• Journal of radiological science and technology
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• v.40 no.2
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• pp.205-211
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• 2017

There is a need for aggressive diagnosis and treatment in middle-aged and high-risk individuals who are more likely to progress from nonalcoholic fatty liver to hepatitis. In this study, nonalcoholic fatty liver was divided into severe, moderate, and severe, and classified by quantitative method using computer analysis of GLCM algorithm. The purpose of this study was to evaluate the characteristics of ultrasound images in the local fat avoidance region. Normal, mild, moderate, severe fatty liver, and focal fat sparing area, 80 cases, respectively. Among the parameters of the GLCM algorithm, the values of the Autocorrelation, Square of the deviation, Sum of averages and Sum of variances with high recognition rate of the liver ultrasound image were calculated. The average recognition rate of the GLCM algorithm was 97.5%. The result of local fat avoidance image analysis showed the most similar value to the normal parenchyma. Ultrasonography can be easily accessed by primary screening, but there may be differences in the accuracy of the test method or the correspondence of results depending on proficiency. GLCM algorithm was applied to quantitatively classify the degree of fatty liver. Local fat avoidance region was similar to normal parenchyma, so it could be predicted to be homogeneous liver parenchyma without fat deposition. We believe that GLCM computer image analysis will provide important information for differentiating not only fatty liver but also other lesions.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.2
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• pp.24-35
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• 2019

In this study, a hotspot analysis was conducted to suggest a new method for interpreting soil heavy-metal contamination data of abandoned metal mines according to statistical significance level. The spatial autocorrelation of the data was analyzed using the Getis-Ord $Gi{\ast}$ statistic in order to check whether soil heavy metal contamination data showing abnormal values appeared concentrated or dispersed in a specific space. As a result, the statistically significant data showing abnormal values in the mine area could be classified as follows: (1) the contamination degree and the hotspot value (z-score) were both high, (2) the contamination degree was high but the z-score was low, (3) the contamination degree was low but the z-score was high and (4) the contamination degree and the z-score were both low. The proposed method can be used to interpret the soil heavy metal contamination data according to the statistical significance level and to support a rational decision for soil contamination management in abandoned mines.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.4
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• pp.69-85
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• 2014

Carbon stocks of NFI plots can be accurately estimated using field survey information. However, an accurate estimation of carbon stocks in other unsurveyed sites is very difficult. In order to fill this gap, various spatial information can be used as an ancillary data. In South Korea, there is the 1:5,000 forest type map that was produced by digital air-photo interpretation and field survey. Because this map contains very detailed forest information, it can be used as the high-quality spatial data for estimating carbon stocks. In this study, we compared three upscaling methods based on the 1:5,000 forest type map and 5th national forest inventory data. Map algebra(method 1), RK(Regression Kriging)(method 2), and GWR(Geographically Weighted Regression)(method 3) were applied to estimate forest carbon stock in Chungcheong-nam Do and Daejeon metropolitan city. The range of carbon stocks from method 2(1.39~138.80 tonC/ha) and method 3(1.28~149.98 tonC/ha) were more similar to that of previous method(1.56~156.40 tonC/ha) than that of method 1(0.00~93.37 tonC/ha). This result shows that RK and GWR considering spatial autocorrelation can show spatial heterogeneity of carbon stocks. We carried out paired t-test for carbon stock data using 186 sample points to assess estimation accuracy. As a result, the average carbon stocks of method 2 and field survey method were not significantly different at p=0.05 using paired t-test. And the result of method 2 showed the lowest RMSE. Therefore regression kriging method is useful to consider spatial variations of carbon stocks distribution in rugged terrain and complex forest stand.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.4
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• pp.73-81
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• 2013

Ordinary least squares (OLS) regression is the primary statistical method in previous studies for vegetation distribution patterns in relation to landform. However, this global regression lacks the ability to uncover some local-specific relationships and spatial autocorrelation in model residuals. This study employed geographically weighted regression (GWR) to examine the spatially varying relationships between NDVI (Normalized Difference Vegetation Index) patterns and changing trends of landform (elevation, slope) and solar intensity (insolation and duration of sunshine) in Mt Geum-gang of North-Korea. Results denoted that GWR was more powerful than OLS in interpreting relationships between NDVI patterns and landform/solar intensity, since GWR was characterized by higher adjusted R2, and reduced spatial autocorrelations in model residuals. Unlike OLS regression, GWR allowed the coefficients of explanatory variables to differ by locality by giving relatively more weight to NDVI patterns which are affected by local landform and solar factors. The strength of the regression relationships in the GWR increased significantly, by showing regression coefficient of higher than 70% (0.744) in the southern ridge of the experimental area. It is anticipated that this research output will serve to increase the scientific and objective vegetation monitoring in relation to landform and solar intensity by overcoming serious constraints suffered from the past non-GWR-based approach.

