• Korean Journal of Food Science and Technology
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• v.40 no.6
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• pp.603-610
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• 2008

The principal objective of current study was to evaluate the potential of near infrared reflectance spectroscopy (NIRS) as a non-destructive method for the prediction of the amylose and protein contents of un-hulled and brown rice in broad-based calibration models. The average amylose and protein content of 75 rice accessions were 20.3% and 7.1%, respectively. Additionally, the range of amylose and protein content were 16.6-24.5% and 3.8-9.3%, respectively. In total, 79 rice germplasms representing a wide range of chemical characteristics, variable physical properties, and origins were scanned via NIRS for calibration and validation equations. The un-hulled and brown rice samples evidenced distinctly different patterns in a wavelength range from 1,440 nm to 2,400 nm in the original NIR spectra. The optimal performance calibration model could be obtained by MPLS (modified partial least squares) using the first derivative method (1:4:4:1) for un-hulled rice and the second derivative method (2:4:4:1) for brown rice. The correlation coefficients $(r^2)$ and standard error of calibration (SEC) of protein and amylose contents for the un-hulled rice were 0.86, 2.48, and 0.84, 1.13, respectively. The $r^2$ and SEC of protein and amylose content for brown rice were 0.95, 1.09 and 0.94, 0.42, respectively. The results of this study suggest that the NIRS technique could be utilized as a routine procedure for the quantification of protein and amylose contents in large accessions of un-hulled rice germplasms.

• Korean Journal of Remote Sensing
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• v.35 no.6_1
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• pp.933-944
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• 2019

This study analyzes the tide deformation of land boundary regions on the east (Region A) and west (Region B) sides of the Ross Ice Shelf in Antarctica using Double-Differential Interferometric Synthetic Aperture Radar (DDInSAR). A total of seven Sentinel-1A SAR images acquired in 2015-2016 were used to estimate the accuracy of tide prediction model and Young's modulus of ice shelf. First, we compared the Ross Sea Height-based Tidal Inverse (Ross_Inv) model, which is a representative tide prediction model for the Antarctic Ross Sea, with the tide deformation of the ice shelf extracted from the DDInSAR image. The accuracy was analyzed as 3.86 cm in the east region of Ross Ice Shelf and it was confirmed that the inverse barometric pressure effect must be corrected in the tide model. However, in the east, it is confirmed that the tide model may be inaccurate because a large error occurs even after correction of the atmospheric effect. In addition, the Young's modulus of the ice was calculated on the basis of the one-dimensional elastic beam model showing the correlation between the width of the hinge zone where the tide strain occurs and the ice thickness. For this purpose, the grounding line is defined as the line where the displacement caused by the tide appears in the DDInSAR image, and the hinge line is defined as the line to have the local maximum/minimum deformation, and the hinge zone as the area between the two lines. According to the one-dimensional elastic beam model assuming a semi-infinite plane, the width of the hinge region is directly proportional to the 0.75 power of the ice thickness. The width of the hinge zone was measured in the area where the ground line and the hinge line were close to the straight line shown in DDInSAR. The linear regression analysis with the 0.75 power of BEDMAP2 ice thickness estimated the Young's modulus of 1.77±0.73 GPa in the east and west of the Ross Ice Shelf. In this way, more accurate Young's modulus can be estimated by accumulating Sentinel-1 images in the future.

• Korean Journal of Agricultural and Forest Meteorology
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• v.7 no.2
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• pp.132-140
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• 2005

This study was conducted to develop regional site index equations for main tree species in Gangwon, Gyunggi-Chungcheong, Gyungsang, and Jeolla area of Korea, using environmental and soil factors obtained from a digital forest site map. Using the large data set obtained from the digital forest map, a total of 28 environmental and soil factors were regressed on site index by tree species for developing the best site index equations for each of the regions. The selected main tree species were Larix 1eptolepis, Pinus koraiensis, Pinus densiflora, Pinus thunbergii, and Quercus acutissima. Finally, four to five environmental and soil factors by species were chosen as independent variables in defining the best regional site index equations with the highest coefficients of determination $(R^2)$. For those site index equations, three evaluation statistics such as mean difference, standard deviation of difference and standard error of difference were applied to the data sets independently collected from fields within the region. According to the evaluation statistics, it was found that the regional site index equations by species developed in this study conformed well to the independent data set, having relatively low bias and variation. It was concluded that the regional site index equations by species had sufficient capability for the estimation of site productivity.

• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.1
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• pp.36-44
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• 2010

In order to rehabilitate forest sites damaged by wildfire via natural or artificial restoration, it is important to determine right tree species, which can acclimate to biogeoclimatic environment at the sites. The objectives of this study were to develop site index equation of different tree species for estimating forest productivity and to provide information on species selection for post-wildfire restoration. Site index equation was developed based on environmental information from wildfire damaged areas in Gangneung, Goseong, Donghae, and Samcheok, where were located in east coastal areas of South Korea. Despite the small numbers (4~5) of environmental variables used for the development of the site index equations, statistical analysis (e.g. mean difference, standard deviation of difference, and standard error of difference) showed relatively low bias and variation, suggesting that those equations can provide relatively high capability of estimation and practical applicability with high effectiveness. The small numbers of the variables enabled the model to be applied in a wide range of usages including determination of appropriate tree species for post-wildfire restoration. The estimation of forest site productivity showed the possibility of large distribution in east coastal region as the best site for Korean ash (Fraxinus rhynchophylla) and original oak (Quercus variabilis) that can be used for firebreak in the region. These results imply that damages by forest fire can be reduced significantly by replacing existing pure coniferous forests in the area with ones dominated by broad-leaved deciduous stands, which can play an important role as fire break and/or prevent a transition from surface fire to crown fire.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.3
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• pp.215-231
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• 2020

Forest landscape models (FLMs) can be used to investigate the complex interactions of various ecological processes and patterns, which makes them useful tools to evaluate how environmental and anthropogenic variables can influence forest ecosystems. However, due to the large spatio-temporal scales in FLMs studies, parameterization and validation can be extremely challenging when applying to new study areas. To address this issue, we focused on the parameterization and application of a spatially explicit forest landscape model, LANDIS-II, to Mt. Gyebang, South Korea, with the use of the National Forest Inventory (NFI) and long-term ecological research (LTER) site data. In this study, we present the followings for the biomass succession extension of LANDIS-II: 1) species-specific and spatial parameters estimation for the biomass succession extension of LANDIS-II, 2) calibration, and 3) application and validation for Mt. Gyebang. For the biomass succession extension, we selected 14 tree species, and parameterized ecoregion map, initial community map, species growth characteristics. We produced ecoregion map using elevation, aspect, and topographic wetness index based on digital elevation model. Initial community map was produced based on NFI and sub-alpine survey data. Tree species growth parameters, such as aboveground net primary production and maximum aboveground biomass, were estimated from PnET-II model based on species physiological factors and environmental variables. Literature data were used to estimate species physiological factors, such as FolN, SLWmax, HalfSat, growing temperature, and shade tolerance. For calibration and validation purposes, we compared species-specific aboveground biomass of model outputs and NFI and sub-alpine survey data and calculated coefficient of determination (R²) and root mean square error (RMSE). The final model performed very well, with 0. 98 R² and 8. 9 RMSE. This study can serve as a foundation for the use of FLMs to other applications such as comparing alternative forest management scenarios and natural disturbance effects.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.29 no.5
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• pp.217-227
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• 2017

The object of this study is to estimate the net volume transport and the residual flow that changed by space and time at southern part of Yeomha channel, Gyeonggi Bay. The cross-section observation was conducted at the mid-part (Line2) and the southern end (Line1) of Yeomha channel for 13 hours during neap and spring-tides, respectively. The Lagrange flux is calculated as the sum of Eulerian flux and Stokes drift, and the residual flow is calculated by using least square method. It is necessary to unify the spatial area of the observed cross-section and average time during the tidal cycle. In order to unify the cross-sectional area containing such a large vertical tidal variation, it was necessary to convert into sigma coordinate system by horizontally and vertically for every hour. The converted sigma coordinate system is estimated to be 3~5% error when compared with the z-level coordinate system which shows that there is no problem for analyzing the data. As a result, the cross-sectional residual flow shows a southward flow pattern in both spring and neap tides at Line2, and also have characteristic of the spatial residual flow fluctuation: it northwards in the main line direction and southwards at the end of both side of the waterway. It was confirmed that the residual flow characteristics at Line2 were changed by the net pressure due to the sea level difference. The analysis of the net volume transport showed that it tends to southwards at $576m^3s^{-1}$, $67m^3s^{-1}$ in each spring tide and neap tide at Line2. On the other hand, in the control Line1, it has tendency to northwards at $359m^3s^{-1}$ and $248m^3s^{-1}$. Based on the difference between the two observation lines, it is estimated that net volume transport will be out flow about $935m^3s^{-1}$ at spring tide stage and about $315m^3s^{-1}$ at neap tide stage as the intertidal zone between Yeongjong Island and Ganghwa Island. In other words, the difference of pressure gradient and Stokes drift during spring and neap tide is main causes of variation for residual current and net volume transport.

