• International Journal of Control, Automation, and Systems
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• v.1 no.2
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• pp.194-202
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• 2003

In this paper, we introduce a category of Multi-FNN (Fuzzy-Neural Networks) models, analyze the underlying architectures and propose a comprehensive identification framework. The proposed Multi-FNNs dwell on a concept of fuzzy rule-based FNNs based on HCM clustering and evolutionary fuzzy granulation, and exploit linear inference being treated as a generic inference mechanism. By this nature, this FNN model is geared toward capturing relationships between information granules known as fuzzy sets. The form of the information granules themselves (in particular their distribution and a type of membership function) becomes an important design feature of the FNN model contributing to its structural as well as parametric optimization. The identification environment uses clustering techniques (Hard C - Means, HCM) and exploits genetic optimization as a vehicle of global optimization. The global optimization is augmented by more refined gradient-based learning mechanisms such as standard back-propagation. The HCM algorithm, whose role is to carry out preprocessing of the process data for system modeling, is utilized to determine the structure of Multi-FNNs. The detailed parameters of the Multi-FNN (such as apexes of membership functions, learning rates and momentum coefficients) are adjusted using genetic algorithms. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between approximation and generalization (predictive) abilities of the model. To evaluate the performance of the proposed model, two numeric data sets are experimented with. One is the numerical data coming from a description of a certain nonlinear function and the other is NOx emission process data from a gas turbine power plant.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.41 no.6
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• pp.91-98
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• 2004

This paper proposes a PCB plane model for generic SPICE circuit simulators. The proposed model reflects two frequency-dependent losses, namely skin and dielectric losses. After power/ground plane pair is divided into arrays of unit-cells, each unit-cell is modeled using a transmission line and two loss models. The loss model is composed of a resistor for DC loss, series HL ladder circuit for skin loss and series RC ladder circuit for dielectric loss. To verify the validity of the proposed model, it is compared with SPICE ac analysis using frequency-dependent resistors. Also, we show that the estimation results using the proposed model have a good correlation with that of VNA measurement for the typical PCB stack-up structure of general desktop PCs. With the proposed model, not only ac analysis but also transient analysis can be easily done for circuits including various non-linear/linear devices since the model consists of passive elements onl.

• The Journal of the Convergence on Culture Technology
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• v.6 no.3
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• pp.369-375
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• 2020

The section of this study is the geological vulnerable zone where groundwater leakage occurred through the tunnel barrier during excavation of the shield tunnel boring machine(TBM) for the construction of the electric power unit. Therefore, a Three D imensions(3D) numerical analysis was performed to analyze the actual situation from before construction to the time when the change in groundwater level occurred, and to reflect the surrounding ground conditions based on the observed change in groundwater level during construction. As a result of the study, the correlation between groundwater level change and tunnel construction around the site was identified. Therefore, it was similar to the measurement result of groundwater level at the target ground. The amount of groundwater discharge to the entrance of the tunnel construction was also similar to the actual measured result, and the numerical analysis method and modeling in this study were analyzed to reflect the site conditions.

• Journal of Convergence Society for SMB
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• v.2 no.2
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• pp.13-19
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• 2012

Various quality requirements have increased in developing embedded systems. One of those requirements in mobile embedded system is to reduce energy consumption because of limited power supply. Especially as the complexity of embedded software is increased, the interests of the software energy consumption analysis is also increased. In recent years, some studies has been carried out model-based analysis because it can be able to reflect energy consumption requirements in design phase. In this paper, we proposes a model-based energy analysis technique using SysML parametric diagram. The proposed technique designs software activity model using characteristics of parametric diagram, and then energy consumption value by the execution of the model is derived. Our technique has merit that can perform tradeoffs analysis for energy quality property between different implementations.