• Journal of the Institute of Convergence Signal Processing
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• v.15 no.2
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• pp.48-54
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• 2014

For the element ${\alpha}{\in}GF(p^n)$, two kinds of bases are known. One is a conventional polynomial basis of the form $\{1,{\alpha},{\alpha}^2,{\cdots},{\alpha}^{n-1}\}$, and the other is a normal basis of the form $\{{\alpha},{\alpha}^p,{\alpha}^{p^2},{\cdots},{\alpha}^{p^{n-1}}\}$. In this paper we consider the method of generating normal bases which construct the finite field $GF(p^n)$, as an n-dimensional extension of the finite field GF(p). And we analyze the code sequence generating algorithm and derive the implementation functions of code sequence generator based on the normal bases. We find the normal polynomials of degrees, n=5 and n=7, which can generate normal bases respectively, design, and construct the code sequence generators based on these normal bases. Finally, we produce two code sequence groups(n=5, n=7) by using Simulink, and analyze the characteristics of the autocorrelation function, $R_{i,i}(\tau)$, and crosscorrelation function, $R_{i,j}(\tau)$, $i{\neq}j$ between two different code sequences. Based on these results, we confirm that the analysis of generating algorithms and the design and implementation of the code sequence generators based on normal bases are correct.

• Journal of Korea Water Resources Association
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• v.49 no.8
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• pp.645-656
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• 2016

The study performed a regional flood frequency analysis and proposed a regression equation to estimate design floods corresponding to return periods for ungauged basins in Geum-river basin. Five preliminary tests were employed to investigate hydrological independence and homogeneity of streamflow data, i.e. the lag-one autocorrelation test, time homogeneity test, Grubbs-Beck outlier test, discordancy measure test ($D_i$), and regional homogeneity measure (H). The test results showed that streamflow data were time-independent, discordant and homogeneous within the basin. Using five probability distributions (generalized extreme value (GEV), three-parameter log-normal (LN-III), Pearson type 3 (P-III), generalized logistic (GLO), generalized Pareto (GPA)), comparative regional flood frequency analyses were carried out for the region. Based on the L-moment ratio diagram, average weighted distance (AWD) and goodness-of-fit statistics ($Z^{DIST}$), the GLO distribution was selected as the best fit model for Geum-river basin. Using the GLO, a regression equation was developed for estimating regional design floods, and validated by comparing the estimated and observed streamflows at the Ganggyeong station.

• Bulletin of the Korean Chemical Society
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• v.7 no.5
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• pp.367-371
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• 1986

Dynamic and equilibrium properties of n-alkane chains immersed in solvent molecules have been investigated by a molecular dynamics method. The n-alkane chain is assumed to be a chain of elements (CH$_2$) interconnected by bonds having a fixed bond length and bond angle, but each bond of the chain is allowed to execute hindered internal rotation. We studied the effect of the number of the chain elements (N$_c$ = 10, 15 and 20) on the equilibrium properties of the system, e.g., the pair correlation functions between a chain element and solvent molecules, g$_{cs}$(r), and between the chain elements, g$_{cc}$(r), and the configurational properties such as the mean-square end-to-end distance < R$^2$ >, the mean-square radius of gyration < S$^2$ >, and the eigenvalues of the moment-of-inertia tensor < S$_i^2$ > / < S$^2$ > (i = 1, 2 and 3). We also studied the dynamic properties of the system, e.g., the autocorrelation function C(A;t) where A = R$^2$(t), = S$^2$(t), or = ${\vec{V}}(t)({\vec{V}}$ = velocity of the center of mass), and the diffusion coefficient D. The g$_{cs}$(r)'s are almost equal irrespective of the change of Nc while g$_{cc}$(r) becomes larger as N$_c$ increases; The MD computed configurational properties < R$^2$2 > and < S$^2$ > were found to be a little different from the values calculated from the statistical equations of < R$^2$ > and < S$^2$ >, it may be due to the fact that our model for the MD simulations includes a long-range volume effect. From the < S$_i^2$ > / < S$^2$ >, it is found that the chain molecule has a nearly spherical shape irrespective of the variation of N$_c$. For the dynamic properties we found that the C(R$^2$;t) and C(S$^2$;t) of lower N$_c$ decay faster than those of higher N$_c$, while the C($\vec V$;t) of the center of mass in the chain is weakly dependent on the N$_c$. The center of mass diffusion coefficient D$_c$ decreases as N$_c$ increases while the end point diffusion coefficient D$_e$ is nearly equal irrespective of the change of N$_c$.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.12
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• pp.963-969
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• 2021

