• Journal of electromagnetic engineering and science
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• v.12 no.3
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• pp.223-225
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• 2012

In this paper, we develop a symbol/frame time and carrier frequency synchronization scheme for multi-carrier signaling in wireless mobile channels. The proposed scheme achieves simultaneous time synchronization and carrier frequency offset estimation. Simulation results show that the frequency offset of multiple sub-carrier spacings can be estimated and that performance is improved with robustness regardless of the cyclic prefix length.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.8
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• pp.711-717
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• 2004

We propose a path planning method to improve the productivity of SMT (surface mount technology) inspection machines with an area camera. A unified method is newly proposed to determine the FOV clusters and camera sequence simultaneously. The proposed method is implemented by a hybrid genetic algorithm to increase the convergence speed. Comparative simulation results are then presented to verify the usefulness of the proposed algorithm.

• Journal of Korea Society of Industrial Information Systems
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• v.2 no.1
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• pp.1-17
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• 1997

Genetic algorithms have proved to be a versatile and effectvie approach for solving optimization problems. Nevertheless, there are many situations that the genetic algorithm does not perform particularly well, and so various methods of hybridization have been proposed. Thus, this paper develop a hybrid method and a precision search method around optimum in the gentic algorithm and the conventional optimization techniques in finding global or near optimum.

• Advances in aircraft and spacecraft science
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• v.9 no.6
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• pp.553-569
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• 2022

In this article, we propose a criterion for ensuring the asymptotic stability of large multiple delays, based on the direct Lyapunov method. Based on this criterion and distributed control scheme, the controllers are synthesized by the PDC to stabilize these large-scale systems with multiple delays. And we focus on the results which shows the high effective by the proposed theory utilized for damage propagation for aircraft structural analysis of composite materials. Finally, the numerical simulations confirmed the effectiveness of the method.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.125-140
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• 2013

We call a data set in which the number of records belonging to a certain class far outnumbers the number of records belonging to the other class, 'imbalanced data set'. Most of the classification techniques perform poorly on imbalanced data sets. When we evaluate the performance of a certain classification technique, we need to measure not only 'accuracy' but also 'sensitivity' and 'specificity'. In a customer churn prediction problem, 'retention' records account for the majority class, and 'churn' records account for the minority class. Sensitivity measures the proportion of actual retentions which are correctly identified as such. Specificity measures the proportion of churns which are correctly identified as such. The poor performance of the classification techniques on imbalanced data sets is due to the low value of specificity. Many previous researches on imbalanced data sets employed 'oversampling' technique where members of the minority class are sampled more than those of the majority class in order to make a relatively balanced data set. When a classification model is constructed using this oversampled balanced data set, specificity can be improved but sensitivity will be decreased. In this research, we developed a hybrid model of support vector machine (SVM), artificial neural network (ANN) and decision tree, that improves specificity while maintaining sensitivity. We named this hybrid model 'hybrid SVM model.' The process of construction and prediction of our hybrid SVM model is as follows. By oversampling from the original imbalanced data set, a balanced data set is prepared. SVM_I model and ANN_I model are constructed using the imbalanced data set, and SVM_B model is constructed using the balanced data set. SVM_I model is superior in sensitivity and SVM_B model is superior in specificity. For a record on which both SVM_I model and SVM_B model make the same prediction, that prediction becomes the final solution. If they make different prediction, the final solution is determined by the discrimination rules obtained by ANN and decision tree. For a record on which SVM_I model and SVM_B model make different predictions, a decision tree model is constructed using ANN_I output value as input and actual retention or churn as target. We obtained the following two discrimination rules: 'IF ANN_I output value <0.285, THEN Final Solution = Retention' and 'IF ANN_I output value ${\geq}0.285$, THEN Final Solution = Churn.' The threshold 0.285 is the value optimized for the data used in this research. The result we present in this research is the structure or framework of our hybrid SVM model, not a specific threshold value such as 0.285. Therefore, the threshold value in the above discrimination rules can be changed to any value depending on the data. In order to evaluate the performance of our hybrid SVM model, we used the 'churn data set' in UCI Machine Learning Repository, that consists of 85% retention customers and 15% churn customers. Accuracy of the hybrid SVM model is 91.08% that is better than that of SVM_I model or SVM_B model. The points worth noticing here are its sensitivity, 95.02%, and specificity, 69.24%. The sensitivity of SVM_I model is 94.65%, and the specificity of SVM_B model is 67.00%. Therefore the hybrid SVM model developed in this research improves the specificity of SVM_B model while maintaining the sensitivity of SVM_I model.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.34 no.2
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• pp.191-196
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• 2010

