• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.10
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• pp.1131-1138
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• 2015

As the size of the internet market grows rapidly, the number of IPv4 addresses available is being exhausted, while transition to IPv6 is being delayed. As the best alternative solution, Network Address Translation(NAT) scheme is being used. It connects the public internet network with the private internet network in order to reduce the waste of IPv4 addresses space. The purpose of this paper is to study the effective example of network based on common virtual network using Packet Tracer with topology designed rather than usual theoretical approach in Dynamic NAT and PAT, which allows more efficient use of address space.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.37 no.4
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• pp.22-27
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• 2000

In this paper, new neural network called dynamic multidimensional wavelet neural network (DMWNN) is proposed. The resulting network from wavelet theory provides a unique and efficient representation of the given function. Also the proposed DMWNN have ability to store information for later use. Therefore it can represent dynamic mapping and decreases the dimension of the inputs needed for network. This feature of DMWNN can compensate for the weakness of diagonal recurrent neural network(DRNN) and feedforward wavelet neural network(FWNN). The efficacy of this type of network is demonstrated through experimental results.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.10
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• pp.40-46
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• 2009

Recently CAN (Controller Area Network) is widely used as an in-vehicle networking protocol for intelligent vehicle. The identifier field (ID) of CAN is used not only to differentiate the messages but also to give different priorities to access the bus. This paper presents a dynamic 10 allocation algorithm in order to enhance the real-time quality-of-service (QoS) performance. When the network traffic is increased, this algorithm can allocate a network resource to lower priority message without degradation of the real-time QoS performance of higher priority message. In order to demonstrate the algorithm's feasibility, message transmission delays have been measured with and without the algorithm on an experimental network test bed.

• International Journal of Control, Automation, and Systems
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• v.6 no.1
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• pp.24-34
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• 2008

A novel neural network model, termed the standard neural network model (SNNM), similar to the nominal model in linear robust control theory, is suggested to facilitate the synthesis of controllers for delayed (or non-delayed) nonlinear systems composed of neural networks. The model is composed of a linear dynamic system and a bounded static delayed (or non-delayed) nonlinear operator. Based on the global asymptotic stability analysis of SNNMs, Static state-feedback controller and dynamic output feedback controller are designed for the SNNMs to stabilize the closed-loop systems, respectively. The control design equations are shown to be a set of linear matrix inequalities (LMIs) which can be easily solved by various convex optimization algorithms to determine the control signals. Most neural-network-based nonlinear systems with time delays or without time delays can be transformed into the SNNMs for controller synthesis in a unified way. Two application examples are given where the SNNMs are employed to synthesize the feedback stabilizing controllers for an SISO nonlinear system modeled by the neural network, and for a chaotic neural network, respectively. Through these examples, it is demonstrated that the SNNM not only makes controller synthesis of neural-network-based systems much easier, but also provides a new approach to the synthesis of the controllers for the other type of nonlinear systems.

• Proceedings of the Korean Biophysical Society Conference
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• 2003.06a
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• pp.77-77
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• 2003

Gene expression in a cell is regulated by mutual activations or repressions between genes. Identifying the gene regulation network will be one of the most important research topics in the post genomic era. We propose a linear dynamic model of gene regulation for the yeast cell cycle. A small gene network consisting of about 40 genes is reconstructed from the analysis of micro-array gene expression data of yeast S. cerevisiae published by P. Spellman et al. We show that the network construction is consistent with the result of the hierarchical cluster analysis.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2488-2491
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• 2000

A Neural network is possible to nonlinear function mapping and parallel processing. Therefore It has been developing for a Diagnosis system of nuclear plower plant. In general Neural Networks is a static mapping but Dynamic Neural Network(DNN) is dynamic mapping. When a fault occur in system, a state of system is changed with transient state. Because of a previous state signal is considered as a information. DNN is better suited for diagnosis systems than static neural network. But a DNN has many weights, so a real time implementation of diagnosis system is in need of a rapid network architecture. This paper presents a algorithm for RCP monitoring Alarm diagnosis system using Self Dynamic Neural Network(SDNN). SDNN has considerably fewer weights than a general DNN. Since there is no interlink among the hidden layer. The effectiveness of Alarm diagnosis system using the proposed algorithm is demonstrated by applying to RCP monitoring in Nuclear power plant.

