• Journal of Communications and Networks
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• v.9 no.1
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• pp.75-83
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• 2007

Orthogonal frequency division multiplexing (OFDM) systems with multiple transmit antennas can exploit space-time block coding on each subchannel for reliable data transmission. Spacetime coded OFDM systems, however, are very sensitive to time variant channels because the channels need to be static over multiple OFDM symbol periods. In this paper, we propose to mitigate the channel variations in the frequency domain using a linear filter in the frequency domain that exploits the sparse structure of the system matrix in the frequency domain. Our approach has reduced complexity compared with alternative approaches based on time domain block-linear filters. Simulation results demonstrate that our proposed frequency domain block-linear filter reduces computational complexity by more than a factor of ten at the cost of small performance degradation, compared with a time domain block-linear filter.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.999-1000
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• 2006

The LDPC Code is focusing a powerful FEC(Forward Error Correction) codes for 4G Mobile Communication system. LDPC codes are used minimizing channel errors by modeling AWGN Channel as VDSL system. The performance of LDPC code is better than that of turbo code in long code word on iterative decoding algorithm. LDPC code are encoded by sparse parity check matrix. there are decoding algorithms for a LDPC code, Bit Flipping, Message passing, Sum-Product. Because LDPC Codes use low density parity bit, mathematical complexity is low and relating processing time becomes shorten.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04a
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• pp.130-132
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• 2003

계산 과학을 사용하는 응용 분야는 공학, 물리, 화학, 생명 과학에서 경제학까지 다양하다. 계산 과학에 사용되는 많은 알고리즘들은 행렬 연산을 포함하고 있으며 이 행렬은 크기가 크고 대부분의 원소가 0값을 갖는 희소 행렬일 경우가 많다. 본 논문에서는 희소 행렬의 연산 중, 희소 행렬 A와 밀집 벡터 x, y에 대하여 ylongleftarrowy＋Ax와 ylongleftarrowy＋$A^{T}$ Ax 의 두 가지 연산에 대한 계산 속도 개선 방법으로서 레지스터 재사용을 높이는 레지스터 블록화와 캐쉬 미스를 줄이기 위한 캐쉬 최적화 방법을 제안하며 또한 희소 행렬의 특성과 target 컴퓨터의 구조에 따라 정해지는 레지스터 블록 크기를 결정하는 방법을 설명한다. Preliminary결과로 이 방법을 Pentium III system상에서 실험한 결과를 보이는데 ylongleftarrowy＋Ax 의 연산에 대하여는 2.5 배, ylongleftarrowy＋$A^{T}$ Ax 의 연산에 대하여는 3.5 배까지의 성능 개선을 이룰 수 있다.

• Journal of Information Processing Systems
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• v.17 no.2
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• pp.352-368
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• 2021

Sign-in point of interest (POI) are extremely sparse in location-based social networks, hindering recommendation systems from capturing users' deep-level preferences. To solve this problem, we propose a content-aware POI recommendation algorithm based on a convolutional neural network. First, using convolutional neural networks to process comment text information, we model location POI and user latent factors. Subsequently, the objective function is constructed by fusing users' geographical information and obtaining the emotional category information. In addition, the objective function comprises matrix decomposition and maximisation of the probability objective function. Finally, we solve the objective function efficiently. The prediction rate and F1 value on the Instagram-NewYork dataset are 78.32% and 76.37%, respectively, and those on the Instagram-Chicago dataset are 85.16% and 83.29%, respectively. Comparative experiments show that the proposed method can obtain a higher precision rate than several other newer recommended methods.

• Journal of Advanced Information Technology and Convergence
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• v.9 no.1
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• pp.89-102
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• 2019

Collagen can be used in building artificial skin replacements for treatment of burns and towards the reconstruction of bone as well as researching cell behavior and cellular interaction. The strength of collagen in connective tissue rests on the characteristics of collagen fibers. 3D confocal imaging of collagen fibers enables the characterization of their spatial distribution as related to their function. However, the image stacks acquired with confocal laser-scanning microscope does not clearly show the collagen architecture in 3D. Therefore, we developed a new method to reconstruct, visualize and characterize collagen fibers from fluorescence confocal images. First, we exploit the tensor voting framework to extract sparse reliable information about collagen structure in a 3D image and therefore denoise and filter the acquired image stack. We then propose to segment the collagen fibers by defining an energy term based on the Hessian matrix. This energy term is minimized by a min cut-max flow algorithm that allows adaptive regularization. We demonstrate the efficacy of our methods by visualizing reconstructed collagen from specific 3D image stack.

