• Journal of the Korean Geotechnical Society
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• v.18 no.5
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• pp.37-42
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• 2002

Artificial neural networks are efficient computing techniques that are widely used to solve complex problems in many fields. In this paper a liquefaction potential was estimated by using a back propagation neural network model applicated to cyclic triaxial test data, soil parameters and site investigation data. Training and testing of the network were based on a database of 43 cyclic triaxial test data from 00 sites. The neural networks are trained by modifying the weights of the neurons in response to the errors between the actual output values and the target output value. Training was done iteratively until the average sum squared errors over all the training patterns were minimized. This generally occurred after about 15,000 cycles of training. The accuracy from 72% to 98% was shown for the model equipped with two hidden layers and ten input variables. Important effective input variables have been identified as the NOC,$D_10$ and (N$_1$)$_60$. The study showed that the neural network model predicted a CSR(Cyclic shear stress Ratio) of silty-sand reasonably well. Analyzed results indicate that the neural-network model is more reliable than simplified method using N value of SPT.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.9
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• pp.1027-1032
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• 2012

Two types of very small multiplying gears and arrays have been developed for new dental hand-pieces, and the increased speed ratios, modules, number of teeth, gear diameters, and gear types were calculated based on the dynamics of the machinery. The contacting and bending strengths were evaluated for gear teeth with two design concepts using AGMA equations and finite element analyses, and the contacting stresses on teeth with and without DLC (diamond-like-carbon) coating layers were calculated. Fatigue and tension tests were performed to obtain an S-N curve, the Young's modulus, and the strength of the gear material, and these were utilized in the analyses. Slightly larger stresses were found for 2-axis-type gears than for other types of gears, and the S-N curves showed that a gear lifetime of 109 cycles was satisfied. The contacting stresses in gears coated with DLC were reduced by 30%. A new prototype model of a hand-piece with small gears was successfully fabricated and tested.

• Korean Journal of Environmental Biology
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• v.39 no.3
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• pp.273-288
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• 2021

We analyzed the spatio-temporal distribution characteristics of water quality and phytoplankton communities in the Isa Stream systems (ISS) from Sangsa Lake to Suncheon Bay. Sangsa Lake showed relatively oligotrophic and mesotrophic conditions, but the freshwater and mixed brackish water zones showed more severe eutrophication than Sangsa Lake and Suncheon Bay due to the influence of industrial waste such as livestock waste. In terms of the phytoplankton community, the number of phytoplankton species was higher in freshwater and mixed brackish water zones than in Sangsa Lake and Suncheon Bay, but the cell density and Chlorophyll-a concentrations (Chl-a) were relatively high in Sanga Lake and Suncheon Bay. In particular, the mesotrophic species Fragilaria crotonensis and Asterionella formosa showed different dominance in the surface and bottom layers, and the influence of A. formosa was significant in the freshwater and mixed brackish water zones in spring and summer. However, Skeletonema costatum-ls, a eutrophic indicator species, dominated in mixed brackish water zones to seawater in autumn and winter. Thus, the severe eutrophication and rapid environmental changes in the ISS could seriously damage the coastal ecosystem in Suncheon Bay. These ecosystem changes are threatening in terms of conservation and management of the UNESCO Suncheon Biosphere Reserve and Yeoja Bay including Suncheon Bay, which recorded the first Ramsar wetland in Korea. Therefore, further research is needed to establish an in-depth management plan.

• Korean Journal of Optics and Photonics
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• v.33 no.1
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• pp.28-34
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• 2022

We study through computational simulation the focal performance of an infrared (IR) Fresnel lens, composed of a multilayer-graphene zone plate formed under a graphene electrode. Here the Fermi level E_F of the patterned multilayer graphene is adjusted by the overlying graphene electrode. The Fresnel lens effect, with respect to the reflectance contrast between the graphene electrode and the 8-layer graphene zone plate placed on a glass substrate, has been analyzed over a broad wavelength range from 4 to 30 ㎛. As the optimal wavelength of 8 ㎛ (considering the reflectance and the reflectance-contrast ratio) is incident upon the Fresnel lens with a focal length of 240 ㎛, the focal intensity is enhanced by a factor of 4.3 as the E_F of multilayer graphene increases from 0.4 eV to 1.6 eV, and is improved by a factor of 5.8 as the number of graphene layers increases from two to eight. As a result, an all-graphene-based IR Fresnel zone-plate lens, exhibiting multifocal function (240 ㎛ and 360 ㎛) according to the selected E_F, is proposed as an ultrathin lens platform.

