• Journal of the Korean Society of Marine Environment & Safety
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• v.13 no.3
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• pp.213-217
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• 2007

Pontoon type very large floating structure has been considered and actively studied as one of the most important ocean space utilization. The hydroelastic displacement of the pontoon type floating structure in waves is the largest at its weather side. The purpose of this study is to investigate the characteristics and effects of the submerged horizontal plate which is developed to reduce the wave exciting forces acting on the pontoon type floating structure using numerical analysis. The numerical method based on the finite difference method has been adopted and compared with the experimental data to confirm the reliability of it. We have performed the numerical computation of wave exciting forces acting on the pontoon type floating structure with/without submerged plate and discuss the results of simulation.

• Journal of the Korea Safety Management & Science
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• v.18 no.3
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• pp.127-135
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• 2016

Korean automobile industrial is in a difficult situation because of more competitive global market and lower demand. Therefore, domestic as well as global automobile manufacturers are making greater efforts in cost reduction to strengthen the competitiveness. According to statistical data, logistics cost in domestic manufacturers is higher than advanced countries. In this study, we developed program to effectively manage standard time of procurement logistics, and confirm based on A-automobile factory data. For the purpose, we develop the system which is possible to manage standard time as well as calculate man-hour. Program is not just for calculating and managing standard man-hour, scenarios analysis function will be added to calculate benefit while introduce logistics automated equipment. In this study we propose scenario using AGV instead of electric motor while move component. In the scenario analysis, job constitution is changed, and then we use system to compare the result. We can confirm standard man-hour is reduced from 22.3M/H to 14.3M/H. In future research, it is necessary scenario analysis function, and develop algorithm with realistic constraint condition.

• Journal of the Society of Naval Architects of Korea
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• v.53 no.5
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• pp.343-352
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• 2016

In this study, a pre-swirl duct for the 180,000 DWT bulk carrier has been designed from a propulsion standpoint using CFD. The stern duct - designed by NMRI - was selected as the initial duct. The objective function is to minimize the value of delivered power in model scale. Design variables of the duct include duct angle, diameter, chord length, and vertical and horizontal displacements from the center. Design variables of the stators are blade number, arrangement angle, chord length, and pitch angle. A parametric design was carried out with the objective function obtained using CFD. Reynolds averaged Navier-Stokes equations have been solved; and the Reynolds stress model applied for the turbulent closure. A double body model is used for the treatment of free-surface. MRF and sliding mesh models have been applied to simulate the actuating propeller. A self-propulsion point has been obtained from the results of towing and self-propelled computations, i.e., form factor obtained from towing computation and towing forces obtained from self-propelled computations of two propeller rotating speeds. The reduction rate of the delivered power of the improved stern duct is 2.9%, whereas that of the initial stern duct is 1.3%. The pre-swirl duct with one inner stator in upper starboard and three outer stators in portside has been designed. The delivered power due to the designed pre-swirl duct is reduced by 5.8%.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.5
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• pp.483-488
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• 2015

This paper presents a local binary pattern(LBP) for effectively classifying textures, which is based on the multidimensional intensity difference between the adjacent pixels in the block image. The intensity difference by considering the a extent of 4 directional changes(verticality, horizontality, diagonality, inverse diagonality) in brightness between the adjacent pixels is applied to reduce the computation load as a results of decreasing the levels of histogram for classifying textures of image. And the binary patterns that is represented by the relevant intensities within a block image, is also used to effectively classify the textures by accurately reflecting the local attributes. The proposed method has been applied to classify 24 block images from USC Texture Mosaic #2 of 128*128 pixels gray image. The block images are different in size and texture. The experimental results show that the proposed method has a speedy classification and makes a free size block images classify possible. In particular, the proposed method gives better results than the conventional LBP by increasing the range of histogram level reduction as the block size becomes larger.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.2
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• pp.53-60
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• 2012

