• Journal of Environmental Science International
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• v.20 no.9
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• pp.1165-1182
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• 2011

The evaluation of potential submarine groundwater is an important research topic for exploring an alternative water resource. Two different approaches, water budget analysis and Rn mass balance method, were employed to investigate the annual variation of submarine groundwater discharge in 2010 at a marine watershed located at the south-eastern part of Korean Peninsula. In order to obtain reliable hydrological data during study period, temporal and spatial variations of rainfall and soil moisture had been collected and hydro-meterological data such as temperature, humidity and wind speed were collected The runoff response was simulated using SCS-CN method with spatial distributions of landuse and soil texture from GIS analysis. Six different methods were used to estimate the monthly variation of evapotranspiration and field measurements of soil moisture were used to account for the infiltration. Comparisons of infiltration and surface runoff between simulation and water balance with measurements showed coincidence. The water budget analysis and Rn mass balance method provide mean daily submarine groundwater as 5.35 and 4.07 $m^3/m/day$ in 2010, respectively.

• Proceedings of the KSR Conference
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• 2009.05a
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• pp.1839-1850
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• 2009

The Korean railway system is a mass transit system in which a various types of trains such as common trains, high-speed train (KTX), Metropolitan Express Railway (EMU) are operated. It is operated based on a timetable and provides us with safety, regularity, quickness and comfortable service. The objective of this study is to propose a method for estimating line capacity considering high-speeding and diversification of trains. In particular, the focus of this study is on the closing gap between the result of the existing line capacity estimation method and the real-world line capacity of the operating agency of the Korean railway. For this, this study introduces a new railway capacity definition by considering TPS of line alignment according to the operation type, train control and signaling system, etc. The verification of the proposed method using a practical schedule diagram exemplification is discussed as well.

• Journal of the Korea Convergence Society
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• v.9 no.8
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• pp.171-177
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• 2018

In 3D printing technologies, many parameters should be optimized for obtaining a part with higher quality. FDM (fused deposition modeling) printer has also diverse parameters to be optimized. Among them, it can be said that nozzle temperature and moving speed of nozzle are fundamental parameters. Thus, it should be preceded to know the optimal combination of the two parameters in the use of FDM 3D printer. In this paper, a new method is proposed to estimate the range of the stable combinations of the two parameters, based on the single line quality. The proposed method was verified by comparing the results between single line printing and multi-layered single line printing. Based on the comparison, it can be said that the proposed method is very meaningful in that it has a simple test approach and can be easily implemented. In addition, it is very helpful to provide the basic data for the optimization of process parameters.

• Journal of Korea Multimedia Society
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• v.15 no.3
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• pp.336-344
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• 2012

As an important part of the Computer Vision, the object recognition and tracking function has infinite possibilities range from motion recognition to aerospace applications. One of methods to improve accuracy of the object recognition, are uses colors which have robustness of orientation, scale and occlusion. Computational cost for extracting features can be reduced by using color. Also, for fast object recognition, predicting the location of the object recognition in a smaller area is more effective than lowering accuracy of the algorithm. In this paper, we propose a method that uses SURF descriptors which applied with color model for improving recognition accuracy and combines with Kalman filter which is Motion estimation algorithm for fast object tracking. As a result, the proposed method classified objects which have same patterns with different colors and showed fast tracking results by performing recognition in ROI which estimates future motion of an object.

• Journal of the Korean Society for Railway
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• v.16 no.3
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• pp.202-206
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• 2013

A submerged floating railway is an innovative tunnel infrastructure passing through the deep sea independent of wave and wind so that high speed trains can run on it. It doesn't depend on water depth and is cost effective due to modular construction on land. The construction period can be reduced drastically. This paper introduces the concept design of a submerged floating railway, and for securing safety, proposes a method to analyze the structural behavior of the body in case of collision with a submarine. The theory of a beam with an elastic foundation was used to calculate the equivalent mass of the body so that the perfect elastic collision could be applied to calculate the collision velocity. The maximum deformation and bending moment was analyzed based on energy conservation. To verify the results, a collision analysis using a finite element analysis code was made. Comparing the results confirmed that this simplified collision analysis method gives enough accurate deformation and bending moment to be used for actual estimation in the initial design stage.

• Economic and Environmental Geology
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• v.56 no.3
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• pp.293-300
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• 2023

The Shape Preferred Orientation (SPO) method has been used to analyze the orientation of fault motion, which is utilized as basic data for fault kinematics studies. The rigid grains, which as quartz, feldspar, and rock fragments, in the fault gouge are arranged in the P-shear direction through rigid body rotation by a given shear stress. Using this characteristic, the fault motion can be estimated from the SPO inversely. Recently, a method for securing precision and reliability by measuring 3D-SPO using X-ray CT images and examining the shape of a large number of particles in a short time has been developed. As a result, the SPO method analyzes the orientation of thousands to tens of thousands of particles at high speed, suggests the direction of fault motion, and provides easy accessibility and reliable data. In addition, the shape information and orientation distribution data of particles, which are by-products obtained in the SPO analysis process, are expected to be used as basic data for conducting various studies such as the local deformation of fault rocks and the fault generation mechanism.

