• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.341-343
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• 2000

Traditionally electric power system are operated in such a way that the total fuel cost is minimized regardless of accounting for tie-lines transmission constraint and emissions produced. But tie-lines transmission and emissions constraint are very important issues in the operation and planning of electric power system. This paper presents the Two-Phase Neural Network(TPNN) to solve the Economic Load Dispatch (ELD) problem with tie-lines transmission and emissions constraint considering transmission losses. The transmission losses are obtained from the B-coefficient which approximate the system losses as s quadratic function of the real power generation. By applying the proposed algorithm to the test system, the usefulness of this algorithm is verified.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.3
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• pp.542-559
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• 2011

Most game-theoretic works of Aloha have emphasized investigating Nash equilibria according to the system state represented by the number of network users and their decisions. In contrast, we focus on the possible change of nodes' utility state represented by delay constraint and decreasing utility over time. These foregone changes of nodes' state are more likely to instigate selfish behaviors in networking environments. For such environment, in this paper, we propose a repeated Bayesian slotted Aloha game model to analyze the selfish behavior of impatient users. We prove the existence of Nash equilibrium mathematically and empirically. The proposed model enables any type of transmission probability sequence to achieve Nash equilibrium without degrading its optimal throughput. Those Nash equilibria can be used as a solution concept to thwart the selfish behaviors of nodes and ensure the system stability.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5324-5337
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• 2017

In this paper, we investigate the feasibility of interference alignment(IA) in signal space in the scenario of multiple cell and multiple user cellular networks, as the feasibility issue is closely related to the solvability of a multivariate polynomial system, we give the mathematical analysis to support the constraint condition obtained from the polynomial equations with the tools of algebraic geometry, and a new distribute IA algorithm is also provided to verify the accessibility of the constraint condition for symmetric system in this paper. Simulation results illustrate that the accessibility of the constraint condition is hold if and only if the degree of freedom(DoF) of each user can be divided by both the transmit and receive antenna numbers.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.887-890
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• 1993

By introducing the notion of constraint-oriented fuzzy inference, we will show that it provides us ways of fuzzy control methods that has abilities of adaptation, learning and self-organization. The basic supporting techniques behind these abilities are“hard”processing by Artificial Intelligence or traditional computational framework and“soft”processing by Neural Network or Genetic Algorithm techniques. The reason that these techniques can be incorporated to fuzzy control systems is that the notion of“constraint”itself has two fundamental properties, that is, the“modularity”property due to its declarativeness and the“logicality”property due to its two-valuedness. From the former property, the modularity property, decomposing and integrating constraints can be done easily and efficiently, which enables us to carry out the above“soft”processing. From the latter property, the logicality property, Qualitative Reasoning and Instance Generalization by Symbolic Reasoning an be carried out, thus enabling the“hard”processing.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.1
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• pp.713-722
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• 2009

Gravity measurement can determine the earth gravitational field, also is the fundamental to the research of earth gravitational field, geodesy and geodynamic, vertical movement of the crust, geoid surface, sea level and climate etc. Recently, National Geographic Information Institute (NGII) introduced FG-5 absolute gravity meter in order to lay a foundation for establishment of Absolute Gravity Network, and furthermore NGII plan to construct about 1,200 multi dimensional and function Unified Control Points(UCP) in nationwide. It will play an important role in development of high accuracy geoid model in South Korea. This paper explains the fundamental theory and method of relative gravity measurement, surveys the relative gravity of 21 stations using latest Scintrex CG-5 relative gravimeter. In addition, it calculates gravity values, compare and analysis gravity survey results using datum-free adjustment and weighted constraint adjustment. The results indicate show that datum-free and weighted constraint adjustment methods are available to determine high accuracy gravity achievement, datum-free method is more advantage than weighted constraint adjustment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.7
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• pp.1777-1791
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• 2012

