• Journal of Microbiology and Biotechnology
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• v.10 no.2
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• pp.169-175
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• 2000

The filamentous soil bacterium Streptomyces coelicolor is known to produce four distinct antibiotics. The simultaneous global regulation for the biosynthesis of those four antibiotics was previously confirmed by absA and absB mutations that blocked all four antibiotics' biosynthesis without influencing their morphological differentiation. To study the complex regulatory cascade that controls the secondary metabolism in Streptomyces, a new abs-like mutation was characterized. namely absR, which is slightly leaky on a complete R2YE medium, yet tight on a minimal medium. A genetic analysis of the absR locus indicated that it is located at 10 o'clock on the genetic map, near the site of absA. A cloned copy of the absA gene that encoded bacterial two-component regulatory kinases did not restore antibiotic biosyntheis to the absR mutant. Accordingly, it is proposed that absR is another abs-type mutation which is less tight than the previously identified absA or absB mutations income medium conditions, and can be used to characterize another global regulatory gene for secondary metabolete formation in S. coelicolor.

• Proceedings of the Korean Geotechical Society Conference
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• 2004.03b
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• pp.219-226
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• 2004

We measure subsidences occurred in a reclaimed coastal land, Noksan industrial complex, by using JERS-1 SAR (1996-1998) and RADARSAT-1 SAR (2002-2003) dataset. SAR with a high spatial resolution (about several or several tens meter) can reveal the two-dimensional distribution of settlement that would be bardly estimated from in situ measurements. The DInSAR results show significant deformation signal associated with soil consolidation. Accuracy of the settlements estimated by 2-pass differential interferometry (DInSAR) is evaluated using the measurements of settlement gauge. A two-dimensional subsidence map is constructed from 7 qualified pairs. Comparing the JERS-1 radar measurements with the ground truth data yields the correlation coefficient of 0.87 (RMSE of 1.44 cm). The regression line shows the gradient of 1.04 and intercepts close to the origin, which implies that the unbiased settlement can be measured by DInSAR technique. The residual settlements are also detected from RADARSAT-1 pairs. The extent and amount of the settlements are matched well with ground truth data.

• International Journal of Ocean Engineering and Technology Speciallssue:Selected Papers
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• v.6 no.1
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• pp.22-29
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• 2003

This research aims at investigation of accuracy potential of RTK(Real-Time Kinematic) GPS in combination with Echo Sounder(E/S) for the coastal mapping. Apart from this purpose, the accuracy of ambiguity resolution with the OTF(On The Fly) method was tested with respect to the initialization time. The result shows that the accuracy is better than 1cm with 5-minute initialization in the distance of 10km baseline. The seaside topography was measured by the RTK GPS only, on the other hand the seafloor topography was surveyed in combination of RTK GPS and E/S. Comparing to the volume of seaside measured by RTK GPS and digital topographical map, the difference of only 2% was achieved. This indicates that the coastal mapping. As a result, it has been revealed that every possible noise in surveying could be corrected and the accuracy could be improved. The accuracy of GPS data acquired in real time was as good as that acquired by post processing. It is expected that it will be useful for the analysis of coastal geographic characteristics because DTM(Digital Terrain Model) can be also constructed for the harbor reclamation, the dredging, and the variation of soil movement in a river.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.77-82
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• 2003

The purpose of this study is to develop landslide susceptibility analysis techniques using artificial neural network and to apply the developed techniques to the study area of janghung in Korea. Landslide locations were identified in the study area from interpretation of satellite image and field survey data, and a spatial database of the topography, soil, forest and land use were consturced. The 13 landslide-related factors were extracted from the spatial database. Using those factors, landslide susceptibility was analyzed by artificial neural network methods, and the susceptibility map was made with a e15 program. For this, the weights of each factor were determinated in 5 cases by the backpropagation method, which is a type of artificial neural network method. Then the landslide susceptibility indexes were calculated using the weights and the susceptibility maps were made with a GIS to the 5 cases. A GIS was used to efficiently analyze the vast amount of data, and an artificial neural network was turned out be an effective tool to analyze the landslide susceptibility.

• Journal of Environmental Health Sciences
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• v.31 no.6
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• pp.467-474
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• 2005

The runoff characteristics of combined sewer overflow(CSO) in the urban area of Jeonju were investigated and analyzed by using the SWMM (Storm Water Management Model) and GIS. From August to November 2004, investigations on two rainfall events were performed and flowrate, pH, BOD, COD, SS, T-N and T-P were measured. these data were used for model calibration. Using GIS technique, watershed characteristics of study area were calculated. that is, divide into sub_basin, total width, slope, make soil map etc. On the basis of the measured data and the simulation results by SWMM, it could be known that the $80-90\%$ of pollution load are discharged in early-stage storm runoff. SMC(site mean Concentration) for combined sewer system area were BOD 28.1, COD 31.5, SS 186 ppm etc. this is shown that during the rain fall, high concentration of waste was loaded to receiving water. Unit loads of combined sewer system area were BOD 306, COD 410, SS 789, T-N 79, T-P 6.8 kg/ha/yr.

