• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.3
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• pp.672-677
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• 2013

This paper have analyzed the change of breakdown voltage for channel dimension of double gate(DG) MOSFET. The breakdown voltage to have the small value among the short channel effects of DGMOSFET to be next-generation devices have to be precisely analyzed. The analytical solution of Poisson's equation have been used to analyze the breakdown voltage, and Gaussian function been used as carrier distribution to analyze closely for experimental results. The breakdown voltages have been analyzed for device parameters such as channel thickness and doping concentration, and projected range and standard projected deviation of Gaussian function. Since this potential model has been verified in the previous papers, we have used this model to analyze the breakdown voltage. As a result, we know the breakdown voltage is influenced on Gaussian function and device parameters for DGMOSFET.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.811-814
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• 2012

This paper have analyzed the change of breakdown voltage for channel dimension of double gate(DG) MOSFET. The breakdown voltage to have the small value among the short channel effects of DGMOSFET to be next-generation devices have to be precisely analyzed. The analytical solution of Poisson's equation have been used to analyze the breakdown voltage, and Gaussian function been used as carrier distribution to analyze closely for experimental results. The breakdown voltages have been analyzed for device parameters such as channel thickness and doping concentration, and projected range and standard projected deviation of Gaussian function. Since this potential model has been verified in the previous papers, we have used this model to analyze the breakdown voltage. Resultly, we know the breakdown voltage is influenced on Gaussian function and device parameters for DGMOSFET.

• Korean Journal of Remote Sensing
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• v.20 no.6
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• pp.419-425
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• 2004

This study has proposed a data fusion method based on the Dempster-Shafer evidence theory The Dempster-Shafer fusion uses mass functions obtained under the assumption of class-independent Gaussian assumption. In the Dempster-Shafer approach, uncertainty is represented by 'belief interval' equal to the difference between the values of 'belief' function and 'plausibility' function which measure imprecision and uncertainty By utilizing the Dempster-Shafer scheme to fuse the data from multiple sensors, the results of classification can be improved. It can make the users consider the regions with mixed classes in a training process. In most practices, it is hard to find the regions with a pure class. In this study, the proposed method has applied to the KOMPSAT-EOC panchromatic image and LANDSAT ETM+ NDVI data acquired over Yongin/Nuengpyung. area of Kyunggi-do. The results show that it has potential of effective data fusion for multiple sensor imagery.

• Composite Materials and Engineering
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• v.3 no.3
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• pp.201-220
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• 2021

In this study, potential of three machine learning techniques i.e., M5P, Support vector machines and Gaussian processes were evaluated to find the best algorithm for the prediction of flexural strength of concrete mix with steel fibre. The study comprises the comparison of results obtained from above-said techniques for given dataset. The dataset consists of 124 observations from past research studies and this dataset is randomly divided into two subsets namely training and testing datasets with (70-30)% proportion by weight. Cement, fine aggregates, coarse aggregates, water, super plasticizer/ high-range water reducer, steel fibre, fibre length and curing days were taken as input parameters whereas flexural strength of the concrete mix was taken as the output parameter. Performance of the techniques was checked by statistic evaluation parameters. Results show that the Gaussian process technique works better than other techniques with its minimum error bandwidth. Statistical analysis shows that the Gaussian process predicts better results with higher coefficient of correlation value (0.9138) and minimum mean absolute error (1.2954) and Root mean square error value (1.9672). Sensitivity analysis proves that steel fibre is the significant parameter among other parameters to predict the flexural strength of concrete mix. According to the shape of the fibre, the mixed type performs better for this data than the hooked shape of the steel fibre, which has a higher CC of 0.9649, which shows that the shape of fibers do effect the flexural strength of the concrete. However, the intricacy of the mixed fibres needs further investigations. For future mixes, the most favorable range for the increase in flexural strength of concrete mix found to be (1-3)%.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.664-667
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• 2011

