• Journal of Korean Society on Water Environment
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• v.33 no.4
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• pp.394-402
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• 2017

In korea, TMDL is being implemented to manage nonpoint pollution sources as well as point pollution sources. LDC is being used for the planning of TMDL. In order to analyze the water quality using LDC, it is necessary to prepare FDC using the daily flow data. However, only the daily flow data is measured at the WAMIS branch, and 8days flow data and water quality data are measured at the monitoring Networks. So, in many researches, the water quality is being grasped by deriving the LDC using the 8days flow or the daily flow obtained by various methods. These fluctuations may lead to differences in determining whether the target load is achieved. In this study, each LDC was prepared using the 8day flow and the related daily flow. Then, the effect using different flow data on the achievement of target load was compared according to flow conditions. As a result, the difference ratio in the number of overloads under flow condition was showed 19% in high flows, 42% in moist conditions, 49% in mid-range flows, 41% in dry conditions, and 104% in low flows. In the top ten watershed with the highest difference ratio, the flow became lower the difference ration increases. These differences can cause uncertainty in assessing the achievement of target load using LDC. Therefore, in order to evaluate the water quality accurately and reliably using LDC, accurate daily flow data and water quality data should be secured through the installation of national nonpoint measurement network.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.11 no.3
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• pp.28-38
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• 2008

The purpose of this study are to compare existing presence-absence predictive models and to predict suitable habitat for Goral (Nemorhaedus caudatus raddeanus) that is an endangered and protected species in Seoraksan national park using the best model among existing predictive models. The methods of this study are as follows. First, 375 location data and 9 environmental data layers were implemented to build a model. Secondly, 4 existing presence-absence models : Generalized Linear Model (GLM), Generalized Addictive Model (GAM), Classification and Regression Tree (CART), and Artificial Neural Network (ANN) were tested to predict the Goal habitat. Thirdly, ROC (Receiver Operating Characteristic) and Kappa statistics were used to calculate a model performance. Lastly, we verified models and created habitat suitability maps. The ROC AUC (Area Under the Curve) and Kappa values were 0.697/0.266 (GLM), 0.729/0.313 (GAM), 0.776/0.453 (CART), and 0.858/0.559 (ANN). Therefore, ANN was selected as the best model among 4 models. The models showed that elevation, slope, and distance to stream were the significant factors for Goal habitat. The ratio of predicted area of ANN using a threshold was 31.29%, but the area decreased when human effect was considered. We need to investigate the difference of various models to build a suitable wildlife habitat model under a given condition.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.19 no.2
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• pp.49-54
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• 2005

Measuring ground resistance is a typical way of performance evaluation of a grounding electrode. Among various ground resistance measurement methods, FOP (Fall-Of-Potential) method has been widely used, especially in case of a relatively large grounding electrode such as a substation grounding mesh grid Since FOP measurement line has to be increased as the size of grounding electrode increases, however, it is often that securing long enough FOP-line is practically impossible. In this paper, a sophisticated interpretation method of FOP measurement ma which is applicable to large grounding electrode networks, is presented.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.9
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• pp.369-374
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• 2014

Path generation methods are required for safe and efficient driving in unmanned autonomous vehicles. There are two kinds of paths: global and local. A global path consists of all the way points including the source and the destination. A local path is the trajectory that a vehicle needs to follow from a way point to the next in the global path. In this paper, we propose a novel method for local path generation through machine learning, with an effective curve function used for initializing the trajectory. First, reinforcement learning is applied to a set of candidate paths to produce the best trajectory with maximal reward. Then the optimal steering angle with respect to the trajectory is determined by training an artificial neural network. Our method outperformed existing approaches and successfully found quality paths in various experimental settings, including the cases with obstacles.

• Journal of the Korean Society for Railway
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• v.20 no.5
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• pp.612-624
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• 2017

As the existing metropolitan area metropolitan railway operates on a one-to-one basis, which leads to long travel times, its competitiveness with other means of transportation is deteriorating. Since there is a limit to attracting road traffic by rail, there is a continuing societal demand to expand express train service. Especially in the northern and the southwestern parts of the metropolitan area, a public transportation network system with express function, connecting to the city center of Seoul, is needed because of the social cost of the increase of traffic congestion and the increase of the travel time. The most efficient express service in Korea is Seoul Subway Line 9, which runs in 27 minutes from Gimpo Airport to the high speed terminal; this is a 40% shorter time compared to 44 minutes by car; the congestion in this area is up to 240%, so the preference for this train is quite high. The technical results of this study are expected to contribute to the implementation of an express service metropolitan railway.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.18 no.2
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• pp.199-209
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• 2000

Recently, GSIS is introduced in the various fields. Especially in hydrology, the useful of GSIS is emphasized to analyze parameters, which are necessary for the analysis of watershed. In this paper, to estimate the direct runoff volume, I used the SCS-CN method which was useful to calculate direct runoff volume in a watershed that was not observed. But because SCS-CN method must treat a great number of spatial data, if we use the GSIS, we can treat numbers of the data easily. GSIS databases is constructed by using the data which is related to soil type, landuse. And runoff curve number was estimated by means of these databases in the study area. Also, the area of covered each subbasin rainfall gauge station was estimated by thiessen polygon network technique. The direct runoff volume was calculated by these subbasin area to the rainfall gauge station. I knew, from this study, that using GSIS, I can calculate parameters needed in direct runoff volume analysis, fast, exactly.