This paper considers a downlink cognitive radio (CR) network where one secondary user (SU) and one primary user (PU) share the same base station (BS). The spectrum of interest is divided into a set of independent, orthogonal subchannels. The communication of the PU is of high priority and the quality of service (QoS) is guaranteed by the minimum rate constraint. On the other hand, the communication of the SU is of low priority and the SU opportunistically accesses the subchannels that were previously discarded by the PU during power allocation. The BS assigns fractions ?? and 1 ?? of the total available transmit power to the PU and the SU respectively. Two power allocation schemes with opportunistic subchannel access are proposed, in which the optimal values of ??'s are also obtained. The objective of one scheme is to maximize the rate of the SU, and the objective of the other scheme is to maximize the sum rate of the SU and the PU, both under the PU minimum rate constraint and the total transmit power constraint. Extensive simulation results are obtained to verify the effectiveness of the proposed schemes.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.11
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• pp.49-58
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• 2010

In this paper, we present a methodology for fast segment restoration under multiple simultaneous link failures in mesh-type MPLS networks. The salient feature of the methodology is that both resilience and QoS constraint conditions have been taken into account for fast segment restoration. For fast restoration, a sufficient condition for testing the existence of backup segments with guaranteed-resilience has been derived for a mesh-type MPLS network. The algorithms for constructing backup segments which can meet both resilience and QoS constraint conditions are then presented with illustrating examples. Finally, simulation has been done to show the efficiency of the proposed segment restoration algorithms.

• Journal of Communications and Networks
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• v.15 no.5
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• pp.469-475
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• 2013

In this paper, we propose an efficient interference management technique which controls the number of resource blocks (or subcarriers) shared with other cells based on statistical interference levels among cells. The proposed technique tries to maximize average throughput of a femto cell user under a constraint on non-real time control of a femto cell network while guaranteeing a target throughput value of a macro cell user. In our proposed scheme, femto cells opportunistically use resource blocks allocated to other cells if the required average user throughput is not attained with the primarily allocated resource blocks. The proposed method is similar to the underlay approach in cognitive radio systems, but resource block sharing among cells is statistically controlled. For the statistical control, a femto cell sever constructs a table storing average mutual interference among cells and periodically updates the table. This statistical approach fully satisfies the constraint of non-real time control for femto cell networks. Our simulation results show that the proposed scheme achieves higher average femto user throughput than conventional frequency reuse schemes for time varying number of users.

• ETRI Journal
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• v.44 no.3
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• pp.389-399
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• 2022

Wireless sensor networks (WSNs) are one of the basic building blocks of Internet of Things (IoT) systems. However, the wireless sensing nodes in WSNs suffer from energy constraint issues because the replacement/recharging of the batteries of the nodes tends to be difficult. Furthermore, a number of realistic IoT scenarios, such as habitat and battlefield monitoring, contain mobile sensing elements, which makes the energy issues more critical. This research paper focuses on realistic WSN scenarios that involve mobile sensing elements with the aim of mitigating the attendant energy constraint issues using the concept of radio-frequency (RF) energy extraction. The proposed technique incorporates a cluster head election workflow for WSNs that includes mobile sensing elements capable of RF energy harvesting. The extensive simulation analysis demonstrated the higher efficacy of the proposed technique compared with the existing techniques in terms of residual energy, number of functional nodes, and network lifetime, with approximately 50% of the nodes found to be functional at the 4000th, 5000th, and 6000th rounds for the proposed technique with initial energies of 0.25, 0.5 and 1 J, respectively.

• Journal of the Korea Society of Computer and Information
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• v.13 no.5
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• pp.219-227
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• 2008

As found in research on constraint satisfaction problems, the choice of variable ordering heuristics is crucial for effective solving of constraint optimization problems. For the special problems such as energy-efficient clustering in heterogeneous wireless sensor networks, in which cluster heads have an inclination to be near a base station, we propose a new approach based on the static preferences variable orderings and provide a pnode heuristic algorithm for a specific application. The pnode algorithm selects the next variable with the highest Preference. In our problem, the preference becomes higher when the cluster heads are closer to the optimal region, which can be obtained a Priori due to the characteristic of the problem. Since cluster heads are the most dominant sources of Power consumption in the cluster-based sensor networks, we seek to minimize energy consumption by minimizing the maximum energy dissipation at each cluster heads as well as sensor nodes. Simulation results indicate that the proposed approach is more efficient than other methods for solving constraint optimization problems with static preferences.