• Journal of the Korean earth science society
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• v.34 no.6
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• pp.515-523
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• 2013

The eastern coast of South Korea is expected to be damaged by volcanic ash when Mt. Baekdusan volcano erupts. Even if the amount of volcanic ash is small, it can be fatal on the agricultural sector withering many plants and causing soil acidification. Thus, in this paper, we aim to estimate agricultural losses caused by the volcanic ash and to visualize them with Google map. To estimate the volcanic ash losses, a damage assessment model is needed. As the volcanic ash hazard depends on the kind of a crops and the ash thickness, the fragility function of damage assessment model should represent the relation between ash thickness and damage rate of crops. Thus, we model the fragility function using the damage rate for each crop of RiskScape. The volcanic ash losses can be calculated with the agricultural output and the price of each crop using the fragility function. This paper also represents the estimated result of the losses in Gangwon province, which is most likely to get damaged by volcanic ashes in Korea. According to the result with gross agricultural output of Gangwon province in 2010, the amount of volcanic ash losses runs nearly 635,124 million wons in Korean currency if volcanic ash is accumulated over four millimeters. This amount represents about 50% of the gross agricultural output of Gangwon province. We consider the damage only for the crops in this paper. However, a volcanic ash fall has the potential to damage the assets for a farm, including the soil fertility and installations. Thus, to estimate the total amount of volcanic ash damage for the whole agricultural sectors, these collateral damages should also be considered.

• Asia pacific journal of information systems
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• v.20 no.3
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• pp.115-137
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• 2010

Information technology (IT) outsourcing, the use of a third-party vendor to provide IT services, started in the late 1980s and early 1990s in Korea, and has increased rapidly since 2000. Recently, firms have increased their efforts to capture greater value from IT outsourcing. To date, there have been a large number of studies on IT outsourcing. Most prior studies on IT outsourcing have focused on outsourcing practices and decisions, and little attention has been paid to objectively measuring the value of IT outsourcing. In addition, studies that examined the performance of IT outsourcing have mainly relied on anecdotal evidence or practitioners' perceptions. Our study examines the contribution of IT outsourcing to economic growth in Korean industries over the 1990 to 2007 period, using a production function framework and a panel data set for 54 industries constructed from input-output tables, fixed-capital formation tables, and employment tables. Based on the framework and estimation procedures that Han, Kauffman and Nault (2010) used to examine the economic impact of IT outsourcing in U.S. industries, we evaluate the impact of IT outsourcing on output and productivity in Korean industries. Because IT outsourcing started to grow at a significantly more rapid pace in 2000, we compare the impact of IT outsourcing in pre- and post-2000 periods. Our industry-level panel data cover a large proportion of Korean economy-54 out of 58 Korean industries. This allows us greater opportunity to assess the impacts of IT outsourcing on objective performance measures, such as output and productivity. Using IT outsourcing and IT capital as our primary independent variables, we employ an extended Cobb-Douglas production function in which both variables are treated as factor inputs. We also derive and estimate a labor productivity equation to assess the impact of our IT variables on labor productivity. We use data from seven years (1990, 1993, 2000, 2003, 2005, 2006, and 2007) for which both input-output tables and fixed-capital formation tables are available. Combining the input-output tables and fixed-capital formation tables resulted in 54 industries. IT outsourcing is measured as the value of computer-related services purchased by each industry in a given year. All the variables have been converted to 2000 Korean Won using GDP deflators. To calculate labor hours, we use the average work hours for each sector provided by the OECD. To effectively control for heteroskedasticity and autocorrelation present in our dataset, we use the feasible generalized least squares (FGLS) procedures. Because the AR1 process may be industry-specific (i.e., panel-specific), we consider both common AR1 and panel-specific AR1 (PSAR1) processes in our estimations. We also include year dummies to control for year-specific effects common across industries, and sector dummies (as defined in the GDP deflator) to control for time-invariant sector-specific effects. Based on the full sample of 378 observations, we find that a 1% increase in IT outsourcing is associated with a 0.012~0.014% increase in gross output and a 1% increase in IT capital is associated with a 0.024~0.027% increase in gross output. To compare the contribution of IT outsourcing relative to that of IT capital, we examined gross marginal product (GMP). The average GMP of IT outsourcing was 6.423, which is substantially greater than that of IT capital at 2.093. This indicates that on average if an industry invests KRW 1 millon, it can increase its output by KRW 6.4 million. In terms of the contribution to labor productivity, we find that a 1% increase in IT outsourcing is associated with a 0.009~0.01% increase in labor productivity while a 1% increase in IT capital is associated with a 0.024~0.025% increase in labor productivity. Overall, our results indicate that IT outsourcing has made positive and economically meaningful contributions to output and productivity in Korean industries over the 1990 to 2007 period. The average GMP of IT outsourcing we report about Korean industries is 1.44 times greater than that in U.S. industries reported in Han et al. (2010). Further, we find that the contribution of IT outsourcing has been significantly greater in the 2000~2007 period during which the growth of IT outsourcing accelerated. Our study provides implication for policymakers and managers. First, our results suggest that Korean industries can capture further benefits by increasing investments in IT outsourcing. Second, our analyses and results provide a basis for managers to assess the impact of investments in IT outsourcing and IT capital in an objective and quantitative manner. Building on our study, future research should examine the impact of IT outsourcing at a more detailed industry level and the firm level.

