• Journal of Information Processing Systems
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• 제14권1호
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• pp.176-190
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• 2018

This paper presents a novel convolutional neural network based multi-feature fusion learning method for non-rigid 3D model retrieval, which can investigate the useful discriminative information of the heat kernel signature (HKS) descriptor and the wave kernel signature (WKS) descriptor. At first, we compute the 2D shape distributions of the two kinds of descriptors to represent the 3D model and use them as the input to the networks. Then we construct two convolutional neural networks for the HKS distribution and the WKS distribution separately, and use the multi-feature fusion layer to connect them. The fusion layer not only can exploit more discriminative characteristics of the two descriptors, but also can complement the correlated information between the two kinds of descriptors. Furthermore, to further improve the performance of the description ability, the cross-connected layer is built to combine the low-level features with high-level features. Extensive experiments have validated the effectiveness of the designed multi-feature fusion learning method.

• 정보보호학회논문지
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• 제22권5호
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• pp.999-1007
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• 2012

공개키 기반 암호화 상에서의 다중 곱셈 연산은 높은 복잡도로 인해 성능 개선을 위해서는 우선적으로 고려되어야 한다. 특히 임베디드 장비는 기존의 환경과는 달리 한정적인 계산 능력과 저장 공간으로 인해 높은 복잡도를 나타내는 공개키 기반의 암호화를 수행하기에는 부적합한 특성을 가진다. 이를 극복하기 위해 다중 곱셈 연산을 빠르게 연산하고 적은 저장공간을 요구하는 기법이 활발히 연구되고 있다. 본 논문에서는 자원 한정적인 센서 네트워크 상에서의 효율적인 공개키 기반 암호화 구현을 위한 다중 곱셈기의 최신 연구 동향을 살펴본다. 이는 앞으로의 센서 네트워크상에서의 공개키 기반 암호화 구현을 위한 참고자료로서 활용이 가능하다.

• Journal of Multimedia Information System
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• 제8권2호
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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.

• 한국멀티미디어학회논문지
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• 제24권11호
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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.

• 한국전자통신학회논문지
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• 제7권3호
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• pp.491-497
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• 2012

네트워크 코딩기법은 여러 개의 패킷을 하나의 패킷으로 압축하여 전송하는 기법으로 무선네트워크에 적용할 경우, 패킷전달횟수를 감소시킬 수 있고 채널효율성을 향상할 수 있어 관련 연구들이 활발히 이루어지고 있다. 본 논문에서는 멀티홉 Ad-hoc 네트워크에서 양방향트래픽 서비스를 위해 라우팅계층과 IP계층에 네트워크코딩기법을 적용하였다. 시뮬레이션 분석결과 트래픽부하와 종단간 홉수가 높을수록 네트워크 코딩이득이 증가하였다.

• International journal of advanced smart convergence
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• 제2권1호
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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.

• 전자공학회논문지B
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• 제31B권7호
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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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• 제9권5호
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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.

• 전기학회논문지
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• 제58권6호
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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.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2009년도 추계학술대회
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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.