• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.7B
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• pp.592-600
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• 2008

In this paper, a Hybrid Scaling based DTW (HS-DTW) mechanism is proposed for detection of periodic shrew TCP attacks. A low-rate TCP attack which is a type of shrew DoS (Denial of Service) attacks, was reported recently, but it is difficult to detect the attack using previous flooding DoS detection mechanisms. A pattern matching method with DTW (Dynamic Time Warping) as a type of defense mechanisms was shown to be reasonable method of detecting and defending against a periodic low-rate TCP attack in an input traffic link. This method, however, has the problem that a legitimate link may be misidentified as an attack link, if the threshold of the DTW value is not reasonable. In order to effectively discriminate between attack traffic and legitimate traffic, the difference between their DTW values should be large as possible. To increase the difference, we analyze a critical problem with a previous algorithm and introduce a scaling method that increases the difference between DTW values. Four kinds of scaling methods are considered and the standard deviation of the sampling data is adopted. We can select an appropriate scaling scheme according to the standard deviation of an input signal. This is why the HS-DTW increases the difference between DTW values of legitimate and attack traffic. The result is that the determination of the threshold value for discrimination is easier and the probability of mistaking legitimate traffic for an attack is dramatically reduced.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.6
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• pp.1159-1166
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• 2010

To improve prediction quality of a nonlinear prediction system, the system's capability for uncertainty of nonlinear data should be satisfactory. This paper presents a TSK fuzzy prediction system that can consider and deal with the uncertainty of nonlinear data sufficiently. In the design procedures of the proposed system, HCBKA(Hierarchical Correlationship-Based K-means clustering Algorithm) was used to generate the accurate fuzzy rule base that can control output according to input efficiently, and the first-order difference method was applied to reflect various characteristics of the nonlinear data. Also, multiple prediction systems were designed to analyze the prediction tendencies of each difference data generated by the difference method. In addition, to enhance the prediction quality of the proposed system, an error compensation method was proposed and it compensated the prediction error of the systems suitably. Finally, the prediction performance of the proposed system was verified by simulating two typical time series examples.

• Journal of Positioning, Navigation, and Timing
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• v.9 no.4
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• pp.397-403
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• 2020

In order to synchronize a remote system time to the reference time like Coordinated Universal Time (UTC), it is required to compare the time difference between the two clocks. The time comparison data may have some outliers and the time synchronization performance can be significantly degraded if the outliers are not removed. Therefore, it is required to employ an effective outlier detection algorithm for keeping high accurate system time. In this paper, an outlier detection method is presented for the time difference data of GNSS time transfer receivers. The time difference data between the system time and the GNSS usually have slopes because the remote system clock is under free running until synchronized to the reference clock time. For investigating the outlier detection performance of the proposed algorithm, simulations are performed by using the time difference data of a GNSS time transfer receiver corrected to a free running Cesium clock with intentionally inserted outliers. From the simulation, it is investigated that the proposed algorithm can effectively detect the inserted outliers while conventional methods such as modified Z-score and adjusted boxplot cannot. Furthermore, it is also observed that the synchronization performance can be degraded to more than 15% with 20 outliers compared to that of original data without outliers.

• Journal of applied mathematics & informatics
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• v.25 no.1_2
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• pp.269-282
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• 2007

In this paper, we consider a two-dimensional fractional space-time diffusion equation (2DFSTDE) on a finite domain. We examine an implicit difference approximation to solve the 2DFSTDE. Stability and convergence of the method are discussed. Some numerical examples are presented to show the application of the present technique.

• Economic and Environmental Geology
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• v.29 no.2
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• pp.183-192
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• 1996

Much computing time and large computer memory are needed to solve the wave equation in a large complex subsurface layer using finite difference method. The time and memory can be reduced by decreasing the number of grid per minimun wave length. However, decrease of grid may cause numerical dispersion and poor accuracy. In this study, we present 49 points weighted average method which save the computing time and memory and improve the accuracy. This method applies a new weighted average to the coordinate determined by transforming the coordinate of conventional 5 points finite difference stars to $0^{\circ}$ and $45^{\circ}$, 25 points finite differenc stars to $0^{\circ}$, $26.56^{\circ}$, $45^{\circ}$, $63.44^{\circ}$ and 49 finite difference stars to $0^{\circ}$, $18.43^{\circ}$, $33.69^{\circ}$, $45^{\circ}$, $56.30^{\circ}$, $71.56^{\circ}$. By this method, the grid points per minimum wave length can be reduced to 2.5, the computing time to $(2.5/13)^3$, and the required core memory to $(2.5/13)^4$ computing with the conventional method.

• Journal of the military operations research society of Korea
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• v.17 no.1
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• pp.105-129
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• 1991

Dynamic Time Warping(in short DTW) is a kind of sequence comparison method. It is widely used in human speech recognition. The timing difference between two speech patterns to be compared is removed by warping the time axes of the speech pattern by minimising the time-normalised distance between them. In the process of finding the minimum time-normalised distance. the efficient method is dynamic programming problem. This paper describes the concept of dynamic time warping method, mathematical formulation and an application.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.497-500
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• 1995

In this paper, a program for real time simulation of a vehicle is developed. The program uses relative coordinates and BEF(Backward Difference Formula) numerical integration method. Numerical tests showed that the proposed implicit method is more stable in carring out the numerical integration for vehicl dynamics than the explicit method. Hardware requirements for real time simulation are suggested. Algorithms of parallel processing is developed with DSP (digital signal processor).

• Proceedings of the KSME Conference
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• 2008.11b
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• pp.2254-2255
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• 2008

Thermoforming is one of the most versatile and economical process to produce polymer products. The drawback of thermoforming is difficult to control thickness of final products. Temperature distribution affects the thickness distribution of final products, but temperature difference between surface and center of sheet is difficult to decrease because of low thermal conductivity of ABS material. In order to decrease temperature difference between surface and center, heating profile must be expressed as exponential function form. In this study, Finite Difference Method was used to find out the coefficients of optimal heating profiles. Through investigation, the optimal results using Finite Difference Method show that temperature difference between surface and center of sheet can be remarkably minimized with satisfying Temperature of Forming Window.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.8
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• pp.1997-2004
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• 1994

A model analysis method has been developed in the paper. The method estimates the modal parameters of multiple input-output systems, assesses their quality, and seperates structural modes form computation ones. The modal parameter extraction algorithm is the least squares method with a finite difference model relating input and output time data. The quality of the estimated system model can be assessed in narrow frequency bands by comparing the measured and model predicted responses in time domain with the aid of digital filters. Structural modes can be effectively separated from computational ones using the convergence factor which represents the pole convergence rate. The modal analysis method has been applied to simulated and experimental vibration data to evaluate its utility and limitations.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.12 no.7
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• pp.1131-1138
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• 2001

This paper presents the new Compact 2D Haar-wavelet-based MultiResolution Time-Domain method (MRTD) as an accelerating algorithm for the conventional Compact BD Finite-Difference Time-Domain method (FDTD). To validate this algorithm, we analyzed the dispersion characteristics of the hollow rectangular waveguide and dielectric slab-loaded rectangular waveguide. The results of the proposed method are very weal agreed with those of both the conventional analytic method and the Compact 2D FDTD method. The CPU time for analysis of this method is reduced to about a half of the conventional Compact 2D FDTD method. The proposed method is valuable as a fast algorithm in the research of dispersion characteristics of waveguide structures.