• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2010.10a
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• pp.543-543
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• 2010

The objective of this research is estimating the location of interested sound source by using the similarity between a beamformer output in time domain and the candidate signal. The waveform of beamformer output at the location of sound source is similar with the waveform emitted by that source. To estimate the location of sound source by using this feature, we define quantified similarity between candidate signal and beamformer output. The candidate signal describes the signal which is generated by interested source. In this paper, similarity is defined by four methods. The two methods use time vector comparison, and the other two methods use time-frequency map or linear prediction coefficients. To figure out the results and performance of localization by using similarities, we demonstrate two conditions. The one is when two pure tone sources exist and the other condition is when several bird sounds exist. As a consequence, inner product with two time-vectors and structural similarity with spectrograms can estimate the locations of interest sound source.

• Journal of the Korea Institute of Military Science and Technology
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• v.1 no.1
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• pp.128-144
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• 1998

The BEM for linear elastic stress analysis is applied to the highly rotating axisymmetric body problem which also involves the thermoelastic effects due to steady-state thermal conduction. The axisymmetric BEM formulation is briefly summarized and an alternative approach for transforming the volume integrals associated with such body force kernels into equivalent boundary integrals is described in a way of using the concept of inner product and vector identity. A discretization scheme for higher order BE is outlined for numerical treatment of the resulting boundary integral equations, and it is consequently illustrated by determining the stress distributions of the turbine rotor disk of the small turbojet engine(ADD 500) for which a FEM stress solution has been furnished by author.

• Journal of the Korea Society of Computer and Information
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• v.11 no.6 s.44
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• pp.269-277
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• 2006

We propose a new expert system for recovering the broken fragments of relics into an original form using computer graphics and image processing. This paper presents a system with an application to tombstones objects of flat plane with letters carved in for assembling the fragments by placing their respective fragments in the right position. The matching process contains three sub-processes: aligning the front and letters of an object, identifying the matching directions, and determining the detailed matching positions. We apply least squares fitting, vector inner product, and geometric and RGB errors to the matching process. It turned out that 2-D translations via fragments-alignment enable us to save the computational load significantly. Based on experimental results from the damaged cultural fragments, the performance of the proposed method is illustrated.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.11
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• pp.73-82
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• 2014

The LM algorithm is used in solving the least square problem in a non linear system, and is used in various fields. However, in cases the applied field's target functionis complicated and high-dimensional, it takes a lot of time solving the inner matrix and vector operations. In such cases, the LM algorithm is unsuitable in embedded environment and requires a hardware accelerator. In this paper, we implemented the LM algorithm in hardware. In the implementation, we used pipeline stages to divide the target function operation, and reduced the period of data input of the matrix and vector operations in order to accelerate the speed. To measure the performance of the implemented hardware, we applied the refining fundamental matrix(RFM), which is a part of 3D reconstruction application. As a result, the implemented system showed similar performance compared to software, and the execution speed increased in a product of 74.3.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1867-1870
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• 2005

The celestial navigation is one of alternatives to GPS system and can be used as a backup of GPS. In the celestial navigation system using more than two star trackers, the vehicle's ground position can be solved based on the star trackers' attitude information if the vehicle's local vertical or horizontal angle is given. In order to determine accurate ground position of flight vehicle, the high accurate local vertical angle measurement is one of the most important factors for navigation performance. In this paper, the Earth geophysical deflection was analyzed in the assumption of using the modern electrolyte tilt sensor as a local vertical sensor for celestial navigation system. According to the tilt sensor principle, the sensor measures the tilt angle from gravity direction which depends on the Earth geoid surface at a given position. In order to determine the local vertical angle from tilt sensor measurement, the relationship between the direction of gravity and the direction of the Earth center should be analyzed. Using a precision orbit determination software which includes the JGM-3 Earth geoid model, the direction of the Earth center and the direction of gravity are extracted and analyzed. Appling vector inner product and cross product to the both extracted vectors, the magnitude and phase of deflection angle between the direction of gravity and the direction of the Earth center are achieved successfully. And the result shows that the angle differences vary as a function of latitude and altitude. The maximum 0.094$^{circ}$angle difference occurs at 45$^{circ}$latitude in case of 1000 Km altitude condition.

