• Journal of applied mathematics & informatics
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• v.19 no.1_2
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• pp.215-229
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• 2005

In this paper, constraint aggregation is combined with the adjoint and multiple shooting strategies for optimal control of differential algebraic equations (DAE) systems. The approach retains the inherent parallelism of the conventional multiple shooting method, while also being much more efficient for large scale problems. Constraint aggregation is employed to reduce the number of nonlinear continuity constraints in each multiple shooting interval, and its derivatives are computed by the adjoint DAE solver DASPKADJOINT together with ADIFOR and TAMC, the automatic differentiation software for forward and reverse mode, respectively. Numerical experiments demonstrate the effectiveness of the approach.

• Journal of the Korean Geographical Society
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• v.46 no.2
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• pp.197-211
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• 2011

Due to the complexity of spatial interaction and the necessity of spatial representation and modeling, aggregation of spatial interaction data is indispensible. Given this, the purpose of this paper is to evaluate the effects of modifiable areal unit problem (MAUP) on a spatial interaction model. Four aggregation schemes are utilized at eight different scales: 1) randomly select seeds of district and then allocate basic spatial units to them, 2) minimize the sum of population weighted distance within a district, 3) maximize the proportion of flow within a district, and 4) minimize the proportion of flow within a district. A simple Poisson regression model with origin and destination constraints is utilized. Analysis results demonstrate that spatial characteristics of residuals, parameter values, and goodness-of-fit of the model were influenced by aggregation scale and schemes. Overall, the model responded more sensitively to aggregation scale than aggregation schemes and the scale effect on the model was varied according to aggregation schemes.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.9
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• pp.424-430
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• 2001

A multi-level optimal power flow(OPF) algorithm has been evolved from a simple two stage optimal Power flow algorithm for constrained power economic dispatch control. In the proposed algorithm, we consider various constraints such as ower balance, generation capacity, transmission line capacity, transmission losses, security equality, and security inequality constraints. The proposed algorithm consists of four stages. At the first stage, we solve the aggregated problem that is the crude classical economic dispatch problem without considering transmission losses. An initial solution is obtained by the aggregation concept in which the solution satisfies the power balance equations and generation capacity constraints. Then, after load flow analysis, the transmission losses of an initial generation setting are matched by the slack bus generator that produces power with the cheapest cost. At the second stage we consider transmission losses. Formulation of the second stage becomes classical economic dispatch problem involving the transmission losses, which are distributed to all generators. Once a feasible solution is obtained from the second stage, transmission capacity and other violations are checked and corrected locally and quickly at the third stage. The fourth stage fine tunes the solution of the third stage to reach a real minimum. The proposed approach speeds up the two stage optimization method to an average gain of 2.99 for IEEE 30, 57, and 118 bus systems and EPRI Scenario systems A through D testings.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.926-928
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• 1998

A fast optimization algorithm has been evolved from a simple two stage optimal power flow(OPF) algorithm for constrained power economic dispatch. In the proposed algorithm, we consider various constraints such as power balance, generation capacity, transmission line capacity, transmission losses, security equality, and security inequality constraints. The proposed algorithm consists of four stages. At the first stage, we solve the aggregated problem that is the crude classical economic dispatch problem without considering transmission losses. An initial solution is obtained by the aggregation concept in which the solution satisfies the power balance equations and generation capacity constraints. Then, after load flow analysis, the transmission losses of an initial generation setting are matched by the slack bus generator that produces power with the cheapest cost. At the second stage we consider transmission losses. Formulation of the second stage becomes classical economic dispatch problem involving the transmission losses, which are distributed to all generators. Once a feasible solution is obtained from the second stage, transmission capacity and other violations are checked and corrected locally and quickly at the third stage. The fourth stage fine tunes the solution of the third stage to reach a real minimum. The proposed approach speeds up the coupled LP based OPF method to an average gain of 53.13 for IEEE 30, 57, and 118 bus systems and EPRI Scenario systems A through D testings.

