• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.2
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• pp.95-107
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• 2014

In general, topographical phenomena are represented graphically by data in the spatial domain, while attributes of the non-spatial domain are expressed by alpha-numeric texts. GIS functions for analysis of attributes in the non-spatial domain remain quite simple, such as search methods and simple statistical analysis. Recently, graph modeling and network analysis of social phenomena are commonly used for understanding various social events and phenomena. In this study, we applied the network analysis functions to the non-spatial domain data of GIS to enhance the overall spatial analysis. For this purpose, a novel design was presented to integrate the spatial database and the graph database, and this design was then implemented into a WebGIS system for better decision makings. The developed WebGIS with underlying synchronized databases, was tested in a simulated application about the selection of water supply households during an epidemic of the foot-and-mouse disease. The results of this test indicate that the developed WebGIS can contribute to improved decisions by taking into account the social proximity factors as well as geospatial factors.

• Journal of the Korean Institute of Navigation
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• v.20 no.1
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• pp.81-85
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• 1996

The defects occurred in knitted fabrics have several types due to some trouble sources. In particular, the defects caused by knitting machine troubles give a serious damage to the whole webs. It is, therefore, necessary to discriminate the kind of defects. The method to discriminate the type and size of defects has been proposed, which is used a pair of narrow band eliminating spatial filters. This method is based upon an isotropic signal processing in time domain. This paper is to confirm that the proposed method can be useful in the discrimination of defects, having analyzed in spatial frequency domain.

• The Pure and Applied Mathematics
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• v.9 no.1
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• pp.31-37
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• 2002

In this paper, we find explicitly the eigenvalues and the eigenfunctions of Laplace operator on a triangle domain with a mixed boundary condition. We also show that a weaker form of the principle of spatial averaging holds for this domain under suitable boundary condition.

• Journal of KIISE
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• v.42 no.2
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• pp.162-168
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• 2015

Image data is mostly stored in compressed form because of its huge size. Therefore, a series of cumbersome procedures is required to apply a transformation to image data: decompression, extraction of spatial data, transformation and recompression. In this paper, we employ DCT(Discrete Cosine Transform) coefficients to change the spatial presentation of images. DCT is commonly used in still image compression standards such as JPEG and moving picture compression standards such as MPEG-2, MPEG-4, and H.264. In this paper, we derived mathematically the relationship between the geometry transformation in the spatial domain and coefficient changes in the DCT domain and verified it with images in the JPEG file format. Because of the efficiency of transformation in the frequency domain, our findings can be utilized for light-weight partial image encryption for privacy data protection or entertainment contents protection.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5481-5495
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• 2018

Single pixel imaging technology has developed for years, however the video acquisition on the single pixel camera is not a well-studied problem in computer vision. This work proposes a new scheme for single pixel camera to acquire video data and a new regularization for robust signal recovery algorithm. The method establishes a single pixel video compressive sensing scheme to reconstruct the video clips in spatial domain by recovering the difference of the consecutive frames. Different from traditional data acquisition method works in transform domain, the proposed scheme reconstructs the video frames directly in spatial domain. At the same time, a new regularization called spatial cluster is introduced to improve the performance of signal reconstruction. The regularization derives from the observation that the nonzero coefficients often tend to be clustered in the difference of the consecutive video frames. We implement an experiment platform to illustrate the effectiveness of the proposed algorithm. Numerous experiments show the well performance of video acquisition and frame reconstruction on single pixel camera.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.729-732
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• 2005

This paper describes a time-spatial domain model for simulating raw data acquisition of space-borne SAR system. The position, velocity and attitude information of the platform at a certain time instance is used for deriving sensor-target model. Ground target is modelled by a set of point scatters with reflectivity and two-dimensional ground coordinates. The signal received by SAR is calculated for each slow and fast time instance by integrating the reflectivity and phase values from all target point scatters. Different from frequency domain simulation algorithms, the proposed time domain algorithm can provide fully physical modelling of SAR raw data simulation without any assumptions or approximations.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.17 no.8
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• pp.693-700
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• 2007

We can predict spatial acoustic pressure distribution on the plane of interest by using acoustic holography. However, the information embedded in the distribution plot is usually much more than what we need: for example, source locations and their overall propagation pattern. One possible candidate to solve the problem is complex envelope analysis. Complex envelope analysis extracts slowly-varying envelope signal from a band signal. We have attempted to extend this method to space domain so that we can have spatial information that we need. We have to modulate two dimensional data for obtaining spatial envelope. Although spatial modulation basically follows the same concept that is used in time domain, the algorithm for the spatial modulation turns out to be different from temporal modulation. We briefly describe temporal complex envelope analysis and extend it to spatial envelope of 2-D acoustic field by introducing geometric transformation. In the end, the results of applying the spatial envelope to the holography are envisaged and verified.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.1
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• pp.20-25
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• 2008

Acoustic holography exhibits the spatial distribution of sound pressure in time or frequency domain. The obtained picture often contains far more than what we need in practice. For example. when we need to know only the locations and overall propagation pattern of sound sources. a method to show only what we need has to be introduced. One way of obtaining the necessary information is to use envelope in space. The spatial envelope is a spatially slowly-varying amplitude of acoustic waves which contains the information of sources' location. A spatial modulation method has been theoretically developed to get a spatial envelope. By applying the spatial envelope. not only the necessary information is obtained but also computation time is reduced during the process of holography. The spatial envelope is verified as an effective visualization scheme in time domain by being applied to complicated sound fields.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2783-2785
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• 2003

In multi-dimensional magnetic resonance imaging, data is obtained in the spatial frequency domain. Since the signal variation in the spatial frequency domain is much larger than that in the spatial domain, analog-to-digital converts with wide conversion bits are required. In this paper, the quantization noise in magnetic resonance imaging is analyzed. The signal-to-quantization noise ratio(SQNR) in the reconstructed image is derived from the level of quantization in the data acquisition. Since the quantization noise is proportional to the signal amplitude, it becomes more dominant in high field imaging. Using the derived formula the SQNR for several MRI systems are evaluated, and it is shown that the quantization noise can be a limiting factor in high field imaging, especially in three dimensional imaging in magnetic resonance imaging.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.565-568
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• 1998

In this paper, we propose a new method for multispectral image compression that is based on highly correlated relational properly taken from a spatial image and its wavelet transform. The highly active regions, such as edges or contour, in the spatial domain are appeared as significant coefficients in the wavelet transform domain; and the low active regions like background as insignificant. These characteristics play an important role in designing the system. The simulation results have shown us that the proposed method has better performance in terms of the reconstructed image quality and the transmitted bit rakes. Practically, our system can be successfully applied to the application areas that require of progressive transmission. For some multispectral images with relatively low activity, we have obtained the more good results.