• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.312-312
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• 2022

우리나라는 하천법 및 소하천정비법에 의거하여 하천기본계획 수립 또는 하천의 지정 및 변경고시 시 하천구역을 지정하고 있다. 하천구역은 일반적으로 제방부지 및 제방하심측 토지경계를 기준으로 지정하나, 제방이 존재하지 않는 무제부 구간의 경우 명확한 제방경계가 없는관계로 하천법 제 10조 3항에서 5항까지 별도의 기준을 통해 하천구역 지정을 권장하고 있는 실정이다. 하천구역 설정 시 기준으로 삼는 횡단측점 자료의 경우 그 특성상 하천의 종단방향으로 불연속적인 특징을 갖고 있어 평면상 정확한 경계의 파악이 어려우며, 도로·철도 등 선형시설경계를 하천구역으로 설정 시 편입용지의 보상기준이 모호하여 다량의 민원이 발생하고 있다. 본 연구에서는 하천정비 시 기본계획이 수립되어 각 횡단측점별 결정된 계획홍수위를 기반으로 인접 지형의 홍수위 영향범위를 자동으로 추출하여 하천구역을 정밀하게 결정할 수 있는 방법론을 정립하고자 한다. 첫째로, 하천중심선의 각 측점의 위치정보와 하천의 지형을 위상정보체계로 구성하여 DB를 구축하였다. 둘째로, 측선과 측선사이 절점에 계획홍수위를 선형보간하여 부여하고 이를 지형도의 최단거리에 위치한 지형의 격자표고와 비교해 침수여부를 판단한다. 셋째, 최단거리 지형격자가 침수로 판단될 시 인접한 8개 지형격자의 지형표고와 홍수위를 비교하여 반복적으로 위 과정 수행을 통해 계획홍수위 기반 침수범위를 추출한다. 마지막으로, 이를 수치지형도에 중첩시켜 최종 정밀 하천구역을 결정할 수 있다. 이를 이용하여 산정된 정밀한 하천구역 경계설정을 통해 하천 내사유지 편입을 최소화함과 동시에 명확한 하천구역 구획기준을 정립하여 토지소유주와 담당부처 간 논의 시 기반자료로 활용될 수 있고, 하천구역의 신속하고 정확한 구역설정을 통해 하천인근의 토지이용 고도화 및 효율적인 이용이 가능할 것으로 기대된다.

• The Journal of the Acoustical Society of Korea
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• v.26 no.2
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• pp.87-94
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• 2007

In active sonar system, aspect angle and length of a target can be estimated by calculating the cross-correlation between left and right split-beams of a LFM(Linear Frequency Modulated) signal. However, high-resolution performances in bearing and range are required to estimate the information of a remote target. Because a certain higher sampling frequency than the Nyquist sampling frequency is required in this performance, an over-sampling process through interpolation method should be required. However, real-time implementation of split-beam processing with over-sampled split-beam outputs on a COTS(commercial off-the-shelf) DSP platform limits its performance because of given throughput and memory capacity. This paper proposes a cumulative processing algorithm for split-beam processing to solve the problems. The performance of the proposed method was verified through some simulation tests. Also, the proposed method was implemented as a real-time system using an ADSP-TS101.

• Journal of the Korean Society of Marine Environment & Safety
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• v.18 no.6
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• pp.545-550
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• 2012

Wind resource assessment is necessary when designing wind farm. To get the assessment, we must use a long term(20 years) observed wind data but it is so hard. so that we usually measured more than a year on the planned site. From the wind data, we can calculate wind energy related with the wind farm site. However, it calculate wind energy to collect the long term data from Met-mast(Meteorology Mast) station on the site since the Met-mast is unstable from strong wind such as Typhoon or storm surge which is Non-periodic. To solve the lack of the long term data of the site, we usually derive new data from the long term observed data of AWS(Automatic Weather Station) around the wind farm area using mathematical interpolation method. The interpolation method is called MCP(Measure-Correlative-Predict). In this study, based on the MCP Regression Model proposed by us, we estimated the wind energy at Handong site using AEP(Annual Energy Production) from Gujwa AWS data in Jeju. The calculated wind energy at Handong was shown a good agreement between the predicted and the measured results based on the linear regression MCP. Short term AEP was about 7,475MW/year. Long term AEP was about 7,205MW/year. it showed an 3.6% of annual prediction different. It represents difference of 271MW in annual energy production. In comparison with 20years, it shows difference of 5,420MW, and this is about 9 months of energy production. From the results, we found that the proposed linear regression MCP method was very reasonable to estimate the wind resource of wind farm.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.9
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• pp.113-127
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• 2012

