• Journal of Advanced Marine Engineering and Technology
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• v.35 no.3
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• pp.341-347
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• 2011

The redundancy allocation problem (RAP) is a famous NP.complete problem that has beenstudied in the system reliability area of ships and airplanes. Recently meta-heuristic techniques have been applied in this topic, for example, genetic algorithms, simulated annealing and tabu search. In particular, tabu search (TS) has emerged as an efficient algorithmic approach for the series-parallel RAP. However, the quality of solutions found by TS depends on the initial solution. As a robust and efficient methodology for the series-parallel RAP, the hybrid metaheuristic (TSA) that is a interactive procedure between the TS and SA (simulated annealing) is developed in this paper. In the proposed algorithm, SA is used to find the diversified promising solutions so that TS can re-intensify search for the solutions obtained by the SA. We test the proposed TSA by the existing problems and compare it with the SA and TS algorithm. Computational results show that the TSA algorithm finds the global optimal solutions for all cases and outperforms the existing TS and SA in cases of 42 and 56 subsystems.

• BMB Reports
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• v.29 no.1
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• pp.1-10
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• 1996

The binding interaction of ethidium to a series of synthetic deoxyoligonucleotides containing a B-Z junction between left-handed Z-DNA and right-handed B-DNA, was studied. The series of deoxyoligonucleotides was designed so as to vary a dinucleotide step immediately adjacent to a B-Z junction region. Ethidium binds to the right-handed DNA forms and hybrid B-Z forms which contain a B-Z junction, in a highly cooperative manner. In a series of deoxyoligonucleotides, the binding affinity of ethidium with DNA forms which were initially hybrid B-Z forms shows over an order of magnitude higher than that with any other DNA forms, which were entirely in B-form DNA The cooperativity of binding isotherms were described by an allosteric binding model and by a neighbor exclusion model. The binding data were statistically compared for two models. The conformation of allosterically converted DNA forms under binding with ethidium is found to be different from that of the initial B-form DNA as examined by CD spectra. The ratio of the binding constant was interestingly correlated to the free energy of base unstacking and the conformational conversion of the dinucleotide. The more the base stacking of the dinucleotide is unstable, or the harder the conversion of B to A conformation, the higher the ratio of the binding constant of ethidium with the allosterically converted DNA forms and with the initial B-Z hybrid forms. DNA sequence around a B-Z junction region affects the binding affinity of ethidium. The results in this study demonstrate that ethidium could preferentially interact with unusual DNA structures.

• The Transactions of the Korean Institute of Power Electronics
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• v.9 no.4
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• pp.303-310
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• 2004

In this paper, for compensating dynamic voltage sag and harmonic current, 3-phase hybrid series active power filter based on the space vector detection is proposed. The Space vector algorithm for detecting the voltage sag and the harmonic current in compared with conventional theory is a simple method for calculating the compensating reference without any coordinated transformation. The effectiveness of the proposed system is verified by the PSIM simulation in the steady state and the transient state, which the proposed system is able to simultaneously compensate harmonics and source voltage unbalance / sag.

• Transactions of the Korean Society of Automotive Engineers
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• v.24 no.1
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• pp.53-58
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• 2016

Modeling of engine coolant temperature was conducted for a series hybrid powertrain system. The purpose of this modeling was a simplification of complex heat transfer process inside a engine cooling system in order to apply it to the vehicle powertrain simulation software. A basic modeling concept is based on the energy conservation equation within engine coolant circuit and are composed of heat rejection from engine to coolant, convection heat transfer from an engine surface and a radiator to ambient air. At the final stage, the coolant temperature was summarized as a simple differential equation. Unknown heat transfer coefficients and heat rejection term were defined by theoretical and experimental methods. The calculation result from this modeling showed a reasonable prediction by comparison with the experimental data.

