• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.2
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• pp.59-75
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• 2004

Recommendation is a personalized information filtering technology to help customers find which products they would like to purchase. Collaborative filtering works by matching customer preferences to other customers in making recommendations. But collaborative filtering based recommendations have two major limitations, sparsity and scalability. To overcome these problems we suggest using adjusted product hierarchy, grain. This methodology focuses on dimensionality reduction and uses a marketer's specific knowledge or experience to improve recommendation quality. The qualify of recommendations using each grain is compared with others by several experimentations. Experiments present that the usage of a grain holds the promise of allowing CF-based recommendations to scale to large data sets and at the same time produces better recommendations. In addition. our methodology is proved to save the computation time by 3∼4 times compared with collaborative filtering.

• KIEE International Transaction on Systems and Control
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• v.12D no.1
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• pp.33-38
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• 2002

In this paper, the infinite time optimal regulation problem for weakly coupled bilinear systems with quadratic performance criteria is obtained by a sequence of algebraic Lyapunov equations. This is the new approach is based on the successive approximation. In particular, the order reduction is achieved by using suitable state transformation so that the original Lyapunov equations are decomposed into the reduced-order local Lyapunov equations. The proposed algorithms not only solve optimal control problems in the weakly coupled bilinear system but also reduce the computation time. This paper also includes an example to demonstrate the procedures.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.1999-2001
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• 2001

The infinite time optimum to regulate the problem of weakly coupled bilinear systems with a quadratic performance criterion is obtained by a sequence of algebraic Lyapunov equations. The new approach is based on the successive approximations. In particular, the order reduction is achieved by using suitable state transformation so that the original Lyapunov equations are decomposed into the reduced-order local Lyapunov equations. The proposed algorithms not only solve optimal control problems in the weakly coupled bilinear system but also reduce the computation time. This paper also includes an example to demonstrate the procedures.

• Journal of Korean Institute of Industrial Engineers
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• v.18 no.1
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• pp.63-80
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• 1992

The concept of rapid prototyping intended for a significant reduction in cost and lead time becomes even more practical with the recent development of various equipments to make the concept concrete. For the purpose of real application of commercially available SLA(stereolithography apparatus), this paper is intended to develop the standard conversion procedure from CAD data to the input data for SLA. While the procedure presented in this paper is based on CAD system "CATIA" and SLA of 3D systems, Inc., which are being used in authors' company DAEWOO Motor Co., Ltd., the basic concept of this paper can be applied to any other CAD systems and machines of using stereolithography process. The algorithm presented in this paper is classified into two stages-node sampling and triangulation. First of all, point data are sampled through the node sampling procedure, and then these are triangulated so that the input data for SLA operation is finally generated. The suggested method is devised in a way to meet the input requirements of SLA and more importantly consume less computation time and generate less number of input data for SLA.

• Journal of Korea Society of Digital Industry and Information Management
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• v.18 no.1
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• pp.1-9
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• 2022

Galois field arithmetic is important in error correcting codes and public-key cryptography schemes. Hardware realization of these schemes requires an efficient implementation of Galois field arithmetic operations. Multiplication is the main finite field operation and designing efficient multiplier can clearly affect the performance of compute-intensive applications. Diverse algorithms and hardware architectures are presented in the literature for hardware realization of Galois field multiplication to acquire a reduction in time and area. This paper presents a low complexity semi-systolic multiplier to facilitate parallel processing by partitioning Montgomery modular multiplication (MMM) into two independent and identical units and two-level systolic computation scheme. Analytical results indicate that the proposed multiplier achieves lower area-time (AT) complexity compared to related multipliers. Moreover, the proposed method has regularity, concurrency, and modularity, and thus is well suited for VLSI implementation. It can be applied as a core circuit for multiplication and division/exponentiation.

