• Journal of the Korean Society for Nondestructive Testing
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• v.32 no.4
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• pp.347-354
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• 2012

Using a single-line pulsed laser beam is well known as a useful noncontact method to generate a directional surface acoustic wave. In this method, different laser beam energy profiles produce different waveforms and frequency characteristics. In this paper, we considered two typical kinds of laser beam energy profiles, Gaussian and square-like, to find out a difference in the frequency characteristics. To achieve this, mathematical models were proposed first for Gaussian laser beam profile and square-like respectively, both of which depended on the laser beam width. To verify the theoretical models, experimental setups with a cylindrical lens and a line-slit mask were respectively designed to produce a line laser beam with Gaussian spatial energy profile and square-like. The frequency responses of the theoretical models showed good agreement with experimental results in terms of the existence of harmonic frequency components and the shift of the first peak frequencies to low.

• Honam Mathematical Journal
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• v.46 no.2
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• pp.249-266
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• 2024

In this work, we study time-like and space-like surfaces invariant by a group of translation isometries of the half-space model ℋ³₁ of the anti-de Sitter space ℍ³₁ . We determine all such surfaces with constant mean curvature and constant Gaussian curvature. We also obtain umbilical surfaces of ℋ³₁.

• Journal of the Korean Society for Nondestructive Testing
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• v.33 no.3
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• pp.257-263
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• 2013

Acoustic nonlinearity of surface waves is an effective method to evaluate the micro damage on the surface of materials. In this method, the $A_1$ (magnitude of the fundamental wave) and $A_2$ (magnitude of the second-order harmonic wave) are measured for evaluation of acoustic nonlinearity. However, if there is another source of second-order harmonic wave other than the material itself, the linear relationship between $A_1{^2}$ and $A_2$ will not be guaranteed. Therefore, the second-order harmonic generation by another source should be fully suppressed. In this paper, we investigated the initial second-order harmonic generation in narrowband surface waves by multi-line laser beams. The spatial profile of laser beam was considered in the cases of Gaussian and square-like. The temporal profile was assumed to be Gaussian. In case of Gaussian spatial profile, the generation of the initial second-order harmonic wave was inevitable. However, when the spatial profile was square-like, the generation of the initial second-order harmonic wave was able to be fully suppressed at specific duty ratio. These results mean that the multi-line laser beams of square-like profile with a proper duty ratio are useful to evaluate the acoustic nonlinearity of the generated surface waves.

• Communications of the Korean Mathematical Society
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• v.36 no.3
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• pp.609-622
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• 2021

In the Galilean space G₃, we study a special kind of tube surfaces, called tube-like surfaces. They are defined by sweeping a space curve along another central space curve. In this setting, we investigate some equations in terms of Gaussian and mean curvatures, showing some relevant theorems. Our theoretical results are illustrated with some plotted examples.

• The Bulletin of The Korean Astronomical Society
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• v.41 no.2
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• pp.58.3-58.3
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• 2016

The Kepler space mission provides quantitative and qualitative photometric time series of oscillating stars. It is possible to examine statistical study with seismic properties of solar-like stars. Global seismic properties - large frequency separation (${\Delta}{\nu}$), frequency of maximum power (${\nu}_{max}$) and amplitude of Gaussian envelope (A) widely have been used to determine empirical scaling relations for inferring the stellar physical quantities - mass, age and temperature. We aim to confirm whether width of Gaussian envelope on power excess (${\delta}{\nu}_{env}$) can be used with parameter of scaling relation before redgiant phase using Kepler data. Therefore we analyze the characteristics of ${\delta}{\nu}_{env}$ of 129 solar-like stars from main-sequence to subgiant. We have demonstrated that ${\delta}{\nu}_{env}$ has highly correlations with global parameters - ${\Delta}{\nu}$ and ${\nu}max$. We have also found the break of ${\delta}{\nu}_{env}-{\Delta}{\nu}$ and ${\nu}_{max}$ relations.

• Journal of the Korean Chemical Society
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• v.38 no.12
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• pp.864-872
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• 1994

Absorption spectra of thermochromic spiropyran and spirooxazine derivatives were investigated. The effects of solvent polarity on the absorption spectra indicate that the merocyanine-like form of non-substituted spiro compound is likely to the quinoid type. However, the merocyanine-like form of electron-withdrawing substituted spiro compound is likely to the zwitter-ion type. The enthalpy changes between the closed and merocyanine-like forms were measured. The enthalpy change of spiro compound decreases as the solvent polarity increases. The UV-Vis spectrum of merocyanine-like form was resolved into three Lorentzian-Gaussian product bands. The solvent dependence of the amount of the three band was also examined.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.470-472
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• 2006

Sensor networks are the results of convergence of very important technologies such as wireless communication and micro electromechanical systems. In recent years, sensor networks found a wide applicability in various fields such as environment and health, industry scene system monitoring, etc. A very important step for these many applications is pattern classification and recognition of data collected by sensors installed or deployed in different ways. But, pattern classification and recognition are sometimes difficult to perform. Systematic approach to pattern classification based on modem learning techniques like Multivariate Gaussian mixture models, can greatly simplify the process of developing and implementing real-time classification models. This paper proposes a new recognition system which is hierarchically composed of many sensor nodes having the capability of simple processing and wireless communication. The proposed system is able to perform context classification of sensed data using the Multivariate Gaussian function. In order to verify the usefulness of the proposed system, it was applied to intelligent dust collecting system.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.5B no.3
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• pp.258-261
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• 2005

The Preisach model needs a distribution function or Everett function to simulate the hysteresis phenomena. To obtain these functions, many experimental data obtained from the first order transition curves are usually required. In this paper, a simple procedure to determine the Preisach density function using the Gaussian distribution function and genetic algorithm is proposed. The Preisach density function for the interaction field axis is known to have Gaussian distribution. To determine the density and distribution, genetic algorithm is adopted to decide the Gaussian parameters. With this method, just basic data like the initial magnetization curve or saturation curves are enough to get the agreeable density function. The results are compared with experimental data and we got good agreements comparing the simulation results with the experiment ones.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.43.3-43
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• 2001

In conventional RBF network, the activation functions of hidden layers generally are symmetric functions like gaussian function. This has been considered to be one of the limiting factors for the network to speed up learning of actuately describing a given function. To avoid this criticism, we propose a pseudo gaussian function (PGF) whose deviation is changed according to the direction of incoming pattern. This property helps to estimate the given function more effectively with a minimal number of centers because of its flexibility of functional representation. A level set method is used to describe the asymmetric shape of deviation of the pseudo gaussian function. To demonstrate the performance of the proposed network ...

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.12
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• pp.991-995
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• 2005

Sensor networks are the results of convergence of very important technologies such as wireless communication and micro electromechanical systems. In recent years, sensor networks found a wide applicability in various fields such as health, environment and habitat monitoring, military, etc. A very important step for these many applications is pattern classification and recognition of data collected by sensors installed or deployed in different ways. But, pattern classification and recognition are sometimes difficult to perform. Systematic approach to pattern classification based on modern teaming techniques like Multivariate Gaussian mixture models, can greatly simplify the process of developing and implementing real-time classification models. This paper proposes a new recognition system which is hierarchically composed of many sensor nodes haying the capability of simple processing and wireless communication. The proposed system is able to perform classification of sensed data using the Multivariate Gaussian function. In order to verify the usefulness of the proposed system, it was applied to hand gesture recognition system.