• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5338-5359
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• 2017

In-band full-duplex (IBFD) wireless communication supports symmetric dual transmission between two nodes and asymmetric dual transmission among three nodes, which allows improved throughput for distributed IBFD wireless networks. However, inter-node interference (INI) can affect desired packet reception in the downlink of three-node topology. The current Half-duplex (HD) medium access control (MAC) mechanism RTS/CTS is unable to establish an asymmetric dual link and consequently to suppress INI. In this paper, we propose a medium access control mechanism for use in distributed IBFD wireless networks, FD-DMAC (Full-Duplex Distributed MAC). In this approach, communication nodes only require single channel access to establish symmetric or asymmetric dual link, and we fully consider the two transmission modes of asymmetric dual link. Through FD-DMAC medium access, the neighbors of communication nodes can clearly know network transmission status, which will provide other opportunities of asymmetric IBFD dual communication and solve hidden node problem. Additionally, we leverage FD-DMAC to transmit received power information. This approach can assist communication nodes to adjust transmit powers and suppress INI. Finally, we give a theoretical analysis of network performance using a discrete-time Markov model. The numerical results show that FD-DMAC achieves a significant improvement over RTS/CTS in terms of throughput and delay.

• The Transactions of the Korea Information Processing Society
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• v.4 no.7
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• pp.1749-1758
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• 1997

This paper suggests the development of dynamic forecasting model for short-term power demand based on Radial Basis Function Network and Pal's GLVQ algorithm. Radial Basis Function methods are often compared with the backpropagation training, feed-forward network, which is the most widely used neural network paradigm. The Radial Basis Function Network is a single hidden layer feed-forward neural network. Each node of the hidden layer has a parameter vector called center. This center is determined by clustering algorithm. Theatments of classical approached to clustering methods include theories by Hartigan(K-means algorithm), Kohonen(Self Organized Feature Maps %3A SOFM and Learning Vector Quantization %3A LVQ model), Carpenter and Grossberg(ART-2 model). In this model, the first approach organizes the load pattern into two clusters by Pal's GLVQ clustering algorithm. The reason of using GLVQ algorithm in this model is that GLVQ algorithm can classify the patterns better than other algorithms. And the second approach forecasts hourly load patterns by radial basis function network which has been constructed two hidden nodes. These nodes are determined from the cluster centers of the GLVQ in first step. This model was applied to forecast the hourly loads on Mar. $4^{th},\;Jun.\;4^{th},\;Jul.\;4^{th},\;Sep.\;4^{th},\;Nov.\;4^{th},$ 1995, after having trained the data for the days from Mar. $1^{th}\;to\;3^{th},\;from\;Jun.\;1^{th}\;to\;3^{th},\;from\;Jul.\;1^{th}\;to\;3^{th},\;from\;Sep.\;1^{th}\;to\;3^{th},\;and\;from\;Nov.\;1^{th}\;to\;3^{th},$ 1995, respectively. In the experiments, the average absolute errors of one-hour ahead forecasts on utility actual data are shown to be 1.3795%.

• Proceedings of the Korea Association of Information Systems Conference
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• 2002.11a
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• pp.289-312
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• 2002

This study suggests the Link weight analysis approach to choose input variables and an integrated model to make more accurate bankruptcy prediction model. the Link weight analysis approach is a method to choose input variables to analyze each input node's link weight which is the absolute value of link weight between an input nodes and a hidden layer. There are the weak-linked neurons elimination method, the strong-linked neurons selection method in the link weight analysis approach. The Integrated Model is a combined type adapting Bagging method that uses the average value of the four models, the optimal weak-linked-neurons elimination method, optimal strong-linked neurons selection method, decision-making tree model, and MDA. As a result, the methods suggested in this study - the optimal strong-linked neurons selection method, the optimal weak-linked neurons elimination method, and the integrated model - show much higher accuracy than MDA and decision making tree model. Especially the integrated model shows much higher accuracy than MDA and decision making tree model and shows slightly higher accuracy than the optimal weak-linked neurons elimination method and the optimal strong-linked neurons selection method.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.7-10
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• 2005

Ad hoc MAC protocols using directional antennas can be used to improve the network capacity. Directional antennas have a Deafness problem and decrease throughput of the network caused by increasing backoff duration. Dual channel protocols have been proposed to mitigate the Deafness and hidden node problems. In this paper, we propose a dual channel MAC protocol using a directional antenna to mitigate the Deafness problem and increase the network capacity. The performance of the proposed Ad hoc MAC protocol is confirmed by computer simulations using Qualnet ver. 3.8 simulator.

