• KOREAN JOURNAL OF CROP SCIENCE
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• v.34 no.3
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• pp.261-269
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• 1989

Agricultural activities in Chejudo require more specialized weather services in this region. The meteorological information available from the Korea Meteorological Service (KMS) is limited in its areal coverage because the KMS stations are located along the narrow band of coastal area. topoclimatological technique which makes use of empirical relationships between the topography and the weather can be applied to produce reasonable estimates of the climatic variables such as air temperature and precipitation over remote land area where routine observations are rare. Presentation of these estimates in a from of fine-mesh grid map can also be helpful to upgrade the quality of weather services in this region. Altitude values of the 250 m grid points were read from a 1: 25000 topographic map and the mean altitude, the mean slope, and the aspect of the slope were determined for each 1 km$^2$ land area from these altitude data. Daily minimum air temperature data were collected from 18 points in Chejudo during the winter period from November 1987 to February 1988. The data were grouped into 3 sets based on synoptic pressure pattern. Departures from the KMS observations were regressed to the topographical variables to delineate empirical relationships between the local minimum temperature under specific pressure patterns and the site topography. The selected regression equations were used to calculate the daily minimum temperature for each 1 km$^2$ land area under the specific pressure patterns. The outputs were presented in a fine-mesh grid map with a 6-level contour capability.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.835-838
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• 2008

Many researches on hierarchical path search have been studied so far. Even though partitioning regions is essential part, the researches are not enough. This paper proposes two efficient methods to partition regions: 1)a method based on voronoi algorithm in which a major node is central point of a region, 2) a method based on fired grid that partitions regions into major and minor. The performances of the proposed methods are compared with the conventional hierarchical path search method in which a region is formed by the boundary line of nearest 4 points of a major node in terms of the path search time and the accuracy. The results obtained from the experiments show that the method based on voronoi achieves short execution time and the method based grid achieves high accuracy.

• Journal of Korean Society for Atmospheric Environment
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• v.34 no.2
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• pp.223-232
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• 2018

As the Seoul metropolitan city has the largest numbers of population and vehicles, the citizens can be exposed to hazardous air pollutants(HAPs) mainly from the vehicular exhaust and human activities. In this study, we proposed a systematic method for the selection of priority monitoring areas for HAPs using Geographic Information System (GIS). First, emission parameters(emission data, vehicle registration, monitoring data, and so on) and population parameters (population and population density) were plotted using the inverse distance weighted (IDW) interpolation. Then, the interpolation data for individual parameters, which were normalized between 1 and 5 points, were compiled for 270 grids with a resolution of $2km{\times}2km$. The total score of each grid was calculated using weights(1~5) for the individual parameters. The final ranking of each grid was assigned by four scenarios with varying fractions of the emission and population parameters from 50 : 50 to 80 : 20. Consequently, nine grids were suggested as priority monitoring areas, and all of them are located in the southwestern part of Seoul.

• Geophysics and Geophysical Exploration
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• v.5 no.3
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• pp.169-177
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• 2002

We develop the weighted-averaging finite-element method which uses four kinds of element sets. By constructing global stiffness and mass matrices for four kinds of element sets and then averaging them with weighting coefficients, we obtain a new global stiffness and mass matrix. With the optimal weighting coefficients minimizing grid dispersion and grid anisotropy, we can reduce the number of grid points required per wavelength to 4 for a $1\%$ upper limit of error. We confirm the accuracy of our weighted-averaging finite-element method through accuracy analyses for a homogeneous and a horizontal-layer model. By synthetic data example, we reconfirm that our method is more efficient for simulating a geological model than previous finite-element methods.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.12 no.2
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• pp.209-218
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• 1994

This study aims to generate triangulated irregular network in a form of digital terrain model which is being increasingly used. In general, grid digital elevation model and triangulated irregular network are reasonable units for solving terrain problems. But, triangulated irregular network is an efficient alternative to grid digital elevation model because of their efficiency in storing data and their convenient data structure for accommodating irregularly spaced elevation data. Various methods represented for extracting triangulated irregular networks from grid digital elevation model, and then algorithm that get accurate results for triangulation with their data set was introduced. The new approach for triangulation in this study uses the Elevation and Changeable Distance criterion, and adding interpolation points and restricted constraint lines can generate triangulated irregular network which is more close to real surface. This made database efficient construction and could be used for many applications of geo-spatial information system.

• Smart Media Journal
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• v.8 no.2
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• pp.9-15
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• 2019

Since the computational complexity for hologram generation increases exponentially with respect to the size of the point cloud, parallel processing using CUDA and/or OpenCL library based on multiple GPUs has recently become popular. The CUDA kernel for parallelization needs to consist of threads, blocks, and grids properly in accordance with the number of cores and the memory size in the GPU. In addition, in case of multiple GPU environments, the distribution in grid-by-grid, in block-by-block, or in thread-by-thread is needed according to the number of GPUs. In order to evaluate the performance of CGH generation, we compared the computational speed in CPU, in single GPU, and in multi-GPU environments by gradually increasing the number of points in a point cloud from 10 to 1,000,000. We also present a memory structure design and a calculation method required in the CUDA-based parallel processing to accelerate the CGH (Computer Generated Hologram) generation operation in multiple GPU environments.

