• 한국전산유체공학회:학술대회논문집
• /
• 2008.10a
• /
• pp.181-185
• /
• 2008

In this study, we attempted to quantify the relative importance of assumptions regarding blood rheology. Three patient-specific carotid bifurcation geometries and time-varying flow rates were obtained using magnetic resonance imaging. For each subject, CFD simulations were carried out assuming two different non-Newtonian rheology models (Carreau and Ballyk models) and rescaled Newtonian viscosities based on characteristic shear rates to account for the shear-thinning property of blood. The sensitivity of WSS and oscillatory shear index (OSI) were contextualized with respect to the reproducibility of the reconstructed geometry and to assumptions regarding the inlet boundary conditions. We conclude that the assumption of Newtonian fluid is reasonable for studies aimed at quantifying the distribution of WSS-based extrema in an image-based CFD model of carotid bifurcation.

• Journal of Institute of Control, Robotics and Systems
• /
• v.17 no.12
• /
• pp.1210-1218
• /
• 2011

GA (Genetic Algorithms) are efficient for searching for global optima but may have some problems such as premature convergence, convergence to local extremum and divergence. These phenomena are related to the evolutionary operators. As population diversity converges to low value, the search ability of a GA decreases and premature convergence or converging to local extremum may occur but population diversity converges to high value, then genetic algorithm may diverge. To guarantee that genetic algorithms converge to the global optima, the genetic operators should be chosen properly. In this paper, we analyze the effects of the selection operator, crossover operator, and mutation operator on convergence properties, and propose the sweeping method of mutation probability and elitist propagation rate to maintain the diversity of the GA's population for getting out of the premature convergence. Results of simulation studies verify the feasibility of using these sweeping operators to avoid premature convergence and convergence to local extrema.

• Bulletin of the Korean Mathematical Society
• /
• v.60 no.4
• /
• pp.873-893
• /
• 2023

In 2017, Nikiforov proposed the A_𝛼-matrix of a graph G. This novel matrix is defined as A_𝛼(G) = 𝛼D(G) + (1 - 𝛼)A(G), 𝛼 ∈ [0, 1], where D(G) and A(G) are the degree diagonal matrix and adjacency matrix of G, respectively. Recently, Zhai, Xue and Liu [39] considered the Brualdi-Hoffman-type problem for Q-spectra of graphs with given matching number. As a continuance of it, in this contribution we consider the Brualdi-Hoffman-type problem for A_𝛼-spectra of graphs with given matching number. We identify the graphs with given size and matching number having the largest A_𝛼-spectral radius for ${\alpha}{\in}[{\frac{1}{2}},1)$.

• The Korean Journal of Applied Statistics
• /
• v.26 no.2
• /
• pp.335-347
• /
• 2013

There are various types of real world signals. For example, an electrocardiogram(ECG) represents myocardium activities (contraction and relaxation) according to the beating of the heart. ECG can be expressed as the fluctuation of ampere ratings over time. A signal is a composite of various types of signals. An orchestra (which boasts a beautiful melody) consists of a variety of instruments with a unique frequency; subsequently, each sound is combined to form a perfect harmony. Various research on how to to decompose mixed stationary signals have been conducted. In the case of non-stationary signals, there is a limitation to use methodologies for stationary signals. Huang et al. (1998) proposed empirical mode decomposition(EMD) to deal with non-stationarity. EMD provides a data-driven approach to decompose a signal into intrinsic mode functions according to local oscillation through the identification of local extrema. However, due to the repeating process in the construction of envelopes, EMD algorithm is not efficient and not robust to a noise, and its computational complexity tends to increase as the size of a signal grows. In this research, we propose a new method to extract a local oscillation embedded in a signal by utilizing the second derivative.

• Phonetics and Speech Sciences
• /
• v.4 no.3
• /
• pp.43-49
• /
• 2012

This paper describes the categorical effects of pitch accent contrasts in a mimicry task. It focuses, specifically, on examining how fundamental frequency (f0) variation reflects phonological contrasts from speakers of two distinct varieties of Korean (i.e., North Kyungsang and South Cholla). The results showed that, in a mimicry task using synthetic speech continua, there was a categorical effect in f0 peak timing for North Kyungsang speakers, but the timing of f0 peaks and valleys in the responses of South Cholla speakers was more variable, presenting a gradient or non-categorical effect. Evidence of categorical effects was represented as the shift of f0 peak times along an acoustic continuum for North Kyungsang speakers. The range for the shift of f0 valley times was much narrower, compared to that of f0 peak times. The degree of a shift near the middle of the continuum showed variability across individual mimicry responses. However, the categorical structure in mimicry responses regarding the clustering of f0 peak points was more significant for North Kyungsang speakers than for South Cholla speakers. Additionally, the finding of the current study implies that the location of f0 peak times depends on individuals' imitative (or cognitive) abilities.

