• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.459-462
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• 2003

Selectivity estimation of queries not only provides useful information to the query processing optimization but also may give users with a preview of processing results. In this paper, we investigate the problem of selectivity estimation in the context of a spatial dataset. Although several techniques have been proposed in the literature to estimate spatial query result sizes, most of those techniques still have some drawback in the case that a large amount of memory is required to retain accurate selectivity. To eliminate the drawback of estimation techniques in previous works, we propose a new method called MW Histogram. Our method is based on two techniques: (a) MinSkew partitioning algorithm that processes skewed spatial datasets efficiently (b) Wavelet transformation which compression effect is proven. We evaluate our method via real datasets. With the experimental result, we prove that the MW Histogram has the ability of providing estimates with low relative error and retaining the similar estimates even if memory space is small.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.5
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• pp.349-356
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• 2017

In this study, we propose a method to investigate topographic characteristics by applying machine learning which is an artificial intelligence analysis method based on the spatial data constructed using UAV and the training data created through spatial analysis. This method provides an alternative to the subjective judgment and accuracy of spatial data, which is a problem of existing topographic characteristics survey for officially assessed land price. The analysis method of this study is expected to improve the problems of topographic characteristics survey method of existing field researchers and contribute to more accurate decision of officially assessed land price by providing more objective land survey method.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.11a
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• pp.23-29
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• 2003

Detection in remotely sensed images can be conducted spatially, spectrally or both [2]. If the images have high spatial resolution, materials can be detected by using spatial and spectral information, unless we can't see the object embedded in a pixel. In this paper, we intend to solve the limit of spatial resolution by using the hyperspectral image which has high spectral resolution. Therefore, the Linear Spectral Mixing(LSM) Model which is sub-pixel detection algorithm is used to solve this problem. To find class Endmembers, we applied Geometric Model with MNF(Minimum Noise Fraction) transformation. From the result of sub-pixel detection algorithm, we can see the detection of water is satisfied and the object shape cannot be extracted but the possibility of material existence can be identified.

• Journal of Computing Science and Engineering
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• v.8 no.2
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• pp.65-77
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• 2014

To address the problem of multi-target retrieval (MTR) of remote sensing images, this study proposes a new object-level feature representation model. The model provides an enhanced application image representation that improves the efficiency of MTR. Generating the model in our scheme includes processes, such as object-oriented image segmentation, feature parameter calculation, and symbolic image database construction. The proposed model uses the spatial representation method of the extended nine-direction lower-triangular (9DLT) matrix to combine spatial relationships among objects, and organizes the image features according to MPEG-7 standards. A similarity metric method is proposed that improves the precision of similarity retrieval. Our method provides a trade-off strategy that supports flexible matching on the target features, or the spatial relationship between the query target and the image database. We implement this retrieval framework on a dataset of remote sensing images. Experimental results show that the proposed model achieves competitive and high-retrieval precision.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.11a
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• pp.320-322
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• 2002

A new simple spatial scheme for base station with adaptive antenna in Code Division Multiplexing Access (CDMA) systems is presented. In the proposed scheme, by applying the new spatial structure lot the receiver, the system can debate the problem of which the number of users exceeds the number of adaptive antenna elements existing in the conventional spatial scheme. An adaptive algorithm based on the Mean Square Error (MSE) criterion is also derived to update the weight matrix of the proposed scheme. The results of the system capacity enhancement can be achieved by using the proposed approach. Numerical simulations are included fer illustration and verification.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.4
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• pp.955-959
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• 2004

Existing Clustering Methods for spatial data mining process only Point objects, not spatial objects with polygonometry such as lines and areas. It is because that distance computation between objects with polygonometry for clustering is more complex than distance computation between point objects. To solve this problem, we design a clustering method based on regular grid cell structures. In details, it reduces cost and time for distance computation using cell relationships in grid cell structures.

• East Asian mathematical journal
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• v.39 no.4
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• pp.479-492
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• 2023

Although Euclidean plane geometry is implemented in the middle school course, there are three major problems in high school space geometry that can be intuitively taken for granted or misinterpreted as circular arguments. In order to solve this problem, this study proved three major problems using sets, Euclidean plane geometry, and parallel line postulates. This corresponds to a logical sequence and has mathematical and mathematical educational values. Furthermore, it will be possible to configure spatial geometry using sets, and by giving legitimacy to non-Euclidean spatial geometry, it will open the possibility of future research.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.4
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• pp.255-262
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• 2018

In order to determine the three-dimensional position in photogrammetry, a spatial resection is a pre-requisite step to determine exterior orientation parameters. The existing spatial resection method is a non-linear equation that requires initial values of exterior orientation parameters and has a problem that a gimbal lock phenomenon may occur. On the other hand, the spatial resection using quaternion is a closed form solution that does not require initial values of EOP (Exterior Orientation Parameters) and is a method that can eliminate the problem of gimbal lock. In this study, to analyze the stability of the quaternion-based spatial resection, the exterior orientation parameters were determined according to the different layout of control points and were compared with the determined values using existing non-linear equation. As a result, it can be seen that the quaternionbased spatial resection is affected by the layout of the control points. Therefore, if the initial value of exterior orientation parameters could not be obtained, it would be more effective to estimate the initial exterior orientation values using the quaternion-based spatial resection and apply it to the collinearity equation-based spatial resection method.

• Journal of Broadcast Engineering
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• v.20 no.6
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• pp.837-847
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• 2015

In this paper, the reception performance of spatial modulation multiple-output multiple-input (MIMO) is analyzed for high speed terrestrial broadcasting. The MIMO scheme is required to reduce the inter symbol interference (ISI) and spatial correlation. The spatial modulation scheme solves the problem of ISI, but the spatial correlation degrades the reception performance of SM scheme. The space-time block coded spatial modulation (STBC-SM) is combined the SM system with space-time block code (STBC) for reducing the effects of the spatial correlation. However, the STBC-SM scheme degrades the spectral efficiency by transmitting same data in the two symbol period. The double space-time transmit diversity with spatial modulation (DSTTD-SM) scheme transmits the data with full antenna combination. To adapt these SM MIMO systems into the terrestrial broadcasting system, the reception performance is analyzed using computer simulation in SUI channel environments.

• Journal of KIISE:Databases
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• v.32 no.5
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• pp.536-546
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• 2005

In this paper, we focus on the filtering step of candidate objects for spatial join operations on the input tables that none of the inputs is indexed. Over the last decade, several spatial Join algorithms for the input tables with index have been extensively studied. Those algorithms show excellent performance over most spatial data, while little research on solving the performance degradation in the presence of skewed data has been attempted. Therefore, we propose a spatial hash strip join(SHSJ) algorithm that can refine the problem of skewed data in the conventional spatial hash Join(SHJ) algorithm. The basic idea is similar to the conventional SHJ algorithm, but the differences are that bucket capacities are not limited while allocating data into buckets and SSSJ algorithm is applied to bucket join operations. Finally, as a result of experiment using Tiger/line data set, the performance of the spatial hash strip join operation was improved over existing SHJ algorithm and SSSJ algorithm.