• Korean Journal of Soil Science and Fertilizer
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• v.22 no.3
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• pp.163-172
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• 1989

In order to study spatial variability of soil physical properties accross the land-partitioned boundary on Hwadong silt clay loam soil (Fine clayey, mixed, mesic family of Aquic Hapludalfs), all measured data were analyzed by means of kriging, fractile diagram, smooth frequency distribution, and autocorrelation. Sampling for soil particle size distribution analysis was made at 225 intersections of $15{\times}15$ grid with 10m interval. Field capacity, bulk density and saturated hydraulic conductivity were measured in situ at 594 intersections of $33{\times}18$ grid with 2.5m interval in only $6,000m^2$ reselected from $22,500m^2$ of sampling area for particle size distribution analysis. Sampled or measured soil depths were 0 to 10cm 25 to 35cm and 50 to 60cm at each intersections. The results are summarized as follows: 1. The coefficient of variance (CV) of various physical properties ranges from 4.8 to 128.8%. Saturated hydraulic conductivity is classified into the high variation group with CV greater than 100%, while the low variation group with CV smaller than 10% consists of bulk density. Other properties belong to the medium variation group with CV between 10 and 100%. 2. The appropriate number of soil samples for the determination of various physical properties with error smaller than 10% are calculated as one for bulk density, six for field moisture capacity, 16 for silt, 19 for clay, 69 for sand and 686 for saturated hydraulic conductivity. 3. Smooth frequency distribution and fractile diagram show that saturated hydraulic conductivity is in lognormal distribution while other physical properties are in normal distribution. 4. Serial correlation analysis reveals that the soil physical properties have spatial dependence between two nearest neighbouring grid points. Autocorrelation analysis of physical properties measured between the serial grid points in the direction of south to north following section boundary shows that the zone of influence showing stationarity ranges from 7.5 to 40m. In the direction of east to west across section boundary, the autocorrelogram of many physical properties shows peaks with the periodic interval of 30m, which are similar to the partitioned land width. This reveals that the land-partitioned boundary causes soil variability.

• Journal of the Korea Society of Computer and Information
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• v.12 no.2 s.46
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• pp.231-242
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• 2007

The existing pattern mining methods[1,2,3,4,5,6,11,12,13] do not use location generalization method on the set of location history data of moving object, but even so they simply do extract only frequent patterns which have no spatio-temporal constraint in moving patterns on specific space. Therefore, it is difficult for those methods to apply to frequent pattern mining which has spatio-temporal constraint such as optimal moving or scheduling paths among the specific points. And also, those methods are required more large memory space due to using pattern tree on memory for reducing repeated scan database. Therefore, more effective pattern mining technique is required for solving these problems. In this paper, in order to develop more effective pattern mining technique, we propose new location generalization method that converts data of detailed level into meaningful spatial information for reducing the processing time for pattern mining of a massive history data set of moving object and space saving. The proposed method can lead the efficient spatial moving pattern mining of moving object using by creating moving sequences through generalizing the location attributes of moving object into 2D spatial area based on $R^*$-Tree and Area Grid Hash Table(AGHT) in preprocessing stage of pattern mining.

• Journal of Korean Society of Forest Science
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• v.30 no.1
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• pp.1-7
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• 1976

This study was performed in Bo-Eun Gun, Chung-Cheong Buk Do. The forest types having been classified, the each area was measured by dot-grid method. The 820 sample points having been obtained by systematic sampling method, the tree heights, crown densities, crown diameters in the points were measured on the aerial photography, and the volumes per hectare were estimated by the comparison with stereogram. Thirty eight plots, which amounted to about 4.5% of all the sample points, were sampled with double sampling method and volume were measured by the ground survey method. the results were summarized as follows; 1. There is no significant differentia between the values measure by dot-grid method and the statistical values obtained by the authority for the area. 2. There is no significant differentia between the estimated values and the measured values for the volume. And the coefficient (b) was 1.18. 3. The heights of conifer trees were easily measured more or less, but it was some difficult for the deciduous trees, because the tops of trees were not observed easily. 4. All the values had a tendencies to be overestimated in the low stocked stand and to be underestimated in the high stocked stand. 5. When the aerial volume table method by ground checking needs to be used together, the work should be performed by the experienced technician and the photgraphic volume table should be made in advanced of the work.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.3
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• pp.329-337
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• 2017

This paper proposes a search method that explores parameters C and σ values of support vector machines (SVM) to improve performance while maintaining search accuracy. A traditional grid search method requires tremendous computational times because it searches all available combinations of C and σ values to find optimal combinations which provide the best performance of SVM. To address this issue, this paper proposes a deep search method that reduces computational time. In the first stage, it divides C-σ- accurate metrics into four regions, searches a median value of each region, and then selects a point of the highest accurate value as a start point. In the second stage, the selected start points are re-divided into four regions, and then the highest accurate point is assigned as a new search point. In the third stage, after eight points near the search point. are explored and the highest accurate value is assigned as a new search point, corresponding points are divided into four parts and it calculates an accurate value. In the last stage, it is continued until an accurate metric value is the highest compared to the neighborhood point values. If it is not satisfied, it is repeated from the second stage with the input level value. Experimental results using normal and defect bearings show that the proposed deep search algorithm outperforms the conventional algorithms in terms of performance and search time.