• Journal of Arbitration Studies
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• v.21 no.1
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• pp.57-72
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• 2011

According to Japanese Patent Act, the Japanese Patent Office, administrative organization, was authorized to decide validation of patent. However, Supreme Court of Japan held that a court is able to decide the invalidation of patent in 11th April, 2000, which caused the reform of Japanese Patent Act in June 2004. Reformed Patent Act established the article 104-3 and makes it for a court to decide the patentability where there are grounds for a patent invalidation. Through this amendment to the Patent Act, the legislative system to decide the patent validation has been reorganized and furthermore alleged infringer is allowed to argue against the patent validation by making use of infringement litigation procedure through defenses against patent invalidation as well as invalidation trial procedure for to file a request for a trial for patent invalidation to the Japanese Patent Office. That is to say, the article 104-3 was established in the Japanese Patent Act in the wake of Kilby, and thus a court, which is judicial authority, not administrative disposition agency is also able to decide the patent validation. Thus this article discuss how a court, the authority of which only patent infringement cases fell under, has been authorized to arbitrate cases about the patent validation and the decision of the patent validation in a court.

• Communications for Statistical Applications and Methods
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• v.21 no.1
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• pp.105-114
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• 2014

In this paper we suggest an efficient method to estimate the distribution function using the Bezier curve, and compare it with existing methods by simulation studies. In addition, we suggest a robust version of cross-validation criterion to estimate the number of Bezier points, and showed that the proposed method is better than the existing methods based on simulation studies.

• Journal of Internet Computing and Services
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• v.23 no.4
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• pp.45-55
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• 2022

The size of the cryptocurrency market is growing. For example, market capitalization of bitcoin exceeded 500 trillion won. Accordingly, many studies have been conducted to predict the price of cryptocurrency, and most of them have similar methodology of predicting stock prices. However, unlike stock price predictions, machine learning become best model in cryptocurrency price predictions, conceptually cryptocurrency has no passive income from ownership, and statistically, cryptocurrency has at least three times higher liquidity than stocks. Thats why we argue that a methodology different from stock price prediction should be applied to cryptocurrency price prediction studies. We propose Reverse Walk-forward Validation (RWFV), which modifies Walk-forward Validation (WFV). Unlike WFV, RWFV measures accuracy for Validation by pinning the Validation dataset directly in front of the Test dataset in time series, and gradually increasing the size of the Training dataset in front of it in time series. Train data were cut according to the size of the Train dataset with the highest accuracy among all measured Validation accuracy, and then combined with Validation data to measure the accuracy of the Test data. Logistic regression analysis and Support Vector Machine (SVM) were used as the analysis model, and various algorithms and parameters such as L1, L2, rbf, and poly were applied for the reliability of our proposed RWFV. As a result, it was confirmed that all analysis models showed improved accuracy compared to existing studies, and on average, the accuracy increased by 1.23%p. This is a significant improvement in accuracy, given that most of the accuracy of cryptocurrency price prediction remains between 50% and 60% through previous studies.

• Proceedings of the CALSEC Conference
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• 2001.08a
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• pp.155-163
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• 2001

There are cases that revoke the certification because of disclosure of private key, deprivation of qualification and the expiration of a term of validity based on PKI. So, a user have to confirm the public key whether valid or invalid in the certification. There are many method such as CRL, Delta-CRL, OCSP for the cert-validation of certification. But these method many problems which are overload traffic on network and the CRL server because of processing for cert-validation of certification. In this paper we proposed the realtime cert-validation of certification method which solved problems that are data integrity by different time between transmission and receiving for CRL, and overload traffic on network and the CRL server based on DARC.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2016.10a
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• pp.158-159
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• 2016

This paper aims to analyze design errors prevented by building information modeling (BIM)-based design validation to identify consideration factors for successfully implementing BIM-based design validation in the architecture, engineering, and construction (AEC) projects. More than 1,300 design errors detected by BIM-based design validation in three BIM-based projects in South Korea are categorized according to its causes, work types, and likelihoods to cause project delay and cost overrun. Each design error is analyzed by conducting face-to-face interviews with practitioners in the three projects.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.122-125
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• 2007

In recent years, there has been an increasing demand for improved accuracy and reliability of Earth Observation Satellite (EOS) data. Most of the data users in the field of remote sensing require understanding of product accuracy and uncertainty. Especially, EOS application products should be validated for practical application in the field. In order to evaluate the availability and applicability of application products, it will be necessary to establish a systematic validation system including techniques, equipments, ground truth data, etc. The Product Validation Site (PVS) for generation and validation of KOMPSAT application products was designed and established with various in-situ equipment and dataset. This paper presents the status of PVS and summarizes some results from experiment studies at PVS.

• Journal of Digestive Cancer Research
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• v.11 no.3
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• pp.157-164
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• 2023

Prediction is a significant topic in clinical research. The development and validation of a prediction model has been increasingly published in clinical research. In this review, we investigated analytical methods and validation schemes for a clinical prediction model used in digestive cancer research. Deep learning and logistic regression, with split-sample validation as an internal or external validation, were the most commonly used methods. Furthermore, we briefly introduced and summarized the advantages and disadvantages of each method. Finally, we discussed several points to consider when conducting prediction model studies.

• Proceedings of the Korean Society of Applied Entomolohy Conference
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• 2003.10a
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• pp.71-71
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• 2003

• Korean Journal of Child Studies
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• v.29 no.4
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• pp.249-268
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• 2008

The Korean version of the Multidimensional Students' Life Satisfaction Scale for children(K-MSLSS) assesses children's subjective perceptions of Life Satisfaction(LS) in five conceptually relevant domains : Friends, School, Family, Living Environment, and Self. The purpose of the present study was to validate the five-factor structure of the K-MSLSS using Confirmatory Factor Analysis(CFA) procedures by means of the AMOS 7.0 statistical program. Of the 681 children(10.5 years, SD=1.1) recruited from three public elementary schools in Seoul 431 children were the calibration sample and 430 children were the validation sample. Results of the analyses found that the five-factor structure of K-MSLSS is applicable for use with Korean children from 9-12 years of age regardless of gender.

• Proceedings of the Korean Statistical Society Conference
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• 2003.05a
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• pp.167-170
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• 2003

We develop semiparametric methods for matched case-control studies using regression splines. Three methods are developed: an approximate crossvalidation scheme to estimate the smoothing parameter inherent in regression splines, as well as Monte Carlo Expectation Maximization (MCEM) and Bayesian methods to fit the regression spline model. We compare the approximate cross-validation approach, MCEM and Bayesian approaches using simulation, showing that they appear approximately equally efficient, with the approximate cross-validation method being computationally the most convenient. An example from equine epidemiology that motivated the work is used to demonstrate our approaches.