• Journal of Korean Society for Geospatial Information Science
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• v.4 no.2 s.8
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• pp.173-180
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• 1996

In a grid based data transformation, the different gridding methods provide different interpretations of scattered data because each method calculate grid node values using a different weighted mathematical algorithms. Therefore, it is necessary to review the interpolated characteristics of some gridding methods according to search distance, search area and search options before determing the best method with a data set. For this, in this paper, six different gridding methods with the same search conditions are applied to a scattered data obtained from sterro-plotter. The interpolated characteristics of the scattered geographic data considered through comparison of coincidence between the data point and the grid node being interpolated. And also, shows the real application of gridding methods through calculating volumes and creating cross sections.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.8
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• pp.251-260
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• 2014

3D point data is utilized in various industry domains for its high accuracy to the surface information of an object. It is substantially utilized in geography for terrain scanning and analysis. Generally, 3D point data need to be changed by Gridding which produces a regularly spaced array of z values from irregularly spaced xyz data. But it requires long processing time and high resource cost to interpolate grid coordination. Kriging interpolation in Gridding has attracted because Kriging interpolation has more accuracy than other methods. However it haven't been used frequently since a processing is complex and slow. In this paper, we presented a parallel Gridding algorithm which contains Kriging and an application of grid data structure to fit MapReduce paradigm to this algorithm. Experiment was conducted for 1.6 and 4.3 billions of points from Airborne LiDAR files using our proposed MapReduce structure and the results show that the total execution time is decreased more than three times to the convention sequential program on three heterogenous clusters.

• Journal of KIISE:Software and Applications
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• v.33 no.2
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• pp.143-153
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• 2006

Microarray which enables us to obtain hundreds and thousands of expression of gene or genotype at once is an epoch-making technology in comparative analysis of genes. First of all, we have to measure the intensity of each gene in an microarray image from the experiment to gain the expression level of each gene. But it is difficult to analyze the microarray image in manual because it has a lot of genes. Meta-gridding method and various auto-gridding methods have been proposed for this, but thew still have some problems. For example, meta-gridding requires manual-work due to some variations in spite of experiment in same microarray, and auto-gridding nay not carried out fully or correctly when an image has a lot of noises or is lowly expressed. In this article, we propose Hierarchical Grid Alignment algorithm for new methodology combining meta-gridding method with auto-gridding method. In our methodology, we necd a meta-grid as an input, and then align it with the microarray image automatically. Experimental results show that the proposed method serves more robust and reliable gridding result than the previous methods. It is also possible for user to do more reliable batch analysis by using our algorithm.

• Korean Journal of Remote Sensing
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• v.6 no.1
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• pp.25-37
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• 1990

Methods of geometric correction for the Advanced Very High Resolution Radiometer imagery of NOAA satellites were developed and applied to the software for image processing of meteorological satellite data. The software for finding the earth location of each scan position and the software for gridding on original imagery were dedigned. On the assumption of circular orbits and the spherical earth, the methods developed were sufficiently accurate in the purpose of most meteorological data analyses.

• Spatial Information Research
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• v.23 no.6
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• pp.43-55
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• 2015

Currently, each organization has developed its gridded data in the form of respective grid system for its own purpose. Interoperability among the organization had been limited and resulted in inconvenient data access and application across domains. In this study, we investigated potential standards for National grid system and their strength and weakness. We also reviewed existing gridding schemes and had a survey of demand about grid system to those who have used or would plan to use gridded data in academic and business sectors. As the result of survey of demand, we suggested national grid system for national grid data integration management system which has the mutual compatibility and also proposed sharing scheme of the grid type for users who need to grid data.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.15 no.2
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• pp.207-213
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• 1997

The purpose of this study is to aim at presenting efficient technique of 3-D Terrain Modelling through multilateral approach methods and to compare with raw data, using low-densed randomly located point data. The subject religion of this study are selected two sites and take into consideration for degree of freedom about low-densed randomly located point data. The result of this study by precision analysis of digital cartographic map-ping using low-densed randomly located point data bave shown that . First, making digital cartographic map, the technique of making it using low-desned randomly located point data by TIN-based results to good and fast run-time in A and B sites all together. Second, the visualization analysis results of digital cartographic map using TIN and GRID-based terrain modeling techniqus similar exacts A and B sites, but the terrain modeling techniqus by TIN-based are small data size than GRID-based with the data with the data size of saving with DXF files. Third, making digital catographic map using terrain modeling techniques by Grid-based, the standard errors of low-densed randomly located point data and interpolated data using gridding method have more good results by radial basis function interpolation techniques at A and B sites all together.

