• Proceedings of the Korean Magnetic Resonance Society Conference
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• 2001.02a
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• pp.15-15
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• 2001

• Journal of the Korean Society of Industry Convergence
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• v.4 no.1
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• pp.87-94
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• 2001

In multibody dynamics, differential and algebraic equations which can satisfy both equation of motion and kinematic constraint equation should be solved. To solve this equation, coordinate partitioning method and constraint stabilization method are commonly used. The coordinate partitioning method divides the coordinate into independent and dependent coordinates. The most typical coordinate partitioning method arc LU decomposition, QR decomposition, projection method and SVD(sigular value decomposition).The objective of this research is to find a efficient coordinate partitioning method in flexible multibody systems and a hybrid decomposition algorithm which employs both LU and projection methods is proposed. The accuracy of the solution algorithm is checked with a slider-crank mechanism.

• ETRI Journal
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• v.34 no.5
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• pp.684-689
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• 2012

A mode-singular-value-decomposition (SVD) maximum likelihood (ML) estimation procedure is proposed for the source localization problem under an additive measurement error model. In a practical situation, the noise variance is usually unknown. In this paper, we propose an algorithm that does not require the noise covariance matrix as a priori knowledge. In the proposed method, the weight is derived by the inverse of the noise magnitude square in the ML criterion. The performance of the proposed method outperforms that of the existing methods and approximates the Taylor-series ML and Cram$\acute{e}$r-Rao lower bound.

• Journal of computational fluids engineering
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• v.22 no.1
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• pp.59-66
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• 2017

The guideline of selecting the number of snapshot dataset, $N_s$ in proper orthogonal decomposition(POD) was presented via the analysis of Eigen values based on the singular value decomposition(SVD). In POD, snapshot datasets from the solutions of Euler or Navier-Stokes equations are utilized to SVD and a reduced order model(ROM) is constructed as the combination of Eigen vectors. The ROM is subsequently applied to reconstruct the flowfield data with new set of flow conditions, thereby enhancing the computational efficiency. The overall computational efficiency and accuracy of POD is dependent on the number of snapshot dataset; however, there is no reliable guideline of determining $N_s$. In order to resolve this problem, the order of maximum to minimum Eigen value ratio, O(R) from SVD was analyzed and presented for the decision of $N_s$; in case of steady flow, $N_s$ should be determined to make O(R) be $10^9$. For unsteady flow, $N_s$ should be increased to make O(R) be $10^{11\sim12}$. This strategy of selecting the snapshot dataset was applied to two dimensional NACA0012 airfoil and vortex flow problems including steady and unsteady cases and the numerical accuracies according to $N_s$ and O(R) were discussed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.5
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• pp.1807-1824
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• 2015

As the technologies advance, mobile peer-to-peer (MP2P) networks or systems become one of the major ways to share resources and information. On such a system, the information retrieval (IR), including the development of scalable infrastructures for indexing, becomes more complicated due to a huge increase on the amount of information and rapid information change. To keep the systems on MP2P networks more reliable and consistent, the index structures need to be updated frequently. For a semantic IR system, the index structure is even more complicated than a classic IR system and generally has higher update cost. The most well-known indexing technique used in semantic IR systems is Latent Semantic Indexing (LSI), of which the index structure is generated by singular value decomposition (SVD). Although LSI performs well, updating the index structure is not easy and time consuming. In an MP2P environment, which is fully distributed and dynamic, the update becomes more challenging. In this work, we consider how to update the sematic index generated by LSI and keep the index consistent in the whole MP2P network. The proposed Concept Space Update (CSU) protocol, based on distributed 2-Phase locking strategy, can effectively achieve the objectives in terms of two measurements: coverage speed and update cost. Using the proposed effective synchronization mechanism with the efficient updates on the SVD, re-computing the whole index on the P2P overlay can be avoided and the consistency can be achieved. Simulated experiments are also performed to validate our analysis on the proposed CSU protocol. The experimental results indicate that CSU is effective on updating the concept space with LSI/SVD index structure in MP2P semantic IR systems.

