• Proceedings of the Korean Society for Quality Management Conference
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• 2006.04a
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• pp.149-152
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• 2006

In this paper, We study several method of CTQ measurement for improvement of Quality. Measurement are cornerstone of basic improvement of Science and Technology and are considered continuous thesis. In this paper, we survey measure several variable for CTQ for Six sigma. We introduce Taguchi's SN ration Which is important example good measure for improve quality Improvement are succeed by good select measure variable which is called CTQ which should agree problem define and final goal.

• Smart Structures and Systems
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• v.4 no.4
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• pp.493-515
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• 2008

Semi-active control systems have attracted a great deal of attention in recent years because these systems can operate on battery power alone, proving advantageous during seismic events when the main power source of the structure may likely fail. The behavior of semi-active devices is often highly non-linear and requires suitable and efficient control algorithm. This paper presents the comparative study and performance of variable semi-active friction dampers by using recently proposed predictive control law with direct output feedback. In this control law, the variable slip force of semi-active variable friction damper is kept slightly lower than the critical friction force, which allows the damper to remain in the slip state during an earthquake, resulting in improved energy dissipation capability. This control algorithm is able to produce a continuous and smooth slip forces for a variable friction damper. The numerical examples include a structure controlled with multiple variable semi-active friction dampers and with multiple passive friction dampers. A parameter, gain multiplier defined as the ratio of damper force to critical damper control force, is investigated under four different real earthquake ground motions, which plays an important role in the present control algorithm of the damper. The numerically evaluated optimum parametric value is considered for the analysis of the structure with dampers. The numerical results of the variable friction dampers show better performance over the passive dampers in reducing the seismic response of structures.

• Transactions of the Korean Society of Automotive Engineers
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• v.17 no.5
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• pp.7-15
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• 2009

This paper introduces a new variable valve actuation mechanism with movable second cam center. Valve lift and open duration can be continuously varied according to engine speed and load conditions. A new method to analyze the kinematic relations between the first and second cam profiles and valve motion are also introduced. Because of rocker motion of the second cam, conventional motion conversion program could not be used in this problem. An example shows continuous variations of valve motion and adequate ramp incorporation throughout all valve lift modes. Valve acceleration profile at the high lift mode is similar to that of conventional valvetrains. Contact geometry analysis of the mechanism gives basic information on the load conditions between the components.

• Journal of Korean Society for Quality Management
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• v.26 no.2
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• pp.39-50
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• 1998

A screening procedure, where one or more correlated variables are used for screeing, is reviewed from the point of statistical hypothesis testing. Without assuming a specific probability model for the joint distribution of the performance and screening variables, some principles are provided to establish the best screeing region. A, pp.ication examples are provided for two cases; ⅰ) the case where the performance variable is dichotomous and ⅱ) the case where the performance variable is continuous. In case ⅰ), a normal model is assumed for the conditional distribution of the screening variable given the performance variable. In case ⅱ), the performance and screening variables are assumed to be jointly normally distributed.

• Journal of Korean Institute of Industrial Engineers
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• v.28 no.3
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• pp.240-246
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• 2002

In this paper, economic screening procedures with dichotomous performance variable T and continuous screening variable X are considered when the rejected items are reprocessed. Two models are considered; normal and logistic models. It is assumed that X given T is normally distributed in the normal model, and P(T=1|X=x) is given by a logistic function in the logistic model. Profit models are constructed which involve four price/cost components; selling price, cost from an accepted nonconforming item, and reprocessing and inspection costs. Methods of finding the optimal screening procedures are presented and numerical examples are given.

• Industrial Engineering and Management Systems
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• v.14 no.2
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• pp.210-219
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• 2015

A classification task requires an exponentially growing amount of computation time and number of observations as the variable dimensionality increases. Thus, reducing the dimensionality of the data is essential when the number of observations is limited. Often, dimensionality reduction or feature selection leads to better classification performance than using the whole number of features. In this paper, we study the possibility of utilizing the Markov blanket discovery algorithm as a new feature selection method. The Markov blanket of a target variable is the minimal variable set for explaining the target variable on the basis of conditional independence of all the variables to be connected in a Bayesian network. We apply several Markov blanket discovery algorithms to some high-dimensional categorical and continuous data sets, and compare their classification performance with other feature selection methods using well-known classifiers.

