• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.12
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• pp.3-9
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• 2012

In this paper, we present novel analysis results of sonar communication using parametric array. We consider transducer diameter, primary frequency, difference frequency and acoustic power as analysis parameters of communication performance. We calculate theoretical BER(Bit Error Rate) and channel capacity of MIMO(Multi Input and Multi Output) communication system. By considering practical parameters, we obtain optimum difference frequency generation condition. The obtained primary frequency is 560 kHz, difference frequency 45kHz and acoustic power is 28.05Watt. For BER of $10^{-4}$, the range gain of parametric array communication is 3.35km compared to primary frequency communication. For channel capacity of 10bps/Hz, the SISO and $2{\times}2$ MIMO communication range of parametric array communication are 3.8km and 3.98km respectively, while primary frequency communication range is 0.83km.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.5
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• pp.701-706
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• 2007

Recently, a number of researches about linear magnetorheological(MR) damper using valve-mode characteristics of MR fluid have sufficiently undertaken, but researches about rotary MR damper using shear-mode characteristics of MR fluid are not enough. In this paper, we performed vibration control of shear-mode MR damper for unlimited rotating actuator of mobile robot. Also fuzzy logic based vibration control for shear-mode MR damper is suggested. The parameters, like scaling factor of input/output and center of the triangular membership functions associated with the different linguistic variables, are tuned by genetic algorithm. Simulation results demonstrate the effectiveness of the fuzzy-skyhook controller for vibration control of shear-mode MR damper under impact force.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.395-395
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• 2000

Optimization of existing processes becomes more important than the past as environmental problems and concerns about energy savings stand out. When we can model a process mathematically, we can easily optimize it by using the model as constraints. However, modeling is very difficult for most chemical processes as they include numerous units together with their correlation and we can hardly obtain parameters. Therefore, optimization that is based on the process models is, in turn, hard to perform. Especially, f3r unknown processes, such as bioprocess or microelectronics materials process, optimization using mathematical model (first principle model) is nearly impossible, as we cannot understand the inside mechanism. Consequently, we propose a few optimization method using empirical model evolutionarily instead of mathematical model. In this method, firstly, designing experiments is executed fur removing unecessary experiments. D-optimal DOE is the most developed one among DOEs. It calculates design points so as to minimize the parameters variances of empirical model. Experiments must be performed in order to see the causation between input variables and output variables as only correlation structure can be detected in historical data. And then, using data generated by experiments, empirical model, i.e. response surface is built by PLS or MLR. Now, as process model is constructed, it is used as objective function for optimization. As the optimum point is a local one. above procedures are repeated while moving to a new experiment region fur finding the global optimum point. As a result of application to the pulp digester benchmark model, kappa number that is an indication fur impurity contents decreased to very low value, 3.0394 from 29.7091. From the result, we can see that the proposed methodology has sufficient good performance fur optimization, and is also applicable to real processes.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.297-299
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• 2021

Predicting future productivity of tight oil is an important task for analyzing residual oil recovery and reservoir behavior. In general, productivity prediction is made using the decline curve analysis(DCA). In this study, we intend to propose an effective model for predicting future production using deep learning-based recurrent neural networks(RNN), LSTM, and GRU algorithms. As input variables, the main parameters are oil, gas, water, which are calculated during the production of tight oil, and the type curve calculated through various cluster analyzes. the output variable is the monthly oil production. Existing empirical models, the DCA and RNN models, were compared, and an optimal model was derived through hyperparameter tuning to improve the predictive performance of the model.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.38 no.11
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• pp.791-803
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• 2001

Mach-Zehnder type traveling-wave Ti：LiNb $O_3$ optical modulators were designed and fabricated. Optimum parameters of optical waveguides were calculated by means of the FDM. Design of CPW traveling-wave electrodes were performed by the FEM in the active region and by the CMM in the input/output section to obtain the conditions of MW effective index and impedance matching. From the measured S parameters, MW characteristics of the traveling-wane electrodes were extracted to be ${\alpha}_m$=0.05426 $\sqrt{f}$, $N_{eff}$=2.2025, and $Z_{c}$=39 ${\Omega}$. The calculated optical response R($\omega$) showed the 3 dB bandwidth of 10 GHz.z..

