• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.200-206
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• 2021

Fraud in e-commerce transaction increased in the last decade especially with the increasing number of online stores and the lockdown that forced more people to pay for services and groceries online using their credit card. Several machine learning methods were proposed to detect fraudulent transaction. Neural networks showed promising results, but it has some few drawbacks that can be overcome using optimization methods. There are two categories of learning optimization methods, first-order methods which utilizes gradient information to construct the next training iteration whereas, and second-order methods which derivatives use Hessian to calculate the iteration based on the optimization trajectory. There also some training refinements procedures that aims to potentially enhance the original accuracy while possibly reduce the model size. This paper investigate the performance of several NN models in detecting fraud in e-commerce transaction. The backpropagation model which is classified as first learning algorithm achieved the best accuracy 96% among all the models.

• Journal of Biomedical Engineering Research
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• v.22 no.3
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• pp.241-247
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• 2001

ABR(auditory brainstem response) is one of the audiometry which measures objective hearing threshold level by acquiring electric evoked potentials emanated from auditory nerve system responding to an auditory stimulation. However, the obtained potentials which are largely interfered by power line noise, have extremely low SNR, thus ensemble average algorithm is generally used. The purpose of this study was to investigate the effect of iteration number in ensemble average on the reduction of the power line noise. The power line noise was modeled to be a 60 Hz sinusoidal signal and the energy of the modeled signal was calculated when it was averaged. It was verified by simulation that the energy had the periodic zero points for each stimulation rate, and 60 Hz signal induced by the power line was applied to the developed ABR system to confirm that the period of zero energy point was the same with that of the simulation. By the properly selected iteration number, power line noise could be reduced and more reliable ABR could be acquired.

• The Journal of Information Technology
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• v.8 no.1
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• pp.119-124
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• 2005

Learning procedure in the neural network is updating of weights between neurons. Unadequate initial learning coefficient causes excessive iterations of learning process or incorrect learning results and degrades learning efficiency. In this paper, adaptive learning algorithm is proposed to increase the efficient in the learning algorithms of Kohonens Self-Organization Neural networks. The algorithm updates the weights adaptively when learning procedure runs. To prove the efficiency the algorithm is experimented to clustering of the random weight. The result shows improved learning rate about 42~55% ; less iteration counts with correct answer.

• Journal of applied mathematics & informatics
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• v.28 no.3_4
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• pp.823-835
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• 2010

In this paper, A FSQP algorithm for degenerate inequality constraints optimization problems is proposed. At each iteration of the proposed algorithm, a feasible direction of descent is obtained by solving a quadratic programming subproblem. To overcome the Maratos effect, a higher-order correction direction is obtained by solving another quadratic programming subproblem. The algorithm is proved to be globally convergent and superlinearly convergent under some mild conditions. Finally, some preliminary numerical results are reported.

• The Korean Journal of Nuclear Medicine Technology
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• v.15 no.1
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• pp.17-24
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• 2011

Purpose: Presently in the nuclear medicine field, the high-speed image reconstruction algorithm like the OSEM algorithm is widely used as the alternative of the filtered back projection method due to the rapid development and application of the digital computer. There is no to relate and if it applies the optimal parameter be clearly determined. In this research, the quality change of the Jaszczak phantom experiment and brain SPECT patient data according to the iteration times and subset number change try to be been put through and analyzed in 3D OSEM reconstruction method of applying 3D beam modeling. Materials and Methods: Patient data from August, 2010 studied and analyzed against 5 patients implementing the brain SPECT until september, 2010 in the nuclear medicine department of ASAN medical center. The phantom image used the mixed Jaszczak phantom equally and obtained the water and 99mTc (500 MBq) in the dual head gamma camera Symbia T2 of Siemens. When reconstructing each image altogether with patient data and phantom data, we changed iteration number as 1, 4, 8, 12, 24 and 30 times and subset number as 2, 4, 8, 16 and 32 times. We reconstructed in reconstructed each image, the variation coefficient for guessing about noise of images and image contrast, FWHM were produced and compared. Results: In patients and phantom experiment data, a contrast and spatial resolution of an image showed the tendency to increase linearly altogether according to the increment of the iteration times and subset number but the variation coefficient did not show the tendency to be improved according to the increase of two parameters. In the comparison according to the scan time, the image contrast and FWHM showed altogether the result of being linearly improved according to the iteration times and subset number increase in projection per 10, 20 and 30 second image but the variation coefficient did not show the tendency to be improved. Conclusion: The linear relationship of the image contrast improved in 3D OSEM reconstruction method image of applying 3D beam modeling through this experiment like the existing 1D and 2D OSEM reconfiguration method according to the iteration times and subset number increase could be confirmed. However, this is simple phantom experiment and the result of obtaining by the some patients limited range and the various variables can be existed. So for generalizing this based on this results of this experiment, there is the excessiveness and the evaluation about 3D OSEM reconfiguration method should be additionally made through experiments after this.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.401-406
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• 2011

