• 한국전산유체공학회:학술대회논문집
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• 2008.03b
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• pp.542-546
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• 2008

In this study, we developed a whole cardiovascular system model combined with a Laplace heart based on the numerical cardiac cell model and a detailed arterial network structure. The present model incorporates the Laplace heart model and pulmonary model using the lumped parameter model with the distributed arterial system model. The Laplace heart plays a role of the pump consisted of the atrium and ventricle. We applied a cellular contraction model modulated by calcium concentration and action potential in the single cell. The numerical arterial model is based upon a numerical solution of the one-dimensional momentum equations and continuity equation of flow and vessel wall motion in a geometrically accurate branching network of the arterial system including energy losses at bifurcations. For validation of the present method, the computed pressure waves are compared with the existing experimental observations. Using the cell-system-arterial network combined model, the pathophysiological events from cells to arterial network are delineated.

• ETRI Journal
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• v.15 no.3
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• pp.1-26
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• 1994

Simulated annealing is an attractive, but expensive, heuristic method for approximating the solution to combinatorial optimization problems. Attempts to parallel simulated annealing, particularly on distributed memory multicomputers, are hampered by the algorithm's requirement of a globally consistent system state. In a multicomputer, maintaining the global state S involves explicit message traffic and is a critical performance bottleneck. To mitigate this bottleneck, it becomes necessary to amortize the overhead of these state updates over as many parallel state changes as possible. By using this technique, errors in the actual cost C(S) of a particular state S will be introduced into the annealing process. This paper places analytically derived bounds on this error in order to assure convergence to the correct optimal result. The resulting parallel simulated annealing algorithm dynamically changes the frequency of global updates as a function of the annealing control parameter, i.e. temperature. Implementation results on an Intel iPSC/2 are reported.

• International Journal of Internet, Broadcasting and Communication
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• v.10 no.1
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• pp.11-15
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• 2018

The application of Wireless Sensor Networks requires a wise utilization of limited energy resources. Therefore, a wide range of routing protocols with a motivation to prolong the lifetime of a network has been proposed in recent years. Hierarchical clustering based protocols have become an object of a large number of studies that aim to efficiently utilize the limited energy of network components. In this paper, the effect of mismatch in parameter estimation is discussed to evaluate the robustness of a distanced based algorithm called distributed clustering protocol in homogeneous and heterogeneous environment. For quantitative analysis, performance simulations for this protocol are carried out in terms of the network lifetime which is the main criteria of efficiency for the energy limited system.

• Convergence Security Journal
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• v.8 no.3
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• pp.57-64
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• 2008

The Security of digital images has become increasingly more important in highly computerized and interconnected world. Therefore, The chaos-based encryption algorithms have suggested some new and efficient ways to develop secure image encryption method. This paper is described for the point at issue in all chaos-based encryption method for distribution of a chaotic signals. It has a method for generation of uniformly distributed chaotic signals that we designed secure algorithm of multi-parameter chaotic systems. So we are present validity of the theoretical models for results of image encryption and decryption for proposed method.

• International Journal of Fluid Machinery and Systems
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• v.10 no.3
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• pp.197-208
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• 2017

When Francis turbines operate at partial load, residual swirl in the draft tube causes low-frequency pulsation of pressure and power output. Scale effects and system response may bias the prediction of prototype behavior based on laboratory tests, but could be overcome by means of a 1D analytical model. This paper deals with the two most important features of such a model, the compliance and the source of excitation. In a distributed-parameter version, compliance should be represented as an exponential function of local pressure. Lack of similarity due to different Froude number can thus be compensated. The normally unknown gas content in the vortex cavity has significant influence on the pulsation, and should therefore be measured and considered as a test parameter.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.6
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• pp.166-175
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• 1999

This paper describes a design and performance evaluation of robust controller which overrides unstable motion and pulls out quickly after water entry of underwater vehicle dropped from aircraft or surface ship. We use 6-DOF equation for model of motions and assume parameter uncertainty to reflect the difference of real motion from modelled motion equation. we represent a nonlinear system with uncertainty as Takagi and Sugeno's(T-S) fuzzy models and design controller stabilizing them. The fuzzy controller utilizes the concept of so-called parallel distributed compensation (PDC). Finally, we confirm stability and performance of the controller through computer simulation and hardware in the loop simulation (HILS).