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.9
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• pp.862-876
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• 1991

In this theses, the procedure for finding the equivalent immittance of an n-line coupled structures is presented in terms of the normal mode parameters of the n-line coupled system. The above generalized equations can be applied to the various Coupled structures including directional couplers, DC blocks, bandpass/band elimination filters, and various other uniformly coupled filters. The design equations are based on a simplified TEM(Quasi TEM) mode. The obtained results and the definition of the scattering parameters for a general coupled line four port with arbitrary terminations are used to present the procedure to determine the optimum physical dimensions matching the given load impedances connected to input, output port. Multiple coupled rnicrostrip two-port with three lines circuit designed shows little discrepancy between the conventional method and this one. Four port with five lines were fabricated on teflon substrate($e$r=2.55) with its thickness h=l.588mm designed at the center frequency, 4 GHz. Their measured results are fairly close to the ones by computation.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.1-14
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• 2010

The back-propagation neural network (BPN) has long been successfully applied in bankruptcy prediction problems. Despite its wide application, some major issues must be considered before its use, such as the network topology, learning parameters and normalization methods for the input and output vectors. Previous studies on bankruptcy prediction with BPN have shown that many researchers are interested in how to optimize the network topology and learning parameters to improve the prediction performance. In many cases, however, the benefits of data normalization are often overlooked. In this study, a genetic algorithm (GA)-based normalization transform, which is defined as a linearly weighted combination of several different normalization transforms, will be proposed. GA is used to extract the optimal weight for the generalization. From the results of an experiment, the proposed method was evaluated and compared with other methods to demonstrate the advantage of the proposed method.

• Korean Journal of Remote Sensing
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• v.26 no.5
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• pp.537-547
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• 2010

The importance of vegetation in studies of global climate and biogeochemical cycles is well recognized. Especially. the FPAR (fraction of photosynthetically active radiation) is one of the important parameters in ecosystem productivity and carbon budget models. Therefore, accurate estimates of vegetation parameters are increasingly important in environmental impact assessment studies. In this study, optical FPAR using the Terra MODIS (MODerate resolution Imaging Spectroradiometer), SPOT VEGETATION and ECOCLIMAP data reproduced on the Korean peninsula. We applied the empirical method which is usually estimated as a linear or nonlinear function of vegetation indices. As results, we estimated the accurate expression which is 0.9039 of $R^2$ in cropland and 0.7901 of $R^2$ in forest. Finally, this study could be demonstrated to calibrate that produced FPAR while the overall pattern and random noise through the comparative analysis of FPAR on the reference data. Optimal use of input parameter on the Korean peninsula should be helping the accuracy of output as well as the improved quality of research.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.14 no.1
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• pp.109-117
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• 2000

A full bridge type double resonant high frequency resonant inverter to give VVVF function in the inverter used as power source of induction heating at high frequency is presented in this paper. This proposed inverter can reduce distribution of the switching current because of using the current of serial resonant circuit to the input current of the parallel one and this paper also realize the output control of independence irrespective of the switching frequency using Phase-shift. The analysis of the proposed circuit is generally described by using the normalized parameters. Also, the principle of basic operating and the its characteristics are estimated by the parameters, such as switching frequency, the variation of phase angle ($\phi$) of Phase-shift.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.755-762
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• 2004

In our country, when the replacement for individual components of equipment in nuclear power plants is required, establishment of individual criteria i.e. Required Response Spectra(RRS) of seismic test/analysis for the component is very difficult because of the absence of Test Response Spectra(TRS) for the individual component to be replaced, from the existing qualification documents. In this case, it is required to perform the structural analysis for the nuclear equipment including the components to be replaced. After the structural analysis, Analysis Response Spectra(ARS) at the point of the component shall be generated and used for seismic test of the component. However, as of today, no standard program authorized for the response spectra generation by using the structural analysis exists in korea. Because of above reason, the STAR-Egs computer program was developed by using the method which calculates directly the expected response spectrum(frequency vs. acceleration type) of the selected points in the nuclear equipment with input spectrum(Required Response Spectra, RRS), based on the dynamic characteristics of the Finite Element(FE) model that is equivalent to the nuclear equipment. The STAR-Egs controls ANSYS/I-DEAS commercial software and automatically extract modal parameters of the FE model. The STAR-Egs calculates response spectrum using the established algorithm based on the extracted modal parameters, too. Reliance on the calculation result of the STAR-Egs was verified through comparison output with the result of MATLAB commercial software based on the identical algorithm. Moreover, actual seismic testing was performed as per IEEE344-1987 for the purpose of program verification by comparison of the FE analysis results.