• Journal of the Korean Institute of Landscape Architecture
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• v.34 no.6 s.119
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• pp.1-9
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• 2007

Land use types within a watershed closely are related with the water quality characteristics of receiving water bodies. Despite of a numerous studies suggesting a strong relationship between water quality and land use, there have been increasing concerns about the geographical variation and a lack of spatial integration in that relationship, which are essential to implementing these findings into land use planning and management. In the meantime, edges mediate the material flux between adjacent systems. This mediating effect of edges is strongly related to the complexity of their shapes. Land use activities within a watershed have a direct impact on the water quality of adjacent aquatic systems, and hydrological processes carry residuals from watershed into adjacent aquatic ecosystems through the edges. Therefore, the geometry of reservoirs theoretically affects the relationship between land uses in the watershed and the quality of receiving bodies of water. In this light, this study integrates the geo-spatial dimensions of land uses in the watershed using GIS and landscape indices in order to explore the relationship between land uses and water quality. Water quality characteristics, land uses and geometry of 133 randomly sampled reservoirs were correlated, based on buffer zones and types of reservoirs. The findings showed that land uses, particularly urban land uses, significantly affect water quality characteristics including BOD, COD, TN and TP, and geometry of reservoirs reduces the concentration of pollutant and nutrients in reservoirs. One of results indicates that the relationship between land use and water quality and effects of spatial dimension may vary with types of reservoirs and pollutants. These results suggest that lakeshore areas are important, particularly for TN reduction and call for a caution to land use activities nearby shoreline areas for sustaining better water quality.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.1
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• pp.22-29
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• 2016

Many studies in detection and classification of the targets in the underwater environments have been conducted for military purposes, as well as for non-military purpose. Due to the complicated characteristics of underwater acoustic signal reflecting multipath environments and spatio-temporal varying characteristics, active sonar target detection technique has been considered as a difficult technique. In this paper, we describe the basic concept of Fractional Fourier transform and optimal transform order. Then we analyze the relationship between time-frequency characteristics of an LFM signal and its spectrum using Fractional Fourier transform. Based on the analysis results, we present active sonar target detection method. To verify the performance of proposed methods, we compared the results with conventional FFT-based matched filter. The experimental results demonstrate the superiority of the proposed method compared to the conventional method in the aspect of AUC(Area Under the ROC Curve).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.8
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• pp.672-678
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• 2013

In the recent year, along with the rapid development of LED technology, many applications using LEDs have been researched and indoor positioning is one of them. In particular, previous indoor positioning systems based on visible light communication combine triangulation manner such as AoA, ToA TDoA. But most of them needs transmitting unique ID of each LED panel. In this paper, we propose an non LED-ID based indoor positioning system in which the visible light radiated from LEDs is used to locate the position of receiver. Compared to current indoor positioning systems using LED light, our system has the advantages of simple implementation, low cost and high accuracy. Through the computer simulation, our system can achieve a high estimation accuracy of 3.6cm in average in the $5{\times}5{\times}3m^3$ room.

• The Transactions of the Korea Information Processing Society
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• v.5 no.9
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• pp.2294-2301
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• 1998

The aim of this paper is to extract features from each news scenes for example, symbol icon which can be distinct each broadcasting corp, icon and caption which are has feature and important information for the scene in respectively, In this paper, we propose extraction methods of caption that has important prohlem of news videos and it can be classified in three steps, First of al!, we converted that input images from video frame to YIQ color vector in first stage. And then, we divide input image into regions in clear hy using equalized color histogram of input image, In last, we extracts caption using edge histogram based on vertical and horizontal line, We also propose the method which can extract news icon in selected key frames by the difference of inter-histogram and can divide each scene by the extracted icon. In this paper, we used comparison method of edge histogram instead of complex methcxls based on color histogram or wavelet or moving objects, so we shorten computation through using simpler algorithm. and we shown good result of feature's extraction.

• Journal of KIISE:Software and Applications
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• v.31 no.6
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• pp.829-839
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• 2004

Methods based on integer programming have been shown to be very effective in solving various crew pairing optimization problems. However, their applicability is limited to problems with linear constraints and objective functions. Also, those methods often require an unacceptable amount of time and/or memory resources given problems of larger scale. Heuristic methods such as neighborhood search, on the other hand, can handle large-scaled problems without too much difficulty and can be applied to problems having any form of objective functions and constraints. However, neighborhood search often gets stuck at local optima when faced with complex search spaces. This paper presents ,i hybrid algorithm of neighborhood search and integer programming, which nicely combines the advantages of both methods. The hybrid algorithm has been successfully tested on a large-scaled crew pairing optimization problem for a real subway line.

