• The Journal of Fisheries Business Administration
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• v.48 no.2
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• pp.1-17
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• 2017

This work studies the variability of flatfish sales revenue. The theoretical analysis draws functions for equilibrium price and quantity using expectation hypotheses. The functions include unpredictable phenomenon with dummy variable and GARCH. The equilibrium function, using adaptive expectation hypothesis, contains the independent variables of supply and demand, while the equilibrium function, embodying rational expectation hypothesis, includes only the independent variables of supply side, because the demand side disappears by the information extraction process theoretically, if economic subjects build the expectation rational. The empirical analysis shows: the variability of flatfish production has a spillover effect on the variability of revenue with the adaptive expectation hypothesis. In the case when the model has a rational expectation hypothesis, the variability of flatfish production has a spillover effect on the revenue (the mean equation of GARCH model). This study indicates that there is the variability in flatfish production and sales revenue, and the spillover effect between them. The result can help to build of the rational system for the fishery income stability.

• ETRI Journal
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• v.41 no.3
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• pp.383-395
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• 2019

Clock Controlled Dual keeper Domino logic structures (CCDD_1 and CCDD_2) for achieving a high-speed performance with low power consumption and a good noise margin are proposed in this paper. The keeper control circuit comprises an additional PMOS keeper transistor controlled by the clock and foot node voltage. This control mechanism offers abrupt conditional control of the keeper circuit and reduces the contention current, leading to high-speed performance. The keeper transistor arrangement also reduces the loop gain associated with the feedback circuitry. Hence, the circuits offer less delay variability. The design and simulation of various wide fan-in designs using 180 nm CMOS technology validates the proposed CCDD_1 and CCDD_2 designs, offering an increased speed performance of 7.2% and 8.5%, respectively, over a conventional domino logic structure. The noise gain margin analysis proves good robustness of the CCDD structures when compared with a conventional domino logic circuit configuration. A Monte Carlo simulation for 2,000 runs under statistical process variations demonstrates that the proposed CCDD circuits offer a significantly reduced delay variability factor.

• Journal of the Korean Operations Research and Management Science Society
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• v.12 no.1
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• pp.111-111
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• 1987

With the increasing interest of reducing process variation, statistical process control has served the pivotal tool in most industrial quality programs. In this study, system analyses have been performed associated with a cost incorporated version of a process control, a quadratic loss-based X over bar control chart model. Specifically, two issues, the capital/research investments for improvement of a system and the precision of a parameter estimation, have been addressed and discussed. Through the analysis of experimental results, we show that process variability is seen to be one of the most important sources of loss and quality improvement efforts should be directed to reduce this variability. We further derive the results that, even if the optimal designs may be sensitive, the model appears to be robust with regard to misspecification of parameters. The approach and discussion taken in this study provide a meaningful guide for proper process control. We conclude this study with providing general comments.

• Korean Management Science Review
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• v.12 no.1
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• pp.111-124
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• 1995

With the increasing interest of reducing process variation, statistical process control has served the pivotal tool in most industrial quality programs. In this study, system analyses have been performed associated with a cost incorporated version of a process control, a quadratic loss-based X over bar control chart model. Specifically, two issues, the capital/research investments for improvement of a system and the precision of a parameter estimation, have been addressed and discussed. Through the analysis of experimental results, we show that process variability is seen to be one of the most important sources of loss and quality improvement efforts should be directed to reduce this variability. We further derive the results that, even if the optimal designs may be sensitive, the model appears to be robust with regard to misspecification of parameters. The approach and discussion taken in this study provide a meaningful guide for proper process control. We conclude this study with providing general comments.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.10a
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• pp.39-44
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• 2004

A desirability function approach to a multiresponse problem is proposed considering process parameter fluctuation as well as distance-to-target of response and response variance. The variation of process parameters amplifies the variance of responses. It is called POE (propagation of error), which is defined as the standard deviation of the transmitted variability in the response as a function of process parameters. In order to obtain more robust process parameters, this variability should be considered in the optimization problem. The proposed method is illustrated using a rubber product case.

