• Speech Sciences
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• v.10 no.3
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• pp.251-261
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• 2003

There has been many research efforts to overcome the problems of speech recognition in noisy conditions. Among the noise-robust speech recognition methods, model-based adaptation approaches have been shown quite effective. Particularly, the PMC (parallel model combination) method is very popular and has been shown to give considerably improved recognition results compared with the conventional methods. In this paper, we experimented with the VTS (vector Taylor series) algorithm which is also based on the model parameter transformation but has not attracted much interests of the researchers in this area. To verify the effectiveness of it, we employed the algorithm in the continuous density HMM (Hidden Markov Model). We compared the performance of the VTS algorithm with the PMC method and could see that the it gave better results than the PMC method.

• International Journal of Precision Engineering and Manufacturing
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• v.4 no.6
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• pp.12-19
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• 2003

This paper presents the effect of boundary conditions in various failure pressure models published for the estimation of failure pressure. Furthermore, this approach is extended to the failure prediction with the aid of a failure probability model. The first order Taylor series expansion of the limit state function is used in order to estimate the probability of failure associated with each corrosion defect in buried pipelines for long exposure period with unit of years. A failure probability model based on the von-Mises failure criterion is adapted. The log-normal and standard normal probability functions for varying random variables are adapted. The effects of random variables such as defect depth, pipe diameter, defect length, fluid pressure, corrosion rate, material yield stress, material ultimate tensile strength and pipe thickness on the failure probability of the buried pipelines are systematically investigated for the corrosion pipeline by using an adapted failure probability model and varying failure pressure model.

• Textile Coloration and Finishing
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• v.19 no.6
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• pp.7-11
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• 2007

A prediction model for yarn density profile was developed using the neural network methodology. The neural network model developed traces mass densities of a yarn within a section and predicts the mass profiles of the next yarn segment yet to be measured. The model does not require an assumption on the existence of a relationship between the past and future data sets. Four high-draft yarns made under different processing conditions were employed in order to test the performance of the model developed. It was shown that the model could predict the yarn density profiles without a significant error.

• Structural Engineering and Mechanics
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• v.43 no.2
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• pp.163-177
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• 2012

This paper presents a LMI(linear matrix inequality)-based fuzzy approach of modeling and active vibration control of geometrically nonlinear flexible plates with piezoelectric materials as actuators and sensors. The large-amplitude vibration characteristics and dynamic partial differential equation of a piezoelectric flexible rectangular thin plate structure are obtained by using generalized Fourier series and numerical integral. Takagi-Sugeno (T-S) fuzzy model is employed to approximate the nonlinear structural system, which combines the fuzzy inference rule with the local linear state space model. A robust fuzzy dynamic output feedback control law based on the T-S fuzzy model is designed by the parallel distributed compensation (PDC) technique, and stability analysis and disturbance rejection problems are guaranteed by LMI method. The simulation result shows that the fuzzy dynamic output feedback controller based on a two-rule T-S fuzzy model performs well, and the vibration of plate structure with geometrical nonlinearity is suppressed, which is less complex in computation and can be practically implemented.

• Computational Structural Engineering
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• v.2 no.1
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• pp.47-53
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• 1989

An efficient model for three-dimensional analysis of multistory structures with flexible floor diaphrgms is proposed in this paper. Three-dimensional analysis of a building structure using a finite element model requires tedious input data preparation, longer computation time, and larger computer memory. The model proposed in this study is developed by assembling a series of two-dimensional resisting systems and is considered to overcome the shortcomings of a three-dimensional finite element model without deteriorating the accuracy of analysis results. Static and dynamic analysis results obtained using the proposed model are in excellent agreement with those obtained using three-dimensional finite element models in terms of displacement, periods, and mode shapes. Effects of floor diaphragm flexibility on seismic response of multistory building structures are investigated.

• Fisheries and Aquatic Sciences
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• v.1 no.2
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• pp.168-179
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• 1998

Circulation in the Jinhae Bay in the southern sea of Korea is examined using the Princeton Ocean Model (POM) with a free surface in a sigma coordinate, governed by primitive equations. The model well corresponds to the time series of the observed velocities at several layers obtained from a long-term mooring observation. In the residual velocity field of the model, persistent downward flow fields are formed along the central deep regions in the bay, and they are caused by bottom topographic effect. In addition, a comparison between a depth-averaged (2D) model and the POM is given, and a dependance of the results on bottom drag coefficient is also examined.

• Nuclear Engineering and Technology
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• v.42 no.3
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• pp.259-270
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• 2010

New generation nuclear reactors are designed using advanced safety analysis methods. A thorough understanding of different interacting physical phenomena is necessary to avoid underestimation and overestimation of consequences of off-normal transients in the reactor safety analysis results. This feature requires a multiphysics reactor simulation model. In this context, a coupled dynamics model based on a multiphysics formulation is developed indigenously for the transient analysis of large pressurized VVER reactors. Major simplifications are employed in the model by making several assumptions based on the physics of individual phenomenon. Space and time grids are optimized to minimize the computational bulk. The capability of the model is demonstrated by solving a series of international (AER) benchmark problems for VVER reactors. The developed model was used to analyze a number of reactivity transients that are likely to occur in VVER reactors.

• Korean Management Science Review
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• v.33 no.1
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• pp.35-47
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• 2016

Generation of electricity using wind power has received considerable attention worldwide in recent years mainly due to its minimal environmental impact. However, volatility of wind power production causes additional problems to provide reliable electricity to an electrical grid regarding power system operations, power system planning, and wind farm operations. Those problems require appropriate stochastic models for the electricity generation output of wind power. In this study, we review previous literatures for developing the stochastic model for the wind power generation, and propose a systematic procedure for developing a stochastic model. This procedure shows a way to build an ARIMA model of volatile wind power generation using historical data, and we suggest some important considerations. In addition, we apply this procedure into a case study for a wind farm in the Republic of Korea, Shinan wind farm, and shows that our proposed model is helpful for capturing the volatility of wind power generation.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.3004-3006
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• 2000

In this paper, we propose an optimal design method of Fuzzy-Neural Networks model with parallel structure for complex and nonlinear systems. The proposed model is consists of a multiple number of FNN connected in parallel. The proposed FNNs with parallel structure is based on Yamakawa's FNN and it uses simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rules. We use a HCM clustering and GAs to identify the structure and the parameters of the proposed model. Also, a performance index with a weighting factor is presented to achieve a sound balance between approximation and generalization abilities of the model. To evaluate the performance of the proposed model. we use the time series data for gas furnace and the numerical data of nonlinear function.

• Structural Engineering and Mechanics
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• v.41 no.1
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• pp.83-94
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• 2012

Assessment of a monumental concrete arch bridge with a total length of 210 meters having three major spans of 30 meters and a height of 65 meters, which is located in an earthquake-prone region in southern part of the country is presented in this study. Three-dimensional finite element model of the bridge was generated using a commercially available general finite element analysis software and based on the outcomes of a series of in-depth acceleration measurements that were conducted on-site, the model was refined. By using the structural parameters obtained from the dynamic and the static tests, calibrated model of the bridge structure was obtained and this model was used for necessary calculations regarding structural assessment and evaluation.