• Journal of Forest and Environmental Science
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• v.39 no.1
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• pp.20-26
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• 2023

Cow pea (Vigna unguiculata) was intercropped with Ziziphus spina-christi as summer forage in two consecutive seasons of 2017 and 2018. The aims to find out suitable agroforestry practice for saline soils of Khartoum State. And to investigate effect of tree spacing on forage biomass yield under semi -irrigated systems. Completely randomized block design with 3 replicates was conducted for this trial. Thus Z.spina-christi that fixed at 4×4 m was intercropped with cowpea at 1 m and 1.5 m spacing from trees trunk. Tree growth parameters were measured in terms of tree height, tree collar diameter, tree crown diameter and fruit yield per tree. While crop were parameters were determined in terms of plant height, number of plant, forage biomass yield per ha and land equivalent ratio. Soil profile of 1×1 m and 1.5 m depth was excavated and its features were described beside its chemical and physical properties were analyzed for 0-10 cm, 0-30 cm, and 30-60 cm and 60-100 cm layers. The results revealed that soil pH, CaCO₃, SAR, ESP, and EC ds/m were increased by increasing soil depths. Meanwhile tree growth in terms of tree height was significant in the first season 2017 when compared with tree collar diameter and tree crown diameter. Also significant differences were recorded for tree growth when compared with sole trees in the second season in 2018. Tree fruit showed marked variations between the two seasons, but it was higher under intercropping particularly at ZS2. Crop plant height was highly significant under sole cropping than intercropping in first season in 2017. In contrast forage biomass yield was significant under intercropping in ZS1 and ZS2 treatments. Land equivalent ratio was advantageous under this agroforestry system particularly under ZS2. Thus it recorded 5 and 9 for ZS2 in the two consecutive seasons respectively. Therefore, it is feasible to introduce this agroforestry system under such arid lands to provide summer forage yield of highly nutritive value and low cost for animals feed as well as to increase farmers' income and to halt desertification and to sequester carbon.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.3D
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• pp.407-415
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• 2008

This study presents the methodology to link with aerial photos for advancing the accuracy of topographic survey data that is used to calculate water volume in urban stream. First, GIS spatial interpolation technique as Inverse Distance Weight (IDW) and Kriging was applied to construct the terrain morphology to the sand-bar and grass area using cross-sectional survey data, and also validation point data was used to estimate the accuracy of created topographic data. As the result of comparison, IDW ($d^{-2}_{ij}$, 2nd square number) in Sand-bar area and Kriging Spherical model in grass area showed more efficient results in the construction of topographic data of river boundary. But the differences among interpolation methods are very slight. Image classification method, Minimum Distance Method (MDM) was applied to extract sand-bar and grass area that are located to river boundary efficiently and the elevation value of extracted layers was allocated to the water level point value. Water volume with topographic data from aerial photos shows the advanced accuracy of 13% (in sand-bar) and 12% (in grass) compared to the water volume of original terrain data. Therefore, terrain analysis method in river linking with aerial photos is efficient to the monitoring about sand-bar and grass area that are located in the downstream of Dam in flooding season, and also it can be applied to calculate water volume efficiently.

• Journal of Korea Water Resources Association
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• v.33 no.5
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• pp.537-550
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• 2000