Face detection methods using image processing have been proposed in many different ways. Generally, the most widely used method for face detection is an Adaboost that is proposed by Viola and Jones. This method uses Haar-like feature for image learning, and the detection performance depends on the learned images. It is well performed to detect face images within a certain distance range, but if the image is far away from the camera, face images become so small that may not detect them with the pre-learned Haar-like feature of the face image. In this paper, we propose the far distance face detection method that combine the Aadaboost of Viola-Jones with a saliency map and user's attention information. Saliency Map is used to select the candidate face images in the input image, face images are finally detected among the candidated regions using the Adaboost with Haar-like feature learned in advance. And the user's eye-tracking information is used to select the interest regions. When a subject is so far away from the camera that it is difficult to detect the face image, we expand the small eye gaze spot region using linear interpolation method and reuse that as input image and can increase the face image detection performance. We confirmed the proposed model has better results than the conventional Adaboost in terms of face image detection performance and computational time.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.2 s.308
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• pp.12-18
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• 2006

This paper presents a method to extract a good high-resolution image from a low-resolution video in an automatic manner. Since a high-resolution image reconstruction method utilizing several low-resolution input images works better than a conventional interpolation method utilizing single low-resolution input image only if the input images are well registered onto a common high-resolution grid, low-resolution input images should be carefully chosen so that the registration errors can be carefully considered. In this paper, the statistics obtained from the motion-compensated low-resolution images are utilized to evaluate the feasibility of the input image candidates. Maximum motion-compensation error is estimated from the high-resolution image observation model. U the motion-compensation error of the input image candidate is greater than the estimated maximum motion-compensation error, the input image candidate is discarded. The number of good input image candidates and the statistics of the motion-compensation errors are used to choose final input images. The final input images chosen from the input image selection block are given to the following high-resolution image reconstruction block. It is expected that the proposed method is utilized to extract a good high-resolution image efficiently from a low-resolution video without any user intervention.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.20 no.5
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• pp.533-541
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• 2007

The Zienkiewicz-Zhu(Z/Z) error estimate is slightly modified for the hierarchical p-refinement, and is then applied to L-shaped plates subjected to bending to demonstrate its effectiveness. An adaptive procedure in finite element analysis is presented by p-refinement of meshes in conjunction with a posteriori error estimator that is based on the superconvergent patch recovery(SPR) technique. The modified Z/Z error estimate p-refinement is different from the conventional approach because the high order shape functions based on integrals of Legendre polynomials are used to interpolate displacements within an element, on the other hand, the same order of basis function based on Pascal's triangle tree is also used to interpolate recovered stresses. The least-square method is used to fit a polynomial to the stresses computed at the sampling points. The strategy of finding a nearly optimal distribution of polynomial degrees on a fixed finite element mesh is discussed such that a particular element has to be refined automatically to obtain an acceptable level of accuracy by increasing p-levels non-uniformly or selectively. It is noted that the error decreases rapidly with an increase in the number of degrees of freedom and the sequences of p-distributions obtained by the proposed error indicator closely follow the optimal trajectory.

