• Journal of Korean Society of Forest Science
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• v.105 no.3
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• pp.309-314
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• 2016

A locally adapted plant population under harsh environmental changes might survive for a long generation through maintaining proper level of genetic diversity. When it happens losing the genetic diversity too much fast, the population could be declining and probably become extinct. An isolated small population of Populus davidiana was investigated to study out the genetic diversity and the fine-scale spatial genetic structure. The estimated number of adult trees in the population of Mt. Worak, South Korea, was 350 in the total area of $14,000m^2$. The number of adults in a study plot ($70m{\times}70m$) was 123. The average age was 16-year-old and a 32-year-old tree was the oldest. The distribution of individuals was slightly aggregated in the plot. Sixty-one among the 123 individuals were randomly sampled to estimate genetic variation using AFLP markers. One hundred fifty-one (77%) of total 196 amplicons were polymorphic from six AFLP primer combinations. The average number of loci per primer combination was 32.7 (S.D.=7.2). Expected heterozygosity ($H_e$) and Shannon's diversity index (S.I.) were 0.154 and 0.254, respectively. These values were extremely lower than those of other P. davidiana populations in South Korea. Genetic patchiness was showed within 21 meters by spatial autocorrelation analysis and the isolated small size of population might be mainly attributed to the formation of such small patch size.

• Environmental Analysis Health and Toxicology
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• v.31
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• pp.6.1-6.10
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• 2016

Objectives This study examined the spatial distribution and the extent of soil contamination by heavy metals resulting from primitive, unconventional informal electronic waste recycling in the Agbogbloshie e-waste processing site (AEPS) in Ghana. Methods A total of 132 samples were collected at 100 m intervals, with a handheld global position system used in taking the location data of the soil sample points. Observing all procedural and quality assurance measures, the samples were analyzed for barium (Ba), cadmium (Cd), cobalt (Co), chromium (Cr), copper (Cu), mercury (Hg), nickel (Ni), lead (Pb), and zinc (Zn), using X-ray fluorescence. Using environmental risk indices of contamination factor and degree of contamination ($C_{deg}$), we analyzed the individual contribution of each heavy metal contamination and the overall $C_{deg}$. We further used geostatistical techniques of spatial autocorrelation and variability to examine spatial distribution and extent of heavy metal contamination. Results Results from soil analysis showed that heavy metal concentrations were significantly higher than the Canadian Environmental Protection Agency and Dutch environmental standards. In an increasing order, Pb>Cd>Hg>Cu>Zn>Cr>Co>Ba>Ni contributed significantly to the overall $C_{deg}$. Contamination was highest in the main working areas of burning and dismantling sites, indicating the influence of recycling activities. Geostatistical analysis also revealed that heavy metal contamination spreads beyond the main working areas to residential, recreational, farming, and commercial areas. Conclusions Our results show that the studied heavy metals are ubiquitous within AEPS and the significantly high concentration of these metals reflect the contamination factor and $C_{deg}$, indicating soil contamination in AEPS with the nine heavy metals studied.

• Journal of Cadastre & Land InformatiX
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• v.48 no.1
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• pp.169-186
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• 2018

The social influence of the elderly population will accelerate in a rapidly aging society. The purpose of this study is to establish a methodology for extracting vulnerable districts of the welfare of the aged through machine learning(ML), artificial neural network(ANN) and geospatial analysis. In order to establish the direction of analysis, this progressed after an interview with volunteers who over 65-year old people, public officer and the manager of the aged welfare facility. The indicators are the geographic distance capacity, elderly welfare enjoyment, officially assessed land price and mobile communication based on old people activities where 500 m vector areal unit within 15 minutes in Yongin-city, Gyeonggi-do. As a result, the prediction accuracy of 83.2% in the support vector machine(SVM) of ML using the RBF kernel algorithm was obtained in simulation. Furthermore, the correlation result(0.63) was derived from ANN using backpropagation algorithm. A geographically weighted regression(GWR) was also performed to analyze spatial autocorrelation within variables. As a result of this analysis, the coefficient of determination was 70.1%, which showed good explanatory power. Moran's I and Getis-Ord Gi coefficients are analyzed to investigate spatially outlier as well as distribution patterns. This study can be used to solve the welfare imbalance of the aged considering the local conditions of the government recently.