• Applied Chemistry for Engineering
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• v.31 no.4
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• pp.347-351
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• 2020

A material changes its physical and chemical properties through the interaction with radiation and also the neutrons, which is electronically neutral so that the penetration depth is relatively deeper than that of other radioactive way including alpha or beta ray. Therefore, the radiation damage by neutron irradiation has been intensively investigated for a long time with respect to the safety of nuclear power plants. The damage induced by neutron irradiation begins with the creation of point defects in atomic scale in the unit of picoseconds, and their progress pattern can be characterized by microstructural defects, such as dislocation loops and voids. Their morphological characteristics affect the properties of neutron-irradiated materials, therefore, it is very important to predict the microstructure at a given neutron irradiation condition. This paper briefly reviews the evolution of radiation damage induced by neutron irradiation and introduces a phase-field model that can be widely used in predicting the microstructure evolution of irradiated materials.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.9 no.6
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• pp.802-812
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• 1998

Safety related to electric field exposure for the personnel of high voltage power plant and substation is of importance. To analyze the induced current influencing on human body in this paper, we calculate directly capacitance in three dimension which is complex and time consuming, as not to separate the voltage source and the induced object using a effective modeling technique. The proposed algorithm in this paper has been applied to 765 kV high voltage transmission line to evaluate human hazard for the induced current through the case study. As the results, the short circuit current of human body has been identified in the range of 0.3 mA to 6.8 mA. Closing to transmission line, this range of short current can exceed 5 mA that ANSI recommended let-go current. Therefore, it is necessary to countermeasure such as putting on conductive clothing in live-line maintenance of transmission line.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.9
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• pp.947-952
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• 2015

To supplement energy needs and take advantage of renewable energy sources, many wind farms are currently being built in mountainous areas under the supervision of the Korean government. However, operation of these wind farms can cause serious threats to national security due to Doppler modulation from the wind turbines causing interference with military radar operating in the vicinity. Therefore it is necessary to develop methods to analyze the Doppler frequency during the operation of wind turbines and the effect on radar signals. Based on modeling of the mountainous region, blockage analysis, turbine motion and the radar signals, this paper proposes a signal processing method to extract and analyze the Doppler frequency. Simulation results showed the change of Doppler frequency over time caused by the geometry of the mountainous area and the wind turbine.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.9
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• pp.1133-1140
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• 2013

A computer model is a useful tool that provides solution via physical modeling instead of expensive testing. In reality, however, it often does not agree with the experimental data owing to simplifying assumption and unknown or uncertain input parameters. In this study, a Bayesian approach is proposed to calibrate the computer model in a probabilistic manner using the measured data. The elasto-plastic analysis of a pyrotechnically actuated device (PAD) is employed to demonstrate this approach, which is a component that delivers high power in remote environments by the combustion of a self-contained energy source. A simple mathematical model that quickly evaluates the performance is developed. Unknown input parameters are calibrated conditional on the experimental data using the Markov Chain Monte Carlo algorithm, which is a modern computational statistics method. Finally, the results are applied to determine the reliability of the PAD.

• The Journal of the Korea Contents Association
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• v.11 no.10
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• pp.234-241
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• 2011

The recent technology boom has created a new digital age. With the help of information technology consumers can have more power than ever and they use digital contents more than ever. This study relates consumer attitude to the recent digital contents using behavior about digital file-sharing. Through the use of the multimethod approach, we identify four characteristics can affect illegal digital contents using behavior. The methodology used was to take in depth look at the consumer with phenomenology as a qualitative research. We select 6 participants who have experience of digital content using. We also examine the structural configurations of the relationship between digital contents characteristics and illegal downloading intention. We surveyed 200 people who also had experience of digital content. This research gives theoretical and practical implication to the marketers related to online communication.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.2
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• pp.166-172
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• 2014

Image classification is an important problem in computer vision. However, it is a very challenging problem due to the variability, ambiguity and scale change that exists in images. In this paper, we propose a method of a hypergraph based modeling can consider the higher-order relationships of semantic attributes of a scene image and apply it to a scene image classification. In order to generate the hypergraph optimized for specific scene category, we propose a novel search method based on a probabilistic subspace method and also propose a method to aggregate the expression values of the member semantic attributes that belongs to the searched subsets based on a linear transformation method via likelihood based estimation. To verify the superiority of the proposed method, we showed that the discrimination power of the feature vector generated by the proposed method is better than existing methods through experiments. And also, in a scene classification experiment, the proposed method shows a competitive classification performance compared with the conventional methods.