• Structural Engineering and Mechanics
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• v.74 no.4
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• pp.521-532
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• 2020

A floating dry dock is an advanced structure that can provide a solution for dry dock space shortages. The critical point in floating dock operation is compensating the deflection caused by a heavy payload by adjusting the water level in the ballast system. An appropriate ballasting plan warrants safe and precise construction on a floating dock. Particularly, in the case of a 2D floating dock, ballasting plan evaluation is crucial due to complex deformation modes. In this paper, we developed a method to calculate the optimal ballasting plan for accurate and precise construction on a 2D floating dock. The finite element method was used for considering the flexibility of the floating dock as well as the construction blocks. Through a gradient-based optimization algorithm, the optimal ballasting plan for the given load condition was calculated in semi-real time (5 min). The present method was successfully used for the actual construction of an offshore structure on the 2D floating dock.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2002.04a
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• pp.35-40
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• 2002

A numerical analysis based on two-dimensional and three-dimensional incompressible Navier-Stokes equations has been carried out for double-circular-arc compressor cascades and the results are compared with available experimental data at various incidence angles. The 2-D and 3-D computational codes based on SIMPLE algorithm adopt pressure weighted interpolation method for non-staggered grid and hybrid scheme for the convertive terms. Turbulence modeling is very important for prediction of cascade flows, which are extremely complex with separation and reattachment by adverse pressure gradient. In this paper k-$\varepsilon$ turbulence model with wall function is used to increase efficiency of computation times.

• International Journal of Contents
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• v.10 no.3
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• pp.9-16
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• 2014

Depth-image-based rendering is generally used in real-time 2D-to-3D conversion for 3DTV. However, inaccurate depth maps cause flickering issues between image frames in a video sequence, resulting in eye fatigue while viewing 3DTV. To resolve this flickering issue, we propose a new 2D-to-3D conversion scheme based on fast and robust depth-map generation from a 2D video sequence. The proposed depth-map generation algorithm divides an input video sequence into several cuts using a color histogram. The initial depth of each cut is assigned based on a hypothesized depth-gradient model. The initial depth map of the current frame is refined using color and motion information. Thereafter, the depth map of the next frame is updated using the difference image to reduce depth flickering. The experimental results confirm that the proposed scheme performs real-time 2D-to-3D conversions effectively and reduces human eye fatigue.

• Journal of Korea Multimedia Society
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• v.7 no.12
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• pp.1680-1691
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• 2004

One of the representative methods of optical flow is a gradient method which estimates the movement of an object based on the differential of image brightness. However, the method is ineffective for large displacement of the object and many improved methods have been proposed to copy with such limitations. One of these improved techniques is the multigrid processing, which is used in many optical flow algorithms. As an alternative novel technique we have been proposing an orthogonal functional expansion method, where whole displacements are expanded from low frequency terms. This method is expected to be applicable to flow estimation with large displacement and deformation including expansion and contraction, which are difficult to cope with by conventional optical flow methods. In the orthogonal functional expansion method, the apparent displacement field is calculated iteratively by a projection method which utilizes derivatives of the invariant constraint equations of brightness constancy. One feature of this method is that differentiation of the input image is not necessary, thereby reducing sensitivity to noise. In this paper, we apply our method to several real images in which the objects undergo large displacement and/or deformation including expansion. We demonstrate the effectiveness of the orthogonal functional expansion method by comparing with conventional methods including our optimally scaled multigrid optical flow algorithm.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.05
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• pp.116-118
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• 1997

In hippocampal morphology Abnormalities, including unilateral or bilateral volume loss, are known to occur in epilepsy, Alzheimer's disease, and in certain amnestic syndromes. To detect such abnormalities in hippocampal morphology, we present a method that combines region growing and dynamic contour model to detect hippocampus from MRI brain data. The segmentation process is performed two steps. First region growing with a seed point is performed in the region of hippocampus and the initial contour of dynamic contour model is obtained. Second, the initial contour is modified on the basis of criteria that integrate energy with contour smoothness and the image gradient along the contour. As a result, this method improves fairly sensitivity to the choice of the initial seed point, which is often seen by conventional contour model. The power and practicality of this method have been tested on two brain datasets. Thus, we have developed an effective algorithm to extract hippocampus from MRI brain data.