• Journal of KIISE:Software and Applications
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• v.33 no.6
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• pp.550-563
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• 2006

Software product line engineering is a method that prepares for the future reuse and supports to seamless reuse in application development process. Commonality and variability play central roles in all product line development processes. Reusable assets will become core assets by explicitly representing C&V. Indeed, the variabilities that art identified at each phase of core assets development have different levels of abstraction. In the past, these variabilities have been handled in an implicit manner and without distinguishing the characteristics of each core assets. In addition, previous approaches have depended on the experience and intuition of a domain expert to recognize commonality and variability. In this paper, we suggest a 2-dimensional analyzing method that analyzes the variabilities of core assets in software product line. In horizontal analysis process, the variation types are analyzed in requirements, architecture, and component that are produced at each phase of development process. In vertical analysis process, variations are analyzed in different abstract levels, in which the region of commonality is identified and the variation points are refined. By this method, the traceability of variations between core assets will be possible and core assets can be reused seamlessly.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2000.10a
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• pp.136-140
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• 2000

It is desirable to predict springback quantitatively and accurately for the tool and process design in sheet stamping operations, however, it is blown very difficult. The result of springback analysis by the finite element method is sensitively influenced by numerical factors such as blank element size, number of integration point, punch velocity, contact algorithm etc. In the present work, a parametric study by Taguchi method is performed in order to evaluate the influence of numerical factors on springback Quantitatively and to obtain the combination of numerical factors which yields the best approximation to experimental data. Since springback is determined by the residual stress after forming process, it is important to evaluate stress distribution accurately. The oscillation in the time history curve of stress obtained by explicit FEM says that the stress solution at termination time is in very unstable state. Therefore, a variability study is also carried out in this study in order to assess the stability of implicit springback analysis starting from the stress solution by explicit forming simulation. The 2D draw bending process, one of the NUMISHEET '93 benchmark problems, is adopted as an application model.

• Journal of KIISE:Software and Applications
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• v.32 no.3
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• pp.163-172
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• 2005

Product Line Engineering (PLE) has been widely accepted as a representative software reuse methodology by using core assets. Product line architecture (PLA) is a key element of core assets. However, current research works on designing PLA do not provide sufficient and detailed guidelines of defining PLA and reflecting variability in the architecture. In this paper, we present a reference model of PLA and propose a process to design PLA with detailed instructions. Especially architectural variability is codified by describing decision model depending variation points and traced through PLA activities. The proposed process would make it feasible to apply PLE to practice areas.

• International Journal of Quality Innovation
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• v.4 no.1
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• pp.148-159
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• 2003

Variation is the archenemy of quality. To reduce or control the variation in a complex production unit, firstly we need to identify the location of the root cause of the variation. This paper discusses the detection of variability and the techniques used for reduction of variation for a production unit consisting of many processes. In the first part of this paper, the background of variability detection in production systems is introduced which is then followed by a weighted network corresponding to correlation matrix of all processes. Based on the network and clustering criterion of maximum spanning tree, a classification of all processes is derived. Furthermore, the variation of each process in a class is determined by residual analysis. In the last part, the use of methods of robust design for the processes with a larger variability is discussed.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.9
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• pp.1691-1699
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• 1992

The experimental results of fatigue crack propagation under constant amplitude loading show that intra-and inter-specimen variability exist. In this paper, a stochastic model for the estimation of mean and variance of crack propagation life is presented To take into account the intra-specimen variability, the material resistance against crack propagation is treated as an 1-dimensional spatial stochastic process, i. e. random field, varying along the propagation path. For the inter-specimen variability, C in paris equation is assumed to be a random variable. Compared with experimental results reported, the present method well estimate the variation in fatigue crack propagation life. And it is confirmed that the thicker the specimen thickness is, the less the variation of propagation life is.