• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.7
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• pp.1412-1418
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• 2005

Recently, more and more portable terminals probably have multiple interfaces to be connected to different access technologies. Each technology has its specific characteristics in terms of coverage area, bandwidth, reliability, etc. For example, the mobile node is equipped with three heterogeneous interfaces; IEEE 802.1lb MLAM link, CDMA Cellular link, and 802.16 WiMAX link These mobile nodes may be reachable through different links at the same time or use each interface alternately depending on the network environment. As like this, the portable terminal equipped multiple interfaces can have many benefits; it should be connect to Internet through other interface in case of occurring to failure for currently activate interface, and it should share a mount of traffic efficiently per interface etc. This environment is called end node Multihoming. However, current most Internet protocols are designed originally with single interface in mind. So these potocols do not provide methods for supporting simultaneous diffentiated use of multiple access technologies. In this paper, firstly we have to refer technical consideration items to use multiple interfaces based on IPv6 simultaneously. And we should propose extended registration mechanism for multiple addresses being acquired from interfaces to support reliable accessibility and vertical handover.

• International Journal of Precision Engineering and Manufacturing
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• v.7 no.1
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• pp.62-66
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• 2006

The learning control develops controllers that learn to improve their performance at executing a given task, based on experience performing this specific task. In a previous work, the authors presented an iterative precision of linear decentralized learning control based on p-integrated learning method for the vertical dynamic multiple systems. This paper develops an indirect decentralized learning control based on adaptive control method. The original motivation of the learning control field was learning in robots doing repetitive tasks such as an assembly line works. This paper starts with decentralized discrete time systems, and progresses to the robot application, modeling the robot as a time varying linear system in the neighborhood of the nominal trajectory, and using the usual robot controllers that are decentralized, treating each link as if it is independent of any coupling with other links. Some techniques will show up in the numerical simulation for vertical dynamic robot. The methods of learning system are shown for the iterative precision of each link.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.4
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• pp.92-98
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• 2005

The learning control develops controllers that learn to improve their performance at executing a given task, based on experience performing this specific task. In a previous work, the authors presented an iterative precision of linear decentralized learning control based on p-integrated learning method for the vertical dynamic multiple systems. This paper develops an indirect decentralized teaming control based on adaptive control method. The original motivation of the teaming control field was loaming in robots doing repetitive tasks such as on an assembly line. This paper starts with decentralized discrete time systems, and progresses to the robot application, modeling the robot as a time varying linear system in the neighborhood of the nominal trajectory, and using the usual robot controllers that are decentralized, treating each link as if it is independent of any coupling with other links. Some techniques will show up in the numerical simulation for vertical dynamic robot. The methods of learning system are shown up for the iterative precision of each link.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.1
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• pp.145-164
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• 2014

Network virtualization provides a promising tool to allow multiple heterogeneous virtual networks to run on a shared substrate network simultaneously. A long-standing challenge in network virtualization is the Virtual Network Embedding (VNE) problem: how to embed virtual networks onto specific physical nodes and links in the substrate network effectively. Recent research presents several heuristic algorithms that only consider single topological attribute of networks, which may lead to decreased utilization of resources. In this paper, we introduce six complementary characteristics that reflect different topological attributes, and propose three topology-aware VNE algorithms by leveraging the respective advantages of different characteristics. In addition, a new KS-core decomposition algorithm based on two characteristics is devised to better disentangle the hierarchical topological structure of virtual networks. Due to the overall consideration of topological attributes of substrate and virtual networks by using multiple characteristics, our study better coordinates node and link embedding. Extensive simulations demonstrate that our proposed algorithms improve the long-term average revenue, acceptance ratio, and revenue/cost ratio compared to previous algorithms.

• Journal of Korean Society of Transportation
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• v.11 no.1
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• pp.67-86
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• 1993

A formulation of dynamic traffic assignment between multiple origins and single destination was first introduced in 1987 by Merchant and Nemhauser, and then expanded for multiple destination in the late 1980's (Carey, 1987). Based on behavioral choice theory which provides proper demand elasticities with respect to changes in policy variables, traffic phenomena can be analysed more realistically, especially in peak periods. However, algorithms for these models are not well developed so far(working with only small toy network) and solutions of these models are not unique. In this paper, a new model is developed which keeps the simplicity of static models, but provides the sensitivity of dynamic models with changes of O-D flows over time. It can be viewed as a joint departure time and route choice model, in the given time periods(6-7, 7-8, 8-9 and 9-10 am). Standard multinomial logit model has been used for simulating the choice behavior of destination, mode, route and departure time within a framework of the incremental network assignment model. The model developed is workable in a PC 386 with 175 traffic zones and 3581 links of Seoul and tested for evaluating the exclusive use of Namsan tunnel for HOV and the left-turn prohibition. Model's performance results and their statistical significance are also presented.