• Journal of Environmental Science International
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• v.25 no.12
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• pp.1653-1660
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• 2016

Drought is a reoccurring worldwide natural hazard that affects not only food production but also economics, health, and infrastructure. Drought monitoring is usually performed with precipitation-based indices without consideration of the actual state and amount of the land surface properties. A drought index based on the actual evapotranspiration can overcome these shortcomings. The severity of a drought can be quantified by making a spatial map. The procedure for estimating actual evapotranspiration is costly and complicated, and requires land surface information. The possibility of utilizing drone-driven remotely sensed data for actual evapotranspiration estimation was analyzed in this study. A drone collected data was used to calculate the normalized difference vegetation index (NDVI) and soil-adjusted vegetation index (SAVI). The spatial resolution was 10 m with a grid of $404{\times}395$. The collected data were applied and parameterized to an actual evapotranspiration estimation. The result shows that drone-based data is useful for estimating actual evapotranspiration and the corresponding drought indices.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.10 no.3
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• pp.39-47
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• 1990

The generation of artificial accelerograms considering the characteristic of earthquakes in the Korean peninsula for a time history analysis of structures is accomplised by the stochastic method. The engineering data such as a representative shape of envelope function and an effective duration are investigated from the instrumental records. The maximum ground acceleration value is based on seismic zoning map which are constructed for the Korean peninsula. The acceleration-time histories are generated for two different types of earthquake motions and two types of soil conditions. In the study, the maximum ground acceleration value of 0.2 g and effective durations of 24 seconds are used. The validity of the artificial accelerograms is obtained by the comparison with the required envelope functions and the design response spectrum.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.44 no.2
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• pp.166-170
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• 1999

The identification of quantitative trait loci (QTL) has the potential to enhance the efficiency of im- proving food processing traits of soybean. In this study, 92 restriction fragment length polymorphism (RFLP) loci and two morphological markers (W$_1$ and T) were used to identify QTL associated with food processing traits of soybean for sprout in 83 F$_2$-derived lines from a cross of ＇Pureun＇ x ＇Jinpum 2＇. The genetic map consisted of 76 loci which covered about 760 cM and converged into 20 linkage groups. Eighteen markers remained unlinked. Phenotypic data were collected for hypocotyl length, abnormal seedling rate, and sprout yield seven days after seed germination at 2$0^{\circ}C$. Based on the single-factor analysis of variance, eight independent markers were associated with hypocotyl length. Four of seven markers associated with abnormal seedling rate were identified as independent. Seven loci were associated with sprout yield. For three different traits, much of genetic variation was explained by the identified QTL in this population. Several RFLP markers in linkage group (LG) Bl were detected as being associated with three traits, providing a genetic explanation for the biological correlation of sprout yield with hypocotyl length (r=OA07＊＊＊) and with abnormal seedling rate (r=-406＊＊＊).

• Korean Journal of Remote Sensing
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• v.31 no.4
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• pp.293-302
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• 2015

Water body extraction is significant for flood disaster monitoring using satellite imagery. Conventional methods have focused on finding an index, which highlights water body and suppresses non-water body such as vegetation or soil area. The Normalized Difference Water Index (NDWI) is typically used to extract water body from satellite images. The drawback of NDWI, however, is that some man-made objects in built-up areas have NDWI values similar to water body. The objective of this paper is to propose a new method that could extract correctly water body with built-up areas in before and after images of flood. We first create a two-element feature vector consisting of NDWI and a Near InfRared band (NIR) and then select a training site on water body area. After computing the mean vector and the covariance matrix of the training site, we classify each pixel into water body based on Mahalanobis distance. We also register before and after images of flood using outlier removal and triangulation-based local transformation. We finally create a change map by combining the before-flooding water body and after-flooding water body. The experimental results show that the overall accuracy and Kappa coefficient of the proposed method were 97.25% and 94.14%, respectively, while those of the NDWI method were 89.5% and 69.6%, respectively.

• Magazine of the Korean Society of Agricultural Engineers
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• v.37 no.3_4
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• pp.23-33
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• 1995

Geographic data which are difficult to handle by the characteristics of spatial variation and variety turned into a possibility to analyze with tlie computer-aided digital map and the use of Geographic Information System(GIS). The purpose of this study is to develop and apply a GIS application model (GISCELWAB) for the spatial simulation of surface runoff from a small watershed. This paper discribes the modeling procedure and the applicability of the cell water balance model (CELWAB) which calculates the water balance of a cell and simulates surface runoff of watershed simultaneously by the interaction of cells. The cell water balance model was developed to simulate the temporal and spatial storage depth and surface runoff of a watershed. The CELWAB model was constituted by Inflow-Outflow Calculator (JOC) which was developed to connect cell-to-cell transport mechanism automatically in this study. The CELWAB model requests detail data for each component of a cell hydrologic process. In this study, therefore, BANWOL watershed which have available field data was selected, and sensitivity for several model parameters was analyzed. The simulated results of surface runoff agreed well with the observed data for the rising phase of hydrograph except the recession phase. Each mean of relative errors for peak discharge and peak time was 0.21% and2.1 1% respectively. In sensitivity analysis of CELWAB , antecedent soil moisture condition(AMC) affected most largely the model.