• Korean Journal of Remote Sensing
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• v.36 no.5_1
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• pp.653-666
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• 2020

Understanding the vegetation structure is important to manage forest resources for sustainable forest development. With the recent development of technology, it is possible to apply new technologies such as drones and deep learning to forests and use it to estimate the vegetation structure. In this study, the vegetation structure of Gongju, Samchuk, and Seoguipo area was identified by fusion of drone-optical images and LiDAR data using Artificial Neural Networks(ANNs) with the accuracy of 92.62% (Kappa value: 0.59), 91.57% (Kappa value: 0.53), and 86.00% (Kappa value: 0.63), respectively. The vegetation structure analysis technology using deep learning is expected to increase the performance of the model as the amount of information in the optical and LiDAR increases. In the future, if the model is developed with a high-complexity that can reflect various characteristics of vegetation and sufficient sampling, it would be a material that can be used as a reference data to Korea's policies and regulations by constructing a country-level vegetation structure map.

• Journal of dental hygiene science
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• v.13 no.4
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• pp.461-470
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• 2013

In order to examine the anticariogenic effect after fluoride varnish was applied to sound enamel and artificial caries enamel, anterior teeth of healthy cattle were used and divided into four groups such as group 1 (sound enamel), group 2 (application of fluoride varnish to sound enamel), group 3 (artificial caries enamel) and group 4 (application of fluoride varnish to artificial caries enamel). Remineralization on the surface of enamel and changes of crystalline structure after demineralization were observed by using a field emission scanning electron microscope (FE-SEM). Quantitative analysis of Ca and P was measured by using the energy dispersive X-ray spectrophotometer (EDS). The following conclusions were obtained: 1)Surface pattern of enamel was the roughest in group 3 due to the defects caused by porosity and microcracks. Group 4, group 1 and group 2 were followed in order; 2) It was found that pattern of crystalline structures in a group of application of fluoride varnish and a group of no application showed bigger change in artificial caries enamel than that in sound enamel. In other words, groups 4 and 1 showed a similar pattern; 3) The contents of Ca and P were higher in groups of application of fluoride varnish (group 2 and group 4) than in groups of no application of fluoride varnish (group 1 and group 3). Taken results of this study together, in the case of application of fluoride varnish, crystalline structure was changed by remineralization even in the sound enamel. In particular, porous structures showed a smooth and uniform pattern due to the recalcification in the artificial caries enamel. In addition, according to results of EDS analysis, the contents of Ca and P were increased and it had great anticariogenic effects which inhibit decalcification of sound enamel and artificial caries enamel.

• Journal of the Korean GEO-environmental Society
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• v.14 no.9
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• pp.31-37
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• 2013

In this study installation diameter, interval, area replacement ratio and ground hardness of applicable ground in C.G.S method should be mastered through surrounding ground by conducting modeling. Optimum artificial neural network was selected through the study of the parameter of artificial neural network and prediction model was developed by the relationship with numerical analysis and artificial neural network. As this result, C.G.S pile settlement and ground settlement were found to be equal in terms of diameter, interval, area replacement ratio and ground hardness, presented in a single curve, which means that the behavior pattern of applied ground in C.G.S method was presented as some form, and based on such a result, learning the artificial neural network for 3D behavior was found to be possible. As the study results of artificial neural network internal factor, when using the number of neural in hidden layer 10, momentum constant 0.2 and learning rate 0.2, relationship between input and output was expressed properly. As a result of evaluating the ground behavior of C.G.S method which was applied to using such optimum structure of artificial neural network model, is that determination coefficient in case of C.G.S pile settlement was 0.8737, in case of ground settlement was 0.7339 and in case of ground heaving was 0.7212, sufficient reliability was known.

• Journal of Korean Society of Steel Construction
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• v.21 no.2
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• pp.175-181
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• 2009

An intelligent control technique using a neural network is proposed for offshore structures exposed to sea-bed earthquakes. Fluid-structure interaction effect was considered in developing controller and a training algorithm for the neural network is presented. In the numerical example, the performance of the proposed neural network controller was compared with that of a passive controller and uncontrolled structures. Based on the example, it can be concluded that the proposed neuro-control scheme can be used for offshore structures with nonlinear characteristics due to its interaction with fluid.

