• Journal of information and communication convergence engineering
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• v.3 no.4
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• pp.209-212
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• 2005

This study proposes hybrid case-based reasoning and genetic algorithms model for customer classification. In this study, vertical and horizontal dimensions of the research data are reduced through integrated feature and instance selection process using genetic algorithms. We applied the proposed model to customer classification model which utilizes customers' demographic characteristics as inputs to predict their buying behavior for the specific product. Experimental results show that the proposed model may improve the classification accuracy and outperform various optimization models of typical CBR system.

• Broadcasting and Media Magazine
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• v.16 no.1
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• pp.30-39
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• 2011

HbbTV는 Hybrid broadcast broadband TV의 약자로서 기존 방송과 함께 브로드밴드(Broadband) 웹 콘텐츠를 거실에 있는 TV 화면에 가장 효과적으로 전송하여 보여 주고, 사용자와 상호 작용 할 수 있도록 유럽에서 시작되어 만들어진 표준이다. HbbTV 표준은 소수의 새로운 기술 요소만 새로 도입하여 표준을 만들고, 대부분 이미 존재하고 검증된 특정 표준을 그대로 재 사용하였기 때문에 개발 비용 및 특히 적시 출시(time-to-market)에 큰 강점을 가지고 있다. HbbTV는 EBU "hybrid broadcast/broadband systems"의 요구 조건을 완전히 만족하는 표준이 되었다.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.11
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• pp.2266-2268
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• 2009

In this paper, a simple method of angle velocity estimation is presented for a passive dynamic biped robot. The estimation problem is not an easy task because its dynamic model is a hybrid system involved with an impact condition. Instead of designing a complex observer for hybrid systems we simply utilize the impact condition to reset the initial condition of the high-pass filter when the non-support leg hits the slope. The approach has been verified by simulation results.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.33
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• pp.111-118
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• 1995

This paper suggests a hybrid genetic algorithm for asymmetric traveling salesman problem(TSP). The TSP was proved to be NP-complete, so it is difficult to find optimal solution in reasonable time. Therefore it is important to develope an algorithm satisfying robustness. The algorithm applies dynamic programming to find initial solution. The genetic operator is uniform order crossover and scramble sublist mutation. And experiment of parameterization has been performed.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.5
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• pp.257-266
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• 2006

Recently TCP/IP Offload Engine (TOE) technology, which processes TCP/IP on a network adapter instead of the host CPU, has become an important approach to reduce TCP/IP processing overhead in the host CPU. There have been two approaches to implementing TOE: software TOE, in which TCP/IP is processed by an embedded processor on a network adapter; and hardware TOE, in which all TCP/IP functions are implemented by hardware. This paper proposes a hybrid TOE that combines software and hardware functions in the TOE. In the hybrid TOE, functions that cannot have guaranteed performance on an embedded processor because of heavy load are implemented by hardware. Other functions that do not impose as much load are implemented by software on embedded processors. The hybrid TOE guarantees network performance near that of hardware TOE and it has the advantage of flexibility, because it is easy to add new functions or offload upper-level protocols of TCP/IP. In this paper, we developed a prototype board with an FPGA and an ARM processor to implement a hybrid TOE prototype. We implemented the hardware modules on the FPGA and the software modules on the ARM processor. We also developed a coprocessing mechanism between the hardware and software modules. Experimental results proved that the hybrid TOE prototype can greatly reduce the load on a host CPU and we analyzed the effects of the coprocessing mechanism. Finally, we analyzed important features that are required to implement a complete hybrid TOE and we predict its performance.

• Proceedings of the KIEE Conference
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• 2008.04a
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• pp.159-160
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• 2008

Initial Ranging Detection and Synchronization is suggested for IEEE 802.16e OFDMA Systems. However ranging is vulnerable to the channel selectivity and other user's interference at low SNR. This paper presents enhanced ranging scheme that improves ranging detection process using the combine multiple FFT blocks and cope with channel selectivity and other user's interference at low SNR. Based on the ranging detection timing offset is calculated for synchronization.

• Journal of the Korean Society of Industry Convergence
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• v.4 no.1
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• pp.87-94
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• 2001

In multibody dynamics, differential and algebraic equations which can satisfy both equation of motion and kinematic constraint equation should be solved. To solve this equation, coordinate partitioning method and constraint stabilization method are commonly used. The coordinate partitioning method divides the coordinate into independent and dependent coordinates. The most typical coordinate partitioning method arc LU decomposition, QR decomposition, projection method and SVD(sigular value decomposition).The objective of this research is to find a efficient coordinate partitioning method in flexible multibody systems and a hybrid decomposition algorithm which employs both LU and projection methods is proposed. The accuracy of the solution algorithm is checked with a slider-crank mechanism.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.5
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• pp.416-422
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• 2013

This paper suggests a hybrid path planning method of multi-robots, where a path deviation prevention for maintaining a specific formation is implemented by using repulsive function, $A^*$ algorithm and UKF (Unscented Kalman Filter). The repulsive function in potential field method is used to avoid collision among robots and obstacles. $A^*$ algorithm helps the robots to find optimal path. In addition, error estimation based on UKF guarantees small path deviation of each robot during navigation. The simulation results show that the swarm robots with designated formation successfully avoid obstacles and return to the assigned formation effectively.

• ETRI Journal
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• v.40 no.2
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• pp.218-226
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• 2018

Multiuser detection (MUD) and channel estimation techniques in space-division multiple-access aided orthogonal frequency-division multiplexing systems recently has received intensive interest in receiver design technologies. The maximum likelihood (ML) MUD that provides optimal performance has the cost of a dramatically increased computational complexity. The minimum mean-squared error (MMSE) MUD exhibits poor performance, although it achieves lower computational complexity. With almost the same complexity, an MMSE with successive interference cancellation (SIC) scheme achieves a better bit error rate performance than a linear MMSE multiuser detector. In this paper, hybrid ML-MMSE with SIC adaptive multiuser detection based on the joint channel estimation method is suggested for signal detection. The simulation results show that the proposed method achieves good performance close to the optimal ML performance at low SNR values and a low computational complexity at high SNR values.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.442-445
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• 1997

We present a hybrid self-tuning method of fuzzy inference systems with hyper elliptic Gaussian membership functions using genetic algorithm(GA) and back-propagation algorithm. The proposed self-tuning method has two phases : one is the coarse tuning process based on GA and the other is the fine tuning process based on back-propagation. But the parameters which is obtained by a GA are near optimal solutions. In order to solve the problem in GA applications, it uses a back-propagation algorithm, which is one of learning algorithms in neural networks, to finely tune the parameters obtained by a GA. We provide Box-Jenkins time series to evaluate the advantage and effectiveness of the proposed approach and compare with the conventional method.