• Journal of Biomedical Engineering Research
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• v.25 no.6
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• pp.589-598
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• 2004

We propose a new algorithm to extract the fetal electrocardiogram (FECG) from a multi-channel electrocardiogram (ECG) recorded at the chest and abdomen of a pregnant woman. To extract the FECG from the composite abdominal ECG, the classical time-domain method based on singular value decomposition (SVD) has been generally used. However, this method has some disadvantages, such as its high degree of computational complexity and the necessary assumption that vectors between the FECG and the maternal electrocardiogram (MECG) should be orthogonal. The proposed algorithm, which uses SVD in a discrete cosine transform (DCT) domain, compensates for these disadvantages. To perform SVD with lower computational complexity, DCT coefficients corresponding to high-frequency components were eliminated on the basis of the properties of the DCT coefficients and the frequency characteristics of the FECG. Moreover, to extract the pure FECG with little influence of the direction of the vectors between the FECG and MECG, three new channels were made out of the MECG suppressed in the composite abdominal ECG, and the new channels were appended to the original multi-channel ECG. The performance of the proposed algorithm and the classical time-domain method based on SVD were compared using simulated and real data. It was experimentally verified that the proposed algorithm can extract the pure FECG with reduced computational complexity.

• Journal of the Korea Society of Computer and Information
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• v.26 no.6
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• pp.19-28
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• 2021

Nowadays, interest in health care is increasing due to Coronavirus (COVID-19), and a lot of people are doing home training as there are more difficulties in using fitness centers and public facilities that are used together. In this paper, we propose a personalized exercise recommendation algorithm using personalized propensity information to provide more accurate and meaningful exercise recommendation to home training users. Thus, we classify the data according to the criteria for obesity with a k-nearest neighbor algorithm using personal information that can represent individuals, such as eating habits information and physical conditions. Furthermore, we differentiate the exercise dataset by the level of exercise activities. Based on the neighborhood information of each dataset, we provide personalized exercise recommendations to users through a dimensionality reduction algorithm (SVD) among model-based collaborative filtering methods. Therefore, we can solve the problem of data sparsity and scalability of memory-based collaborative filtering recommendation techniques and we verify the accuracy and performance of the proposed algorithms.

• Bulletin of the Korean Chemical Society
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• v.24 no.7
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• pp.967-970
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• 2003

A new modified singular value decomposition method, piecewise polynomial truncated SVD (PPTSVD), which was originally developed to identify discontinuity of the earth's radial density function, has been used for large solvent peak suppression and noise elimination in nuclear magnetic resonance (NMR) signal processing. PPTSVD consists of two algorithms of truncated SVD (TSVD) and L₁ problems. In TSVD, some unwanted large solvent peaks and noise are suppressed with a certain soft threshold value, whereas signal and noise in raw data are resolved and eliminated in L₁ problems. These two algorithms were systematically programmed to produce high quality of NMR spectra, including a better solvent peak suppression with good spectral line shapes and better noise suppression with a higher signal to noise ratio value up to 27% spectral enhancement, which is applicable to multidimensional NMR data processing.

• Geophysics and Geophysical Exploration
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• v.22 no.4
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• pp.177-185
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• 2019

Ground roll is a surface wave which is usually observed in the land seismic data. It is one of the typical coherent noise. During the reflection data processing, ground roll is removed because it is considered as noise. This removal process often causes the loss of reflection signals if the ground roll overlaps reflection signals. In this study, we look over Karhunen-Loeve Transform (KLT) and analyze its effects to suppress the ground roll appropriately while reducing the reflection loss. Numerical tests in homogeneous elastic media show that the ground roll has been properly rejected. However, the field data application reveals that there is no significant suppression of ground roll when compared to band-pass filtering. This can be considered that it is hard to calculate horizontally aligned gathers in the field data because the ground roll contains a wide range of frequency bands. On the contrary, the result of singular value decomposition (SVD) filtering shows that the ground roll has been significantly reduced. It is thought that the SVD filtering performs better in the ground roll suppression than KLT because it is easy to calculate the horizontally aligned gathers in the SVD filtering.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.143-148
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• 2013

This paper study about multi-beam for ditection of arrival estimation in wireless system. estimate a direction of arrival of target in multi input-output array antennas system. Beam steering method are divided by beam steering method of elevation angle or beam forming method, stack beam steering, frequency steering, phase steering radar and digital beam forming radar. Proposed algorithm is combined SVD method and antenna weight error compensation method with phase and amplitude compensation to effectivity beam steering. Through simulation, we were analysis of performance that general algorithm and proposed target estimation algorithm in this paper. It was proved to improved proposal algorithm than general algorithm in target direction of arrival estimation.