• International Journal of Quality Innovation
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• v.1 no.1
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• pp.89-96
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• 2000

Evolutionary operation (EVOP) is a continuous improvement system which explores a region of process operating conditions by deliberately creating some systematic changes to the process variable levels without jeopardizing the product. It is aimed at securing a satisfactory operating condition in full-scale manufacturing processes, which is generally different from that obtained in laboratory or pilot plant experiments. Information on how to improve the process is generated from a simple experimental design. Traditional EVOP procedures are established on the assumption that the variance of the response variable should be small and stable in the region of the process operation. However, it is often the case that process noises have an influence on the stability of the process. This process instability is due to many factors such as raw materials, ambient temperature, and equipment wear. Therefore, process variables should be optimized continuously not only to meet the target value but also to keep the variance of the response variables as low as possible. We propose a scheme to achieve robust process improvement. As a process performance measure, we adopted the mean square error (MSE) of the replicate response values on a specific operating condition, and used the Kruskal-Wallis test to identify significant differences between the process operating conditions.

• Journal of Korean Academy of Rural Health Nursing
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• v.10 no.1
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• pp.5-15
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• 2015

Purpose: This study was conducted to analyze the concept of nurses' emotional labor. Method: Rodgers's evolutionary concept analysis was used. Result: Nurses' emotional labor can be defined by two attributes: emotional distortion and self-regulation process. Antecedents of nurses' emotional labor include interactional, organizational and personal factors. The consequences of nurses' emotional labor are emotional dissonance and internalization of organizational display rules. Conclusion: Appropriate instrument to operationalize the concept need to be developed.

• Proceedings of the Korea Concrete Institute Conference
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• 1997.10a
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• pp.533-538
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• 1997

Topology optimization of a concrete structure is discussed using an Evolutionary Structural Optimization(ESO) method introduced by Xie and Steven. During the evolution process low stressed materials are progressively removed from the structure. This paper discussed a proper rejection criterion(RC) to get a more reasonable topology of concrete structure. Some examples are presented to illustrate the optimum topology achieved by such a procedure.

• Journal of the Economic Geographical Society of Korea
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• v.11 no.4
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• pp.509-526
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• 2008

This paper aims to examine the evolutionary dynamics of the Korea's footwear industry by adopting evolutionary perspectives. To explain the evolutionary dynamics of an industry, evolutionary perspectives have paid a particular attention to exploring a variety of factors for influencing the evolution of the industry, such as the selection and imitation of the firm, the mechanism of firm's entry and exit, technological characteristics and innovation processes. The majority of existing research tend to explain that the decline of the Korea's footwear industry since 1990 was mostly due to the rapid rising of wage and the structural changes in labor-intensive industries. On the contrary, this paper attempts to explain the decline of the Korea's footwear industry, in terms of the path of selection and imitation, the dominant technological paradigm, regulatory frameworks and the meso trajectory of industry evolution. This paper concludes that the decline of the Korea's footwear industry since 1990 was appeared as a result of the evolutionary selection processes of the firms in order to adapt to changes in the environment of competition and the regime of market selection in the global footwear industry.

• Journal of the Korean Statistical Society
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• v.36 no.2
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• pp.201-208
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• 2007

Evolutionary operation (EVOP) proposed by Box (1957) is a method for continuous monitoring and improvement of a full-scale manufacturing process with the objective of moving the operating conditions toward the better ones. EVOP consists of systematically making small changes in the levels of the two or three process variables under consideration. Data are collected on the response variable at each point of two level factorial design with the center point and a cycle is said to have been completed. The cycles are replicated sequentially until the decision is made on whether further cycle of experiments is needed to conclude the significance of any of main effects or interaction effects or the curvature. In this paper, an improved flow chart of EVOP is proposed and how to determine the number of cycles is studied based on the size of type II error. In order to reject the alternative hypothesis of interests with more confidence and conclude that we believe in the null hypothesis of no effects, we propose a counter measure $p^*-value$ corresponding to the p-value. The relationship of $p^*-value$ to the probability of type II error ${\beta}$ under the alternative hypothesis of interests is analogous to that of p-value to the probability of type I error ${\alpha}$. Also the implementation of EVOP with a mixture experiment is discussed.

