• Journal of the Korea Computer Industry Society
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• v.4 no.10
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• pp.611-620
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• 2003

This paper presents improved GUI based analysis tool o( load flow of power system (or contingency. It is effective tool to facilitate the teaching and learning of load flow of power system. This software is the named of PFGUI(Power Flow GUI) that written in TooIBookII of Asymetrix. The PFGUI is friendly for study for power system operation and control because picture provide a better visualizing of relationships between input parameters and effects than a tabula type result. This PFGUI enables topology and the output data of load flow for line outages to be shown on same picture page. Users can input the system data for power flow on the the picture and can easily see the the result diagram of bus voltage, bus power, line flow. It is also observe the effects of different types of variation of tap, shunt capacitor, loads level, line outages. Proposed PFGUI has been studied on the Ward-Hale 6-Bus system.

• Journal of Korean Society on Water Environment
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• v.27 no.4
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• pp.533-541
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• 2011

Algal blooms have caused problems for drinking water as well as eutrophication. However it is difficult to control algal blooms by current warning manual in rainy season because the algal blooms happen in a few days. The water quality data, which have high correlations with Chlorophyll-a on Daecheongho station, were analyzed and chosen as input data of Artificial Neural Networks (ANN) for training pattern changes. ANN was applied to early forecasting of algal blooms, and ANN was assessed by forecasting errors. Water temperature, pH and Dissolved oxygen were important factors in the cross correlation analysis. Some water quality items like Total phosphorus and Total nitrogen showed similar pattern to the Chlorophyll-a changes with time lag. ANN model (No. 3), which was calibrated by water temperature, pH and DO data, showed lowest error. The combination of 1 day, 3 days, 7 days forecasting makes outputs more stable. When automatic monitoring data were used for algal bloom forecasting in Daecheong reservoir, ANN model must be trained by just input data which have high correlation with Chlorophyll-a concentration. Modular type model, which is combined with the output of each model, can be effectively used for stable forecasting.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4D
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• pp.573-580
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• 2006

The Saturation headway is a major parameter in estimating the intersection capacity and setting the signal timing. But Existing algorithms are still far from being robust in dealing with factors related to the variation of saturation headways at signalized intersections. So this study apply the fuzzy inference system using ANFIS. The ANFIS provides a method for the fuzzy modeling procedure to learn information about a data set, in order to compute the membership function parameters that best allow the associated fuzzy inference system to track the given input/output data. The climate conditions and the degree of brightness were chosen as the input variables when the rate of heavy vehicles is 10-25 %. These factors have the uncertain nature in quantification, which is the reason why these are chosen as the fuzzy variables. A neuro-fuzzy inference model to estimate saturation headways at signalized intersections was constructed in this study. Evaluating the model using the statistics of $R^2$, MAE and MSE, it was shown that the explainability of the model was very high, the values of the statistics being 0.993, 0.0289, 0.0173 respectively.

• Journal of the Korean Society of Propulsion Engineers
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• v.15 no.6
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• pp.78-90
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• 2011

This paper surveys the recent research activities regarding dynamical modeling of thermo-acoustic instabilities which are fundamental to actively control such phenomena in gas-turbine engines, rockets, and etc. For this, we introduce reduced-order modeling approaches, mainly conducted after 1990s. Particularly, we survey grey-box approaches, which determine the structure of the model based on physical rules and use system's input-output data for estimating parameters of the model. We also introduce black-box approaches using model structures without physics-based interpretation. Finally, we briefly discuss future directions and feasibilities of the research in this field.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.17 no.1
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• pp.48-56
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• 2018

Due to the growing concerns of energy resource depletion and environmental destruction, the mass production of microalgae has been studied. The scale-up of a photobioreactor (PBR) is required for the mass production of biomass. In this paper, the geometric parameters and oxygen transfer rate (OTR) are considered, to scale up a flat panel photobioreactor (FP PBR). The PBR is designed using the goal-driven optimization (GDO) method to accomplish the scale-up. The local sensitivity of each output parameter with respect to the input parameter is analyzed through the design of experiment (DOE), and the design candidates are evaluated with the screening sampling method. The volumetric mass transfer coefficient is measured by the dynamic method.

