• Structural Engineering and Mechanics
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• v.8 no.5
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• pp.453-464
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• 1999

Safety monitoring systems of structures generally resort to detecting possible changes of dynamic system parameters. Sensitivity analysis of these dynamic system parameters may implement these techniques. Conventional structural eigenvalue problems are discussed in the scope of those systems with deterministic parameters. Large and flexible structures, such as suspension bridges, actually possess stochastic material properties and these random properties unavoidably affect the dynamic system parameters. The sensitivity matrix of structural modal parameters to basic design variables has been established in this paper. Moreover, second order statistics of natural frequencies due to the randomness of material properties have been discussed. It is concluded from numerical analysis of a modem suspension bridge that although the second order statistics of frequencies are small relatively to the change of basic design variables, such as density of mass and modulus of elasticity, the sensitivities of modal parameters to these variables at different locations change in magnitude.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.470-473
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• 2004

In this paper, the comparison of speech feature parameters for emotion recognition is studied for emotion recognition using speech signal. For this purpose, a corpus of emotional speech data recorded and classified according to the emotion using the subjective evaluation were used to make statical feature vectors such as average, standard deviation and maximum value of pitch and energy. MFCC parameters and their derivatives with or without cepstral mean subfraction are also used to evaluate the performance of the conventional pattern matching algorithms. Pitch and energy Parameters were used as a Prosodic information and MFCC Parameters were used as phonetic information. In this paper, In the Experiments, the vector quantization based emotion recognition system is used for speaker and context independent emotion recognition. Experimental results showed that vector quantization based emotion recognizer using MFCC parameters showed better performance than that using the Pitch and energy parameters. The vector quantization based emotion recognizer achieved recognition rates of 73.3％ for the speaker and context independent classification.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.153-156
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• 1999

The technique is reported of identifying parameters in off-line process. The technique demands that closed-loop system consists of a reference and two-degree-of-freedom controllers (TDFC) in real process. A model process is the same as the real process except their parameters. Deviations are differences between the reference and the output of the plant or the model. The technique is based on minimizing identification error between the two deviations. The parameter differences between the plant and the model are characterized of mean value and of variance which are derived from the identification error. Consequently, the algorithm which identifies the unknown plant parameters is shown by minimizing the mean value and the variance, respectively, within double convergence loops. The technique is applied to course change of a ship. The plant deviation at the first trial is shown to occur in replacing the nominal parameters by the default parameters. The plant deviation at the second trial is shown to not occur in replacing the nominal parameters by the identified parameters. Hence, the identification technique is confirmed to be feasible in the real field.

• Phonetics and Speech Sciences
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• v.9 no.4
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• pp.91-97
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• 2017

This study categorizes several voice characteristics by subjective listening assessment, and investigates correlation between voice characteristics and speech feature parameters. A model was developed to classify voice characteristics into the defined categories using SVM algorithm. To do this, we extracted various speech feature parameters from speech database for men in their 20s, and derived statistically significant parameters correlated with voice characteristics through ANOVA analysis. Then, these derived parameters were applied to the proposed SVM model. The experimental results showed that it is possible to obtain some speech feature parameters significantly correlated with the voice characteristics, and that the proposed model achieves the classification accuracies of 88.5% on average.

• Korean Journal of Computational Design and Engineering
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• v.4 no.4
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• pp.355-359
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• 1999

This paper presents a method for determining machining parameters in electrical discharge machining process (EDM) based on discharge area. The parameters are the peak value of currents, the pulse-on time, and the pulse-off time, on which the EDM performance depends chiefly. The optimal machining parameters are closely related on discharge area, which can be calculated from a tool electrode and a discharge height. In the paper the discharge area is obtained from NC code for machining the tool electrode instead of its geometric model. The method consists of following three steps. First a Z-Map model is constructed from the NC code. Secondly, the discharge area is obtained from the Z-Map model and a Z-height. Finally, the machining parameters are calculated from the discharge area. An introduced example shows that the machining parameters are calculated by the using a Z-map model obtained from the machining data for a tool electrode.

• Journal of Korean Society for Geospatial Information Science
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• v.13 no.2 s.32
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• pp.39-43
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• 2005

In this study, we analyzed the accuracy of the conversion from DLT parameters to physical camera parameters and optimized the use of DLT model for non-metric cameras in photogrammetric tasks. Using the simulated data, we computed two sets of physical camera parameters from DLT parameters and Bundle adjustment for various cases. Comparing two results based on the RMSE values of check points, we optimized the arrangement of GCPs for DLT.

• Nuclear Engineering and Technology
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• v.30 no.3
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• pp.235-244
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• 1998

The parametric model method determines the accident source term which is Presented by a set of source term parameters. In this method, the cumulative distribution of each source term parameter should be derived for its uncertainty analysis. This paper introduces a method of generating the parameters in the form of cumulative distribution using MAAP version 4.0. In MAAP, there are model parameters which could incorporate uncertain physical and/or chemical phenomena. In general, the model parameters do not have a point value but a range. In this paper, considering that, the input values of model parameters influencing each parameter are sampled using LHS. Then, the computation results are shown in cumulative distribution form. For a case study, the CDFs of FCOR and WES of Kori Unit 1 are derived. The target scenarios for the computation are the ones whose initial events are large LOCA, small LOCA and transient, respectively. It is found that the computed CDF's in this study are consistent to those of NUREG-1150 and the use of MAAP is proven to be adequate in assessing the parameters of the severe accident source term.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.11 no.5
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• pp.347-352
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• 1998

In this paper, the extraction and optimization of SPICE parameters on SONOSFET for NVSM circuit design were discussed. SONOSFET devices with different channel widths and lengths were fabricated using conventional 1.2 um n-well CMOS process. And, electric properties for dc parameters and capacitance parameters were measured on wafer. SPICE parameters for the SONOSFET were extracted from the UC Berkeley level 3 model for the MOSFET. And, local optimization of Ids-Vgs curves has carried out in the bias region of subthreshold, linear, saturation respectively. Finally, the extracted SPICE parameters were optimized globally by comparing drain current (Ids), output conductance(gds), transconductance(gm) curves with theoretical curves in whole region of bias conditions. It is shown that the conventional model for the MOSFET can be applied to the SONOSFET modeling except sidewalk effect.

• Proceedings of the IEEK Conference
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• 2000.11a
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• pp.357-360
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• 2000

This paper describes a parameter extraction method for HBT(Heterojunction Bipolar Transistor) equivalent circuit model without measurements of special test structures or numerical optimizations. Instead, all equivalent circuit parameters are calculated analytically from small-signal S-parameters measured under different bias conditions. These values being extracted from the cutoff mode can be used to extract intrinsic parameters at the active mode. This method yields a deviation of about 1.3 % between the measured and modeled S-parameters.

• Textile Coloration and Finishing
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• v.11 no.5
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• pp.38-43
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• 1999

A calculation method of optimum parameters on dual adsorption isotherm system was examined. The optimum parameters were obtained by non-linear regression analysis based upon a limited solute concentration of dual adsorption isotherm. The results were analyzed with adducing experimental data of formerly reported treaties. The percentage mean deviation of dual adsorption equation calculated with optimum parameters was less than about 5% of experimental data, which was far less than results obtained with parameters of the adduced treatises.