• Title/Summary/Keyword: Data Interpolation

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A Localized Multiquadric (MQ) Interpolation Method on the Hyperbolic Plane (하이퍼볼릭 평면에서의 지역적 MQ 보간법)

  • Park, Hwa-Jin
    • The KIPS Transactions:PartA
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    • v.8A no.4
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    • pp.489-498
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    • 2001
  • A new method for local control of arbitrary scattered data interpolation in the hyperbolic plane is developed in this paper. The issue associated with local control is very critical in the interactive in the interactive design field. Especially the suggested method in this paper could be effectively applied to the interactive shape modeling of genus-N objects, which are constructed on the hyperbolic plane. Since the effects of the changed data affects only the limited area around itself, it is more convenient for end-users to design a genus-N object interactively. Therefore, by improving the global interpolation on the hyperbolic plane where the genus-N object is constructed, this research is aiming at the development and implementation of the local interpolation on the hyperbolic plane. It is implemented using the following process. First, for localizing the interpolating functions, the hyperbolic domain is tessellated into arbitrary triangle patches and the group of adjacent triangle patches of each data point is defined as a sub-domain. On each sub-domain, a weight function is defined. Last, by blending of three weight functions on the overlapped triangles, local MQ interpolation is completed. Consequently, it is compared with the global MQ interpolation using several sample data and functions.

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Comparative analysis of spatial interpolation methods of PM10 observation data in South Korea (남한지역 PM10 관측자료의 공간 보간법에 대한 비교 분석)

  • Kang, Jung-Hyuk;Lee, Seoyeon;Lee, Seung-Jae;Lee, Jae-Han
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.24 no.2
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    • pp.124-132
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    • 2022
  • This study was aimed to visualize the spatial distribution of PM10 data measured at non-uniformly distributed observation sites in South Korea. Different spatial interpolation methods were applied to irregularly distributed PM10 observation data from January, 2019, when the concentration was the highest and in July, 2019, when the concentration was the lowest. Four interpolation methods with different parameters were used: Inverse Distance Weighted (IDW), Ordinary Kriging (OK), radial base function, and scattered interpolation. Six cases were cross-validated and the normalized root-mean-square error for each case was compared. The results showed that IDW using smoothing-related factors was the most appropriate method, while the OK method was least appropriate. Our results are expected to help users select the proper spatial interpolation method for PM10 data analysis with comparative reliability and effectiveness.

An image coding algorithm using fractal interpolation method (이산 트랙탈 보간법을 이용한 영상 부호화 알고리즘)

  • 이승현;정현민;윤택현;최일상;박규태
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.33B no.6
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    • pp.82-91
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    • 1996
  • In this paper, an image coding technique using fractal interpolation is proposed. Similar to the conventional methods, an image is partitioned into blocks and each block is coded independently. However, an interpolation point is ahsared by its neighboring blocks. This means that each block can use all its interpolation points with minimal increase of new data. For a simple implementation, triangular blocks are used instead of square blocks and new coefficients are difined. Data obtained in the encoding process hav estatistical characteristics suitable sfor entropy coding, an dthus arithmetic coding is perfomred for improving the compression efficiency. The results of the proposed coder in comparison with those of a conventional coder show that the interpolation method reduces block effect caused by a memoryless block coder, especially at low bit rates. This improvement is due to sharing of information between adjacent blocks. Moreover, th enumber of iteration required in ecoding process is reduced since more information is used to decode each block.

