• Coupled systems mechanics
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• v.4 no.1
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• pp.67-98
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• 2015

Numerical prediction of dynamic behavior of fully coupled saturated porous media is of great importance in many engineering problems. Specifically, static and dynamic response of soils - porous media with pores filled with fluid, such as air, water, etc. - can only be modeled properly using fully coupled approaches. Modeling and simulation of static and dynamic behavior of soils require significant Verification and Validation (V&V) procedures in order to build credibility and increase confidence in numerical results. By definition, Verification is essentially a mathematics issue and it provides evidence that the model is solved correctly, while Validation, being a physics issue, provides evidence that the right model is solved. This paper focuses on Verification procedure for fully coupled modeling and simulation of porous media. Therefore, a complete Solution Verification suite has been developed consisting of analytical solutions for both static and dynamic problems of porous media, in time domain. Verification for fully coupled modeling and simulation of porous media has been performed through comparison of the numerical solutions with the analytical ones. Modeling and simulation is based on the so called, u-p-U formulation. Of particular interest are numerical dispersion effects which determine the level of numerical accuracy. These effects are investigated in detail, in an effort to suggest a compromise between numerical error and computational cost.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.2
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• pp.114-120
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• 2000

Fossil power plant availability is significantly affected by gradual degradations of equipment as operation of the plant continues. It is quite important to determine whether or not to replace some equipment and when to replace the equipment. Performance calculation and analysis can provide the information. Robustness in the performance calculation can be increased by using verification ＆ validation of measured input data. We suggest new algorithm in which estimation relation for validated measurement can be obtained using correlation between measurements. Input estimation model is obtained using design data and acceptance measurement data of domestic 16 fossil power plant. The model consists of finding mostly correlated state variable in plant state and mapping relation based on the model and current state of power plant.

• Korean Journal of Computational Design and Engineering
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• v.14 no.4
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• pp.225-233
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• 2009

The objective of this paper is to examine a construction method and verify PLC logic using the logical modeling and simulation of a virtual plant has complex manufacturing system and the domain of application is car body assembly line of automotive industrial operated by PLC Program. The proposed virtual plant model for the analysis of the construction method consists of three types of components which are virtual device, intermediary transfer and controller is modeled by logical model but it the case of the verification of PLC program, HMI and PLC logic in the field substitute for the controller. The implementation of the proposed virtual plant model is conducted PLC Studio which is an object-oriented modeling language based on logical model. As a result, proposed methods enable 3D graphics is designed in the analysis step to use for verification of PLC program without special efforts.

• JSTS:Journal of Semiconductor Technology and Science
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• v.10 no.2
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• pp.160-164
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• 2010

The radio frequency (RF) model of SOI FinFETs with gate length of 40 nm is verified by using a 3-dimensional (3-D) device simulator. This paper shows the equivalent circuit model which can be used in the circuit analysis simulator. The RMS modeling error of Y-parameter was calculated to be only 0.3 %.

• IEIE Transactions on Smart Processing and Computing
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• v.2 no.5
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• pp.277-281
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• 2013

Modern speaker verification systems based on support vector machines (SVMs) use Gaussian mixture model (GMM) supervectors as their input feature vectors, and the maximum a posteriori (MAP) adaptation is a conventional method for generating speaker-dependent GMMs by adapting a universal background model (UBM). MAP adaptation requires the appropriate amount of input utterance due to the number of model parameters to be estimated. On the other hand, with limited utterances, unreliable MAP adaptation can be performed, which causes adaptation noise even though the Bayesian priors used in the MAP adaptation smooth the movements between the UBM and speaker dependent GMMs. This paper proposes a sparse MAP adaptation method, which is known to perform well in the automatic speech recognition area. By introducing sparse MAP adaptation to the GMM-SVM-based speaker verification system, the adaptation noise can be mitigated effectively. The proposed method utilizes the L0 norm as a regularizer to induce sparsity. The experimental results on the TIMIT database showed that the sparse MAP-based GMM-SVM speaker verification system yields a 42.6% relative reduction in the equal error rate with few additional computations.