In this paper, threshold voltage characteristics have been analyzed as one of short channel effects occurred in double gate(DG)MOSFET to be next-generation devices. The Gaussian function to be nearly experimental distribution has been used as carrier distribution to solve Poisson's equation, and threshold voltage has been investigated according to projected range and standard projected deviation, variables of Gaussian function. The analytical potential distribution model has been derived from Poisson's equation, and threshold voltage has been obtained from this model. Since threshold voltage has been defined as gate voltage when surface potential is twice of Fermi potential, threshold voltage has been derived from analytical model of surface potential. Those results of this potential model are compared with those of numerical simulation to verify this model. As a result, since potential model presented in this paper is good agreement with numerical model, the threshold voltage characteristics have been considered according to the doping profile of DGMOSFET.

• Journal of applied mathematics & informatics
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• v.17 no.1_2_3
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• pp.73-91
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• 2005

The application of Green's function in calculation of flow characteristics around submerged and floating bodies due to a regular wave is presented. It is assumed that the fluid is homogeneous, inviscid and incompressible, the flow is irrotational and all body motions are small. Two methods based on the boundary integral equation method (BIEM) are applied to solve associated problems. The first is a low order panel method with triangular flat patches and uniform distribution of velocity potential on each panel. The second method is a high order panel method in which the kernels of the integral equations are modified to make it nonsingular and amenable to solution by the Gaussian quadrature formula. The calculations are performed on a submerged sphere and some floating spheroids of different aspect ratios. The excellent level of agreement with the analytical solutions shows that the second method is more accurate and reliable.

• Proceedings of the KIEE Conference
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• 1995.07c
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• pp.1262-1264
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• 1995

The question-"How fast a electron tunnels a potential barrier?" looks like simple, but is controversy for more than 40 years. Because "tunneling" involves complicated internal processes and its definition is ambiguous. Recent experiments showed that the phase time is the best model of tunneling time among other times-for example, dwell time, Larmor clock time etc. In this paper, we simulated the tunneling time for Gaussian wave packet by program InterQuanta and compared with the phase time. In particular we focused on the effect of wave packet spreading in momentum space(or real space) which is not expressed by the phase time formula.

• Industrial Engineering and Management Systems
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• v.15 no.2
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• pp.148-155
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• 2016

Existing power plants may consume significant amounts of fuel and require high operating costs, partly because of poor electrical power output estimates. This paper suggests a continuous conditional random field (C-CRF) model to predict more precisely the full-load electrical power output of a base load operated combined cycle power plant. We introduce three feature functions to model association potential and one feature function to model interaction potential. Together, these functions compose the C-CRF model, and the model is transformed into a multivariate Gaussian distribution with which the operation parameters can be modeled more efficiently. The performance of our model in estimating power output was evaluated by means of a real dataset and our model outperformed existing methods. Moreover, our model can be used to estimate confidence intervals of the predicted output and calculate several probabilities.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.31 no.4
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• pp.162-167
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• 2008

FMEA (failure mode and effect analysis)is a widely used technique to assess or to improve reliability of product not only at early stage of design and development, but at the process and service phase during the product life cycle. In designing a service system, this study proposes a fuzzy service FMEA with the service blueprints as a tool which describes customer actions, onstage contact employees actions, backstage contact employees actions, support processes, and physical evidences, in order to analyse and inform service delivery system design. We fuzzified only two risk factors, occurrence and severity, to more effectively assess the potential failure modes in service. Proposed fuzzy risk grades are applied to Gaussian membership function, defuzzified into Fuzzy Inference System, and eventually identified the ranks on the potential fail points.

• Proceedings of the KSR Conference
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• 2008.11b
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• pp.1303-1311
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• 2008

In this paper, we analyzed the error rate performance of convolution coded 16 QAM signal in impulsive noise Environments. We used convolution code and selective combining diversity for performance improvement. We analyzed the error rate performance of 16 QAM signal in impulsive noise environments compared with gaussian noise environments. As a result of analysis, there is a BER segment where the efficiency of system does not improve until which limit to raise a signal power potential from impulsive noise environment. when the signal power potential which goes over this limit is supplied, BER efficiency improve much more.