• Economic and Environmental Geology
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• v.49 no.5
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• pp.389-410
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• 2016

Wide ranges of fission-track (FT) ages were obtained from the Jurassic granite batholith in Jeonju-Gimje-Jeongeup area, southwestern Okcheon Belt: sphene=158~70 Ma; zircon=127~71 Ma; apatite=72~46 Ma. Thermochronological analyses based on undisturbed primary cooling and reset or partially-reduced FT ages, and some track-length data reveal complicated thermal histories of the granite. The overall cooling of the batholith is characterized by a relatively rapid earlier-cooling (${\sim}20^{\circ}/Ma$) to $300^{\circ}C$ isotherm since its crystallization and a very slow later-cooling ($2.0{\sim}1.5^{\circ}/Ma$) through the $300^{\circ}C-200^{\circ}C-100^{\circ}C$ isotherms to the present surface temperature. It is indicated that the large part of Jurassic granitic body experienced different level of elevated temperatures at least above $170^{\circ}C$ (maximum>$330^{\circ}C$) by a series of igneous activities in late Cretaceous. Consistent FT zircon ages from duplicate measurements for two sites of later igneous bodies define their formation ages: e.g., quartz porphyry=$73{\pm}3Ma$; diorite=$73{\pm}2Ma$; rhyolite=$72{\pm}3Ma$; feldspar porphyry=$78{\pm}4Ma$ (total weighted average=$73{\pm}3Ma$). Intrusions of these later igneous bodies and pegmatitic dyke swarms might play important roles in later thermal rise over the study area including hot-spring districts (e.g., Hwasim, Jukrim, Mogyokri, Hoebong etc.). On the basis of an assumption that the latercooling of granite batholith was essentially controlled by the denudation of overlying crust, the uplift since early Cretaceous was very slow with a mean rate of ~0.05 mm/year (i.e., ~50 m/Ma). Estimates of total uplifts since 100 Ma, 70 Ma and 40 Ma to present-day are ~5 km, ~3.5 km and ~2 km, respectively. The consistent values of total uplifts from different locations may suggest a regional plateau uplift with a uniform rate over the whole granitic body.

• Radiation Oncology Journal
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• v.21 no.2
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• pp.135-142
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• 2003

Purpose: The purpose of this study was to investigate the positional change of the uterus during radiotherapy. Materials and Methods: Between 1997 and 2001, 47 patients received definitive radiotherapy for cervical cancer at the Samsung Medical Center. For each patient, two MRI scans were taken; one before and the other 3$\~$4 weeks after the radiotherapy treatment. In T2 weighted MRI images, the positional change of the uterine was quantified by measuring six quantities; the distance from the cervix os to the isthmus of the uterus (Dcx), the maximum length from the isthmus of the uterus to the uterine fundus (Dco), the maximum vertical distance of the uterine body (Dco-per), the angle between the vertical line and the cervical canal in the sagittal images (Acx), the angle of the uterine corpus from the vertical line in the sagittal plan (Aco-ap), and the relative angle of the uterine corpus from a fixed anatomical landmark in the axial images (Aco-axi). Results: The mean Dcx values, before and during the treatment, were 36.7 and 27.8 mm, respectively. The Dco deviated by more than 10 mm in 14 cases (29.8$\%$). The change in the Acx ranged from 0.1 to 67.8$^{\circ}$ (mean 13.2$^{\circ}$). The Aco-ap changed by a maximum of 84.8$^{\circ}$ (mean 16.9$^{\circ}$). The differences in the Dcx plus the Dco in the smaller (<4 cm) and larger ($geq$4 cm) tumors were 5.3 and 19.4 mm, respectively. With patients less than 60 years old, or with a tumor size larger than 4 cm, the difference in the Acx was statistically significant. Conclusion: The positional changes of the uterus, during radiation treatment, should be considered in the 3DCRT or IMRT treatment planning, particularly in patients under 60 years of age or in those with a tumor size greater than 4 cm in maximum diameter.

• Korean Journal of Environmental Agriculture
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• v.30 no.2
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• pp.153-159
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• 2011