• Korean Journal of Environment and Ecology
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• v.12 no.2
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• pp.138-146
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• 1998

Ten plots were established to study the vegetation structure of the Songinbong virgin forest in Ullungdo. It was classified into three communities Fagus crenata var. multinervis commnunity, Acer okamotoanum-Fagus crenata var. multinervis community, and Acer okamotoanum community. Shannon's diversity indicies of this area were not high(0.5150~0.8437), due to the geographical and vegetational characteristics. Considering the community structure(importance value, distribution of DBH class, and so on), the vegetation of the Songinbong virgin forest are thought to be stable continuously. With the analysis of plant growth type, it was presumed that Acer okamotoanum have increased after artificial disturbances in this area where Fagus crenata var. multinervis had been dominanat.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1788-1791
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• 2002

In the post-genome era. it is one of important research subject to Investigate the roles of the proteins in human body based on decoded genome information during Human Genome Project. In order to clarify them. it is necessary to analyze the structure of the protein crystals and their function. ' Crystallization is the beginning stage of protein structure determination process. There are some methods for structural analysis of the proteins, and general one is X-ray structural analysis method. In order to utilize this method for analyzing the protein crystal's structure, artificial protein crystallization is required. However, since artificial crystallizing work takes much time and manpower. the performance against its cost is still low. Therefore. we started to discuss to develop a supporting system for improving efficiency of the crystallization distinction procedure. In this paper, we examine to realize such supporting system for crystallization distinction using image-processing technique and report about our experimental result with many real protein solution images.

• Journal of Satellite, Information and Communications
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• v.12 no.2
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• pp.11-14
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• 2017

In this paper, we introduce a method of light focusing effect using prism structure to solve optical discontinuity of conventional external signage LED panels. The prims structures were patterned on a transparent polycarbonate substrate with MEMS and femto-second laser process. We have confirmed that the patterned prism structures on the substrate made artificial LED lights on empty space between the panels by light guide effect of the structure. The artificial light's lateral positions were controlled by thickness of polycarbonate substrate. This cost effective prim patterned transparent film can be utilized on digital signage LED panels to achieve good optical communication.

• Earthquakes and Structures
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• v.13 no.6
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• pp.573-588
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• 2017

The earthquake input is required when the soil-structure interaction (SSI) analysis is performed by the direct finite element method. In this paper, the earthquake is considered as the obliquely incident plane body wave arising from the truncated linearly elastic layered half space. An earthquake input method is developed for the time-domain three-dimensional SSI analysis. It consists of a new site response analysis method for free field and the viscous-spring artificial boundary condition for scattered field. The proposed earthquake input method can be implemented in the process of building finite element model of commercial software. It can result in the highly accurate solution by using a relatively small SSI model. The initial condition is considered for the nonlinear SSI analysis. The Daikai subway station is analyzed as an example. The effectiveness of the proposed earthquake input method is verified. The effect of the obliquely incident earthquake is studied.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.10a
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• pp.472-472
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• 2009

The safety of cultural properties, medical treatment and electrical communication equipments in a building was hardly considered against the earthquake induced vibration, while the integrity of the building structure has been taken into account through the resistant earthquake design. This paper presents design of a seismic isolation table for both indoor and outdoor electrical communication equipment. First of all, artificial earthquake waves compatible with floor and ground response spectra for electrical communication equipments are generated using previously recorded seismic waves. Two kinds of one-degree-of-freedom seismic isolation table systems: spring-linear damper and spring-friction damper systems are considered and their responses to artificial earthquake waves are simulated. Design parameter study for two seismic isolation tables are performed through simulations and a seismic isolation table for both indoor and outdoor electrical communication equipment is designed considering the simulation results.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.10a
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• pp.323-335
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• 1999

In this paper, we propose a new hybrid model of artificial neural networks(ANNs) and genetic algorithm (GA) to optimal feature transformation and feature weighting. Previous research proposed several variants of hybrid ANNs and GA models including feature weighting, feature subset selection and network structure optimization. Among the vast majority of these studies, however, ANNs did not learn the patterns of data well, because they employed GA for simple use. In this study, we incorporate GA in a simultaneous manner to improve the learning and generalization ability of ANNs. In this study, GA plays role to optimize feature weighting and feature transformation simultaneously. Globally optimized feature weighting overcome the well-known limitations of gradient descent algorithm and globally optimized feature transformation also reduce the dimensionality of the feature space and eliminate irrelevant factors in modeling ANNs. By this procedure, we can improve the performance and enhance the generalisability of ANNs.