• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권12호
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• pp.6028-6042
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• 2019

Since Sparse Nonnegative Matrix Factorization (SNMF) method can control the sparsity of the decomposed matrix, and then it can be adopted to control the sparsity of facial feature extraction and recognition. In order to improve the accuracy of SNMF method for facial feature recognition, new additive iterative rules based on the improved iterative step sizes are proposed to improve the SNMF method, and then the traditional multiplicative iterative rules of SNMF are transformed to additive iterative rules. Meanwhile, to further increase the sparsity of the basis matrix decomposed by the improved SNMF method, a threshold-sparse constraint is adopted to make the basis matrix to a zero-one matrix, which can further improve the accuracy of facial feature recognition. The improved SNMF method based on the additive iterative rules and threshold-sparse constraint is abbreviated as ASNMF, which is adopted to recognize the ORL and CK+ facial datasets, and achieved recognition rate of 96% and 100%, respectively. Meanwhile, from the results of the contrast experiments, it can be found that the recognition rate achieved by the ASNMF method is obviously higher than the basic NMF, traditional SNMF, convex nonnegative matrix factorization (CNMF) and Deep NMF.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2000년도 춘계학술대회 논문집
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• pp.78-85
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• 2000

Computer algorithms for the loadflow of the DC traction power supply system are examined. Algorithms to solve the nodal equation are reviewed and the two iterative methods to solve the nonlinear nature of the loadflow are analyzed and tested, which are so called conductance matrix method and current vector iterative mettled. The result of the analysis tells that the current vector iterative method makes faster convergency and needs less computing time, and it is verified by the test running of the programs based on each of the iterative methods.

• 한국전자파학회논문지
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• 제23권4호
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• pp.524-532
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• 2012

본 논문에서는 전자파를 이용하여 인체 내 암 조직을 찾아내기 위해 역산란 방법인 BIM(Born Iterative Method)을 이용한 알고리즘으로 구현하였다. Born 반복법을 이용하여 2차원 유방암 진단에 적용하였으며, 전자파산란 해석에는 적분방정식과 2차원 그린함수를 이용한 MoM(Method of Moment)을 이용하였다. 또한, 유방암 진단에 있어 적용된 역산란 알고리즘의 계산 결과를 확인하고, 암진단 의료기기로의 적용가능성과 알고리즘 사용에 제한을 분석하였다.

• KCI Concrete Journal
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• 제11권3호
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• pp.45-52
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• 1999

A Computer-based iterative method is provided for the calculation of minimum thickness values for one-way slabs to satisfy the maximum permissible limits given in the ACI Building Code. An algorithm includes the effects of cracking and time-dependent effects due to creep and shrinkage. Comparison of the calculated minimum thickness values with the current ACI limits is conducted to investigate limitations of the current tabulated minimum thickness. which are constant to a range of design conditions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권6호
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• pp.2761-2781
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• 2018

With the continuous growth of data size and the use of compression technology, data reduction has great research value and practical significance. Aiming at the shortcomings of the existing semantic compression algorithm, this paper is based on the analysis of ItCompress algorithm, and designs a method of bidirectional order selection based on interval partitioning, which named An Optimized Iterative Semantic Compression Algorithm (Optimized ItCompress Algorithm). In order to further improve the speed of the algorithm, we propose a parallel optimization iterative semantic compression algorithm using GPU (POICAG) and an optimized iterative semantic compression algorithm using Spark (DOICAS). A lot of valid experiments are carried out on four kinds of datasets, which fully verified the efficiency of the proposed algorithm.

• Nonlinear Functional Analysis and Applications
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• 제28권1호
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• pp.175-203
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• 2023

In this paper, we study an iterative algorithm that is based on inertial proximal and contraction methods embellished with relaxation technique, for finding common solution of monotone variational inclusion, and fixed point problems of pseudocontractive mapping in real Hilbert spaces. We establish a strong convergence result of the proposed iterative method based on prediction stepsize conditions, and under some standard assumptions on the algorithm parameters. Finally, some special cases of general problem are given as applications. Our results improve and generalized some well-known and related results in literature.

• Design & Manufacturing
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• 제16권3호
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• pp.34-38
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• 2022

Regular expression pattern matching is widely used in applications such as computer virus vaccine, NIDS and DNA sequencing analysis. Hardware-based pattern matching is used when high-performance processing is required due to time constraints. ReCPU, SMPU, and REMP, which are processor-based regular expression matching processors, have been proposed to solve the problem of the hardware-based method that requires resynthesis whenever a pattern is updated. However, these processor-based regular expression matching processors inefficiently handle repetitive operations of regular expressions. In this paper, we propose a new instruction set to improve the inefficient repetitive operations of ReCPU and SMPU. We propose REMPi, a regular expression matching processor that enables efficient iterative operations based on the REMP instruction set. REMPi improves the inefficient method of processing a particularly short sub-pattern as a repeat operation OR, and enables processing with a single instruction. In addition, by using a down counter and a counter stack, nested iterative operations are also efficiently processed. REMPi was described with Verilog and synthesized on Intel Stratix IV FPGA.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.499-502
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• 1996

In this paper, we propose a fuzzy iterative learning controller(FILC). It can control fully unknown dynamic plants through iterative learning. To design learning controllers based on the steepest descent method, it is one of the difficult problems to identify the change of plant output with respect to the change of control input(.part.e/.part.u). To solve this problem, we propose a method as follows: first, calculate .part.e/.part.u using a similarity measure and information in consecutive time steps, then adjust the fuzzy logic controller(FLC) using the sign of .part.e/.part..u. As learning process is iterated, the value of .part.e/.part.u is reinforced. Proposed FILC has the simple architecture compared with previous other controllers. Computer simulations for an inverted pendulum system were conducted to verify the performance of the proposed FILC.

• International Journal of Control, Automation, and Systems
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• 제6권2호
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• pp.269-277
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• 2008

This paper proposes a necessary and sufficient condition of convergence in the $L_2$-norm sense for a feedback-based iterative learning control (ILC) system including a multi-input multi-output (MIMO) linear time-invariant (LTI) plant. It is shown that the convergence conditions for a nominal plant and an uncertain plant are equal to the nominal performance condition and the robust performance condition in the feedback control theory, respectively. Moreover, no additional effort is required to design an iterative learning controller because the performance weighting matrix is used as an iterative learning controller. By proving that the least upper bound of the $L_2$-norm of the remaining tracking error is less than that of the initial tracking error, this paper shows that the iterative learning controller combined with the feedback controller is more effective to reduce the tracking error than only the feedback controller. The validity of the proposed method is verified through computer simulations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권4호
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• pp.1373-1391
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• 2022

We investigate mobile multiple-input multiple-output (MIMO) molecular communication via diffusion (MCvD) system which is consisted of two source nodes, two destination nodes and one relay node in the mobile three-dimensional channel. First, the combinations of decode-and-forward (DF) relaying protocol and network coding (NC) scheme are implemented at relay node. The adaptive thresholds at relay node and destination nodes can be obtained by maximum a posteriori (MAP) probability detection method. Then the mathematical expressions of the average bit error probability (BEP) of this mobile MIMO MCvD system based on DF and NC scheme are derived. Furthermore, in order to minimize the average BEP, we establish the optimization problem with optimization variables which include the ratio of the number of emitted molecules at two source nodes and the initial position of relay node. We put forward an iterative scheme based on block coordinate descent algorithm which can be used to solve the optimization problem and get optimal values of the optimization variables simultaneously. Finally, the numerical results reveal that the proposed iterative method has good convergence behavior. The average BEP performance of this system can be improved by performing the joint optimizations.