• Korean Journal of Soil Science and Fertilizer
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• v.39 no.5
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• pp.259-267
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• 2006

Hydraulic conductivity is the rate of water flux on hydraulic gradient. The van Genuchten Mualem (VGM) model is frequently used for describing unsaturated state of soils, that is composed with the function of soil water potential and soil water content and requests various parameters. This study is to get the value of VGM parameters used Rosetta computer program based on neural network analysis method and to calculate VGM parameters. VGM parameters included Ko(effective saturated hydraulic conductivity), ${\theta}r$(residual soil water content), ${\theta}s$(saturated soil water content), L, n and m. The unsaturated hydraulic conductivity at 10 kPa was calculated by using Rosetta program. Unsaturated hydraulic conductivities of 17 soil series at 1, 3, 5, 7 kPa were also obtained by applying saturated hydraulic conductivity by disk tension infiltrometer based on Gardner and Wooding's equation. Water flow at the water potential of 3 kPa was very low except Namgye, Hagog, Baegsan, Sangju, Seogcheon, Yesan soil series. Unsaturated hydraulic conductivity at 1 kPa showed the highest value for Samgag soil series and was in order of Yesan, Hwabong, Hagog and Baegsan soil series. Those of Gacheon, Seocheon and Ugog soil series were very low. When the value by VGM was compared with the value by disc tension infiltrometer, there was a tendency with exponential function to soils without gravel but there was no tendency to soils including gravel. Conclusively, it would be limited that VGM model for unsaturated hydraulic conductivity analysis applies to Korean agricultural land including gravel and having steep slope, shallow soil depth.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.3
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• pp.363-373
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• 2010

"Curve number" (CN) indicates the runoff potential of an area. The US Soil Conservation Service (SCS)'s CN method is a simple, widely used, and efficient method for estimating the runoff from a rainfall event in a particular area, especially in ungauged basins. The use of soil maps requested from end-users was dominant up to about 80% of total use for estimating CN based rainfall-runoff. This study introduce the use of soil maps with respect to hydrologic and watershed management focused on hydrologic soil group and a case study resulted in assessing effective rainfall and runoff hydrograph based on SCS-CN method in a small watershed. The ratio of distribution areas for hydrologic soil group based on detailed soil map (1:25,000) of Korea were 42.2% (A), 29.4% (B), 18.5% (C), and 9.9% (D) for HSG 1995, and 35.1% (A), 15.7% (B), 5.5% (C), and 43.7% (D) for HSG 2006, respectively. The ratio of D group in HSG 2006 accounted for 43.7% of the total and 34.1% reclassified from A, B, and C groups of HSG 1995. Similarity between HSG 1995 and 2006 was about 55%. Our study area was located in Sosu-myeon, Goesan-gun including an approx. 44 $km^2$-catchment, Chungchungbuk-do. We used a digital elevation model (DEM) to delineate the catchments. The soils were classified into 4 hydrologic soil groups on the basis of measured infiltration rate and a model of the representative soils of the study area reported by Jung et al. 2006. Digital soil maps (1:5,000) were used for classifying hydrologic soil groups on the basis of soil series unit. Using high resolution satellite images, we delineated the boundary of each field or other parcel on computer screen, then surveyed the land use and cover in each. We calculated CN for each and used those data and a land use and cover map and a hydrologic soil map to estimate runoff. CN values, which are ranged from 0 (no runoff) to 100 (all precipitation runs off), of the catchment were 73 by HSG 1995 and 79 by HSG 2006, respectively. Each runoff response, peak runoff and time-to-peak, was examined using the SCS triangular synthetic unit hydrograph, and the results of HSG 2006 showed better agreement with the field observed data than those with use of HSG 1995.