Hybrid heat pumps, which combine the vapor compression and absorption heat pump cycle, can efficiently produce hot water of $80^{\circ}-90^{\circ}C$ from the low temperature of ${\sim}50^{\circ}C$. In this study, the performance of a two-stage hybrid heat pump (HHP) was compared with a single-stage hybrid heat pump using EES (Engineering Equation Solver). For the same operating conditions, the two-stage HHP showed a slightly higher COP (Coefficient Of Performance) and more stable operating conditions than the single-stage HHP. Moreover, the maximum working fluid temperature of the two-stage HHP was found to be lower than that of the single-stage HHP by about 40 K, which makes the working conditions of the lubricating oil safer. The COPs of both systems decreased with increasing UA-values. However, the heat output of the HHP was increased at the same time.

• Journal of Aerospace System Engineering
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• v.14 no.5
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• pp.42-48
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• 2020

This research illustrates how the hybrid engine system comprising of a two-cycle reciprocal engine with an integrated generator and a battery is prepared for the design process. The purpose of this research is to increase flight endurance taking advantage of the high energy density of hybrid propulsion systems as well as to cope with current environmental issues by reducing fossil fuel. The hybrid system is designed to offer 6 kW power, and the power can be adjusted by controlling the engine's RPM in accordance with load variations. In addition, the battery is adopted to offer extra electric power that this hybrid system cannot cover, and can function as the main power source in limited time in the case of an emergency situation. Besides that, the generator is directly mounted on an engine crank-shaft, and in turn, they can share the same RPM. Thus, it is hypothesized that this integration method can make a compact design possible by reducing space for the installation in the fuselage of UAVs.

• Journal of Digital Convergence
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• v.10 no.10
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• pp.539-544
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• 2012

Most of the man-made systems can be modeled as a hybrid system which consists of both the high-level and the low-level component model. High level model is responsible for decision-making and the low-level one takes control of the mechanical component parts. Since the two models requires different interpretation method according to their type, analysis of a hybrid system becomes a difficult job. For the Analysis of the high-level model, methods for discrete event system models such as FSM can be used. On the contrary, numerical analysis techniques are required for the low-level continuous-time system model. Since it becomes a difficult thing for a modeller specifies and develops both the two-level models altogether, we propose an efficient hybrid simulation method which employs a game physics engine that has been widely and successfully used in the area of game industry.

• Transactions of the Korean Society of Automotive Engineers
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• v.19 no.2
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• pp.26-34
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• 2011

Hybrid powertrain systems have been developed to improve the fuel efficiency of internal combustion engines. In the case of a parallel hybrid powertrain system, an engine and a motor are directly coupled. Because of the hardware configuration of the parallel hybrid system, friction and the pumping losses of internal combustion engines always exists. Such losses are the primary factors that result in the deterioration of fuel efficiency in the parallel-type hybrid powertrain system. In particular, the engine operates as a power consumption device during the fuel-cut condition. In order to improve the fuel efficiency for the parallel-type hybrid system, cylinder deactivation (CDA) technology was developed. Cylinder deactivation technology can improve fuel efficiency by reducing pumping losses during the fuel-cut driving condition. In a CDA engine, there are two operating modes: a CDA mode and an SI mode according to the vehicle operating condition. However, during the mode change from CDA to SI, a serious fluctuation of the air-fuel ratio can occur without adequate control. In this study, an air-fuel ratio control algorithm during the mode transition from CDA to SI was proposed. The control algorithm was developed based on the mean value CDA engine model. Finally, the performance of the control algorithm was validated by various engine experiments.

• KIISE Transactions on Computing Practices
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• v.21 no.1
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• pp.88-93
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• 2015

In modern computer systems, DRAM is commonly used as main memory due to its low read/write latency and high endurance. However, DRAM is volatile memory that requires periodic power supply (i.e., memory refresh) to sustain the data stored in it. On the other hand, PCM is a promising candidate for replacement of DRAM because it is non-volatile memory, which could sustain the stored data without memory refresh. PCM is also available for byte-addressable access and in-place update. However, PCM is unsuitable for using main memory of a computer system because it has two limitations: high read/write latency and low endurance. To take the advantage of both DRAM and PCM, a hybrid main memory, which consists of DRAM and PCM, has been suggested and actively studied. In this paper, we propose a novel page replacement algorithm for hybrid main memory. To cope with the weaknesses of PCM, our scheme focuses on reducing the number of PCM writes in the hybrid main memory. Experimental results shows that our proposed page replacement algorithm reduces the number of PCM writes by up to 80.5% compared with the other page replacement algorithms.