BACKGROUND: This experiment was conducted to investigate the distribution and burden characteristics of heavy metal in the rainwater sampled at Taean area, in the middle part of Korea, from April 2002 to October 2003. METHODS AND RESULTS: The relationship between concentration of heavy metal and other chemical properties in the rainwaters was also evaluated. Chemical properties in the rainwater were various differences with raining periods and years. It appeared that a weighted average pH values of rainwater was ranged from 5.0 to 5.1. Heavy metal concentrations in the rainwater were ranked as Pb > Zn > Cu > Ni > As > Cr > Cd. As compared with heavy metal concentrations of rainwater in 2002, Cu, Pb, and Zn were higher than other elements in 2003. There were positive correlation between major ionic components, such as ${NH_4}^+$, $Ca^{2+}$, $Mg^{2+}$, $K^+$, $Na^+$, ${SO_4}^{2-}$ and ${NO_3}^-$, and As, Cd, Zn, Cr, and Ni concentrations in rainwater. For heavy metal distribution of rainwater, the order of average enrichment factor was Cd > Pb > As > Cu > Zn > Ni > Cr, and these were relatively higher than the natural components such as Fe, Mg and Ca. The monthly enrichment factor were relatively high, from August to October at Taean. The monthly amount of heavy metal precipitation was high in the rainy season from July to August because of great influence of rainfall. CONCLUSION(s): The results of this study suggest that the heavy metals(Cd, Pb, As, Cu, and Zn) of rainwater is strongly influenced by anthropogenic sources rather than natural sources.

• Korean Journal of Agricultural and Forest Meteorology
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• v.6 no.4
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• pp.250-255
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• 2004

This study was carried out to investigate the chemical properties of rainwater in the Suwon and Taean areas. Rainwater was collected during the farming seasons of 2002 and 2003. The number of samples collected in Suwon and Taean were 69 and 71, respectively. These were analyzed for chemical composition. The pH of samples collected in April was higher than those collected after June. The most common range of rainwater pH was 5.0-5.6 in Suwon and 4.5-5.0 in Taean during investigation periods. The neutralization capacity of rainwater acidity by $Ca^{2+}$ and N $H_4$$^{+}$ was decreased during the rainy season. The EC of rainwater was lower during the rainy season. Cation concentrations in rainwater were N $H_4$$^{+}$ > $H^{+}$ > $Ca^{2+}$ > $Mg^{2+}$ > $K^{+}$ in Suwon and $Ca^{2+}$ > N $H_4$$^{+}$ > $H^{+}$ > $K^{+}$ > $Mg^{2+}$ in Taean. In the case of anion, the order was sol > N $O_3$$^{[-10]}$ > C $I^{[-10]}$ in Suwon and S $O_4$$^{2-}$ > C $I^{[-10]}$ > N $O_3$$^{[-10]}$ in Taean. The mean values of sulfate in rainwater were 130 $\mu$eq $L^{-1}$ in Suwon and 117 $\mu$eq $L^{-1}$ in Taean. The ratio of non-sea salt sulfate to sulfate (nss-S $O_4$$^{2-}$ > S $O_4$$^{2-}$) was 89% and 88%. This implies that the major origin of sulfate in rainwater might be anthropogenic.ht be anthropogenic..

• Korean Chemical Engineering Research
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• v.57 no.5
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• pp.637-651
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• 2019

In the event of a major accident such as an explosion in a refinery or a petrochemical plant, it has caused a serious loss of life and property and has had a great impact on the insurance market. In the case of catastrophic incidents occurring in process industries such as refinery and petrochemical plants, only the proximate causes of loss have been drawn and studied from inspectors or claims adjustors responsible for claims of property insurers, incident cause investigators, and national forensic service workers. However, it has not been done well for conducting root cause analysis (RCA) and identifying the factors that contributed to the failure and establishing preventive measures before leading to chemical plant's catastrophic incidents. In this study, the criteria of warning signs on CCPS catastrophic incident waning sign self-assessment tool which was derived through the RCA method and the contribution factor analysis method using the swiss cheese model principle has been reviewed first. Secondly, in order to determine the major incident warning signs in an actual chemical plant, 614 recommendations which have been issued during last the 17 years by loss control engineers of global reinsurers were analyzed. Finally, in order to facilitate the assessment index for catastrophic incident warning signs, the criteria for the catastrophic incident warning sign index at chemical plants were grouped by type and classified into upper category and lower category. Then, a catastrophic incident warning sign index for a chemical plant was developed using the weighted values of each category derived by applying the analytic hierarchy process (pairwise comparison method) through a questionnaire answered by relevant experts of the chemical plant. It is expected that the final 'assessment index for catastrophic incident warning signs' can be utilized by the refinery and petrochemical plant's internal as well as external auditors to assess vulnerability levels related to incident warning signs, and identify the elements of incident warning signs that need to be tracked and managed to prevent the occurrence of serious incidents in the future.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.23-46
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• 2017