• Journal of Magnetics
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• v.16 no.1
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• pp.77-82
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• 2011

This paper presents a new self-adjoint material sensitivity formulation for optimal designs and inverse problems in the high frequency domain. The proposed method is based on the continuum approach using the augmented Lagrangian method. Using the self-adjoint formulation, there is no need to solve the adjoint system additionally when the goal function is a function of the S-parameter. In addition, the algorithm is more general than most previous approaches because it is independent of specific analysis methods or gridding techniques, thereby enabling the use of commercial EM simulators and various custom solvers. For verification, the method was applied to the several numerical examples of dielectric material reconstruction problems in the high frequency domain, and the results were compared with those calculated using the conventional method.

• Journal of the Korea Society of Computer and Information
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• v.19 no.9
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• pp.1-10
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• 2014

In this paper, we propose MPI gridding algorithm of LiDAR data that minimizes the communication between the cores. The LiDAR data collected from aircraft is a 3D spatial information which is used in various applications. Since there are many cases where the LiDAR data has too high resolution than actually required or non-surface information is included in the data, filtering the raw LiDAR data is required. In order to use the filtered data, the interpolation using the data structure to search adjacent locations is conducted to reconstruct the data. Since the processing time of LiDAR data is directly proportional to the size of it, there have been many studies on the high performance parallel processing system using MPI. However, previously proposed methods in parallel approach possess possible performance degradations such as imbalanced data size among cores or communication overhead for resolving boundary condition inconsistency. We conduct empirical experiments to verify the effectiveness of our proposed algorithm. The results show that the total execution time of the proposed method decreased up to 4.2 times than that of the conventional method on heterogeneous clusters.

• Investigative Magnetic Resonance Imaging
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• v.12 no.1
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• pp.27-32
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• 2008

Purpose : We developed a 3D CSI (chemical shift imaging) sequence that uses the PRESS (point resolved spectroscopy) excitation scheme and spiral-based readout gradients. Materials and Methods : We implemented constant-density spirals ($32{\times}32$ matrix, $24{\times}24\;cm$ FOV) which use analytic equations to enable real-time prescription on the scanner. In-vivo data from the brain were collected and reconstructed using the gridding algorithm. Results : Data illustrate that with our imaging sequence, the benefits of the PRESS technique, which include elimination of lipid artifacts, remain intact while flexible scan time versus resolution tradeoffs can be achieved using the constant-density spirals. Volumetric high resolution 3D CSI covering 5760 cm3 could be obtained in 12.5 minutes. Conclusion : Spiral-based readout gradients offer a flexible tradeoff between scan time versus resolution. By combining this feature with PRESS based excitation, efficient methods of volumetric spectroscopic imaging can be accomplished by obtaining whole brain coverage while eliminating lipid contamination.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.3
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• pp.227-239
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• 2008

Processing LiDAR (Light Detection And Ranging) data obtained from ALS (Airborne Laser Scanning) systems mainly involves organization and segmentation of the data for 3D object modeling and mapping purposes. The ALS systems are viable and becoming more mature technology in various applications. ALS technology requires complex integration of optics, opto-mechanics and electronics in the multi-sensor components, Le. data captured from GPS, INS and laser scanner. In this study, digital image processing techniques mainly were implemented to gray level coded image of the LiDAR data for building extraction and superstructures segmentation. One of the advantages to use gray level image is easy to apply various existing digital image processing algorithms. Gridding and quantization of the raw LiDAR data into limited gray level might introduce smoothing effect and loss of the detail information. However, smoothed surface data that are more suitable for surface patch segmentation and modeling could be obtained by the quantization of the height values. The building boundaries were precisely extracted by the robust edge detection operator and regularized with shape constraints. As for segmentation of the roof structures, basically region growing based and gap filling segmentation methods were implemented. The results present that various image processing methods are applicable to extract buildings and to segment surface patches of the superstructures on the roofs. Finally, conceptual methodology for extracting characteristic information to reconstruct roof shapes was proposed. Statistical and geometric properties were utilized to segment and model superstructures. The simulation results show that segmentation of the roof surface patches and modeling were possible with the proposed method.