• Journal of Korea Multimedia Society
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• v.13 no.6
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• pp.849-864
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• 2010

This paper proposes a multipath routing protocol called cross-layer multipath AODV (CM-AODV) for wireless ad hoc networks, which selects multiple routes on demand based on the signal-to-interference plus noise ratio (SINR) measured at the physical layer. Note that AODV (Ad hoc On-demand Distance Vector) is one of the most popular routing protocols for mobile ad hoc networks. Each time a route request (RREQ) message is forwarded hop by hop, each forwarding node updates the route quality which is defined as the minimum SINR of serialized links in a route and is contained in the RREQ header. While achieving robust packet delivery, the proposed CM-AODV is amenable to immediate implementation using existing technology by neither defining additional packet types nor increasing packet length. Compared to the conventional multipath version of AODV (which is called AOMDV), CM-AODV assigns the construction of multiple paths to the destination node and makes it algorithmically simple, resulting in the improved performance of packet delivery and the less overhead incurred at intermediate nodes. Our performance study shows that CM-AODV significantly outperforms AOMDV in terms of packet delivery ratio and average end-to-end delay, and results in less routing overhead.

• Journal of Korean Academy of Nursing
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• v.44 no.5
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• pp.515-524
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• 2014

Purpose: The purpose of this study was to identify whether the couple perceived breast cancer as a traumatic event, to evaluate the association among posttraumatic growth, dyadic adjustment, and quality of life and to explore the predictors affecting quality of life of the couple. Methods: A cross-sectional comparative survey design was utilized. Participants were 57 couples recruited from a national cancer center in Korea. Data were analyzed using paired t-test, McNemar test and independent t-test. On the basis of variables found to be significantly associated with quality of life, multiple regression was used to examine the simultaneous influence of multiple predictors. Results: Breast cancers survivors and spouses perceived breast cancer as a traumatic event (43.9% and 24.6%, respectively). The global quality of life was explained by perception as trauma (${\beta}$= -19.79) and posttraumatic growth (${\beta}$=0.46) in survivors, and perception as trauma (${\beta}$= -18.81) and dyadic adjustment (${\beta}$=0.53) in spouses. Conclusion: Results suggest that future research should use qualitative methods to evaluate why contemplating reasons for cancer contributed to posttraumatic growth, examine other potential predictors of quality of life such as dyadic adjustment and intimacy, and identify links between posttraumatic growth and other psychological outcomes such as distress and well-being, using prospective analyses.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.8
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• pp.3201-3223
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• 2020

Wireless communication has become the promising technology in the recent times because of its applications in Internet of Things( IoT) devices. The IEEE 802.15.4e has become the key technology for IoT devices which utilizes the Time-Slotted Channel Hopping (TSCH) networks for the communication between the devices. In this paper, we develop a Two Level Scheduling Algorithm (TLSA) for scheduling multiple packets with different arrival rate at the source nodes in a TSCH networks based on the link activated by a centralized scheduler. TLSA is developed by considering three types of links in a network such as link i with packets arrival type 1, link j with packets arrival type 2, link k with packets arrival type 3. For the data packets arrival, two stages in a network is considered.At the first stage, the packets are considered to be of higher priority.At the second stage, the packets are considered to be of lower priority.We introduce level 1 schedule for the packets at stage 1 and level 2 schedule for the packets at stage 2 respectively. Finally, the TLSA is validated with the two different energy functions i.e., y = e^ax - 1 and y = 0.5x² using MATLAB 2017a software for the computation of average and worst ratios of the two levels.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.325-339
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• 2018

In this paper, we propose a joint adaptive combining and variable tap-length multiuser detector (MUD) for amplify-and-forward (AF) underwater acoustic cooperative interleave-division multiple access (IDMA) communication system. The proposed MUD jointly realizes tap-length adjustment, adaptive combining, and multiuser detection. In contrast to the existing methods, the proposed detector can adaptively combine the received signals from different nodes at destination, and does not need the assumption that full and perfect channel state information (CSI) of all the links at the receiver is known. Moreover, the proposed detector can adaptively adjust the tap coefficient vector and tap-length of each branch according to the specific channel profile of each branch. Simulation results validate the feasibility and show the advantages of the proposed detector against existing counterparts.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.6
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• pp.88-98
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• 1998

Subspace classifier is a popular pattern recognition method based on Karhunen-Loeve transform. This classifier describes a high dimensional pattern by using a reduced dimensional subspace. Because of the loss of information induced by dimensionality reduction, however, a subspace classifier sometimes shows unsatisfactory recognition performance to the patterns having quite similar principal components each other. In this paper, we propose the use of multiple novelty neural network classifiers constructed on novelty vectors to adopt minor components usually ignored and present a method of improving recognition performance through combining those with the subspace classifier. We develop the proposed classifier on handwritten numeral database and analyze its properties. Our proposed classifier shows better recognition performance compared with other classifiers, though it requires more weight links.