Although there have been cases of evaluating the value of specific companies or projects which have centralized on developed countries in North America and Europe from the early 2000s, the system and methodology for estimating the economic value of individual technologies or patents has been activated on and on. Of course, there exist several online systems that qualitatively evaluate the technology's grade or the patent rating of the technology to be evaluated, as in 'KTRS' of the KIBO and 'SMART 3.1' of the Korea Invention Promotion Association. However, a web-based technology valuation system, referred to as 'STAR-Value system' that calculates the quantitative values of the subject technology for various purposes such as business feasibility analysis, investment attraction, tax/litigation, etc., has been officially opened and recently spreading. In this study, we introduce the type of methodology and evaluation model, reference information supporting these theories, and how database associated are utilized, focusing various modules and frameworks embedded in STAR-Value system. In particular, there are six valuation methods, including the discounted cash flow method (DCF), which is a representative one based on the income approach that anticipates future economic income to be valued at present, and the relief-from-royalty method, which calculates the present value of royalties' where we consider the contribution of the subject technology towards the business value created as the royalty rate. We look at how models and related support information (technology life, corporate (business) financial information, discount rate, industrial technology factors, etc.) can be used and linked in a intelligent manner. Based on the classification of information such as International Patent Classification (IPC) or Korea Standard Industry Classification (KSIC) for technology to be evaluated, the STAR-Value system automatically returns meta data such as technology cycle time (TCT), sales growth rate and profitability data of similar company or industry sector, weighted average cost of capital (WACC), indices of industrial technology factors, etc., and apply adjustment factors to them, so that the result of technology value calculation has high reliability and objectivity. Furthermore, if the information on the potential market size of the target technology and the market share of the commercialization subject refers to data-driven information, or if the estimated value range of similar technologies by industry sector is provided from the evaluation cases which are already completed and accumulated in database, the STAR-Value is anticipated that it will enable to present highly accurate value range in real time by intelligently linking various support modules. Including the explanation of the various valuation models and relevant primary variables as presented in this paper, the STAR-Value system intends to utilize more systematically and in a data-driven way by supporting the optimal model selection guideline module, intelligent technology value range reasoning module, and similar company selection based market share prediction module, etc. In addition, the research on the development and intelligence of the web-based STAR-Value system is significant in that it widely spread the web-based system that can be used in the validation and application to practices of the theoretical feasibility of the technology valuation field, and it is expected that it could be utilized in various fields of technology commercialization.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.137-148
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• 2014

Recommender system has become one of the most important technologies in e-commerce in these days. The ultimate reason to shop online, for many consumers, is to reduce the efforts for information search and purchase. Recommender system is a key technology to serve these needs. Many of the past studies about recommender systems have been devoted to developing and improving recommendation algorithms and collaborative filtering (CF) is known to be the most successful one. Despite its success, however, CF has several shortcomings such as cold-start, sparsity, gray sheep problems. In order to be able to generate recommendations, ordinary CF algorithms require evaluations or preference information directly from users. For new users who do not have any evaluations or preference information, therefore, CF cannot come up with recommendations (Cold-star problem). As the numbers of products and customers increase, the scale of the data increases exponentially and most of the data cells are empty. This sparse dataset makes computation for recommendation extremely hard (Sparsity problem). Since CF is based on the assumption that there are groups of users sharing common preferences or tastes, CF becomes inaccurate if there are many users with rare and unique tastes (Gray sheep problem). This study proposes a new algorithm that utilizes Social Network Analysis (SNA) techniques to resolve the gray sheep problem. We utilize 'degree centrality' in SNA to identify users with unique preferences (gray sheep). Degree centrality in SNA refers to the number of direct links to and from a node. In a network of users who are connected through common preferences or tastes, those with unique tastes have fewer links to other users (nodes) and they are isolated from other users. Therefore, gray sheep can be identified by calculating degree centrality of each node. We divide the dataset into two, gray sheep and others, based on the degree centrality of the users. Then, different similarity measures and recommendation methods are applied to these two datasets. More detail algorithm is as follows: Step 1: Convert the initial data which is a two-mode network (user to item) into an one-mode network (user to user). Step 2: Calculate degree centrality of each node and separate those nodes having degree centrality values lower than the pre-set threshold. The threshold value is determined by simulations such that the accuracy of CF for the remaining dataset is maximized. Step 3: Ordinary CF algorithm is applied to the remaining dataset. Step 4: Since the separated dataset consist of users with unique tastes, an ordinary CF algorithm cannot generate recommendations for them. A 'popular item' method is used to generate recommendations for these users. The F measures of the two datasets are weighted by the numbers of nodes and summed to be used as the final performance metric. In order to test performance improvement by this new algorithm, an empirical study was conducted using a publically available dataset - the MovieLens data by GroupLens research team. We used 100,000 evaluations by 943 users on 1,682 movies. The proposed algorithm was compared with an ordinary CF algorithm utilizing 'Best-N-neighbors' and 'Cosine' similarity method. The empirical results show that F measure was improved about 11% on average when the proposed algorithm was used