• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.908-909
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• 2008

A kind of fluorescent lamps CCFL(Cold Cathod Fluorescent Lamp) is used for backlight of LCD and the demand of backlight for TV is getting more. CCFL is also used in a backlight for TFT-LCD panel. BLU(Backlight Unit) has lots of components so it looks a electrical product. As the size of LCD display is larger with increasing of the demand, to drive CCFL inverter is more important. Therefore, a sort of modeling to drive 4 lamps with a transformer is used and we have a simulation test with proposed modeling so we can take some data from the test. The utility of the proposed modeling is verified through using for 30-inch LCD backlight with the data.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.302-305
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• 1996

In this paper, an optimal identification method using fuzzy-neural networks is proposed for modeling of nonlinear complex systems. The proposed fuzzy-neural modeling implements system structure and parameter identification using the intelligent schemes together with optimization theory, linguistic fuzzy implication rules, and neural networks(NNs) from input and output data of processes. Inference type for this fuzzy-neural modeling is presented as simplified inference. To obtain optimal model, the learning rates and momentum coefficients of fuzz-neural networks(FNNs) and parameters of membership function are tuned using genetic algorithm(GAs). For the purpose of its application to nonlinear processes, data for route choice of traffic problems and those for activated sludge process of sewage treatment system are used for the purpose of evaluating the performance of the proposed fuzzy-neural network modeling. The show that the proposed method can produce the intelligence model w th higher accuracy than other works achieved previously.

• Wind and Structures
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• v.22 no.5
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• pp.543-553
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• 2016

The growing complexity of modern technological systems requires more flexible and powerful reliability analysis tools. Existing tools encounter a number of limitations including lack of modeling power to address components interactions for complex systems and lack of flexibility in handling component failure distribution. We propose a reliability modeling framework based on the Bayesian network (BN). It can combine historical data with expert judgment to treat data scarcity. The proposed methodology is applied to wind turbines reliability analysis. The observed result shows that a BN based reliability modeling is a powerful potential solution to modeling and analyzing various kinds of system components behaviors and interactions. Moreover, BN provides performing several inference approaches such as smoothing, filtering, what-if analysis, and sensitivity analysis for considering system.

• Transactions on Electrical and Electronic Materials
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• v.7 no.4
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• pp.210-214
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• 2006

In this paper, two sampling methods which are Latin hypercube sampling (LHS) and simple random sampling were. compared to improve the modeling speed of neural network model. Sampling method was used to generate initial weights and bias set. Electrical characteristic data for $HfO_2$ thin film was used as modeling data. 10 initial parameter sets which are initial weights and bias sets were generated using LHS and simple random sampling, respectively. Modeling was performed with generated initial parameters and measured epoch number. The other network parameters were fixed. The iterative 20 minimum epoch numbers for LHS and simple random sampling were analyzed by nonparametric method because of their nonnormality.

• Journal of the Korea Society of Computer and Information
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• v.7 no.1
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• pp.54-61
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• 2002

In this paper, we implement the XML modeling and data modeling by the class diagram that is made by the use case after drawing out the sequence diagram. For the XML modeling, the guiding line to map the UML classes on the XML document will be presented. Then, an example to generate the ie DTD from the UML classes will be shown under the presented guiding line. In the data modeling, the transformation method from the In classes into the object-oriented database also will be proposed. Finally, we will give an example developed by the Proposed transformation method.

• The Korean Journal of Emergency Medical Services
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• v.26 no.2
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• pp.19-35
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• 2022

Purpose: This study aimed to identify research topics in the emergency medical technician (EMT) field and examine research trends. Methods: In this study, 261 research papers published between January 2000 and May 2022 were collected, and EMT research topics and trends were analyzed using topic modeling techniques. This study used a text mining technique and was conducted using data collection flow, keyword preprocessing, and analysis. Keyword preprocessing and data analysis were done with the RStudio Version 4.0.0 program. Results: Keywords were derived through topic modeling analysis, and eight topics were ultimately identified: patient treatment, various roles, the performance of duties, cardiopulmonary resuscitation, triage systems, job stress, disaster management, and education programs. Conclusion: Based on the research results, it is believed that a study on the development and application of education programs that can successfully increase the emergency care capabilities of EMTs is needed.

• Structural Engineering and Mechanics
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• v.86 no.1
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• pp.85-92
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• 2023

This article examines the seismic vulnerability of soil nail wall structures. Detailed information regarding finite element modeling has been provided. The fragility function evaluates the relationship between ground motion intensities and the probability of surpassing a specific level of damage. The use of incremental dynamic analysis (IDA) has been applied to the soil nail wall against low to severe ground motions. In the nonlinear dynamic analysis of the soil nail wall, a set of twenty seismic ground motions with varying PGA ranges are used. The numerical results demonstrate that the soil-nailed wall reaction is extremely sensitive to earthquake ground vibrations under different intensity measures (IM). In addition, the analytical fragility curve is provided for various intensity values.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.240-247
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• 2023

In this paper, effective data management in industrial sites such as intelligent factories using time series data was studied. For effective management of time series data, variables considering the significance of the data were used, and hyper parameters calculated through LSTM AE were applied. We propose an optimized modeling considering the importance of each data section, and through this, outlier data of time series data can be efficiently processed. In the case of applying data significance and applying hyper parameters to which the research in this paper was applied, it was confirmed that the error rate was measured at 5.4%/4.8%/3.3%, and the significance of each data section and the significance of applying hyper parameters to optimize modeling were confirmed.

• Journal of the Korean Data and Information Science Society
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• v.15 no.2
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• pp.395-403
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• 2004

The purpose of this study is to investigate the structure relationships between job satisfaction of dental residents and its related factors. The study subject was 458 dental residents who were training at 6 university dental hospitals in Korea. Data for this study were obtained by self-administrated questionnaire during 3 months. Structure equation modeling using LISREL procedure was statistically appropriate and well fitted. By the model, the socio-demographic characteristics, working condition, and status perception directly influenced on subscale satisfactions, and the subscale satisfactions positively influenced on job satisfaction.

• Journal of the Microelectronics and Packaging Society
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• v.6 no.2
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• pp.31-36
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• 1999

An efficient method for thermal modeling of QFP is Proposed. Thermal measurement data are given to verify the method. In parallel with the experiment, an exact full 3-D model calculation is also provided. One fonds that there is an excellent agreement between validation data and the efficient model data.