• Journal of the Korea Society of Computer and Information
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• v.22 no.7
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• pp.31-37
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• 2017

There are lots of combined battlefield elements which complete the war. It looks problematic when collecting and analyzing these elements and then predicting the situation of war. Commander's experience and military power assessment have widely been used to come up with these problems, then simulated combat training program recently supplements the war-game models through recording real-time simulated combat data. Nevertheless, there are challenges to assess winning factors of combat. In this paper, we characterize the combat element (ce) by clustering simulated combat data, and then suggest multi-layered artificial neural network (ANN) model, which can comprehend non-linear, cross-connected effects among ces to assess mission completion degree (MCD). Through our ANN model, we have the chance of analyzing and predicting winning factors. Experimental results show that our ANN model can explain MCDs through networking ces which overperform multiple linear regression model. Moreover, sensitivity analysis of ces will be the basis of predicting combat situation.

• Nuclear Engineering and Technology
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• v.49 no.6
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• pp.1114-1124
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• 2017

Acceleration/preconditioning strategies available in the SCEPTRE radiation transport code are described. A flexible transport synthetic acceleration (TSA) algorithm that uses a low-order discrete-ordinates ($S_N$) or spherical-harmonics ($P_N$) solve to accelerate convergence of a high-order $S_N$ source-iteration (SI) solve is described. Convergence of the low-order solves can be further accelerated by applying off-the-shelf incomplete-factorization or algebraic-multigrid methods. Also available is an algorithm that uses a generalized minimum residual (GMRES) iterative method rather than SI for convergence, using a parallel sweep-based solver to build up a Krylov subspace. TSA has been applied as a preconditioner to accelerate the convergence of the GMRES iterations. The methods are applied to several problems involving electron transport and problems with artificial cross sections with large scattering ratios. These methods were compared and evaluated by considering material discontinuities and scattering anisotropy. Observed accelerations obtained are highly problem dependent, but speedup factors around 10 have been observed in typical applications.

• International journal of advanced smart convergence
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• v.10 no.3
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• pp.72-80
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• 2021

Metaverse is an immersive 3D virtual environment, a true virtual artificial community in which avatars act as the user's alter ego and interact with each other. If we do not manage the hype for the metaverse, which has recently been receiving a surge in interest, the metaverse will fail to cross the chasm. In this study, to provide stakeholders with insights for the successful introduction and growth of the 3D immersive next-generation virtual world, metaverse, we analyzed user-side interest, media-side interest, and research-side interest. For this purpose, in this study, search traffic, news frequency and topic, and research article frequency and topic were analyzed. The methodology and results of this study are expected to provide insight for the stable success of metaverse transformation and the coexistence of the real world and the virtual world through hyper-connection and hyper-convergence.

• Journal of Korean Ophthalmic Optics Society
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• v.18 no.4
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• pp.457-463
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• 2013

To determine the impact of artificial tears which include carboxymethyl cellulose on a hydrogel contact lenses. Methods: A contact lenses made of the cross-linking agent, EGDMA (ethylene glycol dimethacrylate) and HEMA (2-hydroxyethyl methacrylate) and with added NVP (n-vinyl-2-pyrrolidone) and MMA (methyl methacrylate) was evaluated for water content, refractive index, spectral transmittance and contact angle of produced contact lens. Results: The physical properties of the sampled copolymerized polymers showed that water content, refractive index, visible ray transmittance and contact angle were in the range of 26.61%~48.58%, 1.422~1.455, 80.8%~91.4% and $33.93^{\circ}{\sim}65.70^{\circ}$, respectively. In addition, after soaking with artificial tears, the water content, refractive index and contact angle were in the range of 24.46%~48.25%, 1.422~1.457, 77.0%~91.0% and $37.25^{\circ}{\sim}77.33^{\circ}$, respectively. The changes of the physical property depending on hydration time and showed an increase of refractive index and contact angle, decrease of water content and visible ray transmittance. Conclusions: Artificial tears which include carboxymethyl cellulose sodium which is used as a wetting agent influenced water content, refractive index, contact angle and spectral transmittance of a hydrogel contact lenses.

