• Journal of Computing Science and Engineering
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• v.6 no.3
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• pp.219-226
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• 2012

Recently, shape analysis of human organs has achieved much attention, owing to its potential to localize structural abnormalities. For a group-wise shape analysis, it is important to accurately restore the shape of a target structure in each subject and to build the inter-subject shape correspondences. To accomplish this, we propose a shape modeling method based on the Laplacian deformation framework. We deform a template model of a target structure in the segmented images while restoring subject-specific shape features by using Laplacian surface representation. In order to build the inter-subject shape correspondences, we implemented the progressive weighting scheme for adaptively controlling the rigidity parameter of the deformable model. This weighting scheme helps to preserve the relative distance between each point in the template model as much as possible during model deformation. This area-preserving deformation allows each point of the template model to be located at an anatomically consistent position in the target structure. Another advantage of our method is its application to human organs of non-spherical topology. We present the experiments for evaluating the robustness of shape modeling against large variations in shape and size with the synthetic sets of the second cervical vertebrae (C2), which has a complex shape with holes.

• Journal of Environmental Science International
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• v.20 no.9
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• pp.1115-1124
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• 2011

There is an increasing incidence in health problems related to environmental issues that originate from inadequate treatment of sewage. This has compelled scientists to engage in innovative technologies to achieve a effective disinfection process. Electrolysis has emerged as one of the more feasible alternatives to conventional disinfection process. The objectives of the present paper were to investigate the effect of chemical characteristics on oxidant formation and Escherichia coli (E. coli) disinfection in synthetic sewage effluents. The influence of parameters such as COD, SS, T-N and T-P were investigated using laboratory scale batch reactor. The results showed that the higher COD, T-N and T-P concentration, the lower N, N-Dimethyl-4-nitrosoaniline (RNO, indicator of the generation of OH radical) degradation and E. coli disinfection was observed. The order of effect of RNO degradation and E. coli disinfection was T-P > COD > T-N > SS. When 4 parameter of water quality were worked simultaneously, oxidants formation and disinfection was decreased with increase of the concentration of sewage. To increase of the disinfection performance, the increase of disinfection time or electric power was need.

• ETRI Journal
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• v.38 no.2
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• pp.337-346
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• 2016

We propose a data-driven kinematic control method for a robotic spatial augmented reality (RSAR) system. We assume a scenario where a robotic device and a projector-camera unit (PCU) are assembled in an ad hoc manner with loose kinematic specifications, which hinders the application of a conventional kinematic control method based on the exact link and joint specifications. In the proposed method, the kinematic relation between a PCU and joints is represented as a set of B-spline surfaces based on sample data rather than analytic or differential equations. The sampling process, which automatically records the values of joint angles and the corresponding external parameters of a PCU, is performed as an off-line process when an RSAR system is installed. In an on-line process, an external parameter of a PCU at a certain joint configuration, which is directly readable from motors, can be computed by evaluating the pre-built B-spline surfaces. We provide details of the proposed method and validate the model through a comparison with an analytic RSAR model with synthetic noises to simulate assembly errors.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.24 no.3
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• pp.443-449
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• 2000

The performance of 2-frame PTV(particle tracking velocimetry) system was improved using an adaptive hybrid scheme. The original 2-frame PTV method based on the match probability concept employs global match parameters for the entire flow field. Since this does not reflect fully the detailed local velocity change, it sometimes reduces the recovery rate of velocity vectors and increases the number of erroneous vectors in the region where an extraordinary flow structure exists. In this study, the preliminary FFT-based PIV results are used as an input parameter to determine the local match parameters needed for the 2-frame particle tracking algorithm. A computer simulation using synthetic particle images was carried out to study the performance of the adaptive 2-frame PTV technique. The adaptive hybrid method shows the better performance with increasing the velocity vector recovery rate and decreasing the computation time, compared to the original 2-frame PTV method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.5103-5115
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• 2015

In radar imaging, a target is usually consisted of a few strong scatterers which are sparsely distributed. In this paper, an improved sparse signal recovery algorithm based on smoothed l₀ (SL0) norm method is proposed to achieve high resolution ISAR imaging with limited pulse numbers. Firstly, one new smoothed function is proposed to approximate the l₀ norm to measure the sparsity. Then a single loop step is used instead of two loop layers in SL0 method which increases the searching density of variable parameter to ensure the recovery accuracy without increasing computation amount, the cost function is undated in every loop for the next loop until the termination is satisfied. Finally, the new set of solution is projected into the feasible set. Simulation results show that the proposed algorithm is superior to the several popular methods both in terms of the reconstruction performance and computation time. Real data ISAR imaging obtained by the proposed algorithm is competitive to several other methods.