• Journal of Soil and Groundwater Environment
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• v.11 no.1
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• pp.65-76
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• 2006

This paper outlines the methodology of grid-based water balance for estimating the spatial distribution of recharge, which is applied to Woedo catchment in the northern area of the Jeju Island. The catchment is divided into grids and a daily water balance in each grid is computed for the period of 5 years. Daily rainfall data in each grid is interpolated from the data of 10 rainfall gauging stations. The spatial distributions of parameters such as SCS curve number, soil water retention capacity and crop coefficients are derived from GIS analyses of soil and land use characteristics. The SCS curve number is obtained by calibrating simulated runoffs with respect to the observed runoffs. The results show that the average annual rainfall increases from 1,665 mm/year to 3,382 mm/year in accordance with the topographic elevation, and the average annual recharge varies from 372 mm/year to 2,576 mm/year according to the average annual rainfall increases. Spatial variability of recharge is the highest among the water balance components such as rainfall, direct runoff, evaprotranspiration and recharge because the rate of runoff and evapotranspiration in the area with relatively low rainfall is higher than the other area.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.3
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• pp.37-48
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• 2010

The purpose of this paper is to evaluate how the rainfall field effect on a runoff simulation using grid radar rainfall data and ground gauge rainfall. The Gwangdeoksan radar and ground-gauge rainfall data were used to estimate a spatial rainfall field, and a hydrologic model was used to evaluate whether the rainfall fields created by each method reproduced a realistically valid spatial and temporal distribution. Pilot basin in this paper was the Naerin stream located in Inje-gun, Gangwondo, 250m grid scale digital elevation data, land cover maps, and soil maps were used to estimate geological parameters for the hydrologic model. For the rainfall input data, quantitative precipitation estimation(QPE), adjusted radar rainfall, and gauge rainfall was used, and then compared with the observed runoff by inputting it into a $Vflo^{TM}$ model. As a result of the simulation, the quantitative precipitation estimation and the ground rainfall were underestimated when compared to the observed runoff, while the adjusted radar rainfall showed a similar runoff simulation with the actual observed runoff. From these results, we suggested that when weather radars and ground rainfall data are combined, they have a greater hydrological usability as input data for a hydrological model than when just radar rainfall or ground rainfall is used separately.

• Journal of the Korean Society for Nondestructive Testing
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• v.21 no.2
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• pp.189-196
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• 2001

Photoelasticity is one of the most widely used methods for whole field stress analysis. In photoelasticity, the difference and the directions of the principal stresses we given isochromatic and isoclinic fringe patterns. Conventionally, principal stress directions are measured manually by relating the polarizer and analyzer of a plane polariscope at the same time. This is known to be the Tardy compensation method. This measurement can be very tedious and time consuming in whole field analysis. It is not possible to separate isoclincs from photoelastic fringes by conventional photoelastic technique. In this study, photoelastic theory is represented by Jones matrices and 4-steps and 8-steps phase shifting methods are described A feasibility study using computer simulation is done to separate isoclincs and isochomatics from photoelastic fringes of a circular disk under diametrical compression. Fringe patterns of the disk are generated using stress optic law. The magnitudes of isoclincs and isochromatics obtained from 8-step phase shifting method are compared with those of theories. From computer simulation, it is verified to separate isoclincs and isochomatics from photoelastic fringes.

• Journal of KIISE:Software and Applications
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• v.37 no.4
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• pp.273-281
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• 2010

In this paper, we propose an automatic segmentation method of the endo- and epicardial boundary by using ray-casting profile based on intensity distribution and gradient information in CT images. First, endo-cardial boundary points are detected by using adaptive thresholding and seeded region growing. To include papillary muscles inside the boundary, the endo-cardial boundary points are refined by using ray-casting based profile. Second, epi-cardial boundary points which have both a myocardial intensity value and a maximum gradient are detected by using ray-casting based adaptive gradient profile. Finally, to preserve an elliptical or circular shape, the endo- and epi-cardial boundary points are refined by using elliptical interpolation and B-spline curve fitting. Then, curvature-based contour fitting is performed to overcome problems associated with heterogeneity of the myocardium intensity and lack of clear delineation between myocardium and adjacent anatomic structures. To evaluate our method, we performed visual inspection, accuracy and processing time. For accuracy evaluation, average distance difference and overalpping region ratio between automatic segmentation and manual segmentation are calculated. Experimental results show that the average distnace difference was $0.56{\pm}0.24mm$. The overlapping region ratio was $82{\pm}4.2%$ on average. In all experimental datasets, the whole process of our method was finished within 1 second.