• Journal of Korean Society for Quality Management
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• v.31 no.3
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• pp.114-125
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• 2003

In this paper, we deal with the problem of modeling of agent-based robot manufacturing cell. Its role is becoming increasingly important in automated manufacturing systems. For Object Oriented & Queueing Petri Nets (OO&QPNs), an extended formalism for the combined quantitative and qualitative analysis of different systems is used for structure and performance analysis of mobile robotic cell. In the case study, the OO&QPN model of a mobile robotic cell is represented and analyzed, considering multi-class parts, non-preemptive priority and alternative routing. Finally, the comparison of performance values between Shortest Process Time (SPT) rule and First Come First Serve (FCFS) rule is suggested. In general, SPT rule is most suitable for parts that have shorter processing time than others.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.9A
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• pp.2289-2304
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• 1998

For the performance analysis and traffic control of ATM networks carrying video sequences, need an appropriate video traffic model. In this paper, we propose a new traffic model for MPEG compressed videos which are widely used for any type of video applications at th emoment. The proposed modeling scheme uses scene-based traffic characteristics and considers the correlation between frames of consecutiv GOPs. Using a simple scene detection algorithm, scene changes are modeled by state transitions and the number of GOPs of a scene state is modeled by a geometric distirbution. Frames of a scene stte are modeled by mean I, P, and B frame size. For more accurate traffic modeling, quantization errors (residual bits) that the state transition model using mean values has are compensated by autoregressive processes. We show that our model very well captures the traffic chracteristics of the original videos by performance analysis in terms of autocorrelation, histogram of frame bits genrated by the model, and cell loss rate in the ATM multiplexer with limited buffers. Our model is able to perrorm translations between levels (i.e., GOP, frame, and cell levels) and to estimate very accurately the stochastic characteristics of the original videos by each level.

• Journal of Integrative Natural Science
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• v.8 no.1
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• pp.75-79
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• 2015

Thromboxane A2 receptors (TXA2-R) are the G protein coupled receptors localized on cell membranes and intracellular structures and play pathophysiological role in various thrombosis/hemostasis, modulation of the immune response, acute myocardial infarction, inflammatory lung disease, hypertension and nephrotic disease. TXA2 receptor antagonists have been evaluated as potential therapeutic agents for asthma, thrombosis and hypertension. The role of TXA2 in wide spectrum of diseases makes this as an important drug target. Hence in the present study, homology modeling of TXA2 receptor was performed using the crystal structure of squid rhodopsin and night blindness causing G90D rhodopsin. 20 models were generated using single and multiple templates based approaches and the best model was selected based on the validation result. We found that multiple template based approach have given better accuracy. The generated structures can be used in future for further binding site and docking analysis.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.7B
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• pp.1279-1288
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• 1999

DEVSim++ is a C++ based, object-oriented modeling/simulation environment which realizes the hierarchical, modular DEVS formalism for discrete event systems specification. The paper describes a methodology for performance modeling and analysis of an ATM-based network system within the DEVSim++ environment. The methodology develops performance models for the system using the DEVS framework and implement the models in C++. Performance indices measured are the length of queues located at connection of the system and cell waiting times with respect to QoS grades for a network bandwidth of 155 Mbps.

• Journal of Power Electronics
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• v.8 no.3
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• pp.239-247
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• 2008

This paper presents the design of 1 kW prototype high frequency link boost half bridge inverter-fed DC-DC power converters with bridge voltage-doublers suitable for small scale PEM fuel cell systems and associated control schemes. The operation principle of this converter is described using fuel cell modeling and some operating waveforms. The switching mode equivalent circuits are based on simulation results and a detailed circuit operation analysis at soft-switching conditions.

