeling of % exhaustion and % fixation in dyeing. It also shows that it is an economical way of obtaining the maximum amount of information in a short period of time with least number of experiments.

• Textile Coloration and Finishing
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• v.19 no.2
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• pp.14-23
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• 2007

This research article explores the use of phthalocyanine reactive dye on nylon substrate. The effect of factors such as pH, temperature, liquor ratio and alkali addition on level of dye exhaustion, fixation and total fixation efficiency. Low pH, high temperature and low liquor ratio were found to be suitable conditions for maximum % exhaustion values. The effect of sulphatoethylsulphone(SES) and vinylsulphone(VS) form of the dyes on level of dye fixation was also discussed. The optimized exhaustion (%E), fixation(%F) and total fixation efficiency were determined. Modification of the dyeing process with alkali addition displayed that dye fixation(%) increased by alkali addition. Vinylsulphone(VS) moiety of the dye was found to be superior to. maximum fixation (%F). Appropriate predictable empirical models, relatively a new approach in dyeing processes, were developed incorporating interactions effects of temperature, pH and liquor ratio for predicting % exhaustion, fixation and total fixation efficiency. The significance of the mathematical model developed was ascertained using microsoft excel regression(solver) analysis module. High correlation coefficient was obtained (R2=0.9895 for % exhaustion, R2=0.9932 for fixation, R2=0.9965 for total fixation efficiency) for the model which shows prominent prediction capacity of the model for my conditions. The predictable polynomial equations developed from tile experimental results were thoroughly analyzed by ANOVA (Analysis of Variance) statistical concepts.

• Journal of Biosystems Engineering
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• v.37 no.4
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• pp.258-264
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• 2012

Purpose: This review aims at introducing 3 modeling approaches classified into 3 categories based on the purpose (estimation or prediction), structure (linear or non-linear) and phase (steady-state or dynamic-state); 1) statistical approaches, 2) kinetic modeling and 3) mechanistic modeling. We hope that this review can be a useful guide in the model-based approach of calcium metabolism as well as illustrates an application of engineering tools in studying biosystems. Background: The meaning of biosystems has been expanded, including agricultural/food system as well as biological systems like genes, cells and metabolisms. This expansion has required a useful tool for assessing the biosystems and modeling has arisen as a method that satisfies the current inquiry. To suit for the flow of the era, examining the system which is a little bit far from the traditional biosystems may be interesting issue, which can enlarge our insights and provide new ideas for prospective biosystem-researches. Herein, calcium metabolic models reviewed as an example of application of modeling approaches into the biosystems. Review: Calcium is an essential nutrient widely involved in animal and human metabolism including bone mineralization and signaling pathways. For this reason, the calcium metabolic system has been studied in various research fields of academia and industries. To study calcium metabolism, model-based system analyses have been utilized according to the purpose, subject characteristics, metabolic sites of interest, and experimental design. Either individual metabolic pathways or a whole homeostasis has been modeled in a number of studies.