• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.10
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• pp.2035-2046
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• 2015

Recently, researches on resource allocation algorithms operating in a distributed way are widely conducted because of the increasing number of network nodes and the rapidly changing the network environment. In this paper, we propose Multi-Hop DESYNC(MH DESYNC), that is bio-inspired TDMA-based resource allocation scheme operating in a distributed manner in multi-hop networks. In this paper, we define a frame structure for the proposed MH DESYNC algorithm and firing message structure which is a reference for resource allocation and propose the related operating procedures. We show that MH DSYNC can resolve the hidden-node problem effectively and verify that each node shares resources fairly among its neighboring nodes. Through simulation evaluations, it is shown that MH DESYNC algorithm works well in a multi-hop networks. Furthermore, results show that MH DESYNC algorithm achieves better performance than CSMA/CA algorithm in terms of throughput.

• International Journal of Contents
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• v.9 no.4
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• pp.11-15
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• 2013

"Protein Folding Problem" is considered to be one of the "Great Challenges of Computer Science" and prediction of disordered protein is an important part of the protein folding problem. Machine learning models can predict the disordered structure of protein based on its characteristic of "learning from examples". Among many machine learning models, we investigate the possibility of multilayer perceptron (MLP) as the predictor of protein disorder. The investigation includes a single hidden layer MLP, multi hidden layer MLP and the hierarchical structure of MLP. Also, the target node cost function which deals with imbalanced data is used as training criteria of MLPs. Based on the investigation results, we insist that MLP should have deep architectures for performance improvement of protein disorder prediction.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.3000-3022
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• 2019

Full-duplex (FD) technologies enable wireless nodes to simultaneously transmit and receive signal using the same frequency-band. The FD modes could improve their physical layer throughputs. However, in the wireless ad hoc networks, the FD communications also produce new interference risks. On the one hand, the interference ranges (IRs) of the nodes are enlarged when they work in the FD mode. On the other hand, for each FD pair, the FD communication may cause the potential hidden terminal problems to appear around the both sides. In this paper, to avoid the interference risks, we first model the IR of each node when it works in the FD mode, and then analyze the conditions to be satisfied among the transmission ranges (TRs), carrier-sensing ranges (CSRs), and IRs of the FD pair. Furthermore, in the media access control (MAC) layer, we propose a specific method and protocol for collision avoidance. Based on the modified Omnet++ simulator, we conduct the simulations to validate and evaluate the proposed FD MAC protocol, showing that it can reduce the collisions effectively. When the hidden terminal problem is serious, compared with the existing typical FD MAC protocol, our protocol can increase the system throughput by 80%~90%.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.445-446
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• 2009

IEEE 802.11 환경은 RTS/CTS(Request To Send/Clear To Send)을 지원한다. TS/CTS의 사용하면 Hidden Node Problem을 해결할 수 있지만 같은 셀안에 다른 노드를 대기상태로 만드는 False Node Problem이 발생하여 전송률을 감소시킨다. 따라서 본 논문에서는 체크포인트 방식을 사용하여 매체점유시간을 줄이는 제어프레임을 설계하고자 한다. 설계한 제어프레임의 OPNET을 사용하여 시뮬레이션하며, 기존의 제어프레임과 제안하는 제어프레임의 Delay를 비교함으로써 무선네트워크 환경에서 전송 효율을 비교 분석한다.

• Proceedings of the IEEK Conference
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• 2001.06c
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• pp.25-28
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• 2001

RBFN has some problem that because the basis function isn't orthogonal to each others the number of used basis function goes to big. In this reason, the Wavelet Neural Network which uses the orthogonal basis function in the hidden node appears. In this paper, we propose the composition method of the actual function in hidden layer with the scaling function which can represent the region by which the several wavelet can be represented. In this method, we can decrease the size of the network with the pure several wavelet function. In addition to, when we determine the parameters of the scaling function we can process rough approximation and then the network becomes more stable. The other wavelets can be determined by the global solutions which is suitable for the suggested problem using the genetic algorithm and also, we use the back-propagation algorithm in the learning of the weights. In this step, we approximate the target function with fine tuning level. The complex neural network suggested In this paper is a new structure and important simultaneously in the point of handling the determination problem in the wavelet initialization.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.05a
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• pp.65-68
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• 2001

RBFN has some problem that because the basis function isnt orthogonal to each others the number of used basis function goes to big. In this reason, the Wavelet Neural Network which uses the orthogonal basis function in the hidden node appears. In this paper, we propose the composition method of the actual function in hidden layer with the scaling function which can represent the region by which the several wavelet can be represented. In this method, we can decrease the size of the network with the pure several wavelet function. In addition to, when we determine the parameters of the scaling function we can process rough approximation and then the network becomes more stable. The other wavelets can be determined by the global solutions which is suitable for the suggested problem using the genetic algorithm and also, we use the back-propagation algorithm in the learning of the weights. In this step, we approximate the target function with fine tuning level. The complex neural network suggested in this paper is a new structure and important simultaneously in the point of handling the determination problem in the wavelet initialization.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.39 no.2
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• pp.66-75
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• 2002

This paper presents an adaptive back propagation algorithm that its able to enhancement for the learning efficiency with updating the learning parameter and varies the number of hidden layer node by the generated error, adaptively. This algorithm is expected to escaping from the local minimum and make the best environment for the convergence of the back propagation neural network. On the simulation tested this algorithm on three learning pattern. One was exclusive-OR learning and the another was 3-parity problem and 7${\times}$5 dot alphabetic font learning. In result that the probability of becoming trapped in local minimum was reduce. Furthermore, the neural network enhanced to learning efficient about 17.6%~64.7% for the existed back propagation. 

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.163.1-163
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• 2001

In this paper, we use time-frequency localization analysis method to analize the target function and the area of the target space. When we analize the function with the time and frequency axis simultaneously, the characteristic of the function is shown more precisely and the area is covered by a certain block. After we analize the target function in the time-frequency space, we can decide the activation functions and compose the hidden layer of the RBFN by choosing the radial basis function which can represent the characteristic of the target function, RBFN made by this method, designs the good structure proper to the target problem because we can decide the number of hidden node first.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.7B
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• pp.463-471
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• 2007

Because of MANET's dynamic characteristic, the hidden node problem can happen. Thus it must use with distributed channel access. In Ad hoc networks, carrier sense multiple access with collision avoidance(CSMA/CA) is one of the most widely used medium access control(MAC) schemes for asynchronous data traffics. However, CSMA/CA could not guarantee the quality of multimedia traffics. CSMA is a contention based protocol. Therefor once a node gets a channel, it can momopolze. Thus the fairness problem with channel starvation will happen. We will propose a new MAC protocol to guarantee QoS for multimedia data in ad hoc networks.

• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.4
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• pp.193-203
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• 2014

This paper implements a weather monitoring system based on wireless sensor network. The wireless sensor network protocol proposed in this paper adopts a TDMA styled MAC. The protocol is designed to balance the energy consumption among sensor nodes. Other purposes of the protocol are to avoid the hidden terminal problem in 2-hop star topology, and to allow a CSMA styled communication in a given time slot to support emergent messages. Also, this paper develops the hardware of sensor node, gateway and electric generator based on solar and windy energy. The test results on the implemented system show that the time slot of each node is shifted in circular manner to balance the waiting time for transmission, and the reliability of wireless communication is over 99%.