• Journal of the Korea Convergence Society
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• v.12 no.10
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• pp.9-17
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• 2021

With the advancement of big data analysis, artificial intelligence, machine learning, etc., data analytics technology has developed to help with optimal decision-making. However, in certain areas, the lack of data restricts the use of these techniques. For example, real estate related data often have a long release cycle because of its recent release or being a non-liquid asset. In order to overcome these limitations, we studied the scalability of the existing time series through the TimeGAN model. A total of 45 time series related to weekly real estate data were collected within the period of 2012 to 2021, and a total of 15 final time series were selected by considering the correlation between the time series. As a result of data expansion through the TimeGAN model for the 15 time series, it was found that the statistical distribution between the real data and the extended data was similar through the PCA and t-SNE visualization algorithms.

• Convergence Security Journal
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• v.23 no.5
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• pp.57-64
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• 2023

In this study, we analyzed how to steal the target model without training data. Input data is generated using the generative model, and a similar model is created by defining a loss function so that the predicted values of the target model and the similar model are close to each other. At this time, the target model has a process of learning so that the similar model is similar to it by gradient descent using the logit (logic) value of each class for the input data. The tensorflow machine learning library was used as an experimental environment, and CIFAR10 and SVHN were used as datasets. A similar model was created using the ResNet model as a target model. As a result of the experiment, it was found that the model stealing method generated a similar model with an accuracy of 86.18% for CIFAR10 and 96.02% for SVHN, producing similar predicted values to the target model. In addition, considerations on the model stealing method, military use, and limitations were also analyzed.

• Korea Trade Review
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• v.43 no.5
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• pp.139-158
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• 2018

As trade volume increases and the business environment becomes more complex and competitive, international trade disputes are also increasing and becoming more complex. Parties need to become more aware of alternatives to costly and time consuming arbitration and litigation. The ADR (Alternative Dispute Resolution) can encompass all dispute resolution processed and can act as a substitute for traditional litigation. Mediation, a type of ADR, offers an amicable dispute settlement mechanism between concerned parties through a natural mediator. There are several strong points of mediation compared with litigation or arbitration. First of all, mediation can take place without having to complete time-consuming and expensive discovery processes associated with litigation. In addition, since mediation is considered a private process, the dispute can remain out of the public eye. It can be embarrassing and disrupt business when customer or suppliers learn that a company is involved in litigation. Lastly, mediation is less adversarial than litigation or arbitration, so the parties often can salvage their relationships. Often the parties to mediation find themselves continuing to conduct business. In spite of such benefits of mediation, it is less used in Korea and therefore, this article aims to promote the mediation system in international trade disputes. However, this paper has limitation, for example, why ADR is not used well in Korea and need to suggest how ADR can work best in international trade disputes.