In order to solve a complex optimization problem more efficiently than traditional approaches, various meta-heuristic algorithms such as genetic algorithm, ant-colony algorithm, and harmony search algorithm have been extensively researched. Compared with other meta-heuristic algorithm, harmony search algorithm shows a better result to resolve the complex optimization issues. Harmony search algorithm is inspired by the improvision process of musician for most suitable harmony. In general, the performance of harmony search algorithm is determined by the value of harmony memory considering rate, and pitch adjust rate. In this paper, modified harmony search algorithm is proposed in order to derive best harmony. If the optimal solution of a specific problem can not be found for a certain period of time, a part of original harmony memory is updated as the selected suitable harmonies. Experimental results using test function demonstrate that the updated harmony memory can induce the approximation of reliable optimal solution in the short iteration, because of a few change of fitness.

• The Transactions of the Korea Information Processing Society
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• v.5 no.5
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• pp.1172-1184
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• 1998

ILP(Instruction Level Parallelism) processors use code reordering algorithms to expose parallelism in a given sequential program. When applied to a loop, this algorithm produces a software-pipelined loop. In a software-pipelined loop, each iteration contains a sequence of parallel instructions that are composed of data-independent instructions collected across from several iterations. For vector loops, however the software pipelining technique can not expose the maximum parallelism because it schedules the program based only on data-dependencies. This paper proposes to schedule differently for vector loops. We develop an algorithm to detect vector loops at object code level and suggest a new vector scheduling algorithm for them. Our vector scheduling improves the performance because it can schedule not only based on data-dependencies but on loop structure or iteration conditions at the object code level. We compare the resulting schedules with those by software-pipelining techniques in the aspect of performance.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.11
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• pp.28-35
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• 2013

The Krylov-Schur algorithm has been applied to reveal the eigen-properties of the wave guide having the square cross section. The eigen-matrix equation has been constructed from FEM with the basis function of the tangential edge-vectors of the triangular element. This equation has been treated firstly with Arnoldi decomposition to obtain a upper Hessenberg matrix. The QR algorithm has been carried out to transform it into Schur form. The several eigen values satisfying the convergent condition have appeared in the diagonal components. The eigen-modes for them have been calculated from the inverse iteration method. The wanted eigen-pairs have been reordered in the leading principle sub-matrix of the Schur matrix. This sub-matrix has been deflated from the eigen-matrix equation for the subsequent search of other eigen-pairs. These processes have been conducted several times repeatedly. As a result, a few primary eigen-pairs of TE and TM modes have been obtained with sufficient reliability.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.3
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• pp.311-317
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• 2013

In this paper, we proposed high speed LDPC decoding algorithm based on DVB-S2 standard for applying marine communications in order to multimedia transmission. For implementing the high speed LDPC decoder, HSS algorithm which reduce the iteration numbers without performance degradation is applied. In HSS algorithm, check node update units are update at the same time of bit node update. HSS can be accelerated to the decoding speed because it does not need to separate calculation of the bit nodes, However, check node calculation blocks need many clocks because of just one memory is used. Therefore, this paper proposed partial memory structure in order to reduced the delay and high speed decoder is possible. The results of the simulation, when the max number of iteration set to 30 times, decoding throughput of HSS algorithm is 326 Mbit/s and decoding speed of proposed algorithm is 2.29 Gbit/s. So, decoding speed of proposed algorithm more than 7 times could be obtained compared to the HSS algorithm.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.240-242
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• 2004

A channel allocation algorithm of multi-user OFDM(orthogonal frequency division multiplexing) system is presented. The proposed algorithm is to reduce the complexity of the system, using the GNN(gradual neural network) with gradual expansion scheme and the algorithm attempts to allocate channel with good channel gain to each user. The method has lower computational complexity and less iteration than other algorithms.