Nearest-neighbor classification predicts the class of an input data with the most frequent class among the near training data of the input data. Even though nearest-neighbor classification doesn't have a training stage, all of the training data are necessary in a predictive stage and the generalization performance depends on the quality of training data. Therefore, as the training data size increase, a nearest-neighbor classification requires the large amount of memory and the large computation time in prediction. In this paper, we propose a prototype selection algorithm that predicts the class of test data with the new set of prototypes which are near-boundary training data. Based on Tomek links and distance metric, the proposed algorithm selects boundary data and decides whether the selected data is added to the set of prototypes by considering classes and distance relationships. In the experiments, the number of prototypes is much smaller than the size of original training data and we takes advantages of storage reduction and fast prediction in a nearest-neighbor classification.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.6
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• pp.63-74
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• 2007

Fast Fourier transform(FFT) is powerful, fast computation framework for convolution in many image restoration application. However, an actually observed image acquired with finite aperture of the acquisition device from the infinite background and it lost data outside the cropped region. Because of these the boundary artifacts are produced. This paper reviewed and summarized the up to date the techniques that have been applied to reduce of the boundary artifacts. Moreover, we propose a new block-based fast image restoration using combined extrapolation and edge-tapering without boundary artifacts with reduced computational loads. We apply edgetapering to the inner blocks because they contain outside information of boundary. And outer blocks use half-convolution extrapolation. For this process it is possible that fast image restoration without boundary artifacts.

• The Transactions of the Korea Information Processing Society
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• v.1 no.1
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• pp.81-91
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• 1994

A DCT map and new cldebook design algorithm based on a two-dimension discrete cosine transform (2D-DCT) is presented for coder of image vector quantizer. We divide the image into smaller subblocks, then, using 2D DCT, separate it into blocks which are hard to code but it bears most of the visual information and easy to code but little visual information, and DCT map is made. According to this map, the significant features of training image are extracted by using the 2D DCT. A codebook is generated by partitioning the training set into a binary tree based on tree-structure. Each training vector at a nonterminal node of the binary tree is directed to one of the two descendants by comparing a single feature associated with that node to a threshold. Compared with the pairwise neighbor (PPN) and classified VQ(CVQ) algorithm, about 'Lenna' and 'Boat' image, the new algorithm results in a reduction in computation time and shows better picture quality with 0.45 dB and 0.33dB differences as to PNN, 0.05dB and 0.1dB differences as to CVQ respectively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.12C
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• pp.1153-1161
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• 2005

The latest standard H.264 coding methods show better efficiency compared to the former coding standards from the rate distortion point of view, but also lead to high complexity. In this paper, we propose an adaptive and fast inter/intra prediction algorithm for H.264 video coding. In the inter prediction algorithm, an effective and simple mode selection method is proposed, which can adaptively adjust to motion estimation to reduce complexity. And proposed intra prediction algorithm reduces its complexity by using calculated Minimum Rate-Distortion costs in the prediction of Intra $16{\times}16$ and $4{\times}4$ modes. From experiment using JM8.4, our algorithm can reduce about $60.9\%$ of computation time as compared to JM, with only negligible PSNR and bitrate degradation.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.3
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• pp.237-246
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• 2001

A high speed context-free marker-controlled and minima imposition-free watershed transform is proposed for efficient multi-object detection and segmentation from a complex background. The context-free markers are extracted from a complex backgrounded multi-object image using a noise tolerant attention operator. These make marker-controlled watershed possible for the over-segmentation reduction without region merging. The proposed method presents a marker-constrained labeling that can speed up the segmentation of a marker-controlled watershed transform by eliminating the necessity of the minima imposition. Simulation results show that the proposed method can efficiently detects and segments multiple objects from a complex background while reducing over- segmentation and the computation time.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.10A
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• pp.823-829
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• 2011

Recently, wireless body area network (WBAN) has received much attention as an application for the ubiquitous healthcare system. In WBAN, each sensor nodes and a personal base station such as PDA have an energy constraint and computation overhead should be minimized due to node's limited computing power and memory constraint. The reliable data transmission also must be guaranteed because it handles vital signals. In this paper, we propose a systematic network coding scheme for WBAN to reduce the network coding overhead as well as total energy consumption for completion the transmission. We model the proposed scheme using Markov chain. To minimize the total energy consumption for completing the data transmission, we made the problem as a minimization problem and find an optimal solution. Our simulation result shows that large amount of energy reduction is achieved by proposed systematic network coding. Also, the proposed scheme reduces the computational overhead of network coding imposed on each node by simplify the decoding process.