• Wind and Structures
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• v.22 no.3
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• pp.349-368
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• 2016

A preconditioning technique is presented for a simultaneous solution to wind-membrane interaction. In the simultaneous equations, a linear elastic model was employed to deal with the fluid-structure data transfer at the interface. A Lagrange multiplier was introduced to impose the specified boundary conditions at the interface and strongly coupled simultaneous equations are derived after space and time discretization. An initial linear elastic model preconditioner and modified one were derived by treating the linearized elastic model equation as a saddle point problem, respectively. Accordingly, initial and modified fluid-structure interaction (FSI) preconditioner for the simultaneous equations were derived based on the initial and modified linear elastic model preconditioners, respectively. Wind-membrane interaction analysis by the proposed preconditioners, for two and three dimensional membranous structures respectively, was performed. Comparison was made between the performance of initial and modified preconditioners by comparing parameters such as iteration numbers, relative residuals and convergence in FSI computation. The results show that the proposed preconditioning technique greatly improves calculation accuracy and efficiency. The priority of the modified FSI preconditioner is verified. The proposed preconditioning technique provides an efficient solution procedure and paves the way for practical application of simultaneous solution for wind-structure interaction computation.

• The Journal of the Acoustical Society of Korea
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• v.19 no.1
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• pp.67-72
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• 2000

Particularly based on the signal bias removal(SBR) algorithm for compensating the corrupted speech, this paper presents a new algorithm which is independent of environments, minimizes the amount of computation, and is readily applicable to the conventional recognition system. To this end, a multiple-bias algorithm and a partial codebook search algorithm have been added to the conventional SBR algorithm. The simulation results show that combining the two algorithms proposed in this paper provides a reduction of computation time to 1/8 times as well as an improvement of the recognition rate from 77.58% of the conventional system to 81.32%.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.12
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• pp.3166-3179
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• 2013

A pre-processing system for adaptive noise removal is proposed based on the principle of identifying and filtering object regions and background regions. Human perception of images depends on bright, well-focused object regions; these regions can be treated with the best filters, while simpler filters can be applied to other regions to reduce overall computational complexity. In the proposed method, bright region segmentation is performed, followed by segmentation of object and background regions. Noise in dark, background, and object regions is then removed by the median, fast bilateral, and bilateral filters, respectively. Simulations show that the proposed algorithm is much faster than and performs nearly as well as the bilateral filter (which is considered a powerful noise removal algorithm); it reduces computation time by 19.4 % while reducing PSNR by only 1.57 % relative to bilateral filtering. Thus, the proposed algorithm remarkably reduces computation while maintaining accuracy.

• Journal of Korea Society of Industrial Information Systems
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• v.7 no.4
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• pp.17-21
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• 2002

Least mean square(LMS) algorithm one of the most popular algorithm in adaptive signal processing because of the simplicity and the small computation. But the convergence speed of time domain adaptive algorithm is slow when the spread width of eigen values is wide. Moreover we have to choose the step size well for convergency. in this paper, ie use adaptive algorithm of wavelet transform. And we propose a new wavelet based adaptive algorithm of wavelet transform. And we propose a high speed wavelet based adaptive algorithm with variable step size, which is linear to absolute value of error signal. We applied this algorithm to adaptive noise canceler. Simulation results are presented to compare the performance of the proposed algorithm with the usual algorithms.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.45 no.9
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• pp.65-70
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• 2008

In FIR filter design, multipliers occupy most of the area. To efficiently reduce the area occupied by multipliers, Common Subexpression Elimination (CSE) algorithm can be used instead of separate multipliers. However, the filter computation time can be increased due to the long carry propagation in CSE circuits. More specifically, when the difference of weights between the two inputs to an adder in CSE circuits is large, long carry propagation time is required due to large sign extension. In this paper, we propose a sign-extension reduction method in common subexpression elimination circuit. By Synopsys simulation using Samsung 0.35um library, it is shown that the proposed method leads to 17%, 31% and 12% reduction in the area, time delay and power consumption, respectively, compared with conventional method.