• Journal of Korea Water Resources Association
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• v.46 no.7
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• pp.697-706
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• 2013

In recent, Korea has faced on water quality management problems in reservoir and river because of increasing water temperature and rainfall frequency caused by climate change. This study is effectively to manage water quality for establishment of algal bloom forecasting models with artificial neural network. Daecheong reservoir located in Geum river has suitable environment for algal bloom because it has lots of contaminants that are flowed by rainfall. By using back propagation algorithm of artificial neural networks (ANNs), a model has been built to forecast the algal bloom over short-term (1, 3, and 7 days). In the model, input factors considered the hydrologic and water quality factors in Daecheong reservoir were analyzed by cross correlation method. Through carrying out the analysis, input factors were selected for algal bloom forecasting model. As a result of this research, the short term algal bloom forecasting models showed minor errors in the prediction of the 1 day and the 3 days. Therefore, the models will be very useful and promising to control the water quality in various rivers.

• Journal of the Korean Institute of Landscape Architecture
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• v.45 no.2
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• pp.11-22
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• 2017

To successfully create a low-carbon landscape in order to become a low-carbon city, it is necessary to understand the dynamics of artificial greening's resources on a multi-scale. Additionally, the effects of carbon storage should be quantitatively evaluated. The purpose of this study is to simulate and evaluate the changes in carbon storages of artificial ground trees using system dynamics throughout a long-term period. The process consisted of analyzing the dynamics of the multi-scale carbon cycle by using a casual loop diagram as well as simulating carbon storage changes in the green roof of the Gangnam-gu office building in 2008, 2018, 2028, and 2038. Results of the study are as follows. First, the causal loop diagram representing the relationship between the carbon storage of the artificial ground trees and the urban carbon cycle demonstrates that the carbon storage of the trees possess mutual cross-scale dynamics. Second, the main variables for the simulation model collected 'Biomass,' 'Carbon storage,' 'Dead organic matter,' and 'Carbon absorption,'and validated a high coefficient of determination, the value being ($R^2$=0.725, p<0.05). Third, as a result of the simulation model, we found that the variation in ranking of tree species was changing over time. This study also suggested the specific species of tree-such as Acer palmatum var. amoenum, Pinus densiflora, and Betula platyphylla-are used to improve the carbon storage in the green roof of the Gangnam-gu office building. This study can help contribute to developing quantitative and scientific criteria when designing, managing, and developing programs on low-carbon landscapes.

• Journal of Science Education
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• v.45 no.1
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• pp.105-117
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• 2021

The purpose of this study is to analyze the gender differences of elementary, junior high, and high school students in the artificial intelligence ethics awareness (hereinafter referred to as AIEA). This is a study to investigate whether there is a gender difference in the AIEA, and if so, when the gender difference will occur. This study was conducted with 198 elementary school students (98 female students, 100 male students), 265 middle school students (166 female students, 99 male students), and 114 high school students (58 female students and 56 male students) in I Metropolitan City. The results are as follows: First, a gender difference in the AIEA between all boys and girls was confirmed. Second, the gender difference in the AIEA tended to be solidified as the school age increased from elementary school to middle school and high school. Third, female students at all stages of elementary school, junior high school, and high school are not yet very reliable in artificial intelligence, and there is a greater concern about non-discrimination than boys. It turns out that they have a negative position on permission to enter the territory. Fourth, the interaction effects of school age and gender have been identified in 'stability and reliability,' and in 'permit and limit' categories. Taken together, these results show that an educational strategy that approaches the gender equality perspective of the educational program is necessary so that there will be no gender difference in the AIEA during artificial intelligence education activities.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.2 no.1
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• pp.48-57
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• 1999