• Journal of Information Processing Systems
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• v.14 no.4
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• pp.807-823
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• 2018

Speaker verification system performance depends on the utterance of each speaker. To verify the speaker, important information has to be captured from the utterance. Nowadays under the constraints of limited data, speaker verification has become a challenging task. The testing and training data are in terms of few seconds in limited data. The feature vectors extracted from single frame size and rate (SFSR) analysis is not sufficient for training and testing speakers in speaker verification. This leads to poor speaker modeling during training and may not provide good decision during testing. The problem is to be resolved by increasing feature vectors of training and testing data to the same duration. For that we are using multiple frame size (MFS), multiple frame rate (MFR), and multiple frame size and rate (MFSR) analysis techniques for speaker verification under limited data condition. These analysis techniques relatively extract more feature vector during training and testing and develop improved modeling and testing for limited data. To demonstrate this we have used mel-frequency cepstral coefficients (MFCC) and linear prediction cepstral coefficients (LPCC) as feature. Gaussian mixture model (GMM) and GMM-universal background model (GMM-UBM) are used for modeling the speaker. The database used is NIST-2003. The experimental results indicate that, improved performance of MFS, MFR, and MFSR analysis radically better compared with SFSR analysis. The experimental results show that LPCC based MFSR analysis perform better compared to other analysis techniques and feature extraction techniques.

• Journal of Korean Society on Water Environment
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• v.31 no.5
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• pp.507-522
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• 2015

In this study, some of the model verification results of STREAM (Spatio-Temporal River-basin Ecohydrology Analysis Model), a newly-developed hybrid watershed model, are presented for the runoff processes of nonpoint source pollution. For verification study of STREAM, the model was applied to a test watershed and a sensitivity analysis was also carried out for selected parameters. STREAM was applied to the Mankyung River Watershed to review the applicability of the model in the course of model calibration and validation against the stream flow discharge, suspended sediment discharge and some water quality items (TOC, TN, TP) measured at the watershed outlet. The model setup, simulation and data I/O modules worked as designed and both of the calibration and validation results showed good agreement between the simulated and the measured data sets: NSE over 0.7 and $R^2$ greater than 0.8. The simulation results also include the spatial distribution of runoff processes and watershed mass balance at the watershed scale. Additionally, the irrigation process of the model was examined in detail at reservoirs and paddy fields.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.06a
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• pp.337-338
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• 2008

• International Journal of Highway Engineering
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• v.17 no.4
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• pp.25-31
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• 2015

PURPOSES: Implementation and verification of the simple linear cohesive viscoelastic contact model that can be used to simulate dynamic behavior of sticky aggregates. METHODS: The differential equations were derived and the initial conditions were determined to simulate a free falling ball with a sticky surface from a ground. To describe this behavior, a combination of linear contact model and a cohesive contact model was used. The general solution for the differential equation was used to verify the implemented linear cohesive viscoelastic API model in the DEM. Sensitivity analysis was also performed using the derived analytical solutions for several combinations of damping coefficients and cohesive coefficients. RESULTS : The numerical solution obtained using the DEM showed good agreement with the analytical solution for two extreme conditions. It was observed that the linear cohesive model can be successfully implemented with a linear spring in the DEM API for dynamic analysis of the aggregates. CONCLUSIONS: It can be concluded that the derived closed form solutions are applicable for the analysis of the rebounding behavior of sticky particles, and for verification of the implemented API model in the DEM. The assumption of underdamped condition for the viscous behavior of the particles seems to be reasonable. Several factors have to be additionally identified in order to develop an enhanced contact model for an asphalt mixture.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.2
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• pp.201-210
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• 2023

Deep learning-based face verificattion model show high performance and are used in many fields, but there is a possibility the user's face image may be leaked in the process of inputting the face image to the model. Althoughde-identification technology exists as a method for minimizing the exposure of face features, there is a problemin that verification performance decreases when the existing technology is applied. In this paper, after combining the face features of other person, a de-identified face image is created through StyleGAN. In addition, we propose a method of optimizingthe combining ratio of features according to the face verification model using HopSkipJumpAttack. We visualize the images generated by the proposed method to check the de-identification performance, and evaluate the ability to maintain the performance of the face verification model through experiments. That is, face verification can be performed using the de-identified image generated through the proposed method, and leakage of face personal information can be prevented.