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A Study on the Interpolation Algorithm to Improve the Blurring of Magnified Image (확대 영상의 몽롱화 현상을 제거하기 위한 보간 알고리즘 연구)

  • Lee, Jun-Ho
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.19 no.4
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    • pp.562-569
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    • 2010
  • This paper analyzes the problems that occurred in the magnification process for a fine input image and investigates a method to improve the blurring of magnified image. This paper applies a curve interpolation algorithm in CAD/CAM for the same test images with the existing image algorithm in order to improve the blurring of magnified image. As a result, the nearest neighbor interpolation, which is the most frequently applied algorithm for the existing image interpolation algorithm, shows that the identification of a magnified image is not possible. Therefore, this study examines an interpolation of gray-level data by applying a low-pass spatial filter and verifies that a bilinear interpolation presents a lack of property that accentuates the boundary of the image where the image is largely changed. The periodic B-spline interpolation algorithm used for curve interpolation in CAD/CAM can remove the blurring but shows a problem of obscuration, and the Ferguson' curve interpolation algorithm shows a more sharpened image than that of the periodic B-spline algorithm. For the future study, hereafter, this study will develop an interpolation algorithm that has an excellent improvement for the boundary of the image and continuous and flexible property by using the NURBS, Ferguson' complex surface, and Bezier surface used in CAD/CAM engineering based on the results of this study.

Research on Touch Function capable of Real-time Response in Low-end Embedded System (저사양 임베디드 시스템에서의 실시간 응답이 가능한 터치 기능 연구)

  • Lee, Yong-Min;Han, Chang Ho
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.4
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    • pp.37-41
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    • 2021
  • This paper presents a study to implement a touch screen capable of real-time response processing in a low-end embedded system. This was done by introducing an algorithm using an interpolation method to represent real-time response characteristics when a touch input is performed. In this experiment, we applied a linear interpolation algorithm that estimates random data by deriving a first-order polynomial from 2-point data. We also applied a Lagrange interpolation algorithm that estimates random data by deriving a quadratic polynomial from 3-point data. As a result of the experiment, it was found that the Lagrange interpolation method was more complicated than the linear interpolation method, and the processing speed was slow, so the text was not smooth. When using the linear interpolation method, it was confirmed that the speed displayed on a screen is 2.4 times faster than when using the Lagrange interpolation method. For real-time response characteristics, it was confirmed that smaller size of the executable file of the algorithm is more advantageous than the superiority of the algorithm itself. In conclusion, in order to secure real-time response characteristics in a low-end embedded system, it was confirmed that a relatively simple linear interpolation algorithm performs touch operations with better real-time response characteristics than the Lagrange interpolation method.

Study on Weather Data Interpolation of a Buoy Based on Machine Learning Techniques (기계 학습을 이용한 항로표지 기상 자료의 보간에 관한 연구)

  • Seong-Hun Jeong;Jun-Ik Ma;Seong-Hyun Jo;Gi-Ryun Lim;Jun-Woo Lee;Jun-Hee Han
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2022.06a
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    • pp.72-74
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    • 2022
  • Several types of data are collected from buoy due to the development of hardware technology.. However, the collected data are difficult to use due to errors including missing values and outliers depending on mechanical faults and meteorological environment. Therefore, in this study, linear interpolation is performed by adding the missing time data to enable machine learning to the insufficient meteorological data. After the linear interpolation, XGBoost and KNN-regressor, are used to forecast error data and suggested model is evaluated by using real-world data of a buoy.

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Trace-based Interpolation Using Machine Learning for Irregularly Missing Seismic Data (불규칙한 빠짐을 포함한 탄성파 탐사 자료의 머신러닝을 이용한 트레이스 기반 내삽)

  • Zeu Yeeh;Jiho Park;Soon Jee Seol;Daeung Yoon;Joongmoo Byun
    • Geophysics and Geophysical Exploration
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    • v.26 no.2
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    • pp.62-76
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    • 2023
  • Recently, machine learning (ML) techniques have been actively applied for seismic trace interpolation. However, because most research is based on training-inference strategies that treat missing trace gather data as a 2D image with a blank area, a sufficient number of fully sampled data are required for training. This study proposes trace interpolation using ML, which uses only irregularly sampled field data, both in training and inference, by modifying the training-inference strategies of trace-based interpolation techniques. In this study, we describe a method for constructing networks that vary depending on the maximum number of consecutive gaps in seismic field data and the training method. To verify the applicability of the proposed method to field data, we applied our method to time-migrated seismic data acquired from the Vincent oilfield in the Exmouth Sub-basin area of Western Australia and compared the results with those of the conventional trace interpolation method. Both methods showed high interpolation performance, as confirmed by quantitative indicators, and the interpolation performance was uniformly good at all frequencies.