This study was aimed to establish biotop unit of the mixed rural city for the method and process of the biotop mapping system. Survey site was Maejuri of Seunghwan(158ha), Gisanri of Mokchon(132ha) and Namkwanri, Pungsemeon(214ha). So the main process was divided by 4 schemes such as Biosphere, Geosphere, Antrosphere and Evaluation. Also the GIS(geographic information system) was used to make the database of the biotop and biotop complex, analyze the cross-combinations and analyze the characters of the biotop. Biotop mapping system had 5 steps which were proceeded with research goals, constructing the spatial database and attribute database, classifying the 3 types of biotop such as tree/shrub biotop, grass biotop and wetland biotop, cross-analyzing 3 biotop types with land use, habitat characters, relief characters and danger/disturbance elements and evaluating the 3 types of biotop. The results of applicating the biotop mapping system on the research site as followings : The distributions of the land uses in Maejuri, Seunghwan eup in Chonan city were recorded by forest(29.8%), orchard(14.1%) and landscaping around building site(9.0%). Gisanri, Mokchonmeon were composed of forest(64.5%), farm(12.8%) and Namkwanri, Pungsemeon were concentrated rice field(39.6%), dwell district(22.4%). The Tree/Shrub biotop type was reclassed by the forest type, natural and artificial decidous type with natural coniferous. The Grass biotop type was reclassed by the wild grassland type, garden type and peddy field with wild grassland. The distributions of the wet land were pointed high at the wet land type with reed marsh and edge vegetation around wet land in reservoir and river. The evaluation of the mapped bitopes was completed to the following aspect, "amenity" and "environmental education". A high value of 7.13%(1 class) was shown Maejuri, Seunghwan eup. The regions which were studied synthetically are divided to three parts ; the area where have nature and art mixed(Seunghwan), the area which is more artificial because people inhabit there for a long time(Pungsemeon) and the area that ecological environment is threatened by development pressure(Mokchonmeon). Therefore, ecological restoration plan which depends on specific property of the regions should be established. Also the interdisplinary researches were needed to develop the BMS(Biotop Mapping System) in Korea because of the differences with Germany, England's ecological habitat conditions.

• Journal of Sericultural and Entomological Science
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• v.38 no.2
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• pp.93-99
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• 1996

By treatment(dropping) of 0.1~0.4% colchicine solution on the sprouts of winter buds of hard wood cutting slips for 4~5 days, two lines of artificial autotetraploids from Yongchonppong and one line from Yeongbyonppong were bred and the important cultivative characteristics of those new lines were as follows. The greentip sprouting stage of the new bred lines in spring season is later than the parental varieties by two days, but growth speed of the new lines after sprouting was faster than that of the parental varieties reaching the same level development with the parental varieties at the fifth leaf sprouting stage to be mid varieties same as the origins. The leaf shape of the new bred lines was wide round and the petioloes were long and thick. The thickness of leaf was thicker than the parental varieties by 17-33% and single leaf weight was heavy. The leaf area weight increased by 21-31% and the content of chlorophyll was also higher by 11-33%. With all the characteristics, the new breds produced good quality of leaves. The length and number of branches were shorter and less, respectively, than the parental varieties, but the internode length was either same or longer than the parents. Looking at the characteristics, the constitution of shoots was slightly inferior to the parental varieties. The cold hardness expressed by the death top rate of Sawonppong 23 and Sawonppong 24 was same level as that of Yongchonppong, but Sawonppong 25 was stronger than Yeongbyonppong in it with a high infection rate of dwarf disease. The productivity was lower than the parental varieties, but young shoot rate to shoot and branch and the ratio of leaf to young shoot were higher than the parental varieties. The fertility of Sawonppong 23 and Sawonppong 24 was comparatively high with 62% of cross success, but that of Sawonppong 25 was low with 23.9% of cross success.

• Journal of Korea Water Resources Association
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• v.53 no.6
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• pp.395-408
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• 2020

This paper aims to develop and apply three different machine learning approaches (i.e., artificial neural networks (ANN), adaptive neuro-fuzzy inference systems (ANFIS), and wavelet-based neural networks (WNN)) combined with an evolutionary optimization algorithm and the k-fold cross validation for multi-step (days) streamflow forecasting at the catchment located in Algeria, North Africa. The ANN and ANFIS models yielded similar performances, based on four different statistical indices (i.e., root mean squared error (RMSE), Nash-Sutcliffe efficiency (NSE), correlation coefficient (R), and peak flow criteria (PFC)) for training and testing phases. The values of RMSE and PFC for the WNN model (e.g., RMSE = 8.590 ㎥/sec, PFC = 0.252 for (t+1) day, testing phase) were lower than those of ANN (e.g., RMSE = 19.120 ㎥/sec, PFC = 0.446 for (t+1) day, testing phase) and ANFIS (e.g., RMSE = 18.520 ㎥/sec, PFC = 0.444 for (t+1) day, testing phase) models, while the values of NSE and R for WNN model were higher than those of ANNs and ANFIS models. Therefore, the new approach can be a robust tool for multi-step (days) streamflow forecasting in the Seybous River, Algeria.