• The Korean Journal of Nuclear Medicine
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• v.32 no.1
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• pp.32-49
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• 1998

For estimation of regional myocardial blood flow with O-15 water PET, a few modifications considering partial volume effect based on single compartment model have been proposed. In this study, we attempted to quantify the degree of heterogeneity and to show the effect of tissue flow heterogeneity on partition coefficient(${\lambda}$) and to find the relation between perfusable tissue index(PTI) and ${\lambda}$ by computer simulation using two modified models. We simulated tissue curves for the regions with homogeneous and heterogeneous blood flow over a various flow range(0.2-4.0ml/g/min). Simulated heterogeneous tissue composed of 4 subregions of the same or different size of block which have different homogeneous flow and different degree of slope of distribution of blood flow. We measured the index representing heterogeneity of distribution of blood flow for each heterogeneous tissue by the constitution heterogeneity(CH). For model I, we assumed that tissue recovery coefficient ($F_{MME}$) was the product of partial volume effect($F_{MMF}$) and PTI. Using model I, PTI, flow, and $F_{MM}$ were estimated. For model II, we assumed that partition coefficient was another variable which could represent tissue characteristics of heterogeneity of flow distribution. Using model II, PTI, flow and ${\lambda}$ were estimated. For the simulated tissue with homogeneous flow, both models gave exactly the same estimates, of three parameters. For the simulated tissue with heterogeneous flow distribution, in model I, flow and $F_{MM}$ were correctly estimated as CH was increased moderately. In model II, flow and ${\lambda}$ were decreased curvi-linearly as CH was increased. The degree of underestimation of ${\lambda}$ obtained using model II, was correlated with CH. The degree of underestimation of flow was dependent on the degree of underestimation of ${\lambda}$. PTI was somewhat overestimated and did not change according to CH. We conclude that estimated ${\lambda}$ reflect the degree of tissue heterogeneity of flow distribution. We could use the degree of underestimation of ${\lambda}$ to find the characteristic heterogeneity of tissue flow and use ${\lambda}$ to recover the underestimated flow.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.177-193
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• 2014

Over the past decade, there has been a rapid diffusion of electronic commerce and a rising number of interconnected networks, resulting in an escalation of security threats and privacy concerns. Electronic commerce has a built-in trade-off between the necessity of providing at least some personal information to consummate an online transaction, and the risk of negative consequences from providing such information. More recently, the frequent disclosure of private information has raised concerns about privacy and its impacts. This has motivated researchers in various fields to explore information privacy issues to address these concerns. Accordingly, the necessity for information privacy policies and technologies for collecting and storing data, and information privacy research in various fields such as medicine, computer science, business, and statistics has increased. The occurrence of various information security accidents have made finding experts in the information security field an important issue. Objective measures for finding such experts are required, as it is currently rather subjective. Based on social network analysis, this paper focused on a framework to evaluate the process of finding experts in the information security field. We collected data from the National Discovery for Science Leaders (NDSL) database, initially collecting about 2000 papers covering the period between 2005 and 2013. Outliers and the data of irrelevant papers were dropped, leaving 784 papers to test the suggested hypotheses. The co-authorship network data for co-author relationship, publisher, affiliation, and so on were analyzed using social network measures including centrality and structural hole. The results of our model estimation are as follows. With the exception of Hypothesis 3, which deals with the relationship between eigenvector centrality and performance, all of our hypotheses were supported. In line with our hypothesis, degree centrality (H1) was supported with its positive influence on the researchers' publishing performance (p<0.001). This finding indicates that as the degree of cooperation increased, the more the publishing performance of researchers increased. In addition, closeness centrality (H2) was also positively associated with researchers' publishing performance (p<0.001), suggesting that, as the efficiency of information acquisition increased, the more the researchers' publishing performance increased. This paper identified the difference in publishing performance among researchers. The analysis can be used to identify core experts and evaluate their performance in the information privacy research field. The co-authorship network for information privacy can aid in understanding the deep relationships among researchers. In addition, extracting characteristics of publishers and affiliations, this paper suggested an understanding of the social network measures and their potential for finding experts in the information privacy field. Social concerns about securing the objectivity of experts have increased, because experts in the information privacy field frequently participate in political consultation, and business education support and evaluation. In terms of practical implications, this research suggests an objective framework for experts in the information privacy field, and is useful for people who are in charge of managing research human resources. This study has some limitations, providing opportunities and suggestions for future research. Presenting the difference in information diffusion according to media and proximity presents difficulties for the generalization of the theory due to the small sample size. Therefore, further studies could consider an increased sample size and media diversity, the difference in information diffusion according to the media type, and information proximity could be explored in more detail. Moreover, previous network research has commonly observed a causal relationship between the independent and dependent variable (Kadushin, 2012). In this study, degree centrality as an independent variable might have causal relationship with performance as a dependent variable. However, in the case of network analysis research, network indices could be computed after the network relationship is created. An annual analysis could help mitigate this limitation.