Data Interpolation and Design Optimisation of Brushless DC Motor Using Generalized Regression Neural Network

  • Umadevi, N.;Balaji, M.;Kamaraj, V.;Padmanaban, L. Ananda
    • Journal of Electrical Engineering and Technology
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    • v.10 no.1
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    • pp.188-194
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    • 2015
  • This paper proposes a generalized regression neural network (GRNN) based algorithm for data interpolation and design optimization of brushless dc (BLDC) motor. The procedure makes use of magnet length, stator slot opening and air gap length as design variables. Cogging torque and average torque are treated as performance indices. The optimal design necessitates mitigating the cogging torque and maximizing the average torque by varying design variables. The data set for interpolation and ensuing design optimisation using GRNN is obtained by modeling a standard BLDC motor using finite element analysis (FEA) tool MagNet 7.1.1. The performance indices of the standard motor obtained using FEA are validated with an experimental model and an analytical method. The optimal design is authenticated using particle swarm optimization (PSO) algorithm and the performance indices of the optimal design obtained using GRNN is validated using FEA. The results indicate the suitability of GRNN as an interpolation and design optimization tool for a BLDC motor.

Comparison of CZCS and SeaWiFS Pigments for Merging the Higher Level Ocean Color Data

  • Jeong, Jong-Chul;Yoo, Shin-Jae
    • Korean Journal of Remote Sensing
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    • v.18 no.5
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    • pp.299-303
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    • 2002
  • Many ocean color sensors are being operated at present and will be continued to operatein the coming years. However, these ocean color sensors have different spectral bands locations and higher level product algorithms. Thus the continuity of ocean color data from the satellite with different missions will be important for monitoring of oceanographic variation with long term research. In this study, CZCS band and algorithm are compared with OCTS and SeaWiFS algorithm for estimating chlorophyll. Missing bands of OCTS and CZCS for chlorophyll algorithm are estimated by linear-interpolation using SeaWiFS data. We were able to evaluate the effectiveness of the correction methods using linear interpolation method. Surprisingly, linear interpolation gave a better result than those of other bands.

Real-time Data Enhancement of 3D Underwater Terrain Map Using Nonlinear Interpolation on Image Sonar (비선형 보간법을 이용한 수중 이미지 소나의 3 차원 해저지형 실시간 생성기법)

  • Ingyu Lee;Jason Kim;Sehwan Rho;Kee–Cheol Shin;Jaejun Lee;Son-Cheol Yu
    • Journal of Sensor Science and Technology
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    • v.32 no.2
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    • pp.110-117
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    • 2023
  • Reconstructing underwater geometry in real time with forward-looking sonar is critical for applications such as localization, mapping, and path planning. Geometrical data must be repeatedly calculated and overwritten in real time because the reliability of the acoustic data is affected by various factors. Moreover, scattering of signal data during the coordinate conversion process may lead to geometrical errors, which lowers the accuracy of the information obtained by the sensor system. In this study, we propose a three-step data processing method with low computational cost for real-time operation. First, the number of data points to be interpolated is determined with respect to the distance between each point and the size of the data grid in a Cartesian coordinate system. Then, the data are processed with a nonlinear interpolation so that they exhibit linear properties in the coordinate system. Finally, the data are transformed based on variations in the position and orientation of the sonar over time. The results of an evaluation of our proposed approach in a simulation show that the nonlinear interpolation operation constructed a continuous underwater geometry dataset with low geometrical error.