• Tunnel and Underground Space
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• v.25 no.4
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• pp.359-372
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• 2015

Rock masses include various rock discontinuities such as faults, joints, and bedding planes. These discontinuities appear as complex structures in geometry. In this study, growth patterns of fractures between two stepping shear fracture tips are numerically modeled using PFC2D (Particle Flow Code). The numerical model showed not only incipient growth of fractures at the tips of preexisting fractures but also subsequent growth of the new fractures. It is observed from all of the experiments that the incipient fractures are tensile cracks developed at $30{\sim}57^{\circ}$ to the preexisting fractures and the subsequent growth of these fractures were at low angles to the preexisting fractures this study.

• Journal of Broadcast Engineering
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• v.23 no.5
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• pp.598-605
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• 2018

Behavior awareness is a technology that recognizes human behavior through data and can be used in applications such as risk behavior through video surveillance systems. Conventional behavior recognition algorithms have been performed using the 2D camera image device or multi-mode sensor or multi-view or 3D equipment. When two-dimensional data was used, the recognition rate was low in the behavior recognition of the three-dimensional space, and other methods were difficult due to the complicated equipment configuration and the expensive additional equipment. In this paper, we propose a method of recognizing human behavior using only CCTV images without additional equipment using only RGB and depth information. First, the skeleton extraction algorithm is applied to extract points of joints and body parts. We apply the equations to transform the vector including the displacement vector and the relational vector, and study the continuous vector data through the RNN model. As a result of applying the learned model to various data sets and confirming the accuracy of the behavior recognition, the performance similar to that of the existing algorithm using the 3D information can be verified only by the 2D information.

• Cartoon and Animation Studies
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• s.14
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• pp.83-99
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• 2008

In general, the cut or dissolve or etc., collective changeover represents the change of scene in the film. Animation film makes scene's various parts to allow intended sensibility and narrative factors by special manufacturing skill generating frame image one by one and transfer it to the different symbolic dimensional expression. Nowadays sequential scene composition is not any more the unique special treatment for 2D animation according to image handling skill like morphing, metamorphosis, etc. becomes diverse and elaborate. But 2D manual animation makes spectator to be absorbed into different visual dimensions continuously and strongly beyond character and background, namely object and space. that is 2D manual animation's strong attractiveness. Finally these characteristics enable literary function which makes it possible to do delicate metaphorical through full scene composition basis and to communicate a implicative meaning system The analysis about scene broke boundary between symbolic perspective world and plane formative world and it became more diverse and complicated. Hereupon the analyzing the composition basis of formative element in the animation film scene and it's application effect make it helpful to analysis and application in the modern image scene having new absorbing methods

• Journal of Sensor Science and Technology
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• v.7 no.6
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• pp.418-425
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• 1998

Stereo cameras are the most widely used sensing systems for automated machines including robots to interact with their three-dimensional(3D) working environments. The position of a target point in the 3D world coordinates can be measured by the use of stereo cameras and the camera calibration is an important preliminary step for the task. Existing camera calibration techniques can be classified into two large categories - linear and nonlinear techniques. While linear techniques are simple but somewhat inaccurate, the nonlinear ones require a modeling process to compensate for the lens distortion and a rather complicated procedure to solve the nonlinear equations. In this paper, a method employing a neural network for the calibration problem is described for tackling the problems arisen when existing techniques are applied and the results are reported. Particularly, it is shown experimentally that by utilizing the function approximation capability of multi-layer neural networks trained by the back-propagation(BP) algorithm to learn the error pattern of a linear technique, the measurement accuracy can be simply and efficiently increased.

• Journal of Intelligence and Information Systems
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• v.7 no.2
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• pp.51-63
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• 2001

In supervised machine learning, an induction algorithm, which is able to extract rules from data with learning capability, provides a useful tool for data mining. Practical induction algorithms are known to degrade in prediction accuracy and generate complex rules unnecessarily when trained on data containing superfluous features. Thus it needs feature subset selection for better performance of them. In feature subset selection on the induction algorithm, wrapper method is repeatedly run it on the dataset using various feature subsets. But it is impractical to search the whole space exhaustively unless the features are small. This study proposes a heuristic method that uses sensitivity analysis of neural networks to the wrapper method for generating rules with higher possible accuracy. First it gives priority to all features using sensitivity analysis of neural networks. And it uses the wrapper method that searches the ordered feature space. In experiments to three datasets, we show that the suggested method is capable of selecting a feature subset that improves the performance of the induction algorithm within certain iteration.