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Radar Polygon 기법의 개발 : 유사강우발생 확률에 근거한 면적강우량 산정기법 (Development of Radar Polygon Method : Areal Rainfall Estimation Technique Based on the Probability of Similar Rainfall Occurrence)

  • 조운기;이동률;이재현;김동균
    • 한국수자원학회논문집
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    • 제48권11호
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    • pp.937-944
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    • 2015
  • 본 연구에서는 실측자료를 기반으로 한 새로운 면적강우량 산정기법인 '레이더 폴리곤 기법(Radar polygon Method, PRM)'을제시하였다. RPM은(1) 강우공간분포의 실측자료인 기상레이더 자료를 이용하여 지점관측소가 위치한 곳에서의 강우강도와 주변지역의 강우강도를 비교하여 유사강우 발생지도 작성; (2) 위의 단계를 관측소별로 반복하여 각 관측소별 유사강우 발생 확률 지도 작성; (3) 주어진 격자에서의 각 관측소의 유사강우 발생 확률의 비교를 통한 지배범위 결정의 알고리즘으로 관측소별 가중치를 결정하는 방법이다. RPM 방법을 안성천 유역에 적용하여 Thiessen법과 결과를 비교하였다. 안성천 유역의 경우 RPM과 Thiessen방법에 근거한 다각형의 공간적 형태는 관측소 위치의 강우 특성에 따라 차이를 보였으나 관측소별 가중치 값의 차이는 크지 않았다. 본 연구는 관측기간 및 정확도의 문제로 인하여 제한적으로 활용되어 온 레이더 강우관측자료의 새로운 활용분야를 개척하였다는 점에서 큰 의미를 찾을 수 있다.

Sigma-Delta STAP의 시뮬레이션과 시험 결과 비교 (Comparison Between Simulation and Test Result of Sigma-Delta STAP)

  • 권보준
    • 한국전자파학회논문지
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    • 제29권6호
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    • pp.457-463
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    • 2018
  • 이 논문에서는 실제 레이다를 이용하여 획득한 신호와 시뮬레이션으로 획득한 신호에 ${\Sigma}{\Delta}-STAP$ 알고리즘을 적용하여 비교하였다. 시험은 무반향 챔버에서 모의신호 발생장치를 이용한 표적 신호와 신호발생기를 이용한 클러터 신호를 레이다로 수신하여 수행하였다. 시뮬레이션은 시험과 동일한 레이다 파라미터에 이상적인 기저대역 신호 모델링을 통하여 수행하였다. 비교 결과, ${\Sigma}{\Delta}-STAP$ 처리된 거리-도플러 맵은 표적 신호의 형태나 잡음 수준이 시뮬레이션과 시험 결과가 거의 유사하였다. SINR 손실의 경우, 두 결과가 비슷한 양상을 보이나, 시뮬레이션 결과가 1~2 dB 가량 높은 값을 보였다. 이를 통하여 일반적인 레이다 신호 시뮬레이션을 수행하여도 실제 시험 결과와 유사한 ${\Sigma}{\Delta}-STAP$ 처리 결과를 얻을 수 있음을 확인하였다.

CMP cross-correlation analysis of multi-channel surface-wave data

  • Hayashi Koichi;Suzuki Haruhiko
    • 지구물리와물리탐사
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    • 제7권1호
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    • pp.7-13
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    • 2004
  • In this paper, we demonstrate that Common Mid-Point (CMP) cross-correlation gathers of multi-channel and multi-shot surface waves give accurate phase-velocity curves, and enable us to reconstruct two-dimensional (2D) velocity structures with high resolution. Data acquisition for CMP cross-correlation analysis is similar to acquisition for a 2D seismic reflection survey. Data processing seems similar to Common Depth-Point (CDP) analysis of 2D seismic reflection survey data, but differs in that the cross-correlation of the original waveform is calculated before making CMP gathers. Data processing in CMP cross-correlation analysis consists of the following four steps: First, cross-correlations are calculated for every pair of traces in each shot gather. Second, correlation traces having a common mid-point are gathered, and those traces that have equal spacing are stacked in the time domain. The resultant cross-correlation gathers resemble shot gathers and are referred to as CMP cross-correlation gathers. Third, a multi-channel analysis is applied to the CMP cross-correlation gathers for calculating phase velocities of surface waves. Finally, a 2D S-wave velocity profile is reconstructed through non-linear least squares inversion. Analyses of waveform data from numerical modelling and field observations indicate that the new method could greatly improve the accuracy and resolution of subsurface S-velocity structure, compared with conventional surface-wave methods.

한국 쌀과 일본 쌀의 물리화학적 특성 연구 (I) NIR을 사용한 한국 쌀과 일본 쌀의 품질 비교 (Comparison of Korean and Japanese Rice Cultivars in Terms of Physicochemical Properties (I) The Comparison of Korean and Japanese Rice by NIR and Chemical Analysis)

  • 김혁일
    • 동아시아식생활학회지
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    • 제14권2호
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    • pp.135-144
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    • 2004
  • A total of 40 Korean and Japanese rice varieties were evaluated for their main chemical components, physical properties, cooking quality, pasting properties, and instrumental measurements. Based on their quality evaluations, it was concluded that Korean and Japanese rice varieties were not significantly different in the basic components of NIR (Near Infra Red) data and the chemical analysis from the uncooked brown and milled rices. Korean rice had a little bit higher protein and amylose contents but much lower fat acidity than those of Japanese rice from the chemical analysis. From all the data of three different kinds of NIR methods, Korean and Japanese milled rice were very similar except the taste score. Japanese rice showed a slightly higher taste score, a little bit higher lightness and whiteness, but lower yellowness and redness than Korean one. From all those data of NIR and the chemical analysis, Korean and Japanese rices had very similar components except the fat content.