• Journal of the Korean Chemical Society
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• v.35 no.3
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• pp.189-195
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• 1991

Two crystal structures of dehydrated $Ag_{2.8}ZN_{4.6}-A$ and of its ethylene sorption complex have been determined by single-crystal X-ray diffraction techniques. The structures were solved and refined in the cubic space group Pm3m at 23(1)$^{\circ}$C. Dehydration of two crystals studied were achieved at 400$^{\circ}$C and $2{\times}10^{-6}$ Torr for 2 days and one crystal was treated with 250 Torr of ethylene at 25(1)$^{\circ}$C. The structures of dehydrated $Ag_{2.8}ZN_{4.6}-A$ (a = 12.137(2) ${\AA}$ and of its ethylene sorption complex (a = 12.106(2)${\AA}$) were refined to final error indices, R(weighted) = 0.044 with 237 reflections and R(weighted) = 0.050 with 301 reflections, respectively, for which I > 3${sigma}$(I). 2.8 $Ag^+$ ions are recessed 0.922(2) ${\AA}$ from (111) plane of three 6-ring oxygens into the large cavity where each forms a lateral ${\pi}$ complex with an ethylene molecule. These $Ag^+$ ions are in 2.240(5)${\AA}$ from three framework oxide ions and 2.290(5) ${\AA}$ from each carbon atom of an ethylene molecule. The $Zn^{2+}$ ions occupy two different threefold axis positions of the unit cell. 2.8 $Zn^{2+}$ ions are recessed 0.408(2) ${\AA}$ from (111) plane of the 6-ring oxygens and each $Zn^{2+}$ ion forms a $\pi$ complex with an $C_2H_4$ molecule. The distances between $Zn^{2+}$ ions and carbon atom of ethylene molecule, Zn(2)-C = 2.78(4) ${\AA}$ are long. This indicates that this bond is relatively weak.

• Journal of the Korea Concrete Institute
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• v.24 no.3
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• pp.293-303
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• 2012

Recently, as construction technology improved, concrete structures not only became larger, taller and longer but were able to perform various functions. However, if extreme loads such as impact, blast, and fire are applied to those structures, it would cause severe property damages and human casualties. Especially, the structural responses from extreme loading are totally different than that from quasi-static loading, because large pressure is applied to structures from mass acceleration effect of impact and blast loads. Therefore, the strain rate effect and damage levels should be considered when concrete structure is designed. In this study, the low velocity impact loading test of steel fiber reinforced concrete (SFRC) slabs including 0%~1.5% (by volume) of steel fibers, and strengthened with two types of FRP sheets was performed to develop an impact resistant structural member. From the test results, the maximum impact load, dissipated energy and the number of drop to failure increased, whereas the maximum displacement and support rotation were reduced by strengthening SFRC slab with FRP sheets in tensile zone. The test results showed that the impact resistance of concrete slab can be substantially improved by externally strengthening using FRP sheets. This result can be used in designing of primary facilities exposed to such extreme loads. The dynamic responses of SFRC slab strengthened with FRP sheets under low velocity impact load were also analyzed using LS-DYNA, a finite element analysis program with an explicit time integration scheme. The comparison of test and analytical results showed that they were within 5% of error with respect to maximum displacements.

• Bulletin of the Korean Chemical Society
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• v.30 no.6
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• pp.1285-1292
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• 2009

Large single crystals of zeolite, |$Na_{75}$|[$Si_{117}Al_{75}O_{384}$]-FAU (Na-Y, Si/Al = 1.56), were synthesized from gels with composition of 3.58Si$O_2$ : 2.08NaAl$O_2$ : 7.59NaOH : 455$H_2$O : 5.06TEA : 2.23TCl. One of these, a colorless single-crystal was ion exchanged by allowing aqueous 0.02 M CsOH to flow past the crystal at 293 K for 3 days, followed by dehydration at 673 K and 1 ${\times}\;10^{-6}$ Torr for 2 days. The crystal structure of fully dehydrated partially $Cs^+$-exchanged zeolite Y, |$Cs_{45}Na_{30}$|[$Si_{117}Al_{75}O_{384}$]-FAU per unit cell (a = 24.9080(10) $\AA$) was determined by single-crystal X-ray diffraction technique in the cubic space group Fd $\overline{3}$ m at 294(1) K. The structure was refined using all intensities to the final error indices (using only the 877 reflections with $F_o\;>\;4{\sigma}(F_o))\;R_1$ = 0.0966 (Based on F) and $R_2\;=\;0.2641\;(Based\;on\;F^2$). About forty-five $Cs^+$ ions per unit cell are found at six different crystallographic sites. The 2 $Cs^+$ ions occupied at site I, at the centers of double 6-ring (D6Rs, Cs-O = 2.774(10) $\AA$ and O-Cs-O = 88.9(3) and 91.1(3)$^o$). Two $Cs^+$ ions are found at site I’ in the sodalite cavity; the $Cs^+$ ions were recessed 2.05 $\AA$ into the sodalite cavity from their 3-oxygen plane (Cs-O = 3.05(3) $\AA$ and O-Cs-O = 77.4(13)$^o$). Site-II’ positions (opposite single 6-rings in the sodalite cage) are occupied by 7 $Cs^+$ ions, each of which extends 2.04 $\AA$ into the sodalite cage from its 3-oxygen plane (Cs-O = 3.067(11) $\AA$ and O-Cs-O = 80.1(3)$^o$). The 26 $Cs^+$ ions are nearly three-quarters filled at site II in the supercage, being recessed 2.34 $\AA$ into the supercage (Cs-O = 3.273(8) $\AA$ and O-Cs-O = 74.3(3)$^o$). The 4 $Cs^+$ ions are found at site III deep in the supercage (Cs-O = 3.321(19) and 3.08(3) $\AA$), and 4 $Cs^+$ ions at another site III’ (Cs-O = 2.87(4) and 3.38(4) $\AA$). About 30 $Na^+$ ions per unit cell are found at one crystallographic site; The $Na^+$ ions are located at site I’ in the sodalite cavity opposite double 6-rings (Na-O = 2.578(11) $\AA$ and O-Na-O = 97.8(4)$^o$).

