• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.6
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• pp.433-439
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• 2004

The Helicopter Simulator System is non-linear and complex. Futhermore, because of absence of its accurate mathematical model, it is difficult to control accurately its attitudes such as elevation angle and azimuth one. Therefore, we proposed a Hybrid GA-PID WAVENET(Genetic Algorithm Proportional Integral Derivative Wavelet Neural Network)control technique to control efficiently these angles. The proposed Hybrid GA-PID WAVENET is made through the following process. First, the WAVENET fundamental functions are defined. And their dilation and translation values are adjusted by GA to construct the optimal WAVENET controller. Secondly, the proportional, integral, and derivative gain coefficients of PR controller are tuned optimally. Finally, WAVENET controller which has a good transient characteristic and GA-PE controller which has a good steady state characteristic is adequately combined in hybrid type. Through the computer simulations, it is proved that the Hybrid GA-PE WAVENET control technique has a more excellent dynamic response than PID control technique and GA-PID one.

• Journal of the Korean Society of Visualization
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• v.20 no.3
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• pp.27-35
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• 2022

A problem on the sloshing flow of highly-viscous fluid in a rectangular box was revisited by both of theoretical approach and experimental visualization method. Based on the theoretical prediction that a linear shape of free surface is prevailing in bulk zone, it has been studied an analogy between a near wall coating flow in sloshing problem and dip coating flow in Landau-Levich problem. Phenomenological observation confirms that, in the case of highly-viscous fluid, I.e., R_e ≪ 1, viscous dominant near-wall flow in sloshing problem is identical to dip coating flow generated by drag-out of the plate being in both motion of vertical translation and horizontal rotation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.2
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• pp.164-173
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• 2013

In this paper, we propose multi-frame based super resolution algorithm by using motion vector normalization and edge pattern analysis. Existing algorithms have constraints of sub-pixel motion and global translation between frames. Thus, applying of algorithms is limited. And single-frame based super resolution algorithm by using discrete wavelet transform which robust to these problems is proposed but it has another problem that quantity of information for interpolation is limited. To solve these problems, we propose motion vector normalization and edge pattern analysis for 2*2 block motion estimation. The experimental results show that the proposed algorithm has better performance than other conventional algorithms.

• Journal of Korea Game Society
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• v.7 no.4
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• pp.63-70
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• 2007

Since the fisheye lens has a wide field of view, it can capture the scene and illumination from all directions from far less number of omnidirectional images. Due to these advantages of the omnidirectional camera, it is widely used in surveillance and reconstruction of 3D structure of the scene In this paper, we present a new self-calibration algorithm of omnidirectional camera from uncalibrated images by considering the inlier distribution. First, one parametric non-linear projection model of omnidirectional camera is estimated with the known rotation and translation parameters. After deriving projection model, we can compute an essential matrix of the camera with unknown motions, and then determine the camera information: rotation and translations. The standard deviations are used as a quantitative measure to select a proper inlier set. The experimental results showed that we can achieve a precise estimation of the omnidirectional camera model and extrinsic parameters including rotation and translation.

• Journal of Korean Academy of Nursing
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• v.49 no.1
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• pp.59-68
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• 2019

Purpose: This study evaluated the psychometric properties of the Korean version of Yale Food Addiction Scale for Children (YFAS-C). Methods: Participants were 419 young adolescent students (11~15 years old). The content validity of the expert group was calculated as the content validity index (CVI) after the translation and reverse translation process of the 25 items of the YFAS-C. The multitrait-multimethod matrix (MTMM) method was used to verify the construct validity; the generalized linear model (GLM) was used to evaluate the concurrent and incremental validity. Reliability was calculated as Kuder-Richardson-20 (KR-20) and Spearman-Brown coefficients. Results: The CVI of the 25 items was greater than the item-level CVI .80 and the scale-level CVI .90. The Korean version of YFAS-C had verified convergent validity in emotional eating and external eating and discriminant validity in restrained eating. In addition, it had verified concurrent validity in emotional eating and external eating. Finally the incremental validity of the Korean version of YFAS-C was statistically significant on BMI. Reliability was KR-20 ${\alpha}=.69$ and the Spearman-Brown coefficient was .64. Conclusion: The Korean version of YFAS-C is a valid and reliable scale for measuring the severity of food addiction; it can be a useful scale for preventing obesity by predicting food addiction early.