• Journal of the Korea Society of Computer and Information
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• v.5 no.2
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• pp.115-120
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• 2000

This papers describes two low-noise amplifiers that use the Hewlett-Packard ATF-10236 low noise GaAs FET device, The actual measured performance of the amplifiers compares favorably to that predicted by the computer simulation(ADS) the noise figure of the 1575MHz amplifier was measured at 1.78dB which is lower that 2dB as specified. Measurement gam measured 33.0075dB which is within 35dB$\pm$0.5㏈ of the GPS specification. Network Analyzer(HP8510) is used to measure all the s-parameters and Noise Figure meter(HP8970B) is used to measure noise figure. As the result of experiment, gain, input VSWR, output VSWR is within the GPS specification sufficiently.

• The Journal of Information Technology
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• v.5 no.4
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• pp.73-79
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• 2002

In this paper, I will propose the Niche-Meta Genetic Algorithm that has a multi-mutation operator for design of fuzzy controller. The gene in the proposed algorithm is formed by several parameters that represent the crossover rate, mutation rate and input-output membership functions. The optimization of fuzzy membership function is performed with local search on sub-population and the optimal structure is constructed with global search on total-population. The multi-mutation is selected under basis of the result of local evolution. A simulation for 2 D.O.F wheeled-mobile robot is showed to prove the efficiency of the proposed algorithm

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.2
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• pp.390-396
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• 2010

An 80MHz surface acoustic wave (SAW)-based gyroscope utilizing a progressive wave was developed on a piezoelectric substrate. The developed sensor consists of two SAW oscillators in which one is used for sensing element and has metallic dots in the cavity between input and output IDTs. The other is used for a reference element. Coupling of mode (COM) modeling was conducted to determine the optimal device parameters prior to fabrication. According to the simulation results, the device was fabricated and then measured on a rate table. When the device was subjected to an angular rotation, oscillation frequency differences between the two oscillators were observed because of the Coriolis force acting on the metallic dots. Depending on the angular rate, the difference of the oscillation frequency was modulated. The obtained sensitivity was approximately 52.35 Hz/deg.s within the angular rate range of 0~1000 deg/s. The performances of devices with three IDT structures for two kinds of piezoelectric substrates were characterized. Good thermal stability was also observed during the evaluation process.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.49 no.8
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• pp.557-564
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• 2000

A very simple control approach using neural network for the robust position control of a Permanent Magnet Synchronous Motor(PMSM) is presented. The linear quadratic controller plus feedforward neural network is employed to obtain the robust PMSM system approximately linearized using field-orientation method for an AC servo. The neural network is trained in on-line phases and this neural network is composed by a feedforward recall and error back-propagation training. Since the total number of nodes are only eight, this system can be easily realized by the general microprocessor. During the normal operation, the input-output response is sampled and the weighting value is trained multi-times by error back-propagation method at each sample period to accommodate the possible variations in the parameters or load torque. In addition, the robustness is also obtained without affecting overall system response. This method is realized by a floating-point Digital Signal Processor DS1102 Board (TMS320C31).

• Journal of the Korea Computer Industry Society
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• v.5 no.9
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• pp.851-858
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• 2004

This paper presents improved teaching and learning GUI for easily analysis tool of load flow of power system with database function for searching solution. In this paper includes not only contingency analysis function but also searching function of conditional solution sets from database of solution for various load levels. The GUI is friendly for study for power system operation and control because picture provide a better visualizing of relationshipsbetween input parameters and effects than a tabula type result. This GUI enables topologyand the output data of load flow for line outages to be shown on same picture page. Userscan input the system data for power flow on the the picture and can easily see the theresult diagram of bus voltage, bus power, line flow. It is also observe the effects of different types of variation of tap, shunt capacitor, loads level, line outages. Proposed GUI has been studied on the Ward-Hale 6-Bus system.