In this study, Neural Networks models were used to forecast daily streamflow at Jindong station of the Nakdong River basin. Neural Networks models consist of CASE 1(5-5-1) and CASE 2(5-5-5-1). The criteria which separates two models is the number of hidden layers. Each model has Fletcher-Reeves Conjugate Gradient BackPropagation(FR-CGBP) and Scaled Conjugate Gradient BackPropagation(SCGBP) algorithms, which are better than original BackPropagation(BP) in convergence of global error and training tolerance. The data which are available for model training and validation were composed of wet, average, dry, wet+average, wet+dry, average+dry and wet+average+dry year respectively. During model training, the optimal connection weights and biases were determined using each data set and the daily streamflow was calculated at the same time. Except for wet+dry year, the results of training were good conditions by statistical analysis of forecast errors. And, model validation was carried out using the connection weights and biases which were calculated from model training. The results of validation were satisfactory like those of training. Daily streamflow forecasting using Neural Networks models were compared with those forecasted by Multiple Regression Analysis Mode(MRAM). Neural Networks models were displayed slightly better results than MRAM in this study. Thus, Neural Networks models have much advantage to provide a more sysmatic approach, reduce model parameters, and shorten the time spent in the model development.

• Korean Journal of Environment and Ecology
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• v.18 no.2
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• pp.124-130
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• 2004

The valley forests at Songgyesa-Motbong-Wolhatan Area in Deogyusan National Park were studied to investigate forest structure in relation to aspect and altitude of the slope. Density, mean DBH, mean height and basal area of the tree and subtree layers in the north-facing slope were greater than those in the south-facing slope. The impotance percentage of Fraxinus mandshurica and Carpinus cordata increased with increasing elevation while those of Quercus serrata and Quercus aliena decreased. Species diversity of the north-facing slope was 1.362 and that of the south-facing slope was 1.242. There was a tendency that number of species and species diversity decreased with increasing elevation. The result of cluster analysis for the tree and sub-tree layer indicated that the studied forests were classified into broad-leaved tree species community at the low and middle elevation belts of the south-facing slope and the north-facing slope, Fraxinus mandshurica-Quercus mongolica community at the high elevation belts of the south-facing slope and the north-facing slope and Quercus mongolica community at the top area. There were significantly positive correlations in the importance percentages among Quercus serrata, Betuzo davurica and Tilia amurensis. Carpinus laxiflora was significantly correlated with Cornus controversa, Tilia amurensis and Lindera obtusiloba. There was significantly negative correlation between Fraxinus mandshurica and Pinus densiflora.

• Economic and Environmental Geology
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• v.50 no.3
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• pp.195-214
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• 2017

Statistical landslide susceptibility analysis, which is widely used among various landslide susceptibility analysis approaches, predicts the unstable area by analyzing statistical relationship between landslide occurrence locations and landslide controlling factors. However, uncertainties are involved in the procedures of the susceptibility analysis and therefore, fuzzy approach has been used to deal properly with uncertainties. The fuzzy approach used fuzzy set theory and fuzzy membership function to quantify uncertainties involved in landslide controlling factors. Various fuzzy approaches were suggested in the procedure of the membership value determination and fuzzy operation in the previous researches. However, few studies were carried out to compare the analysis results obtained from various approaches for membership function determination and fuzzy operation. Therefore, in this study, the authors selected Jinbu area, which a large number of landslides were occurred at in 2006, to apply two most commonly used methods, the frequency ratio and the cosine amplitude method to derive membership values for each controlling factor. In addition, the integration of different thematic layers to produce landslide susceptibility map was performed by several fuzzy operators such as AND, OR, algebraic product, algebraic sum and Gamma operator. The results of the landslide susceptibility analysis using two different methods for the determination of fuzzy membership values and various fuzzy operators were compared on the basis of ROC graph to check the feasibility of the fuzzy based landslide susceptibility analysis.

• Journal of the Korean Vacuum Society
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• v.22 no.2
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• pp.98-104
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• 2013

$VO_2$ is an attractive thermochromic material, in which its electrical and optical properties can be switched by the structural phase-transition about $68^{\circ}C$. Recently, graphene is also a rising material which is researched as a transparent electrode because of its superior electrical and optical characteristics. In this respect, we try to fabricate the hybridized films using $VO_2$ and graphene on transparent sapphire substrate and then we investigate a structure and characterize an optical property for the samples as a function of temperature. According to the result of IR-transmittance analysis of $VO_2$ films as a function of temperature, the graphene-supported sapphire substrates are better about 10% than the bare sapphire substrates. The mean phase transition temperatures are also decreased as the number of graphene-layers increased and the hysteresis of phase transitions are narrowed.