• Journal of KIISE:Computing Practices and Letters
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• v.14 no.9
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• pp.850-863
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• 2008

Business Process is a set of interrelated business functions, which are defined by various business process rule and that will lead a company to accomplishing a specific organizational goal. Many business organizations are using process modeling methods for their business process management, but mostly these methods are accomplished by Human-Based activities. These human-based activities cause unexpected design anomalies in modeling phase. If process engine executed without design anomalies detection, that will be lead to huge loss on costs. To ensure that there is no design anomalies in modeling phase and to detect anomalies of predefined actions within modeling tools are important issues in business process management. In this paper, we provide specific types of design anomalies, which can effectively use to detect design anomalies in business process modeling phase.

• Journal of KIISE:Software and Applications
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• v.36 no.4
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• pp.283-290
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• 2009

Context-awareness is one of the key features of ubiquitous paradigm. A methodology that is specifying the relationships between the contexts and services needs to be developed to intelligently and sensitively deal with dynamic environment. The existing models on context-aware modeling are difficult to verify the correctness of models with respect to timeliness. In this paper we propose an approach which includes timing constraint in the relations of the context model, and verify its effectiveness using colored Petri-Net. Moreover, a context-modeling toolkit including context-awareness engine and simulator is developed to support agent-based context-aware service. The effectiveness of the proposed methodology is demonstrated using an example of Usilvercare.

• Journal of the Korean Chemical Society
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• v.60 no.4
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• pp.276-285
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• 2016

This study aimed to examine preservice science teachers' modeling ability and how it has changed in argument-based chemistry laboratory investigations. The participants for this study were twenty-one freshman students from teachers’ college and they carried out six topics of argument-based chemistry laboratory investigation. Students’ written modeling samples were collected and analyzed to investigate preservice science teacher's modeling ability and changes in it. The results of this study showed that preservice science teacher's modeling ability has improved and progressed through argument-based chemistry laboratory investigations.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.634-636
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• 2021

In this study, we studied the macro-modeling of an feedback field-effect transistor (FBFET) using SPICE simulation. The previously presented macro-model of the FBFET is consisting of two circuits. one is charge integration circuit, and the other is current generation circuit. The previous current generation circuit has problem that can't predict performance accurately of the circuits, due to implementing only I_DS-V_GS characteristics. To solve this problem, we presents a model that can implement not only I_DS-V_GS characteristics but alos I_DS-V_DS characteristics by adding the diode in the current generation circuit.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.2
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• pp.413-418
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• 2011

The thermodynamic properties of steam table are obtained by measurement or approximate calculation under appropriate assumptions. Therefore they are supposed to have basic measurement errors. And thermodynamic properties should be modeled through function approximation for using in numerical analysis. In order to make noised thermodynamic properties corresponding to measurement errors, random numbers are generated, adjusted to appropriate magnitudes and added to original thermodynamic properties. Both neural networks and quadratic spline interpolation method are introduced for function approximation of these modified thermodynamic properties in the saturated water based on pressure and temperature. In analysis spline interpolation method gives much less relative errors than neural networks at both ends of data. Excluding the both ends of data, the relative errors of neural networks is generally within ${\pm}0.2%$ and those of spline interpolation method within ${\pm}0.5$~1.5%. This means that the neural networks give smaller relative errors compared with quadratic spline interpolation method within range of use. From this fact it was confirmed that the neural networks trace the original values better than the quadratic interpolation method and neural networks are more appropriate method in modelling the saturated steam table.

• 전자공학회논문지 IE
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• v.46 no.4
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• pp.8-15
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• 2009

In this paper, we are indicated CMOS Image sensor circuit SPICE analysis for the Photo Diode and pixel Modeling. We get a characteristic of the photoelectric current using a device simulator Medici and develop the Photodiode model for applying a SPICE simulation. For verifying the result, We compared the result of SPICE simulation with the result of mixed mode simulation about the testing circuit structure consisted photodiode and NMOS.

• 전자공학회논문지 IE
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• v.48 no.2
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• pp.19-25
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• 2011

This paper presented neural network modeling method using vehicle data to predict fuel consumption. To acquire data for training and testing the proposed neural network, medium-class gasoline vehicle drove at downtown and parameters measured include speed, engine rpm, throttle position sensor (TPS), and mass air flow (MAF) as input data, and fuel consumption as target data from OBD-II port. Multi layer perception network was used for nonlinear mapping between the input and the output data. It was observed that the neural network model can predict the vehicle quite well with mean squared error was $1.306{\times}10^{-6}$ for the fuel consumption.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.6
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• pp.81-86
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• 2006

Routing signal lines in PCB, line shapes would be straight or bent. time-domain and frequency-domain evaluation of the signal property and interference are archived by precise Modeling of differential signal line. Some of CAD tools can extract equivalent circuit model parameters. but it takes a long time and heavy loads. This paper introduces a basic RLC equivalent circuit model parameter extraction technique for bent differential structures using genetic algorithm by this technique, we can model equivalent circuit of bent differential structures more faster.

• Proceedings of the KIEE Conference
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• 1998.07f
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• pp.1908-1910
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• 1998

지금 까지 유도 가열용 인버터의 여러 가지 회로 방식이 소개 되었다. 그러나, 회로 방식을 선정 하는데 있어서 설계자의 취향, 또는 종래의 회로을 채택으로 인하여, 각기 다른 출력, 스위치 소자의 정격 전압, 전류, 및 수동 소자의 정격 전압, 전류을 만족하는 회로 선정이 될 수 있는 수식적 모델링, 비교 실험이 부족 하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.315-319
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• 2003

This paper presents modeling and analysis of static and dynamic characteristics in PWM Boost AC-AC converter used for input voltage sag compensation of custom power. Especially, using circuit DQ transformation technique, an equivalent circuit in fundamental frequency domain is obtained which has all the system characteristics. Moreover, voltage gain and input power factor is analytically induced and linearized state equation at the specific operating point is given. Finally, simulation results show the validity of the proposed modelling and analyses.