• Journal of the Korea Society of Computer and Information
• /
• v.10 no.6 s.38
• /
• pp.153-166
• /
• 2005

Existing single cache structure has shown difference of hit-ratio according to individually replacement strategy However. It needs new improved cache structure for reducing network traffic and providing advanced hit-ratio. Therefore, this Paper design push agent model using dual cache for increasing hit-ratio by reducing server overload and network traffic by repetition request of persistent and identical information. In this model proposes dual cache structure to do achievement replace gradual cache using by two caches storage space for reducing server overload and network traffic. Also, we show new cache replace techniques and algorithms which executes data update and delete based on replace strategy of Log(Size) +LRU, LFU and PLC for effectiveness of data search in cache. And through an experiment, it evaluates Performance of dual cache push agent model.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.45 no.12
• /
• pp.7-12
• /
• 2008

In this paper, a highly efficiency power amplifier is presented for multi-band antenna system. The class F power amplifier operating in dual-band designed with one LDMOSFET. An operating frequency of power amplifier is 900 MHz and 2.14 GHz respectively Matching networks and harmonic control circuits of amplifier are designed by using the unit cell of composite right/left-handed(CRLH) transmission line(TL) realized with lumped elements. The CRLH TL can lead to metamaterial transmission line with the dual-band holing capability. The dual-band operation of the CRLH TL is achieved by the frequency offset and the nonlinear phase slope of the CRLH TL for the matching network of the power amplifier. Because the control of all harmonic components for high efficiency is very difficult, we have controled only the second- and third-harmonics to obtain the high efficiency with the CRLH TL. Also, the proposed power amplifier has been realized by using the harmonic control circuit for not only the output matching network, but also the input matching network for better efficiency.

• Journal of KIISE:Computer Systems and Theory
• /
• v.29 no.2
• /
• pp.105-115
• /
• 2002

Since NUMA architecture has to access remote memory an interconnection network determines the performance of CC-NUMA system Bus which has been used as a popular interconnection network has many limits to build a large-scale system because of the limited physical scalabilty and bandwidth Dual ring interconnection network composed of high speed point-to-point links is made up for resolving the defects of the bus for large-scale system But it also has a problem that the response latency is rapidly increased when many node are attached to snooping based CC-NUMA system with dual ring In this paper we propose a chordal ring architecture in order to overcome the problem of the dual ring on snooping based CC-NUMA system and design and efficient link controller adopted to this architecture. We also analyze the effects of chordal ring architecture on the system performance and the response latency by using probability driven simulator.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.18 no.4
• /
• pp.938-958
• /
• 2024

Unsupervised Video Object Segmentation (UVOS) is a highly challenging problem in computer vision as the annotation of the target object in the testing video is unknown at all. The main difficulty is to effectively handle the complicated and changeable motion state of the target object and the confusion of similar background objects in video sequence. In this paper, we propose a novel deep Dual-stream Co-enhanced Network (DC-Net) for UVOS via bidirectional motion cues refinement and multi-level feature aggregation, which can fully take advantage of motion cues and effectively integrate different level features to produce high-quality segmentation mask. DC-Net is a dual-stream architecture where the two streams are co-enhanced by each other. One is a motion stream with a Motion-cues Refine Module (MRM), which learns from bidirectional optical flow images and produces fine-grained and complete distinctive motion saliency map, and the other is an appearance stream with a Multi-level Feature Aggregation Module (MFAM) and a Context Attention Module (CAM) which are designed to integrate the different level features effectively. Specifically, the motion saliency map obtained by the motion stream is fused with each stage of the decoder in the appearance stream to improve the segmentation, and in turn the segmentation loss in the appearance stream feeds back into the motion stream to enhance the motion refinement. Experimental results on three datasets (Davis2016, VideoSD, SegTrack-v2) demonstrate that DC-Net has achieved comparable results with some state-of-the-art methods.

