• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.11 no.1
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• pp.41-54
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• 2013

Radionuclide sorption data is necessary for the safety assessment of radioactive waste disposal. However the use of sorption database is often limited due to the accessability. A web-based sorption database program named KAERI-SDB has been developed to provide information on the sorption of radionuclides onto geological media as a function of geochemical conditions. The development of KAERI-SDB was achieved by improving the performance of pre-existing sorption database program (SDB-21C) developed in 1998 and considering user's requirements. KAERI-SDB is designed that users can access it by using a web browser. Main functions of KAERI-SDB include (1) log-in/member join, (2) search and store of sorption data, and (3) chart expression of search results. It is expected that KAERI-SDB could be widely utilized in the safety assessment of radioactive waste disposal by enhancing the accessibility to users who wants to use sorption data. Moreover, KAERI-SDB opened to public would also improve the reliability and public acceptance on the radioactive waste disposal programs.

• Journal of Korean Society of Transportation
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• v.34 no.1
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• pp.1-14
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• 2016

In the recent years, the internet has become accessible without limitation of time and location to anyone with smartphones. It resulted in more convenient travel information access both on the pre-trip and en-route phase. The main objective of this study is to conduct a stationary test for traffic information web/mobile application access indexes from TCS (Toll Collection System); and analyzing the relationship between the web/mobile application access indexes and actual traffic volume on expressways, in order to analyze searching behavior of expressway related travel information. The key findings of this study are as follows: first, the results of ADF-test and PP-test confirm that the web/mobile application access indexes by time periods satisfy stationary conditions even without log or differential transformation. Second, the Pearson correlation test showed that there is a strong and positive correlation between the web/mobile application access indexes and expressway entry and exit traffic volume. In contrast, truck entry traffic volume from TCS has no significant correlation with the web/mobile application access indexes. Third, the time gap relationship between time-series variables (i.e., concurrent, leading and lagging) was analyzed by cross-correlation tests. The results indicated that the mobile application access leads web access, and the number of mobile application execution is concurrent with all web access indexes. Lastly, there was no web/mobile application access indexes leading expressway entry traffic volumes on expressways, and the highest correlation was observed between webpage view/visitor/new visitor/repeat visitor/application execution counts and expressway entry volume with a lag of one hour. It is expected that specific individual travel behavior can be predicted such as route conversion time and ratio if the data are subdivided by time periods and areas and utilizing traffic information users' location.

• Journal of Internet Computing and Services
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• v.16 no.3
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• pp.59-69
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• 2015

Many users visit websites every day to perform information retrieval, shopping, and community activities. On the other hand, there is intense competition among sites which attempt to profit from the Internet users. Thus, the owners or marketing officers of each site try to design a variety of marketing strategies including cooperation with other sites. Through such cooperation, a site can share customers' information, mileage points, and hyperlinks with other sites. To create effective cooperation, it is crucial to choose an appropriate partner site that may have many potential customers. Unfortunately, it is exceedingly difficult to identify such an appropriate partner among the vast number of sites. In this paper, therefore, we devise a new methodology for recommending appropriate partner sites to each site. For this purpose, we perform site clustering from the perspective of visitors' similarities, and then identify a group of sites that has a number of common customers. We then analyze the potential for the practical use of the proposed methodology through its application to approximately 140 million actual site browsing histories.