• Journal of the Computational Structural Engineering Institute of Korea
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• v.33 no.4
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• pp.217-224
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• 2020

In this study, a framework for optimizing the opening in an outrigger wall is proposed. To solve a constrained bounded optimization problem, an in-house finite element program and SQP algorithm in Python SciPy library are utilized. The openings of the outrigger wall are located according to the strut-tie behavior of the outrigger wall deep beam. A linear interpolation method is used to obtain differentiable continuous functions required for optimization, whereas a database is used for the efficiency of the optimization program. By comparing the result of the two-variable optimization through the moving path of the search algorithm, it is confirmed that the algorithm efficiently determines the optimized result. When the size of each opening is set to individual variables rather than the same width of all openings, the value of the objective function is minimized to obtain better optimization results. It was confirmed that the optimization time can be effectively reduced when using the database in the optimization process.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.9C
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• pp.761-770
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• 2010

In this paper, we propose a new Frame Rate Up-Conversion (FRUC) scheme to increase the frame rate from a lower number into a higher one and enhance the decoded video quality at the decoder. The proposed algorithm utilizes the preliminary frames of forward and backward direction using bilateral prediction. In the process of the preliminary frames, an additional interpolation is performed for the occlusion area because if the calculated value of the block with reference frame if larger than the predetermine thresholdn the block is selected as the occlusion area. In order to interpolate the occlusion area, we perform re-search to obtain the osiomal block considerhe osiomnumber of available ne block consblock. The experimental results show that performance of the proposed algorithm has better PSNR and visual quality than the conventional methods.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.2
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• pp.1-10
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• 2005

An unstructured parallel overset mesh method has been developed for the simulation of unsteady flows around multiple bodies in relative motion. For this purpose, an efficient and robust search method is proposed for the unstructured grid system. A new data-structure is also proposed to handle the variable number of data on parallel sub-domain boundary. The interpolation boundary is defined for data communication between grid systems. An interpolation method to retain second-order spatial accuracy and to treat the points inside the neighboring solid bodies are also suggested. A single store separating from the Eglin/Pylon configuration is calculated and the result is compared with experimental data for validation. Simulation of unsteady flows around multiple bodies in relative motion is also performed.

• Journal of the Korea Society of Computer and Information
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• v.19 no.9
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• pp.1-10
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• 2014

In this paper, we propose MPI gridding algorithm of LiDAR data that minimizes the communication between the cores. The LiDAR data collected from aircraft is a 3D spatial information which is used in various applications. Since there are many cases where the LiDAR data has too high resolution than actually required or non-surface information is included in the data, filtering the raw LiDAR data is required. In order to use the filtered data, the interpolation using the data structure to search adjacent locations is conducted to reconstruct the data. Since the processing time of LiDAR data is directly proportional to the size of it, there have been many studies on the high performance parallel processing system using MPI. However, previously proposed methods in parallel approach possess possible performance degradations such as imbalanced data size among cores or communication overhead for resolving boundary condition inconsistency. We conduct empirical experiments to verify the effectiveness of our proposed algorithm. The results show that the total execution time of the proposed method decreased up to 4.2 times than that of the conventional method on heterogeneous clusters.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.2
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• pp.85-92
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• 2009

This paper proposes a full-search block-matching motion estimation circuit with hybrid architecture combining systolic arrays and adder trees for an MPEG-4 encoder. The proposed circuit uses systolic arrays for motion estimation with a small number of clock cycles and adder trees to reduce required circuit resources. The interpolation circuit for 1/2 pixel motion estimation consists of six adders, four subtracters and ten registers. We improved the circuit performance by resource sharing and efficient scheduling techniques. We described the motion estimation circuit for integer and 1/2 pixels at RTL in Verilog HDL. The logic-level circuit synthesized by using 130nm standard cell library contains 218,257 gates and can process 94 D1($720{\times}480$) image frames per second.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.3
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• pp.493-502
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• 2021

A Vegetative Propagation by Runner(VPR) Algorithm-based on MPPT Algorithm that can track MPP by adapting to external environmental changes is presented. VPR is an optimization algorithm that mimics the plant ecology of movement and reproduction based on vegetation organs. The VPR algorithm includes a procedure for aging and a procedure for searching the surroundings by rhizomes. Accordingly, it is possible to continuously search around the optimal point. Therefore, the VPR-based MPPT algorithm can continuously search for an optimal point by adapting the changes in the external environment in the process of executing the MPPT algorithm. In this paper, we analyzed the performance of the VPR-based MPPT algorithm by a number of simulations. In addition, the superiority of performance was compared by performance comparison in the same environment as MPPT algorithm based on PSO.

• Journal of the Korean Solar Energy Society
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• v.26 no.2
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• pp.43-51
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• 2006

New renewable energy information becomes one of the greatest issues all over the world because of serious environment problems and limited fossil resources. The new renewable energy source information system is treated seriously for efficient management and distribution as dealing with these energy problems. However, it is difficult to manage and utilize new renewable energy information because gathering and surveying information is progressed individually in each research field. Therefore this paper will establish ISP(Information Strategy Planning) and propose the basic management system based-on GIS to analyze new renewable energy such as solar energy, wind power, small hydro, biomass, geothermal etc. and build the integration management system. The proposed integration management system can provide spatial analysis using thematic map, data search, data import/export and interpolation about users' queries.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.4C
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• pp.223-229
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• 2005

In this paper, we proposed an extended edge-based line averaging method for deinterlacing with restricted search range. Conversion from interlaced signal to non-interlaced signal is one of important issues. Conventional deinterlacing algorithms usually utilize edge-based line average algorithm(ELA) within pixel-by-pixel approach. However, it is very sensitive to noise and variation of intensity. To reduce the sensitivity, the proposed method adopts a block-by-block approach and provides reliable direction of edge. Simulation results show that it provides a better performance than other pixel-by-pixel ELA-based methods.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1995.10a
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• pp.124-140
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• 1995

The merit of fuzzy rule based systems stems from their capability of encoding qualitative knowledge of experts into quantitative rules. Recent advancement in automatic tuning or self-organization of fuzzy rules from experimental data further enhances their power, allowing the integration of the top-down encoding of knowledge with the bottom-up learning of rules. In this paper, methods of self-organizing fuzzy rules and of performing defuzzification and inference is presented based on a multi-resolution radial basis function network. The network learns an arbitrary input-output mapping from sample distribution as the union of hyper-ellipsoidal clusters of various locations, sizes and shapes. The hyper-ellipsoidal clusters, representing fuzzy rules, are self-organized based of global competition in such a way as to ensute uniform mapping errors. The cooperative interpolation among the multiple clusters associated with a mapping allows the network to perform a bidirectional many-to-many mapping, representing a particular from of defuzzification. Finally, an inference engine is constructed for the network to search for an optimal chain of rules or situation transitions under the constraint of transition feasibilities imposed by the learned mapping. Applications of the proposed network to skill acquisition are shown.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.39 no.4
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• pp.389-394
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• 2002

In this paper, we propose a robust stereo matching algorithm using nonlinear extended Kalman filter. The proposed algorithm estimates disparity using nonlinear extended Kalman filter and compares left image to right image for obtained disparity. As this process is run iteratively, we get disparity only with a few search. And, we can get robust stereo matching results by comparing left image to right image using bilinear interpolation to consider influence of neighborhood pixel. We compared SSD algorithm which is widely used, in stereo matching method, to result of the proposed algorithm. As the result, the proposed algorithm has an outstanding matching performance.