• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.181-186
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• 2005

In collaborative environment, it is necessary that the participants in collaboration should share the same understanding about the semantics of terms. For example, they should know that 'Part' and 'Item' are different word-expressions for the same meaning. In this paper, we consider sharing between CAD and PDM data. In order to handle such problems in information sharing, an information system needs to automatically recognize that the terms have the same semantics. Serving this purpose, the semantic mapping logic and the ontology based mapper system is described in this paper. In the semantic mapping logic topic, we introduce our logic that consists of four modules: Character Matching, Instance Reasoning, definition comparing and Similarity Checking. In the ontology based mapper, we introduce the system architecture and the mapping procedure.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2008.10a
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• pp.460-463
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• 2008

This study tries to apply standard cost accounting model to evaluate the cost of workflow instances. Previous studies mainly focus on matching workflow activities into the elements of Activity based costing in order to assign cost drivers, but rarely examine how to evaluate their instance cost. In this study, we estimate unrealized standard cost from workflow model, and realized cost from accomplished instances. On running, workflow engine cumulates cost of finished activities and it enables to monitor the difference between the target cost and the actual cost dynamically at each step of workflow processes. We implemented a prototype which shows that the proposed work can evaluate effectively the cost of various workflow patterns.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.575-579
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• 1990

This paper describes an algorithm that can efficiently analyze the multichannel ECG signal using the frame. The input is a set of significant features (points) which have been extracted from an original sampled signal by using the split-and-merge algorithm. A signal from each channel can be hierarchical ADN/OR graph on the basis of the priori knowledge for ECG signal. The search mechanisms with some heuristics and the mixed paradigms of data-driven hypothesis formation are used as the major control mechanisms. The mutual relations among features are also considered by evaluating a score based on the relational spectrum. For recognition of morphologies corresponding to OR nodes, an hypothesis modification strategy is used. Other techniques such as instance, priority update of prototypes, and template matching facility are also used. This algorithm exactly recognized the primary points and supporting points from the multichannel ECG signals.

• Journal of the Korea Society of Computer and Information
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• v.12 no.6
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• pp.287-295
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• 2007

This paper proposes a novel data editing techniques with genetic algorithm (GA) in case-based reasoning (CBR) for the prediction of Korea Stock Price Index (KOSPI). CBR has been widely used in various areas because of its convenience and strength in compelax problem solving. Nonetheless, compared to other machine teaming techniques, CBR has been criticized because of its low prediction accuracy. Generally, in order to obtain successful results from CBR, effective retrieval of useful prior cases for the given problem is essential. However. designing a good matching and retrieval mechanism for CBR system is still a controversial research issue. In this paper, the GA optimizes simultaneously feature weights and a selection task for relevant instances for achieving good matching and retrieval in a CBR system. This study applies the proposed model to stock market analysis. Experimental results show that the GA approach is a promising method for data editing in CBR.

• Journal of Soil and Groundwater Environment
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• v.27 no.4
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• pp.37-48
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• 2022

Accurate analysis of petroleum hydrocarbons in soil is an important prerequisite for proper source tracking of contamination. Identification of petroleum compounds is commonly carried out by peak pattern matching in gas chromatography. However, this method has several technical limitations, especially when the soils underwent biological, physical and chemical transformation. For instance, it is very difficult to distinguish jet fuel (JP-8) from kerosene because JP-8 is derivatized from secondary reaction between chemical agents (e.g. anti-oxidants, antifreezer and so on) and kerosene. In this study, an alternative method to separately analyze JP-8 and kerosene in the petroleum hydrocarbon contaminated soil was proposed. Qualitative analyses were performed for representative phenolic antioxidants [2,6-di-tert-butyl phenol (2,6-DTBP), 2,4-di-tert- butylphenol(2,4-DTBP), 2,6-di-tert-butyl-4-methyl phenol (2,6-DTBMP)] using a two dimensional gas chromatograph mass spectrometer (2D GC×GC-TOF-MS). This qualitative analysis of antioxidants in soil would be a useful complementary tool for the peak pattern matching method to identify JP-8 contamination in soil.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2435-2440
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• 2003

Manipulation of the nano/micro scale object has been a key technology in biology as the sizes of DNA, chromosome, nucleus, cell and embryo are within such order. For instance, for embryo cell manipulation, the cell injection is performed manually. The operator often spends over a year to carry out a cell manipulation project. Since the typical success rate of such operation is extremely low, automation of such biological cell manipulation has been asked. As the operator spends most of his time in finding the position of cell in the Petri dish and in injecting bio-material to the cell from the best orientation. In this paper, we propose a new strategy and a vision system, by which one can find, recognize and track nucleus, polar body, and zona pellucida of the embryo cell for automatic biomanipulation. The deformable template matching algorithm has been used in recognizing the nucleus and polar body of each cell. Result suggests that it outperforms the conventional methods.