• Environmental Engineering Research
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• v.15 no.2
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• pp.71-78
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• 2010

To understand the effects of acclimation schemes on the formation of anode biofilms, different electrical performances are characterized in this study, with the roles of suspended and attached bacteria in single-chamber microbial fuel cells (MFCs). The results show that the generation of current in single-chamber MFCs is significantly affected by the development of a biofilm matrix on the anode surface containing abundant immobilized microorganisms. The long-term operation with suspended microorganisms was demonstrated to form a dense biofilm matrix that was able to reduce the activation loss in MFCs. Also, a Pt-coated anode was not favorable for the initial or long-term bacterial attachment due to its high hydrophobicity (contact angle = $124^{\circ}$), which promotes easy detachment of the biofilm from the anode surface. Maximum power ($655.0\;mW/m^2$) was obtained at a current density of $3,358.8\;mA/m^2$ in the MFCs with longer acclimation periods. It was found that a dense biofilm was able to enhance the charge transfer rates due to the complex development of a biofilm matrix anchoring the electrochemically active microorganisms together on the anode surface. Among the major components of the extracellular polymeric substance, carbohydrates ($85.7\;mg/m^2_{anode}$) and proteins ($81.0\;mg/m^2_{anode}$) in the dense anode biofilm accounted for 17 and 19%, respectively, which are greater than those in the sparse anode biofilm.

• The Transactions of the Korea Information Processing Society
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• v.4 no.11
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• pp.2711-2720
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• 1997

Multitasking and microtasking on the CRAY machine provides still another way to improve computational power. Since CRAY-2 has 4 processors we can achieve speedup up to 4 properly designed algorithms. In this paper we present two parallelizations of linear system solution in the CRAY-2 with multitasking and microtasking library. One is the LU decomposition on the dense matrices and the other is the iterative solution of large sparse linear systems with the preconditioner proposed by Radicati di Brozolo. In the first case we realized a speedup of 1.3 with 2 processors for a matrix of dimension 600 with the multitasking and in the second case a speedup of around 3 with 4 processors for a matrix of dimension 600 with the multitasking and in the second case a speedup of around 3 with 4 processors for a matrix of dimension 8192 with the microtasking. In the first case the speedup is limited because of the nonuniform vector lenghts. In the second case the ILU(0) preconditioner with Radicati's technique seem to realize a reasonable high speedup with 4 processors.

• Journal of Internet Computing and Services
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• v.20 no.1
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• pp.1-10
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• 2019

Since big-data text mining extracts many features and data, clustering and classification can result in high computational complexity and low reliability of the analysis results. In particular, a term document matrix obtained through text mining represents term-document features, but produces a sparse matrix. We designed an advanced genetic algorithm (GA) to extract features in text mining for detection model. Term frequency inverse document frequency (TF-IDF) is used to reflect the document-term relationships in feature extraction. Through a repetitive process, a predetermined number of features are selected. And, we used the sparsity score to improve the performance of detection model. If a spam mail data set has the high sparsity, detection model have low performance and is difficult to search the optimization detection model. In addition, we find a low sparsity model that have also high TF-IDF score by using s(F) where the numerator in fitness function. We also verified its performance by applying the proposed algorithm to text classification. As a result, we have found that our algorithm shows higher performance (speed and accuracy) in attack mail classification.

• Journal of the Korean Operations Research and Management Science Society
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• v.21 no.3
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• pp.63-74
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• 1996

Ordering plays an important role in solving an LP problem with sparse matrix by the interior point method. Since ordering is NP-complete, we try to find an efficient method. The objective of this paper is to present an efficient heuristic ordering method for implementation of the minimum deficiency method. Both the ordering method and the data structure play important roles in implementation. First we define a new heuristic pseudo-deficiency ordering method and a data structure for the method-quotient graph and cliqued storage. Next we show an experimental result in terms of time and nonzero numbers by NETLIB problems.

• 한국지구물리탐사학회:학술대회논문집
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• 2003.11a
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• pp.402-409
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• 2003

Inversion of traveltime requires an efficient algorithm for computing the traveltime as well as its $Frech\hat{e}t$ derivative. We compute the traveltime of the head waves using the damped wave solution in the Laplace domain and then present a new algorithm for calculating the $Frech\hat{e}t$ derivative of the head wave traveltimes by exploiting the numerical structure of the finite element method, the modem sparse matrix technology, and SWEET algorithm developed recently. Then, we use a properly regularized steepest descent method to invert the traveltime of the Marmousi-2 model. Through our numerical tests, we will demonstrate that the refraction tomography with large aperture data can be used to construct the initial velocity model for the prestack depth migration.