• Journal of IKEEE
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• v.18 no.2
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• pp.272-281
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• 2014

In electrical impedance tomography (EIT), modified Newton Raphson (mNR) method is widely used inverse algorithm for static image reconstruction due to its convergence speed and estimation accuracy. The unknown conductivity distribution is estimated iteratively by minimizing a cost functional such that the residual error namely the difference in measured and calculated voltages is reduced. Although, mNR method has good estimation performance, EIT inverse problem still suffers from ill-conditioned and ill-posedness nature. To mitigate the ill-posedness, generally, regularization methods are adopted. The inverse solution is highly dependent on the choice of regularization parameter. In most cases, the regularization parameter has a constant value and is chosen based on experience or trail and error approach. In situations, when the internal distribution changes or with high measurement noise, the solution does not get converged with the use of constant regularization parameter. Therefore, in this paper, in order to improve the image reconstruction performance, we propose a new scheme to determine the regularization parameter. The regularization parameter is computed based on residual error and updated every iteration. The proposed scheme is tested with numerical simulations and laboratory phantom experiments. The results show an improved reconstruction performance when using the proposed regularization scheme as compared to constant regularization scheme.

• Smart Structures and Systems
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• v.32 no.4
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• pp.267-279
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• 2023

Data modelling and interpretation for structural health monitoring (SHM) field data are critical for evaluating structural performance and quantifying the vulnerability of infrastructure systems. In order to improve the data modelling accuracy, and extend the application range from data regression analysis to out-of-sample forecasting analysis, an improved most likely heteroscedastic Gaussian process (iMLHGP) methodology is proposed in this study by the incorporation of the outof-sample forecasting algorithm. The proposed iMLHGP method overcomes this limitation of constant variance of Gaussian process (GP), and can be used for estimating non-stationary typhoon-induced response statistics with high volatility. The first attempt at performing data regression and forecasting analysis on structural responses using the proposed iMLHGP method has been presented by applying it to real-world filed SHM data from an instrumented cable-stay bridge during typhoon events. Uncertainty quantification and correlation analysis were also carried out to investigate the influence of typhoons on bridge strain data. Results show that the iMLHGP method has high accuracy in both regression and out-of-sample forecasting. The iMLHGP framework takes both data heteroscedasticity and accurate analytical processing of noise variance (replace with a point estimation on the most likely value) into account to avoid the intensive computational effort. According to uncertainty quantification and correlation analysis results, the uncertainties of strain measurements are affected by both traffic and wind speed. The overall change of bridge strain is affected by temperature, and the local fluctuation is greatly affected by wind speed in typhoon conditions.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1615-1615
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• 2001

During the past ten years, Near Infrared Spectroscopy has been successfully applied to the analysis of a great variety of agriculture products. Previous works (Morra et al., 1991; Salgo et al., 1998) have shown the potential of this technology for soil analysis, estimating different parameters just with one single scan. The main advantages of NIR applications in soils are the speed of response, allowing the increase of the number of samples analysed to define a particular soil, and the instantaneous elaboration of recommendations for fertilization and soil amendment. Another advantage is to avoid the use of chemical reagents at all, being an environmentally safe technique. In this paper, we have studied a set of 129 soil samples selected from representative glasshouse soils from Southern Spain. The samples were dried, milled, and sieved to pass a 2 mm sieve and then analysed for organic carbon, total nitrogen, inorganic nitrogen (nitrate ammonium), hygroscopic humidity, pH and electrical conductivity in the 1:1 extract. NIR spectra of all samples were obtained in reflectance mode using a Foss NIR Systems 6500 spectrophotometer equipped with a spinning module. Calibration equations were developed for seven analytical parameters (ph, Total nitrogen, organic nitrogen, organic carbon, C/N ratio and Electric Conductivity). Preliminary results show good correlation coefficients and standard errors of cross validation in equations obtained for Organic Carbon, Organic Nitrogen, Total Nitrogen and C/N ratio. Calibrations for nitrates and nitrites, ammonia and electric conductivity were not acceptable. Calibration obtained for pH had an acceptable SECV, but the determination coefficient was found very poor probably due to the reduced range in reference values. Since the estimation of Organic Carbon and C/N ratio are acceptable NIIRS could be used as a fast method to assess the necessity of organic amendments in soils from Mediterranean regions where the low level of organic matter in soils constitutes an important agronomic problem. Furthermore, the possibility of a single and fast estimation of Total Nitrogen (tedious determination by modifications of the Kjeldahl procedure) could provide and interesting data to use in the estimation of nitrogen fertilizer rates by means of nitrogen balances.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.10
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• pp.3858-3874
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• 2021

As an essential part of the urban transportation system, precise perception of the traffic flow parameters at the traffic signal intersection ensures traffic safety and fully improves the intersection's capacity. Traditional detection methods of road traffic flow parameter can be divided into the micro and the macro. The microscopic detection methods include geomagnetic induction coil technology, aerial detection technology based on the unmanned aerial vehicles (UAV) and camera video detection technology based on the fixed scene. The macroscopic detection methods include floating car data analysis technology. All the above methods have their advantages and disadvantages. Recently, indoor location methods based on wireless signals have attracted wide attention due to their applicability and low cost. This paper extends the wireless signal indoor location method to the outdoor intersection scene for traffic flow parameter estimation. In this paper, the detection scene is constructed at the intersection based on the received signal strength indication (RSSI) ranging technology extracted from the wireless signal. We extracted the RSSI data from the wireless signals sent to the road side unit (RSU) by the vehicle nodes, calibrated the RSSI ranging model, and finally obtained the traffic flow parameters of the intersection entrance road. We measured the average speed of traffic flow through multiple simulation experiments, the trajectory of traffic flow, and the spatiotemporal map at a single intersection inlet. Finally, we obtained the queue length of the inlet lane at the intersection. The simulation results of the experiment show that the RSSI ranging positioning method based on wireless signals can accurately estimate the traffic flow parameters at the intersection, which also provides a foundation for accurately estimating the traffic flow state in the future era of the Internet of Vehicles.