• Geophysics and Geophysical Exploration
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• v.7 no.4
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• pp.234-244
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• 2004

In order to calculate 3-dimensional wavefield using finite-element method in frequency domain, we must factor so huge sparse impedance matrix. Because of difficulties of handling of this huge impedance matrix, 3-dimensional wave equation modeling is conducted mainly in time domain. In this study, we simulate the 3-D wavefield using finite-element method in Laplace domain by combining high-performance parallel finite-element solver and SWEET (Suppressed Wave Equation Estimation of Traveltime) algorithm which can calculate the traveltime and the amplitude. To verify this combination, we applied it to the SEG/EAGE 3D salt model in serial and parallel computing environments.

• Geophysics and Geophysical Exploration
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• v.15 no.2
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• pp.85-91
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• 2012

Multiple Lapse Time Window (MLTW) analysis for obtaining intrinsic attenuation value require numerous data without directional bias to compensate focal mechanism. The first window of MLTW, therefore, shows large deviation in fitting smoothed theoretical curve. The information on the focal mechanism may reduce burdens of number and distribution. This study combined algorithm of computing focal mechanism to DSMC method by Yoshimoto (2000). However, the MLTW method based on the numerous data was not applicable to this study, because of the limited data to the almost same fault plane solution. This study showed that the available data was too insufficient to construct smoothed theoretical curve, although the deviation of the first window was improved. Instead of conventional solution by more data, the study seems to be needed for new constraints to obtain smoothed curve.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.37 no.3
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• pp.259-266
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• 2013

An automated cell tracking system is used to automatically analyze and track the changes in cell behavior in time-lapse cell images acquired using a microscope with a cell culture. Clustering is the partial overlapping of neighboring cells in the process of cell change. Separating clusters into individual cells is very important for cell tracking. In this study, we proposed an algorithm for separating clusters by using ellipse fitting based on a direct least square method. We extracted the contours of clusters, divided them into line segments, and then produced their fitted ellipses using a direct least square method for each line segment. All of the fitted ellipses could be used to separate their corresponding clusters. In experiments, our algorithm separated clusters with average precisions of 91% for two overlapping cells, 84% for three overlapping cells, and about 73% for four overlapping cells.

• The Korean Journal of Applied Statistics
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• v.27 no.1
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• pp.43-59
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• 2014

Cut-off sampling has been widely used for a highly skewed population like a business survey by discarding a part of the population, so called a take-nothing stratum. For a more accurate estimate of the population total, Hwang and Shin (2013) suggested a composite estimator of a take-nothing stratum total that combined the survey results of a take-nothing stratum and a take-some sub-stratum (a part of take-some stratum). In this paper we propose a new cut-off sampling scheme by considering a cost function and a composite estimator based on the proposed sampling scheme. Small simulation studies compared the performances of known composite estimators and the new composite estimator suggested in this study. We also use Briquette Consumption Survey data for real data analysis.

• Journal of Digital Convergence
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• v.11 no.12
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• pp.345-352
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• 2013

In this paper, a depth estimate method is proposed using GPU(Graphics Processing Unit) in monocular image. a monocular image is a 2D image with missing 3D depth information due to the camera projection and we used a monocular cue to recover the lost depth information by the projection present. The proposed algorithm uses an energy function which takes a variety of cues to create a more generalized and reliable depth map. But, a processing time is late because energy function is defined from the various monocular cues. Therefore, we propose a depth estimate method using GPGPU(General Purpose Graphics Processing Unit). The objective effectiveness of the algorithm is shown using PSNR(Peak Signal to Noise Ratio), a processing time is decrease by 61.22%.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.6
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• pp.411-418
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• 2020

In this paper, approximation and optimization methods are proposed for the structural performance of the composite fan blade. Using these methods, we perform the optimal design of the stacking sequence to maximize stiffnesses without changing the mass and the geometric shape of the composite fan blade. In this study, the lamination parameters are introduced to reduce the design variables and space. From the characteristics of lamination parameters, we generate response surface model having a high fitness value. Considering the requirements of the optimal stacking sequence, the multi-objective optimization problem is formulated. We apply the two-step optimization method that combines gradient-based method and genetic algorithm for efficient search of an optimal solution. Finally, the finite element analysis results of the initial and the optimized model are compared to validate the approximation and optimization methods based on the lamination parameters.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.4
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• pp.150-160
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• 2011

IT convergence and integration technology aims to create new synergies by combining IT related technology and performance. This study conducted a basic research for combining construction and IT technology to create new synergies. Specifically, the purpose of this study is to combine USN and GIS technology and then apply it to urban facilities management. For this, we have developed the USN hardware, tested propagation communications, and made the GIS Algorithm and a system. Existing sensor node allocation method is mostly to install in a random way or with in-situ survey, but the problem with this method is contradictory to cost effectiveness and efficiency. To solve this problem, we developed a new method for sensor allocation. Using this method, the USN technology could be applied in the range of city unit. This technology can be applied to the ubiquitous urban development such as U-City and Smart City.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.1
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• pp.219-223
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• 2020

To guarantee AI model's prominent recognition rate and recognition precision, obtaining the large number of data is essential. In this paper, we propose transfer learning-based object detection algorithm for maintaining outstanding performance even when the volume of training data is small. Also, we proposed a tranfer learning network combining Resnet-50 and YOLO(You Only Look Once) network. The transfer learning network uses the Leeds Sports Pose dataset to train the network that detects the person who occupies the largest part of each images. Simulation results yield to detection rate as 84% and detection precision as 97%.

• The Journal of Korean Association of Computer Education
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• v.5 no.2
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• pp.21-28
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• 2002

This paper proposes a new approach to rollback-recovery using multi-agent in distributed computing system. Previous rollback-recovery protocols are dependent on inherent communication and operating system, which causes a decline of computing performance in distributed computing system. By using multi-agent, we propose rollback-recovery protocol that is independent on operating system. We define three kinds of agent. One is a recovery agent that performs rollback-recovery protocol after a failure. Other is an information agent that constructs domain knowledge as a rule of fault tolerance and information during failure-free operation. The other is facilitator agent that controls the efficient communication between agents. Also we propose rollback-recovery protocol using multi-agent and simulated the proposed rollback-recovery protocol using JAVA and agent communication language in CORBA environment.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.4
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• pp.377-385
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• 2015

This paper proposes a novel forward vehicle tracking algorithm based on the WMIL(Weighted Multiple Instance Learning) equipped with a particle filter. In the proposed algorithm Haar-like features are used to train a vehicle object detector to be tracked and the location of the object are obtained from the recognition result. In order to combine both the WMIL to construct the vehicle detector and the particle filter, the proposed algorithm updates the object location by executing the propagation, observation, estimation, and selection processes involved in particle filter instead of finding the credence map in the search area for every frame. The proposed algorithm inevitably increases the computation time because of the particle filter, but the tracking accuracy was highly improved compared to Ababoost, MIL(Multiple Instance Learning) and MIL-based ones so that the position error was 4.5 pixels in average for the videos of national high-way, express high-way, tunnel and urban paved road scene.