• Carbon letters
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• v.13 no.4
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• pp.205-211
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• 2012

Methanol as a carbon source in chemical vapor deposition (CVD) graphene has an advantage over methane and hydrogen in that we can avoid optimizing an etching reagent condition. Since methanol itself can easily decompose into hydrocarbon and water (an etching reagent) at high temperatures [1], the pressure and the temperature of methanol are the only parameters we have to handle. In this study, synthetic conditions for highly crystalline and large area graphene have been optimized by adjusting pressure and temperature; the effect of each parameter was analyzed systematically by Raman, scanning electron microscope, transmission electron microscope, atomic force microscope, four-point-probe measurement, and UV-Vis. Defect density of graphene, represented by D/G ratio in Raman, decreased with increasing temperature and decreasing pressure; it negatively affected electrical conductivity. From our process and various analyses, methanol CVD growth for graphene has been found to be a safe, cheap, easy, and simple method to produce high quality, large area, and continuous graphene films.

• Korean Journal of Remote Sensing
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• v.27 no.3
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• pp.225-234
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• 2011

This study proposes an inversion algorithm to extract the surface parameters, such as surface roughness and soil moisture contents, using multi-frequency SAR data. The study areas include the tidal flats of Jebu Island and the reclaimed lands of Hwaong district on the western coasts of the Korean peninsula. SAR data of three frequencies were accordingly calibrated to provide precise backscattering coefficients through absolute radiometric calibration. The root mean square (RMS) height and the correlation length, which can describe the surface roughness, were extracted from the backscattering coefficients using the inversion of the Integral Equation Method (IEM). The IEM model was appropriately modified to accommodate the environmental conditions of tidal flats. Volumetric soil moisture was also simultaneously extracted from the dielectric constant using the empirical model, which define the relations between volumetric soil moistures and dielectric constants. The results obtained from the proposed algorithm were verified with the in-situ measurements, and we confirmed that multi-frequency SAR observations combined with the surface scattering model for tidal flats can be used to quantitatively retrieve the geophysical surface parameters in tidal flats.

• Journal of the Korea Society of Computer and Information
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• v.11 no.1 s.39
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• pp.129-138
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• 2006

Various techniques have been applied to solve the maximal covering problem. Tabu search is also one of them. But, existing researches were lacking of the synthetic analysis and the effort for performance improvement about neighborhood search techniques such as hill-climbing search and simulated annealing including tabu search. In this paper, I introduce the way to improve performance of neighborhood search techniques through various experiments and analyses. Basically, all neighborhood search algorithms use the k-exchange neighborhood generation method. And I analyzed how the performance of each algorithm changes according to various parameter settings. Experimental results have shown that simple hill-climbing search and simulated annealing can produce better results than any other techniques. And I confirmed that simple hill-climbing search can produce similar results as simulated annealing unlike general case.

• Computers and Concrete
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• v.24 no.6
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• pp.555-560
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• 2019

During the application of shotcrete, a part of the concrete bounces back after hitting to the surface, the reinforcement or previously sprayed concrete. This rebound material is definitely not added to the mixture and considered as waste. In this study, a deep neural network model was developed to predict the rebound material during shotcrete application. The factors affecting rebound and the datasets of these parameters were obtained from previous experiments. The Long Short-Term Memory (LSTM) architecture of the proposed deep neural network model was used in accordance with this data set. In the development of the proposed four-tier prediction model, the dataset was divided into 90% training and 10% test. The deep neural network was modeled with 11 dependents 1 independent data by determining the most appropriate hyper parameter values for prediction. Accuracy and error performance in success performance of LSTM model were evaluated over MSE and RMSE. A success of 93.2% was achieved at the end of training of the model and a success of 85.6% in the test. There was a difference of 7.6% between training and test. In the following stage, it is aimed to increase the success rate of the model by increasing the number of data in the data set with synthetic and experimental data. In addition, it is thought that prediction of the amount of rebound during dry-mix shotcrete application will provide economic gain as well as contributing to environmental protection.

• Journal of Korea Water Resources Association
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• v.32 no.4
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• pp.427-435
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• 1999

The Clark unit hydrograph is a three parameter synthetic unit hydrograph procedure that can be used in flood hydrology. The present work is an attempt to estimate parameters of the Clark model in ungaged basin by means of relationships that provides for the hydrologic similarity. The time area concentration curve was determined by analytic method and the Clark model was generalized by being made dimensionless form. Calculation of the concentration time was made with the formula fractal concept used, and the storage coefficient was estimated by the empirical and regional equation. Evaluation on Dongok basin was performed to prove the validity of the proposed model. The derived hydrograph predicted the observed hydrograph fairly well.