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A METHOD OF IMAGE DATA RETRIEVAL BASED ON SELF-ORGANIZING MAPS

  • Lee, Mal-Rey;Oh, Jong-Chul
    • Journal of applied mathematics & informatics
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    • 제9권2호
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    • pp.793-806
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    • 2002
  • Feature-based similarity retrieval become an important research issue in image database systems. The features of image data are useful to discrimination of images. In this paper, we propose the highspeed k-Nearest Neighbor search algorithm based on Self-Organizing Maps. Self-Organizing Maps (SOM) provides a mapping from high dimensional feature vectors onto a two-dimensional space. The mapping preserves the topology of the feature vectors. The map is called topological feature map. A topological feature map preserves the mutual relations (similarity) in feature spaces of input data. and clusters mutually similar feature vectors in a neighboring nodes. Each node of the topological feature map holds a node vector and similar images that is closest to each node vector. In topological feature map, there are empty nodes in which no image is classified. We experiment on the performance of our algorithm using color feature vectors extracted from images. Promising results have been obtained in experiments.

발사체 이륙 시 음향 하중 예측 정확도 향상 (Improved Prediction of Lift-off Acoustic Loads for a Launch Vehicle)

  • 최상현;이정권;이익진
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2014년도 춘계학술대회 논문집
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    • pp.207-210
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    • 2014
  • This paper is concerned with the prediction of lift-off acoustic loads for a launch vehicle. Intense acoustic load is generated when a launch vehicle is lifted off, and it can induce vibrations of a launch vehicle which cause damage or malfunction of a launch vehicle and a satellite. Lift-off acoustic loads of NARO are predicted by the modified Eldred's second method and the result is compared with the measured data in flight test. The prediction shows similar peak and shape of spectrum to the test data, but some discrepancy can be observed due to the predicted margin. In order to reduce such discrepancy, the sound pressure levels with four source distribution assumptions are calculated. Also, the surface diffraction effects are considered in the predict ion of lift-off acoustic loads, and the predicted result is more similar to the test data.

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원격측정 토양수분자료, (C-band 측정치 vs. L-band 측정치)의 공간변화도 비교 (Comparison of the Spatial Variability of C- and L-Band Remotely Sensed Soil Moisture)

  • 김광섭;임태경
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2004년도 학술발표회
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    • pp.705-708
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    • 2004
  • The spatial variability of the L- and C- band large scale remotely sensed soil moisture data, obtained during tire Southern Great Plain 1999 (SGP'99), was characterized. The results demonstrate that soil moisture data using L-band show the break in statistical symmetry (multiscaling behavior) with the variation of scale of observation, which is similar to that of the soil property such as sand content. Also, soil moisture data using C-band show single scaling behavior with the variation of scale of observation, which Is similar to that of the vegetation condition.

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FEROM: Feature Extraction and Refinement for Opinion Mining

  • Jeong, Ha-Na;Shin, Dong-Wook;Choi, Joong-Min
    • ETRI Journal
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    • 제33권5호
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    • pp.720-730
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    • 2011
  • Opinion mining involves the analysis of customer opinions using product reviews and provides meaningful information including the polarity of the opinions. In opinion mining, feature extraction is important since the customers do not normally express their product opinions holistically but separately according to its individual features. However, previous research on feature-based opinion mining has not had good results due to drawbacks, such as selecting a feature considering only syntactical grammar information or treating features with similar meanings as different. To solve these problems, this paper proposes an enhanced feature extraction and refinement method called FEROM that effectively extracts correct features from review data by exploiting both grammatical properties and semantic characteristics of feature words and refines the features by recognizing and merging similar ones. A series of experiments performed on actual online review data demonstrated that FEROM is highly effective at extracting and refining features for analyzing customer review data and eventually contributes to accurate and functional opinion mining.

Hiding Secret Data in an Image Using Codeword Imitation

  • Wang, Zhi-Hui;Chang, Chin-Chen;Tsai, Pei-Yu
    • Journal of Information Processing Systems
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    • 제6권4호
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    • pp.435-452
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    • 2010
  • This paper proposes a novel reversible data hiding scheme based on a Vector Quantization (VQ) codebook. The proposed scheme uses the principle component analysis (PCA) algorithm to sort the codebook and to find two similar codewords of an image block. According to the secret to be embedded and the difference between those two similar codewords, the original image block is transformed into a difference number table. Finally, this table is compressed by entropy coding and sent to the receiver. The experimental results demonstrate that the proposed scheme can achieve greater hiding capacity, about five bits per index, with an acceptable bit rate. At the receiver end, after the compressed code has been decoded, the image can be recovered to a VQ compressed image.

점운증강을 위한 프로젝션 손실 (Projection Loss for Point Cloud Augmentation)

  • 오신모;이효종
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2019년도 춘계학술발표대회
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    • pp.482-484
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    • 2019
  • Learning and analyzing 3D point clouds with deep networks is challenging due to the limited and irregularity of the data. In this paper, we present a data-driven point cloud augmentation technique. The key idea is to learn multilevel features per point and to reconstruct to a similar point set. Our network is applied to a projection loss function that encourages the predicted points to remain on the geometric shapes with a particular target. We conduct various experiments using ShapeNet part data to evaluate our method and demonstrate its possibility. Results show that our generated points have a similar shape and are located closer to the object.