• Journal of Soil and Groundwater Environment
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• v.13 no.6
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• pp.85-92
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• 2008

Water in Soyang River is an essential source for citizens of Chuncheon and Seoul areas. In 2006, turbid water in Soyang River aggravated by the typhoon Ewiniar, sustained for over 280 days unlike conventional years, then which interrupted water supply of Chuncheon and Seoul areas. Soil erosion derived from high cool lands constituting about 55% of Soyang River area is considered one of main causes for the turbid water, including imprudent development of mountainous area, road expansion, and road construction for forestry. According to analysis of turbidity, precipitation and reservoir level in Soyang River region for June 2006${\sim}$August 2008, the turbidity showed a peak correlation (r = 0.28) at a lag time of 49 days and especially did an excellent correlation (r = 0.60) with the reservoir level at a lag of 4 days. In the meantime, a critical turbidity of 31 NTU at Soyanggang Dam was estimated, over which would cause turbid water at Paldang Dam. In addition, a master recession curve was suggested, from which sustaining time of turbid water can be predicted.

• Journal of Korea Multimedia Society
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• v.10 no.10
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• pp.1284-1294
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• 2007

In this paper, a blind nonlinear channel equalization is implemented by using a Modified Fuzzy C-Means (MFCM) algorithm. The proposed MFCM searches the optimal channel output states of a nonlinear channel from the received symbols, based on the Bayesian likelihood fitness function instead of a conventional Euclidean distance measure. Next, the desired channel states of a nonlinear channel are constructed with the elements of estimated channel output states, and placed at the center of a Radial Basis Function (RBF) equalizer to reconstruct transmitted symbols. In the simulations, binary signals are generated at random with Gaussian noise. The performance of the proposed method is compared with that of a hybrid genetic algorithm (GA merged with simulated annealing (SA): GASA), and the relatively high accuracy and fast searching speed are achieved.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.3
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• pp.229-235
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• 2011

Traffic noise pollution is a growing problem that highly affects the health of people in urban areas. In order to implement effective measures against traffic noise the noise mapping about its distribution is imperative. Urban traffic noise maps will help to establish the existing baseline so that we will be able to look for the effective way to control the noise. They will also let us see in an understandable and visual way how noise spreads from roads into residential areas. In this paper we considered three development types between roads and residential areas, and applied the interpolation of ArcGIS for noise attenuation with distance from the roads to find the noise level at the parcels positions in residential areas, and then generated the noise map using the interpolated results. Therefore we present results that the traffic noise level within residential areas exceed the national noise standard and also can estimate the noise level of individual parcels. These results can be used for traffic noise control planning or assessment of officially assessed land price in near future.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.10B
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• pp.1937-1945
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• 1999

In paper, we propose a 3D polygonal mesh simplification technique based on vertex clustering. The proposed method differentiates the size of each cluster according to the local property of a 3D object. We determine the size of clusters by considering the normal vector of triangles and the vertex distribution. The subdivisions of cluster are represented by octree. In this paper, we use the Harsdorff distance between the original mesh and the simplified one as a meaningful error value. Because proposed method adaptively determine the size of cluster according to the local property of the mesh, it has smaller error as compared with the previous methods and represent the small regions on detail. Also it can generate a multiresolution model and selectively refine the local regions.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.27 no.3
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• pp.306-313
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• 1994

In order to estimate the degree of genetic divergence between the two types of finespotted flounder, Pleuronichthys cornutus which is important commercially in Japan, isozyme analysis was carried out by starch gel electrophoresis. Twenty two loci coding for fourteen enzymes were scored in two types of finespotted flounder and three completely divergent loci (Acp, Idh-2 and Mdh-2), with no common alleles, were observed between these two types. Nei's genetic distance between two types was 0.46592. However, the expected average heterozygosity was 0.120 in type A (Hon meitagarei) and 0.095 in type B (Bake meitagarei) These results mean that the existence of two types of finespotted flounder was established in this study which may have had genetic divergence and the divergence time of these two types may have been about $2.3{\times}10^6$ years ago.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.2
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• pp.155-160
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• 2014