• Journal of Korea Water Resources Association
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• v.45 no.3
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• pp.243-252
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• 2012

The objective of this study is to analyze lateral inflow hydrologically. The IUH of lateral inflow is sum of the impulse responses of total cells in basin. This IUH bases on the Muskingum channel routing method, which hydrologically re-analysed to represent it as a linear combination of the linear channel model considering only the translation and the linear reservoir model considering only the storage effect. Rectangular and triangular basins were used as imaginary basins and IUH of each basin were derived. The derived IUH have different characteristics with respect to basin's shape. The storage coefficient of lateral inflow was also derived mathematically using general definitions of concentration time and storage coefficient. As a result, the storage coefficient of lateral inflow could be calculated easily using basin's width, length and hydrological characteristics of channel.

• Journal of Educational Research in Mathematics
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• v.14 no.1
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• pp.39-69
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• 2004

This paper investigates the teaching and learning of Linear function relating functional contexts and suggests the improved methods of representation-shift through this analysis. The methods emphasize the link between students' preacquired knowledge of mathematical representations and the way of using those. This methods are explanatory teaching, teaching and teaming based on modelling perspectives or tasks (interpretation, prediction, translation and scaling). We categorize the 8th grade middle school students' errors on the linear function relating real contexts and make a comparative study of the error-remedial effects and the teaching and teaming methods. We present the results of a study in which representation-shift methods based on modelling perspectives and tasks are more effective in terms of flexible connection of representations and error remediation. Also, We describe how students used modelling perspective-taking to explain and justify their conceptual models, to assess the quality of their models and to make connection to other mathematical representation during the problem solving focusing on the students' self-diagnosis.

• Journal of Broadcast Engineering
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• v.19 no.6
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• pp.798-809
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• 2014

Video stabilization is performed to remove unexpected shaky and irregular motion from a video. It is often used as preprocessing for robust feature tracking and matching in video. Typical video stabilization algorithms are developed to compensate motion from surveillance video or outdoor recordings that are captured by a hand-help camera. However, since the vehicle video contains rapid change of motion and local features, typical video stabilization algorithms are hard to be applied as it is. In this paper, we propose a novel approach to compensate shaky and irregular motion in vehicle video using linear regression model and vertical projection histogram matching. Towards this goal, we perform vertical projection histogram matching at each sub region of an input frame, and then we generate linear regression model to extract vertical translation and rotation parameters with estimated regional vertical movement vector. Multiple binarization with sub-region analysis for generating the linear regression model is effective to typical recording environments where occur rapid change of motion and local features. We demonstrated the effectiveness of our approach on blackbox videos and showed that employing the linear regression model achieved robust estimation of motion parameters and generated stabilized video in full automatic manner.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.3
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• pp.175-185
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• 2020

Three-dimensional registration is a process of matching data with or without a coordinate system to a reference coordinate system, which is used in various fields such as the absolute orientation of photogrammetry and data combining for producing precise road maps. Three-dimensional registration is divided into a method using points and a method using linear features. In the case of using points, it is difficult to find the same conjugate point when having different spatial resolutions. On the other hand, the use of linear feature has the advantage that the three-dimensional registration is possible by using not only the case where the spatial resolution is different but also the conjugate linear feature that is not the same starting point and ending point in point cloud type data. In this study, we proposed a method to determine the scale and the three-dimensional translation after determining the three-dimensional rotation angle between two data using quaternion to perform three-dimensional registration using linear features. For the verification of the proposed method, three-dimensional registration was performed using the linear features constructed an indoor and the linear features acquired through the terrestrial mobile mapping system in an outdoor environment. The experimental results showed that the mean square root error was 0.001054m and 0.000936m, respectively, when the scale was fixed and if not fixed, using indoor data. The results of the three-dimensional transformation in the 500m section using outdoor data showed that the mean square root error was 0.09412m when the six linear features were used, and the accuracy for producing precision maps was satisfied. In addition, in the experiment where the number of linear features was changed, it was found that nine linear features were sufficient for high-precision 3D transformation through almost no change in the root mean square error even when nine linear features or more linear features were used.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.9
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• pp.377-384
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• 2015

In this paper we propose a visualization tool for distortion-free time-series matching. Supporting distortion-free is a very important factor in time-series matching to get more accurate matching results. In this paper, we visualize the result of time-series matching, which removes various time-series distortions such as noise, offset translation, amplitude scaling, and linear trend by using moving average, normalization, linear detrending transformations, respectively. The proposed visualization tool works as a client-server model. The client sends a user-selected time-series, of which distortions are removed, to the server and visualizes the matching results. The server efficiently performs the distortion-free time-series matching on the multi-dimensional R*-tree index. By visualizing the matching result as five different charts, we can more easily and more intuitively understand the matching result.