• Journal of Biomedical Engineering Research
• /
• v.29 no.4
• /
• pp.278-285
• /
• 2008

In this study the complex-valued continuous wavelet transform (CWT) has been applied in detection of Electrocardiograms (ECG) as response to various signal classification methods such as Fourier transforms and other tools of time frequency analysis. Experiments have shown that CWT may serve as a detector of non-stationary signal changes as ECG. The tested signal is corrupted by short time events. We applied CWT to detect short-time event and the result image representation of the signal has showed us that one can easily find the discontinuity at the time scale representation. Analysis of ECG signal using complex-valued continuous wavelet transform is the first step to detect possible changes and alternans. In the second step, modulus and phase must be thoroughly examined. Thus, short time events in the ECG signal, and other important characteristic points such as frequency overlapping, wave onsets/offsets extrema and discontinuities even inflection points are found to be detectable. We have proved that the complex-valued CWT can be used as a powerful detector in ECG signal analysis.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.1283-1286
• /
• 2005

Multimodal optimization is one of the most interesting topics in evolutionary computational discipline. Simple genetic algorithm, a basic and good-performance genetic algorithm, shows bad performance on multimodal problems, taking long generation time to obtain the optimum, converging on the local extrema in early generation. In this paper, we propose a new genetic algorithm with two new genetic mutational operators, i.e. global and local mutation operators, and no genetic crossover. The proposed algorithm is similar to Simple GA and the two genetic operators are as simple as the conventional mutation. They just mutate the genes from left or right end of a chromosome till the randomly selected gene is replaced. In fact, two operators are identical with each other except for the direction where they are applied. Their roles of shaking the population (global searching) and fine tuning (local searching) make the diversity of the individuals being maintained through the entire generation. The proposed algorithm is, therefore, robust and powerful.

• Smart Structures and Systems
• /
• v.3 no.4
• /
• pp.423-437
• /
• 2007

The empirical mode decomposition (EMD) method is well-known for its ability to decompose a multi-component signal into a set of intrinsic mode functions (IMFs). The method uses a sifting process in which local extrema of a signal are identified and followed by a spline fitting approximation for decomposition. This method provides an effective and robust approach for decomposing nonlinear and non-stationary signals. On the other hand, the IMF components do not automatically guarantee a well-defined physical meaning hence it is necessary to validate the IMF components carefully prior to any further processing and interpretation. In this paper, an attempt to use the EMD method to identify properties of nonlinear elastic multi-degree-of-freedom structures is explored. It is first shown that the IMF components of the displacement and velocity responses of a nonlinear elastic structure are numerically close to the nonlinear normal mode (NNM) responses obtained from two-dimensional invariant manifolds. The IMF components can then be used in the context of the NNM method to estimate the properties of the nonlinear elastic structure. A two-degree-of-freedom shear-beam building model is used as an example to illustrate the proposed technique. Numerical results show that combining the EMD and the NNM method provides a possible means for obtaining nonlinear properties in a structure.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.13 no.3
• /
• pp.178-185
• /
• 2013

As computer technology continues to develop, computer networks are now widely used. As a result, there are many new intrusion types appearing and information security is becoming increasingly important. Although there are many kinds of intrusion detection systems deployed to protect our modern networks, we are constantly hearing reports of hackers causing major disruptions. Since existing technologies all have some disadvantages, we utilize algorithms, such as the fuzzy C-means (FCM) and the support vector machine (SVM) algorithms to improve these technologies. Using these two algorithms alone has some disadvantages leading to a low classification accuracy rate. In the case of FCM, self-adaptability is weak, and the algorithm is sensitive to the initial value, vulnerable to the impact of noise and isolated points, and can easily converge to local extrema among other defects. These weaknesses may yield an unsatisfactory detection result with a low detection rate. We use a genetic algorithm (GA) to help resolve these problems. Our experimental results show that the combined GA and FCM algorithm's accuracy rate is approximately 30% higher than that of the standard FCM thereby demonstrating that our approach is substantially more effective.

• Journal of Communications and Networks
• /
• v.14 no.1
• /
• pp.21-26
• /
• 2012

As electrocardiogram (ECG) signals are generally sampled with a frequency of over 200 Hz, a method to compress diagnostic information without losing data is required to store and transmit them efficiently on a wireless personal area network (WPAN). In this paper, an ECG signal compression method for communications onWPAN, which uses feature points based on curvature, is proposed. The feature points of P, Q, R, S, and T waves, which are critical components of the ECG signal, have large curvature values compared to other vertexes. Thus, these vertexes were extracted with the proposed method, which uses local extrema of curvatures. Furthermore, in order to minimize reconstruction errors of the ECG signal, extra vertexes were added according to the iterative vertex selectionmethod. Through the experimental results on the ECG signals from Massachusetts Institute of Technology-Beth Israel hospital arrhythmia database, it was concluded that the vertexes selected by the proposed method preserved all feature points of the ECG signals. In addition, it was more efficient than the amplitude zone time epoch coding method.