• Biotechnology and Bioprocess Engineering:BBE
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• v.5 no.5
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• pp.382-385
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• 2000

A mathematical model was developed, based on the time dependent changes of the specific growth rate, for prediction of the typical microbial cell growth in batch cultures. This model could predict both the lag growth phase and the stationary growth phase of batch cultures, and it was tested with the batch growth of Trichoderma reesei and Lactobacillus delbrueckii.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.12
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• pp.2079-2084
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• 2003

In biological cell manipulation, manual thrust or penetration of an injection pipette into an embryo cell is currently performed by a skilled operator, relying on visual feedback information only. Accurately measuring cellular forces is a requirement for minimally invasive cell injections. Moreover, the cellular force sensing is essential in investigating the biophysical properties for cell injury and membrane modeling studies. This paper presents cellular force measurements for the force feedback-based biomanipulation. Cellular force measurement system using piezoelectric polymer sensor is implemented to measure the penetration force of a zebrafish egg cell. First, measurement system setup and calibration are described. Second, the force feedback-based biomanipulation is experimentally carried out. Experimental results show that it successfully supplies real-time cellular force feedback to the operator at tens of uN and thus plays a main role in improving the reliability of biological cell injection tasks.

• Journal of Electrical Engineering and Technology
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• v.11 no.6
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• pp.1664-1673
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• 2016

Lithium rechargeable cells are used in many industrial applications, because they have high energy density and high power density. For an effective use of these lithium cells, it is essential to build a reliable battery management system (BMS). Therefore, the state of charge (SOC) estimation is one of the most important techniques used in the BMS. An appropriate modeling of the battery characteristics and an accurate algorithm to correct the modeling errors in accordance with the simplified model are required for practical SOC estimation. In order to implement these issues, this approach presents the comparative analysis of the SOC estimation performance using equivalent electrical circuit modeling (EECM) and noise suppression technique (NST) in three representative $LiCoO_2/LiFePO_4/LiNiMnCoO_2$ cells extensively applied in electric vehicles (EVs), hybrid electric vehicles (HEVs) and energy storage system (ESS) applications. Depending on the difference between some EECMs according to the number of RC-ladders and NST, the SOC estimation performances based on the extended Kalman filter (EKF) algorithm are compared. Additionally, in order to increase the accuracy of the EECM of the $LiFePO_4$ cell, a minor loop trajectory for proper OCV parameterization is applied to the SOC estimation for the comparison of the performances among the compared to SOC estimation performance.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.6
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• pp.627-633
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• 1999

In this paper, we propose a method of cooperative control (T-cell modeling) and selection of group behavior strategy (B-cell modeling) based on immune system in distributed autonomous robotic system (DARS). Immune system is living body's self-protection and self-maintenance system. These features can be applied to decision making of optimal swarm behavior in dynamically changing environment. For applying immune system to DARS, a robot is regarded as a ？3-cell, each environmental condition as an antigen, a behavior strategy as an antibody and control parameter as a T-cell respectively. When the environmental condition (antigen) changes, a robot selects an appropriate behavior strategy (antibody). And its behavior strategy is stimulated and suppressed by other robot using communication (immune network). Finally much stimulated strateby is adopted as a swarm behavior strategy. This control scheme is based on clonal selection and immune network hypothesis, and it is used for decision making of optimal swarm strategy. Adaptation ability of robot is enhanced by adding T-cell model as a control parameter in dynamic environments.

• Journal of Power Electronics
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• v.13 no.3
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• pp.429-436
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• 2013

Online simulations are utilized to reduce time and cost in the development and performance optimization of plug-in hybrid electric vehicle (PHEV) and electric vehicles (EV) systems. One of the most important factors in an online simulation is the accuracy of the model. In particular, a model of a battery should accurately reflect the properties of an actual battery. However, precise dynamic modeling of high-capacity battery systems, which significantly affects the performance of a PHEV, is difficult because of its nonlinear electrochemical characteristics. In this study, a dynamic model of a high-capacity battery cell for a PHEV is developed through the extraction of the equivalent impedance parameters using electrochemical impedance spectroscopy (EIS). Based on the extracted parameters, a battery cell model is implemented using MATLAB/Simulink, and charging/discharging profiles are executed for comparative verification. Based on the obtained results, the model is optimized for a high-capacity battery cell for a PHEV. The simulation results show good agreement with the experimental results, thereby validating the developed model and verifying its accuracy.