• Journal of Korea Multimedia Society
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• v.9 no.7
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• pp.854-863
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• 2006

As WiBro service providers which provide a wireless multimedia communication service are selected, the commercial service will emerge in the near future. Although the use of efficient multicast technology for multimedia will be essentially required, it would be difficult to design the overall communication network in the early stage by using IP multicast due to technological or commercial issues. Application layer multicast schemes or hybrid multicast schemes also should be considered. In this paper, we propose a hybrid multicast scheme and evaluate its performance against typical IP multicast schemes on modelling of the WiBro network for one of WiBro service providers. We also propose a simulation method for the hybrid multicast on the simulation network for performance evaluation. If the number of mobile nodes reaches a certain point, the performance difference between the hybrid multicast and IP multicast is reduced significantly. We show that hybrid multicast technology can be applied for WiBro service without much performance degradation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.2
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• pp.932-945
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• 2018

Everything in the world is becoming connected and interactive due to the Internet. The future of interactive smart environments such as smart cities, smart industries, or smart farms demand high network bandwidth, high network flexibility, and self-organization systems without costly hardware upgrades, and they provide a sustainable, scalable, and replicable smart environment backbone infrastructure. This paper presents a new Hybrid Software-Defined architecture for integrating Internet-of-Things technologies that are essential technologies for smart environments. It combines a software-defined networking infrastructure and a real-time distributed network framework with an advanced optimization to enable self-configuration, self-management, and self-adaption for providing seamless communication and efficiently managing a vast number of smart heterogeneous devices.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.538-541
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• 1995

Joint flexibilities and frictional uncertainties are known to be a major cause of performance degration in motion control systems. This paper investigates the modeling and compensation of these undesired effects. A hybrid controller, which consists of a predictive controller and a neural network controller, is designed to overcome these undesired effects. Also learning scheme for friction uncertainies, which don't interfere with feedback controller dynamics, is discussed. Through simulation works with two inetia-torsional spring system having Coulomb friction, the effectiveness of the proposed hybrid controller was tested. The proposed predictive & neural network hybrid controller shows better performance over one when only predictive controller used.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.287-289
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• 2005

This paper presents a hybrid neural network system which used a Self-Organizing Map and Multilayer Perceptron for the problem of Malay syllables speech recognition. The novel idea in this system is the usage of a two-dimension Self-organizing feature map as a sequential mapping function which transform the phonetic similarities or acoustic vector sequences of the speech frame into trajectories in a square matrix where elements take on binary values. This property simplifies the classification task. An MLP is then used to classify the trajectories that each syllable in the vocabulary corresponds to. The system performance was evaluated for recognition of 15 Malay common syllables. The overall performance of the recognizer showed to be 91.8%.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.05a
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• pp.325-329
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• 2003

This paper discuss the method of the system's efficient control using a Intelligent hybrid algorithm in nonlinear dynamics systems. Existing neural network and genetic algorithm for the control of non-linear systems work well in static states. but it be not particularly good in changeable states and must re-learn for the control of the system in the changed state. This time spend a lot of time. For the solution of this problem we suggest the intelligent hybrid self-tuning controller. it includes neural network, genetic algorithm and immune system. it is based on neural network, and immune system and genetic algorithm are added against a changed factor. We will call a change factor an antigen. When an antigen broke out, immune system come into action and genetic algorithm search an antibody. So the system is controled more stably and rapidly. Moreover, The Genetic algorithm use the memory address of the immune bank as a genetic factor. So it brings an advantage which the realization of a hardware easy.

• Journal of Korean Society of Transportation
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• v.14 no.4
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• pp.49-76
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• 1996

Until recently, the inductive loop detecters(ILD) have been used to collect a traffic information in a part of traffic manangment and control. The ILD is able to collect a various traffic data such as a occupancy time and non-occupancy time, traffic volume, etc. The occupancy time of these is very important information for traffic control algorithms, which is required a high accuracy. This accuracy may be improved by classifying a vehicle type with ILD. To classify a vehicle type based on a Analog Digital Converted data collect form ILD, this study used a typical and modifyed statistic method and General Learning Vector Quantization unsuperviser neural network model and a hybrid model of GLVQ and statistic method, As a result, the hybrid model of GLVQ neural network model is superior to the other methods.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.11
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• pp.1081-1087
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• 2006

Generally, biped walking is difficult to control because a biped robot is a nonlinear system with various uncertainties. In this paper, we propose a hybrid sliding-mode control method using a WNN uncertainty observer for stable walking of the 5-link biped robot with model uncertainties and the external disturbance. In our control system, the sliding mode control is used as main controller for the stable walking and a wavelet neural network(WNN) is used as an uncertainty observe. to estimate uncertainties of a biped robot model, and the error compensator is designed to compensate the reconstruction error of the WNN. The weights of WNN are trained by adaptation laws that are induced from the Lyapunov stability theorem. Finally, the effectiveness of the proposed control system is verified through computer simulations.

• Journal of Information Processing Systems
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• v.17 no.2
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• pp.426-439
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• 2021

To alleviate the cold-start problem and data sparsity in web service recommendation and meet the personalized needs of users, this paper proposes a personalized web service recommendation method based on a hybrid social network and multi-objective immune optimization. The network adds the element of the service provider, which can provide more real information and help alleviate the cold-start problem. Then, according to the proposed service recommendation framework, multi-objective immune optimization is used to fuse multiple attributes and provide personalized web services for users without adjusting any weight coefficients. Experiments were conducted on real data sets, and the results show that the proposed method has high accuracy and a low recall rate, which is helpful to improving personalized recommendation.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.1
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• pp.35-42
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• 2010

Geo-location using a cellular network is a core technology for LBS together with GPS. With preamble symbols broadcasted in each frame, geo-location using WiBro network can be easily implemented. Because the WiBro network has a cellular structure, it is difficult for a mobile station to detect signals from multiple base stations. In order to get user position using trilateration, long integration techniques for sensitivity enhancement should be employed. This paper presents hybrid integration scheme for WiBro network. By analyzing coherent and non-coherent integration loss according to frequency residual and SNR respectively, optimal combination of the hybrid integration is proposed. Simulation results show that the hybrid integration method is profitable in WiBro network when the frequency residual is estimated and compensated accurately.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.5
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• pp.949-956
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• 2016

By recent development of wired and wireless communication technology, any service can be delivered through broadcasting networks or communication networks. So contents consumers want to receive broadcasting program via any accessible network. Network independent broadcasting system can receive optimized multimedia contents by combining the high-quality multimedia contents transmitted through broadcasting network and the additional contents delivered through communication network. Additional contents can be other multimedia contents, URL of contents, some texts for indicating information of received multimedia, etc. Network independent broadcasting system is in early stage of development, and receivers and the monitoring system for hybrid broadcast are under development. Thus the multiplexing method and demultiplexing method to perform hybrid broadcasting is on study. In this paper, we designed the demultiplexing algorithm to perform hybrid broadcasting system and implemented demultiplexer system based on modulator interface system standard T2-MI of DVB-T2.