• Korean Journal of Artificial Intelligence
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• v.6 no.2
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• pp.17-22
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• 2018

According to the World Health Organization, the top 10 causes of death worldwide include heart disease. Heart diseases include coronary disease, which induces acute myocardial infarction. Ticagrelor drugs are being used to treat acute alliances, but it has become difficult to breathe due to the drugs. In a related study, Tobias predicted that uric acid causes acute respiratory distress independently of other factors, including BNP. And in the Ahmad study, serum uric acid numbers were related to the left ventricle depending on the level of uric acid. Experimental data are data used after 155 patients who received coronary intervention took ticagrelor. The research methods were leveraged by gradient decent algorithm and linear regression. In order to avoid overfitting in the experiment, training data and test data were separated into 70 and 30 percent respectively. The experimental results lacked the predictability of other attributes except DT in the correlation coefficient and crystal coefficient. However, all attributes related to dyspnea other than DT are determined to be related to causing relaxation of the heart in the left ventricle. Therefore, the attribute causing dyspnea is determined to be an attribute causing relaxation of the heart of the DT and left ventricle.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.12
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• pp.1220-1225
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• 2010

This paper proposes a novel active noise control (ANC) approach that uses an IIR filter and neural network techniques to effectively reduce interior noise. We construct a multiple-channel IIR filter module which is a linearly augmented framework with a generic IIR model to generate a primary control signal. A three-layer perceptron neural network is employed for establishing a secondary-path model to represent air channels among noise fields. Since the IIR module and neural network are connected in series, the output of an IIR filter is transferred forward to the neural model to generate a final ANC signal. A gradient descent optimization based learning algorithm is analytically derived for the optimal selection of the ANC parameter vectors. Moreover, re-estimation of partial parameter vectors in the ANC system is proposed for online learning. Lastly, we present the results of a numerical study to test our ANC methodology with realistic interior noise measurement obtained from Korean railway trains.

• International Journal of Advanced Culture Technology
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• v.5 no.2
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• pp.82-89
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• 2017

The range of problems that can be handled by the activation of big data and the development of hardware has been rapidly expanded and machine learning such as deep learning has become a very versatile technology. In this paper, mnist data set is used as experimental data, and the Cross Entropy function is used as a loss model for evaluating the efficiency of machine learning, and the value of the loss function in the steepest descent method is We applied the GradientDescentOptimize algorithm to minimize and updated weight and bias via backpropagation. In this way we analyze optimal reliability value corresponding to the number of exercises and optimal reliability value without overfitting. And comparing the overfitting time according to the number of data changes based on the number of training times, when the training frequency was 1110 times, we obtained the result of 92%, which is the optimal reliability value without overfitting.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.5
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• pp.413-418
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• 2001

In this paper, we propose a new camera calibration method which is based on a fuzzy model instead of a physical camera model of the conventional method. The camera calibration is to determine the correlation between camera image coordinate and real world coordinate. The camera calibration method using a fuzzy model can not estimate camera physical parameters which can be obtained in the conventional methods. However, the proposed method is very simple and efficient because it can determine the correlation between camera image coordinate and real world coordinate without any restriction, which is the objective of camera calibration. With calibration points acquired out of experiments, 3-D real world coordinate and 2-D image coordinate are estimated using the fuzzy modeling method and the results of the experiments demonstrate the validity of the proposed method.

• Proceedings of the Korean Geotechical Society Conference
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• 2004.03b
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• pp.904-909
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• 2004

The study area adjoins with Yangsan fault in Sangbuk-myeon, Samsam-ri, Kyongsang-namdo and consist of the natural steep slope. After drawing data layer which have altitude by using digital topography data, it is converted to lattice DEM of $10m{\times}10m$ size. From this, gradient map of unit lattice, slant direction map and shadow relif map are made. Using flow apportioning algorithm, upper slope contributing area and wetness index by established lattice can be calculated. Area that have high wetness index shows lineament structure of northwest-southeast direction, and this agrees with shear fracture system. The result of electricity specific resistance survey in the study area shows that area of high wetness index has low electricity specific resistance anomaly. That is, wetness index conforms with distribution of fractured zone that accompanied chemical weathering of rock. Therefore, wetness index can be used as the method of detecting fractured zones and judging the stability of the area.