• Korean Journal of Cognitive Science
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• v.28 no.3
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• pp.173-191
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• 2017

The theories of cultural evolution hold subtly or clearly different stances about definition of culture, pattern of cultural evolution, biases that affect cultural evolution, and relationship between culture and organism. However, the cultural evolution theories have a common problem to solve: As the evolutionary theory of life tries to explain the early steps and the origin of life, the cultural evolution theories also must explain the early steps of the cultural evolution and the role of the human capability that makes cultural evolution possible. Therefore, explanations of the human's unique traits including the cultural ability are related to determine which one is the most plausible among many cultural evolution theories. Theories that tried to explain human uniqueness commonly depict the coevolution of gene (organism) and culture. We will explicitly call the niche construction theory and the dual inheritance theory the 'gene-culture co-evolutionary theory'. In these theories, the most important concept is the 'concept of positive feedback'. In this paper, we distinguish between core positive feedback and marginal positive feedback, according to whether the trait that the concept of positive feedback explains is the trait of human uniqueness. Both types of positive feedback effectively explain the generality of human uniqueness and the diversity of human traits driven by cultural groups. However, this positive feedback requires an end, in contrast to negative feedback which can be continued in order to maintain homeostasis. We argue that the co-evolutionary process in the gene-culture co-evolutionary theories include only the positive feedback, not covering the cultural evolution after the positive feedback. This thesis strives to define the coevolution concept more comprehensively by suggesting the potential relationships between gene and culture after the positive feedback.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.195-204
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• 2003

Network optimization is being increasingly important and fundamental issue in the fields such as engineering, computer science, operations research, transportation, telecommunication, decision support systems, manufacturing, and airline scheduling. Networks provide a useful way to modeling real world problems and are extensively used in practice. Many real world applications impose on more complex issues, such as, complex structure, complex constraints, and multiple objects to be handled simultaneously and make the problem intractable to the traditional approaches. Recent advances in evolutionary computation have made it possible to solve such practical network optimization problems. The invited talk introduces a thorough treatment of evolutionary approaches, i.e., hybrid genetic algorithms approach to network optimization problems, such as, fixed charge transportation problem, minimum cost and maximum flow problem, minimum spanning tree problem, multiple project scheduling problems, scheduling problem in FMS.

• Journal of Global Scholars of Marketing Science
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• v.7
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• pp.71-103
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• 2001

Marketing practice varies among firms. However, the prescriptive literature emphasises a universal view of practice, a 'one size fits all' view. This paper addresses the issue of explaining diversity in marketing practice in competitive space and in time. Diversity in competitive space reflects the existence of different routes to high performance. Diversity in time reflects some combination of change in the individual firm and change in a population of firms. In the former case, diversity is shaped by organisational change; in the latter by the disbandment and founding of firms in the population. In so far as diversity is the norm, the manner in which practice will be shaped by evolutionary processes is considered. Fnally, the role of the academy as one of the forces driving the evolutionary process is discussed. Miles and Snow's (1978, 1986) work is taken as a main point of departure in the search for explanation and ecological and evolutionary concepts are drawn on for support and to suggest an explanation for the nature of diversity over time.

• Journal of Mechanical Science and Technology
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• v.14 no.9
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• pp.913-919
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• 2000

The purpose of this study was to develop a new element removal method for ESO (Evolutionary Structural Optimization), which is one of the topology optimization methods. ESO starts with the maximum allowable design space and the optimal topology emerges by a process of removal of lowly stressed elements. The element removal ratio of ESO is fixed throughout topology optimization at 1 or 2%. BESO (bidirectional ESO) starts with either the least number of elements connecting the loads to the supports, or an initial design domain that fits within the maximum allowable domain, and the optimal topology evolves by adding or subtracting elements. But the convergence rate of BESO is also very slow. In this paper, a new element removal method for ESO was developed for improvement of the convergence rate. Then it was applied to the same problems as those in papers published previously. From the results, it was verified that the convergence rate was significantly improved compared with ESO as well as BESO.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.643-646
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• 2002

This paper proposes an evolutionary computation approach for automated design of mechanical structures especially in its early stage of design phases. Due to the known characteristics of the stage, the approach basically involves a synthetic design method with the composition of building blocks representing the elements of mechanical objects. In order for the building blocks to be more suitable for representation and evolution of mechanical structures, Elementary Cell Blocks (ECBs) are introduced as new building blocks. A new Darwinian evolution process for the new building blocks is also necessarily involved in the approach. We have demonstrated the implementation of the approach with the design of multi-step gear systems.