• Proceedings of the Korean Vacuum Society Conference
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• 2014.02a
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• pp.351.2-351.2
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• 2014

Indium tin oxide (ITO) has a lot of variations of its properties because it is basically in an amorphous state. Therefore, the differences in composition ratio of ITO can result in alteration of electrical properties. Normally, ITO is considered as transparent conductive oxide (TCO), possessing excellent properties for the optical and electrical devices. Quantitatively, TCO has transparency over 80 percent within the range of 380nm to 780nm, which is visible light although its specific resistance is less than $10-3{\Omega}/cm$. Thus, the solar cell is the best example for which ITO has perfectly matching profile. In addition, when ITO is used as transparent conductive electrode, this material essentially has to have a proper work function with contact materials. For instance, heterojunction with intrinsic thin layer (HIT) solar cell could have both front ITO and backside ITO. Because each side of ITO films has different type of contact materials, p-type amorphous silicon and n-type amorphous silicon, work function of ITO has to be modified to transport carrier with low built-in potential and Schottky barrier, and approximately requires variation from 3 eV to 5 eV. In this study, we examine the change of work function for different sputtering conditions using ultraviolet photoelectron spectroscopy (UPS). Structure of ITO films was investigated by spectroscopic ellipsometry (SE) and scanning electron microscopy (SEM). Optical transmittance of the films was evaluated by using an ultraviolet-visible (UV-Vis) spectrophotometer

• The Journal of Asian Finance, Economics and Business
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• v.5 no.4
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• pp.127-133
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• 2018

Corporate social responsibility (CSR) is one of the strategies for managing firms' business activities but may have heterogeneity depending on ownership structures. This study investigates the association between group-affiliation and CSR activities. Drawing on a theory from the prior research, this study predicts that group-affiliated firms are less likely to invest on CSR activities. For instance, prior research finds that controlling shareholders expropriate the values of minority shareholders. As one of the motivations of investing on CSR activities is the harmonization among the stakeholders, it leads to the prediction that firms controlled by large shareholders are less likely to engage in CSR activities. Second, group-affiliated firms under poor financial performance benefit from other group members through sharing their financial resources. Thus, there is less incentive for managers of group-affiliated firms to increase their financial performance by conducting CSR. By leveraging firms listed in Korean stock market and CSR score from Korea Economic Justice Institute, the result shows that the group-affiliation is negatively related to CSR activities. The result is consistent in case of applying propensity score-matched sample. Based on the findings of this study, this paper contributes to the related literature by showing the significant association between group-affiliation and CSR decisions.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.11a
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• pp.516-525
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• 2005

Case-based reasoning (CBR) has been widely used in various areas due to its convenience and strength in complex problem solving. Generally, in order to obtain successful results from CBR, effective retrieval of useful prior cases for the given problem is essential. However, designing a good matching and retrieval mechanism for CBR systems is still a controversial research issue. Most prior studies have tried to optimize the weights of the features or selection process of appropriate instances. But, these approaches have been performed independently until now. Simultaneous optimization of these components may lead to better performance than in naive models. In particular, there have been few attempts to simultaneously optimize the weight of the features and selection of the instances for CBR. Here we suggest a simultaneous optimization model of these components using a genetic algorithm (GA). We apply it to a customer classification model which utilizes demographic characteristics of customers as inputs to predict their buying behavior for a specific product. Experimental results show that simultaneously optimized CBR may improve the classification accuracy and outperform various optimized models of CBR as well as other classification models including logistic regression, multiple discriminant analysis, artificial neural networks and support vector machines.

• Nonlinear Functional Analysis and Applications
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• v.28 no.2
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• pp.497-520
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• 2023

Numerous problems in science and engineering defined by nonlinear functional equations can be solved by reducing them to an equivalent fixed point problem. Fixed point theory provides essential tools for solving problems arising in various branches of mathematical analysis, such as split feasibility problems, variational inequality problems, nonlinear optimization problems, equilibrium problems, complementarity problems, selection and matching problems, and problems of proving the existence of solution of integral and differential equations.The theory of fixed is known to find its applications in many fields of science and technology. For instance, the whole world has been profoundly impacted by the novel Coronavirus since 2019 and it is imperative to depict the spread of the coronavirus. Panda et al. [24] applied fractional derivatives to improve the 2019-nCoV/SARS-CoV-2 models, and by means of fixed point theory, existence and uniqueness of solutions of the models were proved. For more information on applications of fixed point theory to real life problems, authors should (see [6, 13, 24] and the references contained in).