• KEPCO Journal on Electric Power and Energy
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• v.8 no.2
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• pp.159-179
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• 2022

Often a network becomes complex, and multiple entities would get in charge of managing part of the whole network. An example is a utility grid. While the entire grid would go under a single utility company's responsibility, the network is often split into multiple subsections. Subsequently, each subsection would be given as the responsibility area to the corresponding sub-organization in the utility company. The issue of how to make subsystems of adequate size and minimum number of interconnections between subsystems becomes more critical, especially in real-time simulations. Because the computation capability limit of a single computation unit, regardless of whether it is a high-speed conventional CPU core or an FPGA computational engine, it comes with a maximum limit that can be completed within a given amount of execution time. The issue becomes worsened in real time simulation, in which the computation needs to be in precise synchronization with the real-world clock. When the subject of the computation allows for a longer execution time, i.e., a larger time step size, a larger portion of the network can be put on a computation unit. This translates into a larger margin of the difference between the worst and the best. In other words, even though the worst (or the largest) computational burden is orders of magnitude larger than the best (or the smallest) computational burden, all the necessary computation can still be completed within the given amount of time. However, the requirement of real-time makes the margin much smaller. In other words, the difference between the worst and the best should be as small as possible in order to ensure the even distribution of the computational load. Besides, data exchange/communication is essential in parallel computation, affecting the overall performance. However, the exchange of data takes time. Therefore, the corresponding consideration needs to be with the computational load distribution among multiple calculation units. If it turns out in a satisfactory way, such distribution will raise the possibility of completing the necessary computation in a given amount of time, which might come down in the level of microsecond order. This paper presents an effective way to split a given electrical network, according to multiple criteria, for the purpose of distributing the entire computational load into a set of even (or close to even) sized computational loads. Based on the proposed system splitting method, heavy computation burdens of large-scale electrical networks can be distributed to multiple calculation units, such as an RTDS real time simulator, achieving either more efficient usage of the calculation units, a reduction of the necessary size of the simulation time step, or both.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.4
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• pp.1024-1034
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• 1998

Most public cryptosystem widely used in communication network are based on the exponentiation-arithmetic. But, cryptosystem has to use bigger and bigger key parameter to attain an adequate level of security. This situation increases both computation and time delay. Montgomery, yang and Kawamura presented a method by using the pre-computation, intermediately computing and table look-up on modular reduction. Coster, Brickel and Lee persented also a method by using the pre-computation on exponentiation. This paper propose to reduce computation of exponentiation with spare prime. This method is to enhance computation efficiency in cryptosystem used discrete logarithms.

• Proceedings of the Acoustical Society of Korea Conference
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• 1998.06c
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• pp.155-158
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• 1998

IMBE(Improved Multi-Band Excitation) vocoders exhibit good performance at low data rates. The major drawback to IMBE coders is their large computational requirements. In this paper, thus, we propose a new pitch search method that preserves the quality of the IMBE vocoder with reduced complexity. The basic idea is to reduce computation complexity of the pitch searching by using the SAMDF. Applying the proposed method to the IMBE vocoder, we can get approximately 52.02% searching time reduction in the pitch search. There is no difference in voice quality between conventional IMBE and proposed IMBE.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.149-154
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• 2022

In recent years, the application of deep learning method to computer vision has shown to achieve great performances. Thus, many research projects have also applied deep learning technology to railroad defect detection. In this paper, we have reviewed the researches that applied computer vision based deep learning method to railroad defect detection and inspection, and have discussed the current trend and the direction of those researches. Many research projects were targeted to operate automatically without visual inspection of human and to work in real-time. Therefore, methods to speed up the computation were also investigated. The reduction of the number of learning parameters was considered important to improve computation efficiency. In addition to computation speed issue, the problem of annotation was also discussed in some research projects. To alleviate the problem of time consuming annotation, some kinds of automatic segmentation of the railroad defect or self-supervised methods have been suggested.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.05a
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• pp.1432-1436
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• 2006