• Journal of the Korean association of regional geographers
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• v.21 no.3
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• pp.583-592
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• 2015

As the increase of an environmental disease has become a social problem after industrialization, academic interest in a spatial difference and characteristics of an environmental disease is on rise. The purpose of this study is to analyze the spatial distribution and characteristics of an environmental disease using the data provided by National Health Insurance Corporation in 2009. This research is focusing on atopic dermatitis among a variety of environmental diseases and shows the map that atopic dermatitis patients are distributed. Also, The Local Moran's I show how spatial autocorrelation of atopic dermatitis patients are distributed. First, the distribution of atopic dermatitis patients show the spatial difference. Second, 42 places including the western part of Incheon are hot spots of atopic dermatitis. Third, 39 places including Danyang are cold spot of atopic dermatitis. Forth, Jeju-si and Seogwipo-si are unusually hot spot of atopic dermatitis. These results have important implications that further research need to be done in public health geography.

• Journal of Korean Society of Forest Science
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• v.97 no.2
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• pp.165-170
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• 2008

Litterfall has been recognized an important part of the forest ecosystem production, playing a major pathway in energy flow and nutrient cycling through the ecosystem. This study was carried out to examine the quantity and components, temporal variation, and spatial heterogeneity of the litterfall in the mixed broadleaved-Korean pine forest. The data were collected from the 9ha permanent experimental plot, of which on the center area, i.e. $150m{\times}150m$, the total number of 319 circular litterfall traps with the size of $0.5m^2$ were established to collect falling litterfall. The results showed that the annual amount of litterfall was totalized 3,033.7 kg/ha, occupying broad-leaves of 39.3%, conifer-leaves of 29.5%, others of 18.5%, branches of 10.4%, and seeds of 2.3%. The peak point of the litterfall production was made at the end of September, proportionating 32.2% of total amount. The analysis of semivariogram revealed the existence of high spatial heterogeneity, calculated the scale of spatial heterogeneity ranged from 11.6 m to 29.1 m. The result of proportion (C/[Co+C]) showed that spatial heterogeneity of autocorrelation in total spatial heterogeneity were from 97.0% to 100%. The relatively heavy branches and others had significant differences in litterfall production between the areas of canopy gap and closed canopy in the 95% probability level, but the other components did not show statistical differences.

• The Korean Journal of Applied Statistics
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• v.29 no.5
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• pp.873-885
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• 2016

Onions are grown in a few specific regions of Korea that depend on the climate and the regional characteristic of the production area. Therefore, when onion yields are to be estimated, it is reasonable to use a statistical model in which both the climate and the region are considered simultaneously. In this paper, using a spatial panel regression model, we predicted onion yields with the different weather conditions of the regions. We used the spatial auto regressive (SAR) model that reflects the spatial lag, and panel data of several climate variables for 13 main onion production areas from 2006 to 2015. The spatial weight matrix was considered for the model by the threshold value method and the nearest neighbor method, respectively. Autocorrelation was detected to be significant for the best fitted model using the nearest neighbor method. The random effects model was chosen by the Hausman test, and the significant climate variables of the model were the cumulative duration time of sunshine (January), the average relative humidity (April), the average minimum temperature (June), and the cumulative precipitation (November).