• Journal of Broadcast Engineering
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• v.13 no.1
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• pp.119-127
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• 2008

Transmission of video over Internet or wireless network requires coded stream capable of adapting to dynamic network conditions instantly. To meet this requirement, various scalable video coding schemes have been developed, among which the Scalable Video Coding (SVC) extension of the H.264/AVC is the most recent one. In comparison with the scalable profiles of previous video coding standards, the SVC achieves significant improvement on coding efficiency performance. For adapting to dynamic network bandwidth, the SVC employs inter-layer switching between different temporal, spatial or/and fidelity layers, which is currently supported with instantaneous decoding refresh (IDR) access unit. However, for real-time adaptability, the SVC has to frequently employ the IDR picture, which dramatically decreases the coding efficiency. Therefore, an extension of SP picture from the AVC to the SVC for an efficient inter-layer switching is investigated and presented in this paper. Simulations regarding the adaptability to dynamic network bandwidth are implemented. Results of experiment show that the SP picture added SVC provides an average 1.2 dB PSNR enhancement over the current SVC while providing similar adaptive functionality.

• International Journal of Computer Science & Network Security
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• v.23 no.11
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• pp.21-31
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• 2023

In this paper, we focused on the problem of evaluating multi-class classification accuracy and simulation of multiple classifier performance metrics. Multi-class classifiers for sentiment analysis involved many challenges, whereas previous research narrowed to the binary classification model since it provides higher accuracy when dealing with text data. Thus, we take inspiration from the non-linear Support Vector Machine to modify the algorithm by embedding dynamic hyperplanes representing multiple class labels. Then we analyzed the performance of multi-class classifiers using macro-accuracy, micro-accuracy and several other metrics to justify the significance of our algorithm enhancement. Furthermore, we hybridized Enhanced Convolution Neural Network (ECNN) with Dynamic Support Vector Machine (DSVM) to demonstrate the effectiveness and efficiency of the classifier towards multi-class text data. We performed experiments on three hybrid classifiers, which are ECNN with Binary SVM (ECNN-BSVM), and ECNN with linear Multi-Class SVM (ECNN-MCSVM) and our proposed algorithm (ECNNDSVM). Comparative experiments of hybrid algorithms yielded 85.12 % for single metric accuracy; 86.95 % for multiple metrics on average. As for our modified algorithm of the ECNN-DSVM classifier, we reached 98.29 % micro-accuracy results with an f-score value of 98 % at most. For the future direction of this research, we are aiming for hyperplane optimization analysis.

• Journal of KIISE:Information Networking
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• v.31 no.5
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• pp.519-531
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• 2004

Ad-hoc networks are temporary wireless systems composed of mobile nodes without any fixed infrastructure. The life time of each node in the ad-hoc network significantly affects the life time of whole ad-hoc network. A node which drained out its battery may incur the partition of whole network in some network topology The life time of each node depends on the battery capacity of each node. Therefore if all mobile nodes in the network live evenly long, the life time of the network will be longer. In this paper, we propose Power-Aware Dynamic Source Routing (PADSR) which selects the best path to make the life time of the network be longer. In PADSR, when a source node finds a path to the destination node, it selects the best path that makes nodes in the network live evenly long. To find the best path, PADSR considers the consumption of transmission energy and residual battery capacity of nodes upon the path. Consequently the network lives longer if we use PADSR.

• The KIPS Transactions:PartC
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• v.15C no.2
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• pp.79-86
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• 2008

MANET(Mobile Ad hoc Network) is a collection of two or more nodes equipped with wireless communications and constrained by the factor of energy limitation. The running out of energy on some nodes may bring down the performance of network seriously. For solving the problems above, this paper uses completely separated Node-Disjoint multipaths from a source to a destination as many as possible. And, based on average, minimum or variance of energy values on the each multipath, the packets are distributed on paths. Generally, collecting methods for energy information can be classified into two main categories, Static and Dynamic. As the different energy values collected, the packet distribution methods are classified into six criteria, Static-Average, Static-Minimum, Static-Variance, Dynamic-Average, Dynamic-Minimum and Dynamic-Variance respectively. The performance of the packet distribution methods and that of AODV are compared by NS2 simulation.