• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.5
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• pp.999-1007
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• 2012

Multi-precision multiplication over public key cryptography should be considered for performance enhancement due to its computational complexity. Particularly, embedded device is not suitable to execute high complex computation, public key cryptography, because of its limited computational power and capacity. To overcome this flaw, research on multi-precision multiplication with fast computation and small capacity is actively being conducted. In the paper, we explore the cutting-edge technology of multi-precision multiplication for efficient implementation of public key cryptography over sensor network. This survey report will be used for further research on implementation of public key cryptography over sensor network.

• Journal of Multimedia Information System
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• v.8 no.2
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• pp.101-110
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• 2021

In computer vision, single-image super resolution has been an area of research for a significant period. Traditional techniques involve interpolation-based methods such as Nearest-neighbor, Bilinear, and Bicubic for image restoration. Although implementations of convolutional neural networks have provided outstanding results in recent years, efficiency and single model multi-scalability have been its challenges. Furthermore, previous works haven't placed enough emphasis on real-number scalability. Interpolation-based techniques, however, have no limit in terms of scalability as they are able to upscale images to any desired size. In this paper, we propose a convolutional neural network possessing the advantages of the interpolation-based techniques, which is also efficient, deeming it suitable in practical implementations. It consists of convolutional layers applied on the low-resolution space, post-up-sampling along the end hidden layers, and additional layers on high-resolution space. Up-sampling is applied on a multiple channeled feature map via bicubic interpolation using a single model. Experiments on architectural structure, layer reduction, and real-number scale training are executed with results proving efficient amongst multi-scale learning (including scale multi-path-learning) based models.

• Journal of Korea Multimedia Society
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• v.24 no.11
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• pp.1526-1537
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• 2021

Due to the difference between the underwater communication environment and the terrestrial communication environment, the radio communication mainly used on the ground cannot be used in underwater. For this reason, in the underwater communication environment, various communication media such as acoustic waves, infrared rays, light and so on has been studied, but there exist several difficulties in operating them individually due to their physical limitations. The concept for overcoming these difficulties is the very underwater multi-media communication, a method to select a communication medium best suitable for the current underwater environment among underwater communication multimedia whenever there occurs underwater communication failure. In this paper, we present an underwater multi-media communication network based on star topology and a fragmentation and reassembly technique to solve the problems caused by the different MTU (Maximum Transmission Unit) sizes among different underwater communication media. We also present the estimations and analysis on processing times in each of fragmentation and reassembly and the total data amount for transmitting fragments in our proposed underwater multi-media communication network.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.3
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• pp.491-497
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• 2012

Network coding is that the nodes can combine and mix the packets rather than merely forward them. Therefore, network coding is expected to improve throughput and channel efficiency in the wireless network. Relevant researches have been carried out to adapt network coding to wireless multi-hop network. In this paper, we designed the network coding for bidirectional traffic service in routing layer and IP layer of Ad-hoc network. From the simulation result, the traffic load and the end to end distance effect the performance of the network coding. As end to end distance and the traffic load become larger, the gain of network coding become more increased.

• International journal of advanced smart convergence
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• v.2 no.1
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• pp.6-11
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• 2013

Network Coding (NC) is a new paradigm for network communication. In network coding, intermediate nodes create new packets by algebraically combining ingress packets and send it to its neighbor node by broadcast manner. NC has rapidly emerged as a major research area in information theory due to its wide applicability to communication through real networks. Network coding is expected to improve throughput and channel efficiency in the wireless multi-hop network. Many researches have been carried out to employ network coding to wireless ad-hoc network. In this paper, we proposed a dynamic queue management to improve coding opportunistic to enhance efficiency of NC. In our design, intermediate nodes are buffering incoming packets to encode queue. We expect that the proposed algorithm shall improve encoding rate of network coded packet and also reduce end to end latency. From the simulation, the proposed algorithm achieved better performance in terms of coding gain and packet delivery rate than static queue management scheme.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.7
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• pp.179-189
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• 1994

A two-phase neural network finds exact feasible solutions for a constrained optimization programming problem. The time-varying programming neural network is a modified steepest-gradient algorithm which solves time-varying optimization problems. In this paper, we propose a time-varying two-phase optimization neural network which incorporates the merits of the two-phase neural network and the time-varying neural network. The proposed algorithm is applied to system identification and function approximation using a multi-layer perceptron. Particularly training of a multi-layer perceptrion is regarded as a time-varying optimization problem. Our algorithm can also be applied to the case where the weights are constrained. Simulation results prove the proposed algorithm is efficient for solving various optimization problems.

• Journal of information and communication convergence engineering
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• v.9 no.5
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• pp.523-529
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• 2011

In this paper an inter-layer protocol, referred to as a Multi-Network Selector (MNS) is proposed for multiband maritime networks. A MNS is located between the data-link layer and the network layer and performs vertical handover when a ship moves another radio network. In order to provide seamless data transfer to different radio networks, the MNS uses received signal strength (RSS) and ship's location information as decision parameters for vertical handover, which can avoid ping-pong effect and reduces handover latency. In addition, we present related issues in order to implement the MNS for a multiband maritime network.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.6
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• pp.1238-1240
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• 2009

In the wireless sensor network, cooperative transmission is an effective technique to combat multi-path fading and reduce transmitted power. Relay selection and power allocation are important technical issues to determine the performance of cooperative transmission. In this paper, we proposed a new multi-relay selection and power allocation algorithm to increase network lifetime. The proposed relay selection scheme minimizes the transmitted power and increase the network lifetime by considering residual power as well as channel conditions. Simulation results show that proposed algorithm obtains much longer network lifetime than the conventional algorithm.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.11a
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• pp.165-172
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• 2009

Integrated management model (SNMP/SMI) for lubiquitous egacy remote communication network or service make possible combination of various architecture. However, legacy management system cannot be applied some problems such as inefficient, complexly, implement and large network by reason of integration of voice and data, wired and wireless, and service area between service provider. For improve this, supplied JMX(Java Management eXtensions) on network management technology from SUN. JMX is integrated architecture for existing network management and monitoring. In this paper, we design and implement for integrated network management through multi-protocol agent using JMX.

• Journal of the Korean Society of Industry Convergence
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• v.16 no.3
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• pp.61-68
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• 2013

Long-term runoff model can be used to establish the effective plan of water reources allocation and the determination of the storage capacity of reservoir. So this study aims at the development of monthly runoff model using artificial neural network technique. For this, it was selected multi-layer neural network(MLN) and radial basis function neural network(RFN) model. In this study, it was applied model to analysis monthly runoff process at the Wi stream basin in Nakdong river which is representative experimental river basin of IHP. For this, multi-layer neural network model tried to construct input 3, hidden 7, and output 1 for each number of layer. As the result of analysis of monthly runoff process using models connected with artificial neural network technique, it showed that these models were effective in the simulation of monthly runoff.