• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.10
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• pp.2267-2272
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• 2012

This study has presented the analysis of subthreshold swings based on scaling theory for double gate MOSFET. To solve the analytical potential distribution of Poisson's equation, we use Gaussian function to charge distribution. The scaling theory has been used to analyze short channel effect such as subthreshold swing degradation. These scaling factors for gate length, oxide thickness and channel thickness has been modified with the general scaling theory to include effects of double gates. We know subthreshold swing degradation is rapidly reduced when scaling factor of gate length is half of general scaling factor, and parameters such as projected range and standard projected deviation have greatly influenced on subthreshold swings.

• Steel and Composite Structures
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• v.39 no.3
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• pp.275-290
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• 2021

The main purpose of this research work is to investigate the critical buckling load of functionally graded (FG) porous plates with graphene platelets (GPLs) reinforcement using generalized differential quadrature (GDQ) method at thermal condition. It is supposed that the GPL nanofillers and the porosity coefficient vary continuously along the plate thickness direction. Generally, the thermal distribution is considered to be nonlinear and the temperature changing continuously through the thickness of the nanocomposite plates according to the power-law distribution. To model closed cell FG porous material reinforced with GPLs, Halpin-Tsai micromechanical modeling in conjunction with Gaussian-Random field scheme are used, through which mechanical properties of the structures can be extracted. Based on the third order shear deformation theory (TSDT) and the Hamilton's principle, the equations of motion are established and solved for various boundary conditions (B.Cs). The fast rate of convergence and accuracy of the method are investigated through the different solved examples and validity of the present study is evaluated by comparing its numerical results with those available in the literature. A special attention is drawn to the role of GPLs weight fraction, GPLs patterns through the thickness, porosity coefficient and distribution of porosity on critical buckling load. Results reveal that the importance of thermal condition on of the critical load of FGP-GPL reinforced nanocomposite plates.

• Bulletin of the Society of Naval Architects of Korea
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• v.11 no.1
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• pp.17-26
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• 1974

In this paper, authors investigate and analyze the effects of the anti-rolling tank which are calculated in accord with the tank damping coefficients by the computer, and which are represented with both the tank water's saturating state and the normal state in the irregular waves by analog computer. As the results of these studies, we immediately find that the tank optimum damping coefficient $b_{to}$, is 0.3877 due to calculating $\mu$-values, analyzing and comparing inclinations of $\mu$-values, and that although a nonlinear elements are included in the response character of the ship-tank system, the output is no longer Gaussian distribution, even when the sea waves are considered as Gaussian, and can not be expressed by the spectral forms which premise the superposition theory.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.8
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• pp.1454-1463
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• 2008

Blind source separation by independent component analysis (ICA) has applied in signal processing, telecommunication, and image processing to recover unknown original source signals from mutually independent observation signals. Neural networks are learned to estimate the original signals by unsupervised learning algorithm. Because the outputs of the neural networks which yield original source signals are mutually independent, then mutual information is zero. This is equivalent to minimizing the Kullback-Leibler convergence between probability density function and the corresponding factorial distribution of the output in neural networks. In this paper, we present a learning algorithm using information theory and higher order statistics to solve problem of blind source separation. For computer simulation two deterministic signals and a Gaussian noise are used as original source signals. We also test the proposed algorithm by applying it to several discrete images.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5B
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• pp.559-573
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• 2008

In this study, we newly proposed 3-D nonlinear wave driver utilizing the Navier-Stokes Eq. the numerical integration of which is carried out using SPH (Smoothed Particle Hydrodynamics), an internal wave generation with the source function of Gaussian distribution and an energy absorbing layer. For the verification of new 3-D nonlinear wave driver, we numerically simulate the sloshing problem within a parabolic water basin triggered by a Gaussian hump and uniformly inclined water surface by Thacker (1981). It turns out that the qualitative behavior of sloshing caused by relaxing the external force which makes a free surface convex or uniformly inclined is successfully simulated even though phase error is visible and an inundation height shrinks as numerical simulation more proceeds. For the more severe test, we also simulate the nonlinear shoaling and refraction over uniform beach of wedge shape. It is shown that numerically simulated waves are less refracted than the linear counterpart by Hamiltonian ray theory due to nonlinearity, energy dissipation at the bottom and side walls, energy loss induced by breaking, and the hydraulic jump occurring when breaking waves encounter a down-rush by the preceding wave.