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.3
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• pp.63-70
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• 2018

In this study, a simple probabilistic approach using equivalent coefficient of consolidation ($c_e$) was proposed to consider the spatial variability of coefficient of vertical consolidation ($c_v$), and the effect of the probability distribution of coefficient of consolidation on degree of consolidation in heterogeneous soil was investigated. The statistical characteristics of consolidation coefficient were estimated from 1,226 field data, and four probability distributions (Normal, Log-normal, Gamma, and Weibull) were applied to consider the effect of probability distribution. The random fields of coefficient of consolidation were generated based on Karhunen-Loeve expansion. Then, the equivalent coefficient of consolidation was calculated from the random field and used as the input value of consolidation analysis. As a result, the probabilistic analysis can be performed effectively by separating random field and numerical analysis, and probabilistic analysis was performed using a Latin hypercube Monte Carlo simulation. The results showed that the statistical properties of $c_e$ were changed by the probability distribution and spatial variability of $c_v$, and the probability distribution of $c_v$ has considerable effects on the probabilistic results. There was a large difference of failure probability depend on the probability distribution when the autocorrelation distance was small (i.e., highly heterogeneous soil). Therefore, the selection of a suitable probability distribution of $c_v$ is very important for reliable probabilistic analysis of consolidation.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.23 no.7 s.166
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• pp.1139-1146
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• 1999

Reliability analysis of structures based on fracture mechanics requires knowledge on statistical characteristics of the parameter C and m in the fatigue crack growth law, $da/dN=C({\Delta}K)^m$. The purpose of the present study is to investigate if it is possible to predict fatigue crack growth rate by only the fluctuation of the parameter C. In this study, Paris-Erdogan law is adopted, where the author treat the parameter C as random and m as constant. The fluctuation of crack growth rate is assumed only due to the parameter C. The growth resistance coefficient of material to fatigue crack growth (Z=1/C) was treated as a spatial stochastic process, which varies randomly on the crack path. The theoretical crack growth rates at various stress intensity factor range are discussed. Constant ${\Delta}K$ fatigue crack growth tests were performed on the structural steel, SM45C. The experimental data were analyzed to determine the autocorrelation function and Weibull distributions of the fatigue crack growth resistance. And also, the effect of the parameter m of Paris' law due to variation of fatigue crack growth resistance was discussed.

• Journal of Digital Convergence
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• v.19 no.5
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• pp.93-103
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• 2021

The special means of transportation introduced to improve the mobility of the transportation vulnerable met the number of legal standards in 2016, but lack of development in terms of quality, such as the existence of long waiting times. In order to streamline the operation of special means of transportation, long-term standby traffic, which is the top 25% of the wait time, was extracted from the Daegu Metropolitan Government's special transportation history data, and spatial autocorrelation analysis and social network analysis were conducted. As a result of the analysis, the correlation between the average waiting time of special transportation users and the space was high. As a result of the analysis of internal degree centrality, the peak time zone is mainly visited by general hospitals, while the off-peak time zone shows high long-term waiting demand for visits by lawmakers. The analysis of external degree centrality showed that residential-based traffic demand was high in both peak and off-peak hours. The results of this study are considered to contribute to the improvement of the quality of the operation of special transportation means, and the academic implications and limitations of the study are also presented.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.10a
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• pp.11-18
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• 2004

In this paper, an efficient model reduction scheme is presented for large scale dynamic systems. The method is founded on a modal analysis in which optimal eigenvalue is extracted from time samples of the given system response. The techniques we discuss are based on classical theory such as the Karhunen-Loeve expansion. Only recently has it been applied to structural dynamics problems. It consists in obtaining a set of orthogonal eigenfunctions where the dynamics is to be projected. Practically, one constructs a spatial autocorrelation tensor and then performs its spectral decomposition. The resulting eigenfunctions will provide the required proper orthogonal modes(POMs) or empirical eigenmodes and the correspondent empirical eigenvalues (or proper orthogonal values, POVs) represent the mean energy contained in that projection. The purpose of this paper is to compare the reduced order model using Karhunen-Loeve expansion with the full model analysis. A cantilever beam and a simply supported plate subjected to sinusoidal force demonstrated the validity and efficiency of the reduced order technique by K-L method.