The wind data measured from local meteorological masts is used to evaluate wind speed distribution and energy production in the specified site for wind farm However, wind data measured from meteorological masts often contain missing information or insufficient desired height or data length, making it difficult to perform wind turbine control and performance simulation. Therefore, long-term continuous wind data is very important to assess the annual energy production and the capacity factor for wind turbines or wind farms. In addition, if seasonal influences are distinct, such as on the Korean Peninsula, wind data with seasonal characteristics should be considered. This study presents methodologies for generating synthetic wind that take into account fluctuations in both wind speed and direction using the hidden Markov model, which is a statistical method. The wind data for statistical processing are measured at Maldo island in the Kokunnsan-gundo, Jeonbuk Province using the Automatic Weather System (AWS) of the Korea Meteorological Administration. The synthetic wind generated using the hidden Markov model will be validated by comparing statistical variables, wind energy density, seasonal mean speed, and prevailing wind direction with measurement data.

• Journal of Korea Trade
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• v.26 no.6
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• pp.1-19
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• 2022

Purpose - This study empirically investigates the effects of Official Development Assistance (ODA) on the economic activities of private actors in recipient countries. As a proxy for the economic activities of private actors, we utilize the job creation activities of foreign subsidiaries in recipient countries. The foreign subsidiaries provide a foundation for economic development by creating paying jobs. That is, if ODA has been successfully transferred to foreign subsidiaries, then these foreign subsidiaries should help economic growth and help create a boom in the local market by providing jobs. These jobs eventually lead to the achievement of the primary aims of foreign aid, including poverty reduction. Thus, this study empirically examines the relationship between ODA and the number of jobs created by foreign subsidiaries in recipient countries. Design/methodology - This is the first study to examine the effects of the ODA on the job creation of foreign subsidiaries because it has been hard to obtain internal information related to the employment status of foreign subsidiaries. Fortunately, we have a unique panel dataset provided by the Export-Import Bank of Korea (KEXIM) for 2006 to 2013. In terms of the empirical specification, we use the generalized least squares (GLS) method. The panel GLS estimator allows us to have an efficient estimation that overcomes the limitations of the panel data. It employs assumptions about the heteroscedasticity between the panels and makes an autocorrelation of the error term within each panel. Findings - We find that ODA influences job creation in foreign subsidiaries. In particular, we found that ODA creates more jobs in sales than in managerial or production positions. This study also shows that the effect of the ODA on the foreign subsidiaries' job creation activities depend on the purpose of the ODA. By examining ODA effects on the foreign subsidiaries' economic activities (e.g., job creation), this study fills a gap in the current literature. Originality/value - Existing studies that focus on the ODA effect have either a macroeconomic point or a microeconomic point of view. However, both approaches do not explain how well foreign aid has influenced private economic actors of recipient countries. In essence, previous researchers found it difficult to obtain the necessary data for internal employment status from foreign subsidiaries. However, thanks to the Korea Export-Import Bank, this study shows that ODA indeed influences the job creation activities of foreign subsidiaries even after controlling for other factors such as FDI, GDP growth rate, employment rate, household expenditure, mother firms' share, etc. By doing so, we can examine how ODA influences the job creation of foreign subsidiaries, which might help economic development and reduce the amount of poverty in recipient countries.

• Journal of the Korean Regional Science Association
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• v.34 no.2
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• pp.3-19
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• 2018

The objective of this study is to observe the efficiency of clinical performance on the supply and demand of medical resources in Korea. For the empirical analysis, we constructed the dataset on age standardized mortality rate, the number of physician, specialist, surgery, medical institution, ratio of general hospitals of 16 provinces in Korea from 2006 to 2013. The panel probability frontier model is employed as an analysis method and considered heteroscedasticity and autocorrelation of the error in panel data. In addition, the demographic and socioeconomic characteristics of the 16 provinces, unemployment rate, elderly population ratio, GRDP per capita, and ratio of hospitals in comparison to the general hospitals are used to find the effect on the technical efficiency of clinical performance on supply and demand of medical resources. The results are as follows. First, for the clinical performance, the supply side of human resources such as doctors and specialists and the demand side factors such as chronic illness clinic per unit population have a significant influence, respectively. Second, the technical efficiency of clinical performance on the supply and demand of medical resources of each input component was 59-70% in terms of clinical efficiency in each region. Third. estimates of technical efficiency of inputs that affect clinical performance showed a slight increase in all regions during the analysis period, but the increase trend decreased slightly. Fourth, the ratio of the elderly population and GRDP per capita have a positive influence on the technical efficiency of clinical performance on the supply and demand of medical resources. The difference of each efficiency by region is due to the regional differences of the input medical resources and the combination of them and the demographic and socioeconomic characteristics of the region. It is understood that the differences in technological efficiency due to the complexity of supply and demand of medical resources, demographic structure and economic difference affecting clinical performance by region are different.