• Journal of the Korean Society for Geothermal and Hydrothermal Energy
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• v.9 no.3
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• pp.11-18
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• 2013

Small and medium-size buildings employ a multi-distributed individual air-conditioning system utilizing package air conditioners instead of centralized cooling systems, which can allow easier building management and maintenance along with a diversification of facility use. Inverter driven system heat pumps have been developed to achieve not only easy distribution control allowing free combination of indoor units with different models and different capacities, but also wide applications to an intelligent air conditioning. In this study, the transient performance of a system heat pump was analysed with the variation of compressor speed and EEV openings. The superheat was selected as a control parameter of the system, because the variation of it was consistent with each indoor unit capacity.

• International Journal of Reliability and Applications
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• v.16 no.1
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• pp.35-53
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• 2015

This investigation deals with reliability and sensitivity analysis of a repairable embedded system with standby wherein repairman takes multiple vacations. The hardware system consists of 'M' operating and 'S' standby components. The repairman can leave for multiple vacations of random length during its idle time. Whenever any operating unit fails, it is immediately replaced by a standby unit if available. Moreover, governing equations of an embedded system are constructed using appropriate birth-death rates. The vacation and repair time of repairman are exponentially distributed. The matrix method is used to find the steady-state probabilities of the number of failed components in the embedded system as well as other performance measures. Reliability indexes are presented. Further, numerical experiments are carried out for various system characteristics to examine the effects of different parameter. Using a special class of neuro-fuzzy systems i.e. Adaptive Network-based Fuzzy Interference Systems (ANFIS), we also approximate various performance measures. Finally, the conclusions and future research directions are provided.

• Steel and Composite Structures
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• v.23 no.6
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• pp.683-690
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• 2017

In the stability and sensitivity design and diagnosis approaches, there are various methodologies available. Bond graph modeling by lumping technique is one of the universal methodologies in methodical analysis used by many researchers in all over the world. The accuracy of the method is validated in different arenas. Bond graphs are a concise, pictorial representation of the energy storage, dissipation and exchange mechanisms of interacting dynamic systems, subsystems and components. This paper proposes a bond graph modeling for distributed parameter systems using lumping techniques. Therefore, a steel frame structure was modeled to analyze employing bond graph modeling of distributed system using lumping technique. In the analytical part, the effectiveness of bond graphs to model this system is demonstrated. The dynamic responses of the system were computed and compared with those computed from the finite element analysis. The calculated maximum deflection time histories were found to be comparable. The sensitivity and the stability of the steel frame structure was also studied in different aspects. Thus, the proposed methodology, with its simplicity, can be used for stability and sensitivity analyses as alternative to finite element method for steel structures. The major value brought in the practical design is the simplicity of the proposed method for steel structures.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.993-996
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• 1993

This paper addresses the structure and its associated learning algorithms of a feedforward multi-layered connectionist network, which has distributed learning abilities, for realizing the basic elements and functions of a traditional fuzzy logic controller. The proposed neural-network-based fuzzy logic control system (NN-FLCS) can be contrasted with the traditional fuzzy logic control system in their network structure and learning ability. An on-line supervised structure/parameter learning algorithm dynamic learning algorithm can find proper fuzzy logic rules, membership functions, and the size of output fuzzy partitions simultaneously. Next, a Reinforcement Neural-Network-Based Fuzzy Logic Control System (RNN-FLCS) is proposed which consists of two closely integrated Neural-Network-Based Fuzzy Logic Controllers (NN-FLCS) for solving various reinforcement learning problems in fuzzy logic systems. One NN-FLC functions as a fuzzy predictor and the other as a fuzzy controller. As ociated with the proposed RNN-FLCS is the reinforcement structure/parameter learning algorithm which dynamically determines the proper network size, connections, and parameters of the RNN-FLCS through an external reinforcement signal. Furthermore, learning can proceed even in the period without any external reinforcement feedback.