• The Journal of Information Technology and Database
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• v.3 no.2
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• pp.75-96
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• 1996

This study is intended to compare the effectiveness of the neural network inductive learning model with a vector space model in information retrieval. As a result, searches responding to incomplete queries in the neural network inductive learning model produced a higher precision and recall as compared with searches responding to complete queries in the vector space model. The results show that the hybrid methodology of integrating an inductive learning technique with the neural network model can help solve information retrieval problems that are the results of inconsistent indexing and incomplete queries--problems that have plagued information retrieval effectiveness.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.120.2-120
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• 2002

In this paper auto-tuning scheme of weight function in the neural networks has been suggested by immune algorithm for nonlinear process. A number of structures of the neural networks are considered as learning methods for control system. A general view is provided that they are the special cases of either the membership functions or the modification of network structure in the neural networks. On the other hand, since the immune network system possesses a self organizing and distributed memory, it is thus adaptive to its external environment and allows a PDP (parallel distributed processing) network to complete patterns against the environmental situation. Also. It can provi..

• Journal of KIISE:Information Networking
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• v.34 no.6
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• pp.493-504
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• 2007

With the advance and proliferation of computer and wireless network technology, it is common to access to network through the wireless network using mobile device. The ratio of using the streaming media out of many applications through the network is increasing not only in the wired network but also in the wireless network. The streaming media is much bigger than other contents and requires more network bandwidth to communicate and more computing resources to process. However the mobile devices have relatively poor computing resource and low network bandwidth. If the streaming media service is provided for mobile devices without any consideration about the network bandwidth and computing power, it is difficult for the client to get the service of high quality. Since especially mobile devices are supported with very limited energy capacity from the battery, the streaming media service should be adjusted to the varying energy state of mobile devices to ensure the complete playback of streaming media. In this paper, we propose a new method to guarantee the complete playback time of the streaming media for the mobile clients by dynamically controlling transmitted frame rate to the client according to the estimated available time of mobile device using battery model reflecting the characteristic of the battery. Since the proposed method controls the number of frames transmitting to the client according to the energy state of the mobile device, the complete playback time is guaranteed to mobile clients.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.6
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• pp.877-884
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• 1994

In the power system state estimation, the J(x)-index test and normalized residuals ${\gamma}$S1NT have been the presence of bad measurements and identify their location. But, these methods require the complete re-estimation of system states whenever bad data is identified. This paper presents back-propagation neural network medel using autoregressive filter for identification of bad measurements. The performances of neural network method are compared with those of conventional mehtods and simulation results show the geed performance in the bad data identification based on the neural network under sample power system.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.2
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• pp.234-237
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• 1991

A new neural network model, based on the Hopfield crossbar associative network, is presented and shown to be an effective tool for the NP-Complete problems. This model is applied to a class of layer assignment problems for VLSI routing. The results indicate that this modified Hopfield model, improves stability and accuracy.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.9
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• pp.789-794
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• 2005

This paper describes an algorithm for minimal turning complete coverage Path planning for cleaning robots. This algorithm divides the whole cleaning area by cellular decomposition, and then provides the path planning among the cells employing a flow network. It also provides specific path planning inside each cell guaranteeing the minimal turning of the robots. The minimal turning of the robots is directly related to the faster motion and energy saving. The proposed algorithm is compared with previous approaches in simulation and the result shows the validity of the algorithm.

• BMB Reports
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• v.37 no.1
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• pp.28-34
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• 2004

The discovery of biochemical and cellular functions of unannotated gene products begins with a database search of proteins with structure/sequence homologues based on known genes. Very recently, a number of frontier groups in structural biology proposed a new paradigm to predict biological functions of an unknown protein on the basis of its three-dimensional structure on a genomic scale. Structural proteomics (genomics), a research area for structure-based functional discovery, aims to complete the protein-folding universe of all gene products in a cell. It would lead us to a complete understanding of a living organism from protein structure. Two major complementary experimental techniques, X-ray crystallography and NMR spectroscopy, combined with recently developed high throughput methods have played a central role in structural proteomics research; however, an integration of these methodologies together with comparative modeling and electron microscopy would speed up the goal for completing a full dictionary of protein folding space in the near future.

• The Journal of Korea Robotics Society
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• v.6 no.3
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• pp.255-262
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• 2011

Many intelligent robots have to be given environmental information to perform tasks. In this paper an intelligent robot, that is, a cleaning robot used a sensor fusing method of two sensors: LRF and StarGazer, and then was able to obtain the information. Throughout wall following using laser displacement sensor, LRF, the working area is built during the robot turn one cycle around the area. After the process of wall following, a path planning which is able to execute the work effectively is established using flow network algorithm. This paper describes an algorithm for minimal turning complete coverage path planning for intelligent robots. This algorithm divides the whole working area by cellular decomposition, and then provides the path planning among the cells employing flow networks. It also provides specific path planning inside each cell guaranteeing the minimal turning of the robots. The proposed algorithm is applied to two different working areas, and verified that it is an optimal path planning method.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.1
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• pp.79-89
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• 1993

This paper deals with a computer aided control of an adjustment process for the complete electronic devices by means of an application of artificial neural network and an implementation of neuro-controller for intelligent control. Multi-layer neural network model is employed as artificial neural network with the learning method of the error back propagation. Information initially available from real plant under control are the initial values of plant output, and the augmented plant input and its corresponding plant output at that time. For the intelligent control of adjustment process utilizing artificial neural network, the neural network emulator (NNE) and the neural network controller(NNC) are developed. The initial weights of each neural network are determined through off line learning for the given product and it is also employed to cope with environments of the another product by on line learning. Computer simulation, as well as the application to the real situation of proposed intelligent control system is investigated.

• 한국정보통신설비학회:학술대회논문집
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• 2006.08a
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• pp.87-90
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• 2006

Nowadays, we can enjoy access to high speed network and advanced services of convergence between broadcasting and communication anywhere and anytime through a ubiquitous computing. So, now digital convergence devices come out constantly. These devices are required faster network environment for high speed data processing than before. In this paper, we describe the design of InfiniBnad network adapter, which is included two FPGA chipsets. When this adapter is installed to Digital Convergence Platform (DCP) network performance will be improved. The adapter includes 12channel serial ports for external communication and internally, uses PCI-Express bus. We have finished the test of high speed serial based network adapter through composing complete InfiniBand network and applied fabric management software. So, we have verified that it can be applied on DCP environment.