• Tribology and Lubricants
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• v.16 no.6
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• pp.461-468
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• 2000

In this study, a neural network based diagnostic system of a rotating spindle system supported by ball bearings was introduced. In order to create actual failure situations, two exemplary abnormal status were made. Out of several possible data source locations, ten measurement spots were chosen. In order to discriminate multiple abnormal status, a neural network system was introduced using back propagation algorithm updating connecting weight between each nodes. In order to find the optimal structure of the neural network system reducing the information sources, magnitude of the weight of the network was referred. Hinton diagram was used to visually inspect the least sensitive weight connecting between input and hidden layers. Number of input node was reduced from 10 to 7 and prediction rate was increased to 100%.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04a
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• pp.121-123
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• 2002

무선 통신은 제한된 통신 자원으로 인한 제한적 대역과 단말기능에 있어서의 제약으로 무선 환경에서 제공받는 멀티미디어 통신 서비스를 수용하기가 쉽지 않다. 이러한 문제점을 해소하는 방안으로 무선 접속 기능을 향상하기 위한 통신장비간 무선 통신을 ad hoc 네트워크라고 부른다. 본 논문에서는 이러한 ad hoc 망상에서 CSMA을 이용한다. 그리고 ad hoc 네트워크의 히든노드(hidden node)문제를 해결하기 위하여 아주 작은 단위의 제어프레임을 사용하여 다음에 전송할 데이터패킷의 우선순위를 두고, 더 전송할 데이터패킷의 유무를 구분한다. RTS와 CTS를 전송하고 제어프레임을 받은 후 T-ready만큼 기다려, 새로운 최소 패킷을 받는 즉시 데이터패킷의 우선순위를 판단하여 우선순위가 높은 패킷일 경우에는 채널을 양보하므로 하나의 노드가 채널을 독점하는 기아 현상을 줄인다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.221-224
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• 2001

In this paper, we propose the initial optimized structure of the Radial Basis Function Network which is more simple in the part on the structure and converges more faster than Neural Network with the analysis method using Time-Frequency Localization and genetic algorithm. When we construct the hidden node with the Radial Basis Function whose localization is similar with an approximation target function in the plane of the Time and Frequency, we have initial structure of RBFN, After that, we evaluate the parameters of RBF in the network and the parameters needed for the network is more a few. Finally, we make a good decision of the initial structure having an ability of approximation.

• Journal of Korea Multimedia Society
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• v.15 no.10
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• pp.1212-1220
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• 2012

In this paper, a collision-free resource reservation scheme for WUSB (Wireless Universal Serial Bus) networks with WiMedia D-MAC (Distributed Medium Access Control). Since distributed characteristic of the WiMedia D-MAC supporting DRP (Distributed Reservation Protocol) scheme may cause lots of conflicts, overall performances of the WUSB with WiMedia D-MAC can be deteriorated. In addition, when we consider multi-hop environment, "mobile" hidden node problem due to mobility of WUSB devices can be happened, and it is a critical problem to mobile WUSB devices transceiving real-time QoS (Quality of Service) traffic. To tackle the problem, we propose a new DRP reservation mechanism to prevent DRP conflicts for multi-hop mobility support in WUSB networks with WiMedia D-MAC and show its improved performance via simulation results.

• Journal of the Korean Society for information Management
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• v.17 no.2
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• pp.189-205
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• 2000

We investigate the appropriate design and implementation of an Inductive Learning Alogrithm with a Neural Network in order to solve both inconsistent indexing and incomplete query problems on the web. Specifically, the proposed system based queries and documents in the field of Mathematics shows how inductive learning method and neural networks can apply to information retreival. Also, this study examines all of parameters of the neural networks -- the number of node in input and output, hidden layer size and learning parameters etc. -- which are significant in determining how well the neural network will converge.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.2
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• pp.35-44
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• 1998

This paper describes multiple fault diagnosis method in complex system with hierarchical structure. Complex system is divided into subsystem, item and component. For diagnosing this hierarchical complex system, it is necessary to implement special neural network. We introduced Modular Artificial Neural Network(MANN) for this purpose. MANN consists of four level neural network, first level for symptom classification, second level for item fault diagnosis, third level for component symptom classification, forth level for component fault diagnosis. Each network is multi layer perceptron with 7 inputs, 30 hidden node and 7 outputs trained by backpropagation. UNIX IPC(Inter Process Communication) is used for implementing MANN with multitasking and message transfer between processes in SUN workstation. We tested MANN in reactor system.