• International Journal of Fluid Machinery and Systems
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• v.9 no.4
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• pp.370-381
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• 2016

As a single-channel pump is used for wastewater treatment, this particular pump type can prevent performance reduction or damage caused by foreign substances. However, the design methods for single-channel pumps are different and more difficult than those for general pumps. In this study, a design optimization method to improve the hydrodynamic performance of a single-channel pump impeller is implemented. Numerical analysis was carried out by solving three-dimensional steady-state incompressible Reynolds-averaged Navier-Stokes equations using the shear stress transport turbulence model. As a state-of-the-art impeller design method, two design variables related to controlling the internal cross-sectional flow area of a single-channel pump impeller were selected for optimization. Efficiency was used as the objective function and was numerically assessed at twelve design points selected by Latin hypercube sampling in the design space. An optimization process based on a radial basis neural network model was conducted systematically, and the performance of the optimum model was finally evaluated through an experimental test. Consequently, the optimum model showed improved performance compared with the base model, and the unstable flow components previously observed in the base model were suppressed remarkably well.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.21 no.9
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• pp.835-843
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• 2008

We have fabricated the source-drain electrodes for OTFTs by screen printing method and manufactured Ag pastes as conductive paste. To obtain excellent conductivity and screen-printability of Ag pastes, the dispersion characteristics of Ag pastes prepared from two types of acryl resins with different molecular structures and Ag powder treated with caprylic acid, triethanol amine and dodecane thiol as surfactant respectively were investigated. The Ag pastes containing Ag powder treated with dodecane thiol having thiol as anchor group or AA4123 with carboxyl group(COOH) of hydrophilic group as binder resin exhibited excellent dispersity. But, Ag pastes(CA-41, TA-41, DT-41) prepared from AA4123 fabricated the insulating layer since the strong interaction between surface of Ag powder and carboxyl group(COOH) of AA4123 interfered with the formation of conduction path among Ag powders. The viscosity behavior of Ag pastes exhibited shear-thinning flow in the high shear rate range and the pastes with bad dispersion characteristic demonstrated higher shear-thinning index than those with good dispersity due to the weak flocculated network structure. The output curve of OTFT device with a channel length of 107 ${\mu}m$ using screen-printed S-D electrodes from DT-30 showed good saturation behavior and no significant contact resistance. And this device exhibited a saturation mobility of $4.0{\times}10^{-3}$ $cm^2/Vs$, on/off current ratio of about $10^5$ and a threshold voltage of about 0.7 V.

• Proceedings of the Korea Contents Association Conference
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• 2008.05a
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• pp.285-288
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• 2008

This study aims to rout optimized design flood discharge through prediction of the frequency-based precipitation from the frequency analysis with density of rainfall gage networks in urban watershed. Frequency analysis was examined for the measured rainfall depth with low density of a point and high density of the sub-basin divided into 13 points in watershed. The used rainfall data in order to analyze consists of two groups based on measured rainfall depth for a day duration with 39years of a point and 6years of 13 points by an extending as annual exceedance series, respectively. Selected rainfall data in this analysis show that low-network has maximum rainfall depth with duration 1hr-79.1mm and 24hrs-329.1mm, and high-networks have ones with duration of 1hr-93.0 mm and 24 hrs-245.0 mm, respectively. As the result, probability of the best in this study determined the Gumbel method from the goodness of fit test and the method of prime 6 probability distributions.

• Journal of the Institute of Convergence Signal Processing
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• v.6 no.1
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• pp.15-22
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• 2005

In this paper, we propose a face recognition system by using the CCD color image. We first get the face candidate image by using YCbCr color model and adaptive skin color information. And we use it initial curve of active contour model to extract face region. We use the Eye map and mouth map using color information for extracting facial feature from the face image. To obtain center point of Log-polar image, we use extracted facial feature from the face image. In order to obtain feature vectors, we use extracted coefficients from DCT and wavelet transform. To show the validity of the proposed method, we performed a face recognition using neural network with BP learning algorithm. Experimental results show that the proposed method is robuster with higher recogntion rate than the conventional method for the rotation and scale variant.