• KSBB Journal
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• v.16 no.2
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• pp.107-114
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• 2001

The dynamic evolution process has resulted in the myriad shapes, functions, and systems evident in every living organism. For centuries, people have been harnessing the power of evolution to produce new varieties of plants and animals, such as producing tomatoes from berries and Chihuahuas from wolves. Now scientists are using it to produce better molecules, ranging from drugs to industrial chemicals, and doing it in days or weeks rather than eons. The ingenious process, which creates genetic diversity and selects those with desired features in the laboratory, is called directed evolution or test tube evolution. In this paper, concepts of directed molecular evolution and some examples will be discussed.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2008.10a
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• pp.38-41
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• 2008

To investigate the evolution of microstructure and texture in AZ31 Mg alloy, direct/indirect extrusion process was carried out at $300^{\circ}C$ with various extrusion speeds. The distribution of grain size depends on extrusion method and extrusion speed. More homogeneous grain site can be obtained at higher extrusion speed of indirect extrusion process. Extrusion speed does not affect significantly texture evolution during extrusion process regardless of extrusion method. ODF section is more useful to understand texture evolution during extrusion process compared with pole figure.

• Journal of Technology Innovation
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• v.28 no.4
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• pp.63-93
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• 2020

We suggest a new way of specifying the co-evolution of product and process technologies, and integrating it into one of the well-received technology intelligence tools - a technology radar. Cross impact analysis enables us to identify the core technologies of product-process co-evolution. Combining expert judgment with its results, we can clarify the technological co-evolution trajectory with mainstream as well as emerging core technologies. Reflecting these in the assessment process of a technology radar, we could improve reliance of the technology assessment process and technology portfolio. From the academic perspective, our research provides a point where the co-evolution theory encouners technology intelligence methods. Practically, strategic capability of future-preparedness and strategic management could improve by adopting our method based on our example of co-evolution of semiconductor product and process technologies.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2007.10a
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• pp.53-56
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• 2007

Computer simulation of microstructure evolution during hot forging process is of great interest in recent years. Recrystallization model and grain growth model which use a phenomenological approach were summarized. For the waspaloy, upsetting process and cogging process were simulated using $DEFORM^{TM}$ and the change in grain size were investigated in each deformation procedure.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.11
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• pp.1809-1814
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• 2003

Differential evolution (DE) algorithm is presented and applied to global optimization in this research. DE suggested initially fur the solution to Chebychev polynomial fitting problem is similar to genetic algorithm(GA) including crossover, mutation and selection process. However, differential evolution algorithm is simpler than GA because it uses a vector concept in populating process. And DE turns out to be converged faster than CA, since it employs the difference information as pseudo-sensitivity In this paper, a trial vector and its control parameters of DE are examined and unconstrained optimization problems of highly nonlinear multimodal functions are demonstrated. To illustrate the efficiency of DE, convergence rates and robustness of global optimization algorithms are compared with those of simple GA.

• Journal of Computing Science and Engineering
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• v.9 no.2
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• pp.73-82
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• 2015

Understanding how the topic evolves is an important and challenging task. A topic usually consists of multiple related events, and the accurate identification of event evolution relationship plays an important role in topic evolution analysis. Existing research has used the traditional vector space model to represent the event, which cannot be used to accurately compute the semantic similarity between events. This has led to poor performance in identifying event evolution relationship. This paper suggests constructing a semantic aspect-based vector space model to represent the event: First, use hierarchical Dirichlet process to mine the semantic aspects. Then, construct a semantic aspect-based vector space model according to these aspects. Finally, represent each event as a point and measure the semantic relatedness between events in the space. According to our evaluation experiments, the performance of our proposed technique is promising and significantly outperforms the baseline methods.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.4
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• pp.701-710
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• 2002

The framework, described in this paper, involves artificial evolutionary systems that re -produce aimed solutions through a simulated Darwinian evolution process. Through this process the framework designs structures of machines innovatively and emergently especially in the stages of conceptual and basic design. Since the framework simulates the evolution of nature, it inevitably involves processes that converse the natural evolution to the artificial evolution. For the conversion, based on several methods as the building block modeling, Artificial Life, evolutionary computation and the law of natural selection, we propose a series of processes that consists of modeling, evaluation, selection, evolution etc. We have demonstrated the implementation of the framework with the design of multi-step gear systems.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.7
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• pp.129-138
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• 1998

The objective of this study is to demonstrate the ability of a computer simulation of microstructural evolution in hot forging of C-Mn steels. The development of microstructure is strongly dependent on process variables and metallurgical factors that affect time history of thermodynamical variables such as temperature, strain. and strain rate during deformation. Then finite element method is applied for the prediction of microstructural evolution, and it should be coupled with heat transfer analysis to consider the change of thermodynamical properties during forming process. In this study, Yada's recrystallization model and rigid-thermoviscoplastic finite element method are employed in order to analyze microstructural evolution during hot forging process. To show the validity and effectiveness of the proposed method, experiments are accomplished and the results of experiments are compared with those of simulations.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.5
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• pp.119-133
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• 2022

The purpose of this study is to examine how change recipients react to change (affective commitment to change) and how change leads to positive consequences (job satisfaction) in Revolution and Evolution, taking into account the change content (perceived change impact), change context (change climate), and change process (participation in the change process). The present study uses a deductive approach with an exploratory research design. Data was collected from 254 employees of the head offices of three major banks, who have gone through Revolution, and 354 employees of the head offices, three banks who have gone through Evolution in the last five years. The hypothesized model is tested and analyzed through structural equation modeling using SmartPLS. The findings revealed that, in the case of Revolution, the presence of the favorable context and process might revert the negative perception of the change and lead towards explicit positive reactions (affective commitment to change) and change consequences (job satisfaction). In the case of Evolution, the change can be more effectively implemented using favorable context and process by achieving explicit positive reactions (affective commitment to change) and change consequences (job satisfaction).

• Journal of applied mathematics & informatics
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• v.5 no.3
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• pp.785-796
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• 1998

In this paper we propose a model of HIv population through method of phases with non-Markovian evolution of immi-gration. The analysis leads to an explicit differnetial equations for the generating functions of the total population size. The detection process of antibodies (against the antigen of virus) is analysed and an explicit expression for the correlation functions are provided. A measure of bunching is also introduced for some particular choice of parameters.