• Journal of the Korean BIBLIA Society for library and Information Science
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• v.34 no.1
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• pp.239-258
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• 2023

As sharing of research data has become essential, overseas publishers are providing authors with DAS templates to facilitate data sharing. However, the domestic academic market is still lacking in policies related to such research. This study proposes a data sharing policy and DAS template that can be applied to domestic academic societies in order to activate data sharing. To this end, data sharing policies of 5 foreign publishers including Nature and 12 DAS templates including AMS were investigated and analyzed. As a result of the study, an overview of the data sharing policy applicable to domestic academic conferences and a DAS template consisting of 12 items were derived. It is judged that the data sharing policy and DAS template to be presented as a result of this study can be a practical guide and tool for data sharing.

• Journal of the Korea Society of Computer and Information
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• v.19 no.9
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• pp.85-91
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• 2014

Encryption is a method to convert information to no-sense code in order to prevent data from being lost or altered by use of illegal means. Audit logging creates audit log of users' activities, exceptions, and information security events, and then conserves it for a certain period for investigation and access-control auditing. Our paper suggests that confidentiality and integrity of information should be guaranteed when transmitting and storing important information in encryption. Encryption should consider both one-way encryption and two-way one and that encryption key should assure security. Also, all history related to electronic financial transactions should be logged and kept. And, it should be considered to check the details of application access log and major information. In this paper, we take a real example of encryption and log audit for safe data transmission and periodic check.

• Journal of the Korean Data and Information Science Society
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• v.21 no.5
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• pp.873-882
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• 2010

This paper considers a Bayesian approach to replacement policy following the expiration of non-renewing combination warranty. The non-renewing combination warranty is the combination of the non-renewing free replacement warranty and the non-renewing pro-rata replacement warranty. We use the criterion based on the expected cost and the expected downtime to determine the optimal replacement period. To do so, we obtain the expected cost rate per unit time and the expected downtime per unit time, respectively. When the failure times are assumed to follow a Weibull distribution with uncertain parameters, we propose the optimal replacement policy based on the Bayesian approach. The overall value function suggested by Jiang and Ji (2002) is utilized to determine the optimal replacement period. Also, the numerical examples are presented for illustrative purpose.

• Journal of Korean Society of Transportation
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• v.18 no.6
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• pp.63-75
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• 2000

Stated Preference (SP) data has been regarded as more useful than Revealed Preference (RP) data, because researchers can investigate the respondents\` Preference and attitude for a traffic condition or a new traffic system by using the SP data. However, the SP data has two bias: the first one is the bias inherent in SP data and the latter one is the attrition bias in SP panel data. If the biases do not corrected, the choice model using SP data may predict a erroneous future demand. In this Paper, six route choice models are constructed to deal with the SP biases, and. these six models are classified into cross-sectional models (model I∼IH) and dynamic models (model IV∼VI) From the six models. some remarkable results are obtained. The cross-sectional model that incorporate RP choice results of responders with SP cross-sectional model can correct the biases inherent in SP data, and also the dynamic models can consider the temporal variations of the effectiveness of state dependence in SP responses by assuming a simple exponential function of the state dependence. WESML method that use the estimated attrition probability is also adopted to correct the attrition bias in SP Panel data. The results can be contributed to the dynamic modeling of SP Panel data and also useful to predict more exact demand.