• Journal of the Korean Mathematical Society
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• v.40 no.2
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• pp.251-272
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• 2003

Multidimensional integrals are expressed in terms of lower dimensional integrals and function evaluations. An iterative process is used where a trapezoidal and three point identities are used as generators for higher dimensional identities. Bounds are obtained utilising the resulting identities. It is demonstrated that earlier Ostrowski type results are obtained as particular instances of the current work.

• Bulletin of the Korean Mathematical Society
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• v.55 no.5
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• pp.1405-1417
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• 2018

The aim of this work is to introduce several different volume computational methods of graph polytopes associated with various types of finite simple graphs. Among them, we obtained the recursive volume formula (RVF) that is fundamental and most useful to compute the volume of the graph polytope for an arbitrary finite simple graph.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.546-549
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• 2002

In this paper, a simulation system, which is almost same with the real motor-mechanical control system, is established. The real system is identified by using the data from DSP(TMS320F240). The RLS(Recursive Least Square) algorithm is used for the identification and MATLAB Simulink program is used for simulation. The exact simulation system obtained by using the proposed method is very useful for analysis and design of motor-mechanical control systems.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.371-376
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• 1994

This paper presents an on-line modeling method approach for the machine condition. the machine condition is continuously monitored with a sensor such as, a vibration, a current, an acoustic emission (AE) sensor. In this study, neural network modeling by radial basis function is designed for analysis a prediction error. An on-line learning algorithm is designed using the RLS(recursive least square) estimation and the existing clustering method of Kohonen neural network. Experimental results show that the proposed RBNN modeling is suitable for predicting simulated data.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.1778-1782
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• 2004

A new algorithm, CBIR (Correlation-Based Image Registration) was proposed to improve the resolution of image registration for PSP (Pressure-Sensitive Paint). The local displacement vectors were obtained by finding the displacement which maximizes the cross-correlation between two interrogation windows of 'wind-off' and 'wind-on' images. A recursive multigrid processing was employed to increase the non-linear spatial resolutions. The variations of image were precisely measured without identifying the control points.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.2
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• pp.124-129
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• 2002

This paper demonstrates that the largest Lyapunov exponent λ of recurrent neural networks can be controlled efficiently by a stochastic gradient method. An essential core of the proposed method is a novel stochastic approximate formulation of the Lyapunov exponent λ as a function of the network parameters such as connection weights and thresholds of neural activation functions. By a gradient method, a direct calculation to minimize a square error (λ - λ$\^$obj/)$^2$, where λ$\^$obj/ is a desired exponent value, needs gradients collection through time which are given by a recursive calculation from past to present values. The collection is computationally expensive and causes unstable control of the exponent for networks with chaotic dynamics because of chaotic instability. The stochastic formulation derived in this paper gives us an approximation of the gradients collection in a fashion without the recursive calculation. This approximation can realize not only a faster calculation of the gradient, but also stable control for chaotic dynamics. Due to the non-recursive calculation. without respect to the time evolutions, the running times of this approximation grow only about as N$^2$ compared to as N$\^$5/T that is of the direct calculation method. It is also shown by simulation studies that the approximation is a robust formulation for the network size and that proposed method can control the chaos dynamics in recurrent neural networks efficiently.

• Journal of Digital Contents Society
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• v.19 no.2
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• pp.415-423
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• 2018

In recent years, Computer-based learning, such as machine learning and deep learning in the computer field, is attracting attention. They start learning from the lowest level and propagate the result to the highest level to calculate the final result. Research literature has shown that systematic learning and growth can yield good results. However, systematic models based on systematic models are hard to find, compared to various and extensive research attempts. To this end, this paper proposes the first TNT(Transitive Nested Triangle)model, which is a growth and fusion model that can be used in various aspects. This model can be said to be a recursive model in which each function formed through geometric forms an organic hierarchical relationship, and the result is used again as they grow and converge to the top. That is, it is an analytical method called 'Horizontal Sibling Merges and Upward Convergence'. This model is applicable to various aspects. In this study, we focus on explaining the TNT model.

• Journal of Software Assessment and Valuation
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• v.17 no.2
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• pp.39-46
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• 2021

To analyze and defend malware codes, reverse engineering is used as identify function location information. However, the stripped binary is not easy to find information such as function location because function symbol information is removed. To solve this problem, there are various binary analysis tools such as BAP and BitBlaze IDA Pro, but they are based on heuristics method, so they do not perform well in general. In this paper, we propose a technique to extract function information using LSTM-based models by applying algorithms of N-byte method that is extracted binaries corresponding to reverse assembling instruments in a recursive descent method. Through experiments, the proposed techniques were superior to the existing techniques in terms of time and accuracy.

• Journal of the Korean Institute of Telematics and Electronics
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• v.17 no.1
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• pp.23-30
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• 1980

The reconstruction problem in a low dose case requires some compromise of resolution and noise artifacts, and also some modification of filter kernels depending on the signal-to-noise ratio of projection data. In this paper, ail algorithm for the reconstruction of an image function from noisy projection data is suggested, based on minimum-mean-square error criterion. Modification of the falter kernel is made from information (statistics) obtained from the projection data. The simulation study Proves that this algorithm, based on the Wiener falter approach, provides substantially improved image with reduction of noise as well as improvement of the resolution. An approximate method was also studied which leads to the possible use of a recursive filter in the convolution process of image reconstruction.

• Journal of Welding and Joining
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• v.27 no.5
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• pp.81-87
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• 2009

Recently, extruded aluminium-alloy panels have been used in the car bodies for the purpose of the light-weight of railway vehicles and FSW(Friction Stir Welding), which is superior to the arc weldings, has been applied in the railway vehicles. This paper presents the optimum design of the FSW process on A6005 extruded alloy for railway vehicles to improve its mechanical properties. Rotational speed, welding speed and tilting angle of the tool tip were chosen as design parameters. Three objective functions were determined; maximizing the tensile strength, minimizing the hardness and maximizing the difference between the normalized tensile strength and hardness. The tensile tests and the hardness tests for fifteen FSW experiments were carried out according to the central composite design table. Recursive model functions on three characteristic values, such as the tensile strength, the hardness difference(${\Delta}Hv$) and the difference of normalized tensile strength and ${\Delta}Hv$, were estimated according to the classical response surface analysis methodology. The reliability of each recursive function was verified by F-test using the analysis of variance table. Sensitivity analysis on each characteristic value was done. Finally, the optimum values of three design parameters were found using Sequential Quadratic Programming algorithm.