In this paper, an algorithm using RGB-depth camera is proposed to detect smoke in interrior. RGB-depth camera, the Kinect provides RGB color image and depth information. The Kinect sensor consists of an infra-red laser emitter, infra-red camera and an RGB camera. A specific pattern of speckles radiated from the laser source is projected onto the scene. This pattern is captured by the infra-red camera and is analyzed to get depth information. The distance of each speckle of the specific pattern is measured and the depth of object is estimated. As the depth of object is highly changed, the depth of object plain can not be determined by the Kinect. The depth of smoke can not be determined too because the density of smoke is changed with constant frequency and intensity of infra-red image is varied between each pixels. In this paper, a smoke detection algorithm using characteristics of the Kinect is proposed. The region that the depth information is not determined sets the candidate region of smoke. If the intensity of the candidate region of color image is larger than a threshold, the region is confirmed as smoke region. As results of simulations, it is shown that the proposed method is effective to detect smoke in interior.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.8
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• pp.1179-1186
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• 2013

In this paper, an efficient vehicle detection and tracking algorithm for detection incident in tunnel is proposed. The proposed algorithm consists of three steps. The first one is a step for background estimates, low computational complexity and memory consumption Running Gaussian Average (RGA) is used. The second step is vehicle detection step, Adaboost algorithm is applied to this step. In order to reduce false detection from a relatively remote location of the vehicles, local features according to height of vehicles are used to detect vehicles. If the local features of an object are more than the threshold value, the object is classified as a vehicle. The last step is a vehicle tracking step, the Kalman filter is applied to track moving objects. Through computer simulations, the proposed algorithm was found that useful to detect and track vehicles in the tunnel.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.9
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• pp.1840-1846
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• 2011

It is necessary to estimate the Doppler spectrum for each range cell for the extraction of useful information from the return echoes in radar systems used for the remote sensing purpose such as detection of moving targets and weather surveillance. The signal amplitude in the beat frequency band is the important parameter in the detection and tracking of targets. However, strong clutter echoes do exist in most radar operation environments and the system phase noise spreads both the clutter and signal echoes of the target. In this paper, the effects of this system phase noise are analyzed concerning the clutter and the signal beat spectrum. It is shown that the separation capability of adjacent beat signal depends on the degree of spread in the clutter and beat signal caused by the radar system phase noise

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.11
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• pp.2463-2470
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• 2010

In some cases of u-health services, it is important and then required to pursue the location of users in real time because users could occasionally be in the situation beyond self-regulation. Location positioning has used two such typical techniques as trilateration and fingerprinting. A trilateration technique is usually based on three resident coordinates to identify the location of the target node. Ranging that measures distances between coordinates and the node is essential for applying the trilateration technique. Users especially in u-health services could be out of reachability in any such reasons as out of propagation ranges, fault of a communication counterpart, non-existence of possible communication facility, etc. This paper proposes a real-time locating method which can improve to identify and track the location of mobile objects. The method is based on references of identified mobile nodes as well as resident coordinates even though they may be partially out of communication reachability.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.7
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• pp.1371-1378
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• 2017

In this paper, we present an upsampling technique for depth map image using selective bilateral weights and a color weight using laplacian function. These techniques prevent color texture copy problem, which problem appears in existing upsamplers uses bilateral weight. First, we construct a high-resolution image using the bicubic interpolation technique. Next, we detect a color texture region using pixel value differences of depth and color image. If an interpolated pixel belongs to the color texture edge region, we calculate weighting values of spatial and depth in $3{\times}3$ neighboring pixels and compute the cost value to determine the boundary pixel value. Otherwise we use color weight instead of depth weight. Finally, the pixel value having minimum cost is determined as the pixel value of the high-resolution depth image. Simulation results show that the proposed algorithm achieves good performance in terns of PSNR comparison and subjective visual quality.