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.99-112
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• 2010

Ensemble learning is a method for improving the performance of classification and prediction algorithms. It is a method for finding a highly accurateclassifier on the training set by constructing and combining an ensemble of weak classifiers, each of which needs only to be moderately accurate on the training set. Ensemble learning has received considerable attention from machine learning and artificial intelligence fields because of its remarkable performance improvement and flexible integration with the traditional learning algorithms such as decision tree (DT), neural networks (NN), and SVM, etc. In those researches, all of DT ensemble studies have demonstrated impressive improvements in the generalization behavior of DT, while NN and SVM ensemble studies have not shown remarkable performance as shown in DT ensembles. Recently, several works have reported that the performance of ensemble can be degraded where multiple classifiers of an ensemble are highly correlated with, and thereby result in multicollinearity problem, which leads to performance degradation of the ensemble. They have also proposed the differentiated learning strategies to cope with performance degradation problem. Hansen and Salamon (1990) insisted that it is necessary and sufficient for the performance enhancement of an ensemble that the ensemble should contain diverse classifiers. Breiman (1996) explored that ensemble learning can increase the performance of unstable learning algorithms, but does not show remarkable performance improvement on stable learning algorithms. Unstable learning algorithms such as decision tree learners are sensitive to the change of the training data, and thus small changes in the training data can yield large changes in the generated classifiers. Therefore, ensemble with unstable learning algorithms can guarantee some diversity among the classifiers. To the contrary, stable learning algorithms such as NN and SVM generate similar classifiers in spite of small changes of the training data, and thus the correlation among the resulting classifiers is very high. This high correlation results in multicollinearity problem, which leads to performance degradation of the ensemble. Kim,s work (2009) showedthe performance comparison in bankruptcy prediction on Korea firms using tradition prediction algorithms such as NN, DT, and SVM. It reports that stable learning algorithms such as NN and SVM have higher predictability than the unstable DT. Meanwhile, with respect to their ensemble learning, DT ensemble shows the more improved performance than NN and SVM ensemble. Further analysis with variance inflation factor (VIF) analysis empirically proves that performance degradation of ensemble is due to multicollinearity problem. It also proposes that optimization of ensemble is needed to cope with such a problem. This paper proposes a hybrid system for coverage optimization of NN ensemble (CO-NN) in order to improve the performance of NN ensemble. Coverage optimization is a technique of choosing a sub-ensemble from an original ensemble to guarantee the diversity of classifiers in coverage optimization process. CO-NN uses GA which has been widely used for various optimization problems to deal with the coverage optimization problem. The GA chromosomes for the coverage optimization are encoded into binary strings, each bit of which indicates individual classifier. The fitness function is defined as maximization of error reduction and a constraint of variance inflation factor (VIF), which is one of the generally used methods to measure multicollinearity, is added to insure the diversity of classifiers by removing high correlation among the classifiers. We use Microsoft Excel and the GAs software package called Evolver. Experiments on company failure prediction have shown that CO-NN is effectively applied in the stable performance enhancement of NNensembles through the choice of classifiers by considering the correlations of the ensemble. The classifiers which have the potential multicollinearity problem are removed by the coverage optimization process of CO-NN and thereby CO-NN has shown higher performance than a single NN classifier and NN ensemble at 1% significance level, and DT ensemble at 5% significance level. However, there remain further research issues. First, decision optimization process to find optimal combination function should be considered in further research. Secondly, various learning strategies to deal with data noise should be introduced in more advanced further researches in the future.