• Journal of Fisheries and Marine Sciences Education
• /
• v.25 no.4
• /
• pp.998-1007
• /
• 2013

At container terminals, a major measurement of productivity can be work efficiency. For improving the productivity of container crane, the more efficient container yard operation method is necessary in container terminals. Recently, container terminal operators make an experiment on the dual cycle operation, which ship loading/unloading were carried out simultaneously, for increasing the productivity of container crane. In this paper, propose a system operating efficient dual cycle methods as utilize Ad-hoc technology in distributed port operation system. The dual cycle methods that proposed recognizes position information of Y/T during an action in Ad-hoc networks in case of container transfer works by real time as load an Ad-hoc module to Y/T taking charge of a container transfer with quay and yard. Utilize Ad-hoc networks technology in an operating system of container yard, and efficiently distributed processing done Y/T to container crane compare with operation systems of the existing dedicated method, and an improvement can do an operating system of an yard.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.19 no.3
• /
• pp.1-14
• /
• 1994

In this paper, an analytical model of the message delay in the DQDB (Distributed Queue Dual Bus) network is investigated. The DQDB network has been adopted as a subnetwork for the IEEE 802 MAN (Metropolitan Area Network) standard. The DQDB network consists of two high speed undirectional buses and a series of stations attached to both of the buses. Massages arriving at each station consists of severla packets according to its size. This system is approximated into " $B^{[x]}$/G/1 with exceptional first service queueing " by defining the concept of service time on a packet. The service time for a packet is defined as the time from the instant the packet arrives at the transmission buffer until the time the packet is fully transmitted. By using the BASTA property and the average work in the system, the mean message delay time is obtained.age work in the system, the mean message delay time is obtained.d.

• Proceedings of the IEEK Conference
• /
• 2006.06a
• /
• pp.953-954
• /
• 2006

Guaranteeing survivability is the most important issue in designing and operating optical transmission network. For dual system of optical transmission network, there should be two routes of the optical to prepare an error in one cable route. If a route is selected based on the standard of unused optical core when choosing an optical cable, dual optical cable routes could be installed in duplicated line. This paper simulates the installation of duplicated line when designing an optical transmission network, detects the status of duplicated line that could happen during transfer construction and switching and accomplishes a system that can confirm the location based on a map.

• Journal of Institute of Control, Robotics and Systems
• /
• v.4 no.2
• /
• pp.264-272
• /
• 1998

This paper proposes a fault detection and recovery mechanism for a fault-tolerant Mini-MAP system, and provides detailed techniques for its implementation. This paper considers the fault-tolerant Mini-MAP system which has dual layer structure from the LLC sublayer down to the physical layer to cope with the faults of those layers. For a good fault detection, a redundant and hierarchical fault supervision architecture is proposed and its implementation technique for a stable detection operation is provided. Information for the fault location is provided from data reported with a fault detection and obtained by an additional network diagnosis. The faults are recovered by the stand-by sparing method applied for a dual network composed of two equivalent networks. A network switch mechanism is proposed to achieve a reliable and stable network function. A fault-tolerant Mini-MAP system is implemented by applying the proposed fault detection and recovery mechanism.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.30 no.5B
• /
• pp.287-294
• /
• 2005

It is impossible to replace overnight the present Internet Protocol Version 4(IPv4)-based Internet with Internet Protocol Version 6(IPv6). These two protocols are expected to coexist for a number of years during the transition period. A number of transition mechanisms are proposed by Internet Engineering Task Force(IETF) Next Generation Transition Working Group(Ngtrans WG). However, most of them provide only the mechanism to initiate sessions from hosts within the IPv6 network to those within the IPv4 network, but do not support the initiation from IPv4 hosts to IPv6 ones. In this paper, we propose the IPv4-to-IPv6 Dual Stack Transition Mechanism(4to6 DSTM) which can operate even in the case that IPv4 clients in the IPv4 network initiate connections with dual stack servers in the IPv6 network.

• Journal of Korea Multimedia Society
• /
• v.23 no.4
• /
• pp.525-538
• /
• 2020

A practical animal face classification system that classifies animals in image and video data is considered as a pivotal topic in machine learning. In this research, we are proposing a novel method of fully connected dual Deep Convolutional Neural Network (DCNN), which extracts and analyzes image features on a large scale. With the inclusion of the state of the art Batch Normalization layer and Exponential Linear Unit (ELU) layer, our proposed DCNN has gained the capability of analyzing a large amount of dataset as well as extracting more features than before. For this research, we have built our dataset containing ten thousand animal faces of ten animal classes and a dual DCNN. The significance of our network is that it has four sets of convolutional functions that work laterally with each other. We used a relatively small amount of batch size and a large number of iteration to mitigate overfitting during the training session. We have also used image augmentation to vary the shapes of the training images for the better learning process. The results demonstrate that, with an accuracy rate of 92.0%, the proposed DCNN outruns its counterparts while causing less computing costs.