• Title/Summary/Keyword: Similar Data

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

  • Cho, Woonki;Lee, Dongryul;Lee, Jaehyeon;Kim, Dongkyun
    • Journal of Korea Water Resources Association
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    • v.48 no.11
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    • pp.937-944
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    • 2015
  • This study proposed a novel technique, namely the Radar Polygon Method (RPM), for areal rainfall estimation based on radar precipitation data. The RPM algorithm has the following steps: 1. Determine a map of the similar rainfall occurrence of which each grid cell contains the binary information on whether the grid cell rainfall is similar to that of the observation gage; 2. Determine the similar rainfall probability map for each gage of which each grid cell contains the probability of having the rainfall similar to that of the observation gage; 3. Determine the governing territory of each gage by comparing the probability maps of the gages. RPM method was applied to the Anseong stream basin. Radar Polygons and Thiessen Polygons of the study area were similar to each other with the difference between the two being greater for the rain gage highly influenced by the orography. However, the weight factor between the two were similar with each other. The significance of this study is to pioneer a new application field of radar rainfall data that has been limited due to short observation period and low accuracy.

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

  • Kwon, Bojun
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.29 no.6
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    • pp.457-463
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    • 2018
  • This paper compares the results of ${\Sigma}{\Delta}-STAP$ applied to actual radar test data and simulation data. The radar received a target signal from a virtual target generator and the clutter signal from a signal generator in an anechoic chamber. The simulation data were generated from ideal baseband radar signal modeling using the same parameter as that for the test radar. The ${\Sigma}{\Delta}-STAP$ results of the test and simulation data are similar in terms of the target signal shape and noise level. The SINR(Signal-to-Interfrence-plus-Noise Ratio) loss also had similar aspects, but the simulation result shows 1~2 dB higher SINR loss than the test result. This result verified that the simulation data can be a reasonable alternative test data when the ${\Sigma}{\Delta}-STAP$ is applied.

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

  • Hayashi Koichi;Suzuki Haruhiko
    • Geophysics and Geophysical Exploration
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    • v.7 no.1
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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.

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 (한국 쌀과 일본 쌀의 물리화학적 특성 연구 (I) NIR을 사용한 한국 쌀과 일본 쌀의 품질 비교)

  • 김혁일
    • Journal of the East Asian Society of Dietary Life
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    • v.14 no.2
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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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    • v.9 no.2
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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.

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

  • Choi, Sang-Hyeon;Ih, Jeong-Guon;Lee, Ik-Jin
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2014.04a
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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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Comparison of the Spatial Variability of C- and L-Band Remotely Sensed Soil Moisture (원격측정 토양수분자료, (C-band 측정치 vs. L-band 측정치)의 공간변화도 비교)

  • Kim, Gwangseob;Lim, TaeKyung
    • Proceedings of the Korea Water Resources Association Conference
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    • 2004.05b
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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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    • v.33 no.5
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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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    • v.6 no.4
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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.

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

  • Wu, Chenmou;Lee, Hyo-Jone
    • Proceedings of the Korea Information Processing Society Conference
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    • 2019.05a
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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.