• Journal of the Korean Society of Propulsion Engineers
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• v.25 no.1
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• pp.68-76
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• 2021

The series hybrid system targeted in this study uses a reciprocating engine, a generator, and a battery as a main power source for the unmanned aerial vehicle. The generator is directly connected to the drive shaft of the reciprocating engine, and the operating characteristics of the reciprocating engine-generator set were confirmed through ground integration tests. In this study, based on the test results, a control logic is proposed an efficient use of the reciprocating engine-generator power and battery power. Also, the power variations of the reciprocating engine-generator and battery according to the logic were verified through simulation. As a result, it was confirmed that the engine-generator power supplied the power required for propulsion along with the battery power by the proposed control logic.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.1281-1284
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• 1998

This paper proposes an efficient time series prediction of the nonlinear dynamical discrete-time systems using multilayer neural networks of a hybrid learning algorithm. The proposed learning algorithm is a hybrid backpropagation algorithm based on the steepest descent for high-speed optimization and the dynamic tunneling for global optimization. The proposed algorithm has been applied to the y00 samples of 700 sequences to predict the next 100 samples. The simulation results shows that the proposed algorithm has better performances of the convergence and the prediction, in comparision with that using backpropagation algorithm based on the gradient descent for multilayer neural network.

• Journal of Power Electronics
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• v.11 no.4
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• pp.424-429
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• 2011

In this paper, the simulator of an on-line monitoring system for the range extender electric vehicle has been developed. The messages from the four control modules, the air pressure and fuel level sensors data, and the on/off switching states of 31 indicator lamps can be received through the control area network (CAN), and displayed on the graphic panel. The simulator was designed using the four DSP boards, variable resistors, and toggle switches instead of the four control modules, sensors, and switching state of indicator lamps on an actual series hybrid electric vehicle (SHEV) bus, respectively. The performance of the monitoring technologies was verified with the simulator at the laboratory, and then it was tested on an actual SHEV bus. The simulator is very useful at the initial development of the monitoring system at the hybrid-type or electrical vehicles.

• Structural Engineering and Mechanics
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• v.13 no.5
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• pp.491-504
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• 2002

Recently we formulated a 2D hybrid stress element from the 3D Hellinger-Reissner principle for the analysis of thick bodies that are symmetric to the thickness direction. Polynomials have typically been used for all the displacement and stress fields. Although the element predicted the dominant stress and all displacement fields accurately, its prediction of the out-of-plane shear stresses was affected by the very high order terms used in the polynomials. This paper describes an improved formulation of the 2D element using Fourier series expansion for the out-of-plane displacement and stress fields. Numerical results illustrate that its predictions have markedly improved.

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.1968-1977
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• 2008

A bimodal low-floor tram is designed to provide the flexibility of bus and the punctuality of trains together to the passengers. Its propulsion system is a series hybrid type using a set of CNG engine generator and Li-polymer battery. The present paper describes the specifications of the propulsion system in the bimodal tram which was drawn by a desirable driving cycle. In addition, it shows how the propulsion system of the bimodal tram can be controlled. With using a computer simulation tool of hybrid vehicles, ADVISOR, the performance of the bimodal tram was verified.

• Journal of Information Processing Systems
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• v.18 no.1
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• pp.115-129
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• 2022

Adopting Internet of Things (IoT)-based technologies in smart homes helps users analyze home appliances electricity consumption for better overall cost monitoring. The IoT application like smart home system (SHS) could suffer from large missing values gaps due to several factors such as security attacks, sensor faults, or connection errors. In this paper, a novel framework has been proposed to predict large gaps of missing values from the SHS home appliances electricity consumption time-series datasets. The framework follows a series of steps to detect, predict and reconstruct the input time-series datasets of missing values. A hybrid convolutional neural network-long short term memory (CNN-LSTM) neural network used to forecast large missing values gaps. A comparative experiment has been conducted to evaluate the performance of hybrid CNN-LSTM with its single variant CNN and LSTM in forecasting missing values. The experimental results indicate a performance superiority of the CNN-LSTM model over the single CNN and LSTM neural networks.