• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.12
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• pp.602-607
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• 2000

This paper presents the new simulation algorithms using network methods to analysis the steady-state train voltage distribution characteristics in ac auto-transformer fed railroads. In general, the supply system of railroads is composed of non-symmetrical and unbalance transmission line. Therefore, the general method using simplified old algorithms have the self-contradictory errors because the supply line of train railroads is completely unbalanced. In this paper, the simulation results of new developed algorithms is compared with those of EMTP to confirm the effectiveness.

• Journal of Information Processing Systems
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• v.14 no.1
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• pp.101-128
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• 2018

Thanks to its potential in many applications, Blockchain has recently been nominated as one of the technologies exciting intense attention. Blockchain has solved the problem of changing the original low-trust centralized ledger held by a single third-party, to a high-trust decentralized form held by different entities, or in other words, verifying nodes. The key contribution of the work of Blockchain is the consensus algorithm, which decides how agreement is made to append a new block between all nodes in the verifying network. Blockchain algorithms can be categorized into two main groups. The first group is proof-based consensus, which requires the nodes joining the verifying network to show that they are more qualified than the others to do the appending work. The second group is voting-based consensus, which requires nodes in the network to exchange their results of verifying a new block or transaction, before making the final decision. In this paper, we present a review of the Blockchain consensus algorithms that have been researched and that are being applied in some well-known applications at this time.

• Electronics and Telecommunications Trends
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• v.37 no.1
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• pp.73-83
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• 2022

Visual object tracking can be utilized in various applications and has attracted considerable attention in the field of computer vision. Visual object tracking technology is classified in various ways based on the number of tracking objects and the methodologies employed for tracking algorithms. This report briefly introduces the visual object tracking challenge that contributes to the development of single object tracking technology. Furthermore, we review ten Siamese network-based algorithms that have attracted attention, owing to their high tracking speed (despite the use of neural networks). In addition, we discuss the prospects of the Siamese network-based object tracking algorithms.

• Journal of information and communication convergence engineering
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• v.22 no.1
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• pp.1-6
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• 2024

Energy efficiency in wireless sensor networks (WSNs) is a critical issue because batteries are used for operation and communication. In terms of scalability, energy efficiency, data integration, and resilience, WSN-cluster-based routing algorithms often outperform routing algorithms without clustering. Low-energy adaptive clustering hierarchy (LEACH) is a cluster-based routing protocol with a high transmission efficiency to the base station. In this paper, we propose an energy consumption model for LEACH and compare it with the existing LEACH, advanced LEACH (ALEACH), and power-efficient gathering in sensor information systems (PEGASIS) algorithms in terms of network lifetime. The energy consumption model comprises energy-sensitive cluster formation and a cluster head selection technique. The setup and steady-state phases of the proposed model are discussed based on the cluster head selection. The simulation results demonstrated that a low-energy-consumption network was introduced, modeled, and validated for LEACH.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.145-148
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• 2002

In a network communication process, cryptographic algorithms play important role for secure process. This paper presents a new system architecture named "DCCS." This system can handle flexible operations of both cryptographic algorithms and the keys. For experimental evaluation, two representative cryptographic algorithms DES and Triple-DES are designed and implemented into an FPGA chip on the SEBSW-1. Then the developed board is confirmed to change its cryptographic algorithms dynamically. Also its throughput confirmed the ability of the real-time net-work use of the designed system.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.552-557
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• 2004

Mobile Ad Hoc Network (MANET) is a network architecture, which has no backbone network and is deployed temporarily and rapidly in emergency or war without fixed mobile infrastructures. All communications between network entities are carried in ad-hoc networks over the wireless medium. Due to the radio communications being extremely vulnerable to propagation impairments, connectivity between network nodes is not guaranteed. Therefore, previously developed routing algorithms in wired networks cannot be used. And many new algorithms have been undergone. This study proposes the secondary leader approach to the cluster based routing protocol(CBRP). In case, the primary leader becomes abnormal status so that the primary leader cannot participate the communications between network entities, the secondary leader immediately replaces the primary header without selecting process of the new primary leader. The performances of proposed algorithm ACBRP(Advanced Cluster. Based Routing Protocol;CBRP using secondary leader) are compared with CBRP and results are presented in order to show the effectiveness of the algorithm.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.8
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• pp.471-481
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• 2003

The acts of biological immune system are similar to the navigation for autonomous mobile robots under dynamically changing environments. In recent years, many researchers have studied navigation algorithms using artificial immune networks. Conventional artificial immune algorithms consist of an obstacle-avoidance behavior and a goal-reaching behavior. To select a proper action, the navigation algorithm should combine the obstacle-avoidance behavior with the goal-reaching behavior. In this paper, the neural network is employed to combine the behaviors. The neural network is trained with the surrounding information. the outputs of the neural network are proper combinational weights of the behaviors in real-time. Also, a velocity control algorithm is constructed with the artificial immune network. Through a simulation study and experimental results for a autonomous mobile robot, we have shown the validity of the proposed navigation algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.6
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• pp.2711-2733
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• 2018

Minimizing power consumption in bandwidth limited optical traffic grooming networks is presented as a two-objective optimization problem. Since the main objective is to route a connection, the network throughput is maximized first, and then the minimum power consumption solution is found for this maximized throughput. Both transparent IP over WDM (Tp-IPoWDM) and translucent IP over WDM (Tl-IPoWDM) network may be applied to examine such bi-objective algorithms. Simulations show that the bi-objective algorithms are more energy-efficient than the single objective algorithms where only the throughput is optimized. For a Tp-IPoWDM network, both link based ILP (LB-ILP) and path based ILP (PB-ILP) methods are formulated and solved. Simulation results show that PB-ILP can save more power than LB-ILP because PB-ILP has more path selections when lightpath lengths are limited. For a Tl-IPoWDM network, only PB-ILP is formulated and we show that the Tl-IPoWDM network consumes less energy than the Tp-IPoWDM network, especially under a sparse network topology. For both kinds of networks, it is shown that network energy efficiency can be improved by over-provisioning wavelengths, which gives the network more path choices.

• Journal of applied mathematics & informatics
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• v.9 no.2
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• pp.607-620
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• 2002

In this paper, we consider the updating problems to reconstruct the biconnected-components and to reconstruct the weighted shortest path in response to the topology change of the network. We propose two distributed algorithms. The first algorithm solves the updating problem that reconstructs the biconnected-components after the several processors and links are added and deleted. Its bit complexity is O((n'+a+d)log n'), its message complexity is O(n'+a+d), the ideal time complexity is O(n'), and the space complexity is O(e long n+e' log n'). The second algorithm solves the updating problem that reconstructs the weighted shortest path. Its message complexity and ideal-time complexity are $O(u^2+a+n')$ respectively.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2000.04a
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• pp.347-356
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• 2000

This paper compares four models of artificial neural networks (ANN) supported by genetic algorithms the prediction of stock price index. Previous research proposed many hybrid models of ANN and genetic algorithms(GA) in order to train the network, to select the feature subsets, and to optimize the network topologies. Most these studies, however, only used GA to improve a part of architectural factors of ANN. In this paper, GA simultaneously optimized multiple factors of ANN. Experimental results show that GA approach to simultaneous optimization for ANN (SOGANN3) outperforms the other approaches.