Feasibility of optimizing Zwicker's loudness has been shown by using MSC/NASTRAN, SYSNOISE, and a semi-analytical design sensitivity by Wang and Kang. Design sensitivity analysis of Zwicker's loudness is developed by using ANSYS, COMET, and an adjoint variable method in order to reduce computation. A numerical example shows significant reduction of computation time for design sensitivity analysis.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.3
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• pp.563-568
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• 2007

We propose the computation reduction method of real root method that is used in the EVRC(Enhanced Variable Rate Codec) system. The real root method is that if polynomial equations have the real roots, we are able to find those and transform them into LSP. However, this method takes much time to compute, because the root searching is processed sequentially in frequency region. But, the important characteristic of LSP is that most of coefficients are occurred in specific frequency region. So, to reduce the computation time of real root, we used the met scale that is linear below 1kHz and logarithmic above. In order to compare real root method with proposed method, we measured the following two. First, we compared the position of transformed LSP(Line Spectrum Pairs) parameters in the proposed method with these of real root method. Second, we measured how long computation time is reduced. The experimental result is that the searching time was reduced by about 48% in average without the change of LSP parameters.

• Journal of Information Technology Applications and Management
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• v.22 no.3
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• pp.105-114
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• 2015

This paper presents a fast Time Difference of Arrival (TDOA) estimation for sound source localization. TDOA is the time difference between the arrival times of a signal at two sensors. We propose a partial cross correlation method to increase the speed of TDOA estimation for sound source localization. We do this by predicting which part of the cross correlation function contains the required TDOA value with the help of the signal energies, and then we compute the cross correlation function in that direction only. Experiments show approximately 50% reduction in the cross correlation computation time thereby increasing the speed of TDOA computation. This makes it very relevant for real world surveillance.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.639-642
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• 2005

Motion Estimation(ME) is an important part of video compression, because it requires a large amount of computation. Half-pixel and quarter-pixel motion estimation allows high video compression rates but it also has high computation complexity. In this paper we suggest a new and efficient motion estimation algorithm for half-pixel and quarter-pixel motion estimation using SAD values. In the method, an integer-pixel motion vector is found and then only three neighboring points of the integer-pixel motion vector is evaluated to find the half-pixel motion vector. The quarter-pixel motion vector is also found by using a similar method. Experimental results of our method shows 20% reduction in computation time, when compared with those of a conventional method, while producing same quality motion vectors.

• MALSORI
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• no.51
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• pp.71-84
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• 2004

In this paper, we propose the automatic speech database verification method(or called automatic verification) based on confidence measure for a large speech database. This method verifies the consistency between given transcription and speech using the confidence measure. The automatic verification process consists of two stages : the word-level likelihood computation stage and multi-level likelihood ratio computation stage. In the word-level likelihood computation stage, we calculate the word-level likelihood using the viterbi decoding algorithm and make the segment information. In the multi-level likelihood ratio computation stage, we calculate the word-level and the phone-level likelihood ratio based on confidence measure with anti-phone model. By automatic verification, we have achieved about 61% error reduction. And also we can reduce the verification time from 1 month in manual to 1-2 days in automatic.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.10
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• pp.791-798
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• 2018

The CFAR algorithm is mainly used for target detection in radar systems. In particular, OS CFAR is used in a non-uniform noise environment. However, it requires a large amount of computation, because it should sort reference cells in ascending order. This makes it difficult to apply the radar system in real time. In this paper, we describe how to reduce the computational burden of OS CFAR. We compared the power of the test cell and reference cell to determine only the presence or absence of target detection. The common reference cells overlapping in the reference cells of the three test cells are obtained. We first compare the test cell with the highest power value among the three test cells to the common reference cells. Next, we compare each test cell to general reference cells, excluding the common reference cells. The computation time is shortened by reducing the power comparison computation amounts.