• Journal of Auto-vehicle Safety Association
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• v.11 no.2
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• pp.29-34
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• 2019

This paper presents a new method for construction of a static obstacle map. A static obstacle is important since it is utilized to path planning and decision. Several established approaches generate static obstacle map by grid method and counting algorithm. However, these approaches are occasionally ineffective since the density of LiDAR layer is low. Our approach solved this problem by applying probability theory. First, we converted all LiDAR point to Gaussian distribution to considers an uncertainty of LiDAR point. This Gaussian distribution represents likelihood of obstacle. Second, we modeled dynamic transition of a static obstacle map by adopting the Hidden Markov Model. Due to the dynamic characteristics of the vehicle in relation to the conditions of the next stage only, a more accurate map of the obstacles can be obtained using the Hidden Markov Model. Experimental data obtained from test driving demonstrates that our approach is suitable for mapping static obstacles. In addition, this result shows that our algorithm has an advantage in estimating not only static obstacles but also dynamic characteristics of moving target such as driving vehicles.

• Korean Journal of Remote Sensing
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• v.28 no.6
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• pp.611-622
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• 2012

This study proposed two multisensor fusion methods for segment-based image classification utilizing a region-growing segmentation. The proposed algorithms employ a Gaussian-PDF measure and an evidential measure respectively. In remote sensing application, segment-based approaches are used to extract more explicit information on spatial structure compared to pixel-based methods. Data from a single sensor may be insufficient to provide accurate description of a ground scene in image classification. Due to the redundant and complementary nature of multisensor data, a combination of information from multiple sensors can make reduce classification error rate. The Gaussian-PDF method defines a regional measure as the PDF average of pixels belonging to the region, and assigns a region into a class associated with the maximum of regional measure. The evidential fusion method uses two measures of plausibility and belief, which are derived from a mass function of the Beta distribution for the basic probability assignment of every hypothesis about region classes. The proposed methods were applied to the SPOT XS and ENVISAT data, which were acquired over Iksan area of of Korean peninsula. The experiment results showed that the segment-based method of evidential measure is greatly effective on improving the classification via multisensor fusion.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.5
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• pp.982-988
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• 2012

This paper has presented the relation of scaling theory and threshold voltage of double gate(DG) MOSFET. In the case of conventional MOSFET, current and switching frequency have been analyzed based on scaling theory. To observe the possibility of application of scaling theory for threshold voltage of DGMOSFET, the change of threshold voltage has been observed and analyzed according to scaling theory. The analytical potential distribution of Poisson equation has been used, and this model has been already verified. To solve Poisson equation, charge distribution such as Gaussian function has been used. As a result, it has been observed that threshold voltage is grealty changed according to scaling factor and change rate of threshold voltages is traced for scaling of doping concentration in channel. This paper has explained for the best modified scaling theory reflected the influence of two gates as using weighting factor when scaling theory has been applied for channel length and channel thickness.

• Journal of Communications and Networks
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• v.9 no.2
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• pp.185-191
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• 2007

Alpha stable distribution is better for modeling impulsive noises than Gaussian distribution in signal processing. This class of process has no closed form of probability density function and finite second order moments. In general, Wiener filter theory is not meaningful in S$\alpha$SG environments because the expectations may be unbounded. We proposed a new adaptive recursive least p-norm Kalman filtering algorithm based on least p-norm of innovation process with infinite variances, and a new robust multiuser detection method based on least p-norm Kalman filtering. The simulation experiments show that the proposed new algorithm is more robust than the conventional Kalman filtering multiuser detection algorithm.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2002.11a
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• pp.139-145
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• 2002

The flow zone through propeller jets are used in evaluating the environmental and constructional effects of navigation on the waterway. It relies on the characteristics of ships and water depth. A numerical model using the momentum theory of the propeller and Shield's diagram was developed in a restricted waterway. Equations for discharge are presented based on thrust coefficients and propeller speed and are the most accurate means of defining discharge. Approximate methods for discharge are developed based on applied ship's power. Equations for discharge are as a function of applied power, propeller diameter, and ship speed. Water depth of the waterway and draft of the shop are also necessary for the calculation of the grain size of the initial motion. The velocity distribution of discharge from the propeller was simulated by the Gaussian normal distribution function. The shear velocity and shear stress were from the Sternberg's formula. Case studies to show the influence of significant factors on sediment movement induced by the ship's propeller at the channel bottom are presented.