• The Journal of Information Systems
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• v.26 no.3
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• pp.211-228
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• 2017

Purpose This study proposes a research model based on Expectation-Confirmation theory in order to investigate impacts of three variables(expectation confirmation, social interaction, and perceived usefulness) on continuous intention to uss SNS in MICE industry. Design/methodology/approach A survey approach was used in order to measure each latent variable in the research model. A total of 140 responses were collected from actual users of SNS in MICE industry. A structural equation modeling with SmartPLS 2.0 was conducted in order to analyze each relationship in the proposed research model. Findings The results indicated the expectation confirmation had a positive impact on the perceived usefulness, social interaction, and satisfaction. Second, perceived usefulness had a significant positive impact on satisfaction and continuous intention to use SNS in MICE industry. Thrid, social interaction had a positive influence on both satisfaction and continuous intention to use SNS in MICE industry. Finally, the relationship between satisfaction and continuous intention in SNS of MICE industry was fully supported.

• Journal of Information Processing Systems
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• v.16 no.3
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• pp.588-598
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• 2020

An alternative state estimation filtering algorithm is designed for continuous time systems with noises as well as control input. Two kinds of estimation filters, which have different measurement memory structures, are operated selectively in order to use both filters effectively as needed. Firstly, the estimation filter with infinite memory structure is operated for a certain continuous time system. Secondly, the estimation filter with finite memory structure is operated for temporarily uncertain continuous time system. That is, depending on the presence of uncertainty, one of infinite memory structure and finite memory structure filtered estimates is operated selectively to obtain the valid estimate. A couple of test variables and declaration rule are developed to detect uncertainty presence or uncertainty absence, to operate the suitable one from two kinds of filtered estimates, and to obtain ultimately the valid filtered estimate. Through computer simulations for a continuous time aircraft engine system with different measurement memory lengths and temporary model uncertainties, the proposed state estimation filtering algorithm can work well in temporarily uncertain as well as certain continuous time systems. Moreover, the proposed state estimation filtering algorithm shows remarkable superiority to the infinite memory structure filtering when temporary uncertainties occur in succession.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.4
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• pp.463-468
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• 2011

Context prediction methods have been developed in two ways - one is a prediction for discrete context and the other is for continuous context. As most of the prediction methods have been used with prediction algorithms in specific domains suitable to the environment and characteristics of contexts, it is difficult to conduct a prediction for a user's context which is based on various environments and characteristics. This study suggests a context prediction method available for both discrete and continuous contexts without being limited to the characteristics of a specific domain or context. For this, we conducted a context prediction based on sequence matching by generating sequences from contexts in consideration of association rules between context attributes and by applying variable weights according to each context attribute. Simulations for discrete and continuous contexts were conducted to evaluate proposed methods and the results showed that the methods produced a similar performance to existing prediction methods with a prediction accuracy of 80.12% in discrete context and 81.43% in continuous context.

• The Journal of the Acoustical Society of Korea
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• v.22 no.7
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• pp.528-538
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• 2003

A SCCRS (Speech and Character Combined Recognition System) is developed for working on mobile devices such as PDA (Personal Digital Assistants). In SCCRS, the feature extraction is separately carried out for speech and for hand-written character, but the recognition is performed in a common engine. The recognition engine employs essentially CHMM (Continuous Hidden Markov Model), which consists of variable parameter topology in order to minimize the number of model parameters and to reduce recognition time. For generating contort independent variable parameter model, we propose the SSMS(Successive State and Mixture Splitting), which gives appropriate numbers of mixture and of states through splitting in mixture domain and in time domain. The recognition results show that the proposed SSMS method can reduce the total number of GOPDD (Gaussian Output Probability Density Distribution) up to 40.0% compared to the conventional method with fixed parameter model, at the same recognition performance in speech recognition system.