• Journal of Cadastre & Land InformatiX
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• v.46 no.2
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• pp.239-251
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• 2016

Hyperspectral image is widely used for land cover classification because it has a number of narrow bands and allow each pixel to include much more information in comparison with previous multi-spectral image. However, Higher spectral resolution of hyperspectral image results in an increase in data volumes and a decrease in noise efficiency. SAM(Spectral Angle Mapping), a method based on vector inner product to compare spectrum distribution, is a highly valuable and popular way to analyze continuous spectrum of hyperspectral image. SAM is shown to be less accurate when it is used to analyze hyperspectral image for land cover classification using spectral library. this inaccuracy is due to the effects of atmosphere. We suggest a decision tree based method to compensate the defect and show that the method improved accuracy of land cover classification.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.5
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• pp.375-381
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• 2007

A novel method to register images onto 3D data, such as 3D point cloud, 3D vectors, and 3D surfaces, is proposed. The proposed method estimates the exterior orientation of a camera with respective to the 3D data though fitting pairs of the normal vectors of two planes passing a focal point and 2D and 3D lines extracted from an image and the 3D data, respectively. The fitting condition is that the angle between each pair of the normal vectors has to be zero. This condition can be represented as a numerical formula using the inner product of the normal vectors. This paper demonstrates the proposed method can estimate the exterior orientation for the image registration as simulation tests.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.15 no.1
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• pp.58-70
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• 1990

This paper describes a VLSI implementation of real-time two dimensional DCT processor for the subprimary rate video codec system. The proposed architecture exploits the parallelism and concurrency of the distributes architecture for vector inner product operation of DCT and meets the CCITT performance requirements of video codec for full CSIF 30 frames/sec. It is also shown that this architecture satisfies all the CCITT IDCT accuracy specification by simulating the suggested architecture in bit level. The efficient VLSI disign methodology to design suggested architecture is considered and the module generator oriented design environments are constructed based on SUN 3/150C workstation. Using the constructed design environments. the suggensted architecture have been designed by double metal 2micron CMOS technology. The chip area fo designed 8x8 2-D DA-DCT (Distributed Arithmetic DCT) processor is about 3.9mmx4.8mm.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.40 no.9
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• pp.597-604
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• 2016

A parallel algorithm of bi-conjugate gradient method was developed based on CUDA for parallel computation of the incompressible Navier-Stokes equations. The governing equations were discretized using splitting P2P1 finite element method. Asymmetric stenotic flow problem was solved to validate the proposed algorithm, and then the parallel performance of the GPU was examined by measuring the elapsed times. Further, the GPU performance for sparse matrix-vector multiplication was also investigated with a matrix of fluid-structure interaction problem. A kernel was generated to simultaneously compute the inner product of each row of sparse matrix and a vector. In addition, the kernel was optimized to improve the performance by using both parallel reduction and memory coalescing. In the kernel construction, the effect of warp on the parallel performance of the present CUDA was also examined. The present GPU computation was more than 7 times faster than the single CPU by double precision.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.5
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• pp.409-416
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• 2017

In this paper, we consider a framework of compressed sensing over finite fields. One measurement sample is obtained by an inner product of a row of a sensing matrix and a sparse signal vector. A recovery algorithm proposed in this study for sparse signals based probabilistic decoding is used to find a solution of compressed sensing. Until now compressed sensing theory has dealt with real-valued or complex-valued systems, but for the processing of the original real or complex signals, the loss of the information occurs from the discretization. The motivation of this work can be found in efforts to solve inverse problems for discrete signals. The framework proposed in this paper uses a parity-check matrix of low-density parity-check (LDPC) codes developed in coding theory as a sensing matrix. We develop a stochastic algorithm to reconstruct sparse signals over finite field. Unlike LDPC decoding, which is published in existing coding theory, we design an iterative algorithm using probability distribution of sparse signals. Through the proposed recovery algorithm, we achieve better reconstruction performance as the size of finite fields increases. Since the sensing matrix of compressed sensing shows good performance even in the low density matrix such as the parity-check matrix, it is expected to be actively used in applications considering discrete signals.