• Journal of Electrical Engineering and Technology
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• v.7 no.4
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• pp.501-512
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• 2012

Social welfare maximization in a double-sided auction market is performed by implementing an aggregation-based particle swarm optimization (CAPSO) algorithm for optimal placement and sizing of one Static Synchronous Series Compensator (SSSC) device. Dallied simulation results (without/with line flow constraints and without/with SSSC) are generated to demonstrate the impact of SSSC on the congestion levels of the modified IEEE 14-bus test system. The proposed CAPSO algorithm employs conventional quadratic smooth and augmented quadratic nonsmooth generator cost curves with sine components to improve the accurate of the model by incorporating the valve loading effects. CAPSO also employs quadratic smooth consumer benefit functions. The proposed approach relies on particle swarm optimization to capture the near-optimal GenCos and DisCos, as well as the location and rating of SSSC while the Newton based load flow solution minimizes the mismatch equations. Simulation results of the proposed CAPSO algorithm are compared to solutions obtained by sequential quadratic programming (SQP) and a recently implemented Fuzzy based genetic algorithm (Fuzzy-GA). The main contributions are inclusion of customer benefit in the congestion management objective function, consideration of nonsmooth generator characteristics and the utilization of a coordinated aggregation-based PSO for locating/sizing of SSSC.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.4B
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• pp.303-310
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• 2006

In sensor network environments, a sensor node has a limited power because of their resource constraints. Therefore it is important to efficiently use its power in sensor networks. Power consumption of sensor node is closely related to its amount of transmission data. So, we need to reduce the transmission data in order to minimize the power consumption. And sensor networks are inherently unreliable because radio transmission can fail, node can move, and so on. In this paper, we propose the reliable data aggregation protocol in order to these problems. This protocol performs the routing and the query inserting process at the same time to minimize the packet loss caused by network changes. And, this protocol removes the unnecessary routing caused by the periodic routing without query. Additionally, we suggest the countermeasure algorithm against the frequent errors in sensor networks.

• ETRI Journal
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• v.27 no.6
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• pp.733-746
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• 2005

In the context of multi-protocol label switching (MPLS) traffic engineering, this paper proposes a scalable constraintbased shortest path first (CSPF) routing algorithm with multiple QoS metrics. This algorithm, called the multiple constraint-based shortest path first (M_CSPF) algorithm, provides an optimal route for setting up a label switched path (LSP) that meets bandwidth and end-to-end delay constraints. In order to maximize the LSP accommodation probability, we propose a link weight computation algorithm to assign the link weight while taking into account the future traffic load and link interference and adopting the concept of a critical link from the minimum interference routing algorithm. In addition, we propose a bounded order assignment algorithm (BOAA) that assigns the appropriate order to the node and link, taking into account the delay constraint and hop count. In particular, BOAA is designed to achieve fast LSP route computation by pruning any portion of the network topology that exceeds the end-to-end delay constraint in the process of traversing the network topology. To clarify the M_CSPF and the existing CSPF routing algorithms, this paper evaluates them from the perspectives of network resource utilization efficiency, end-to-end quality, LSP rejection probability, and LSP route computation performance under various network topologies and conditions.

• Journal of the Korean Society for Railway
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• v.9 no.1 s.32
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• pp.50-56
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• 2006

This paper presents a mathematical model of the long-term track tamping scheduling problem in the Korean highspeed railway system. The presented model encompasses various operational field constraints, moreover improves a state-of-the-art model in extending the feasible space. We show the model is sized up to intractable scale, then propose another approximation model that is possible to handle with the present computer system and commercial optimization package, directly. The aggregated index, lot, is selected, considering the resolution of the planning horizon as well as scheduling purpose. Lastly, this paper presents two test results for the approximation model. The results expose the approximation model to quite promising in deploying it into an operational software program for the long-term track tamping scheduling problem.

• ETRI Journal
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• v.27 no.6
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• pp.725-732
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• 2005

The reconfiguration management scheme changes a logical topology in response to changing traffic patterns in the higher layer of a network or the congestion level on the logical topology. In this paper, we formulate a reconfiguration scheme with a shared buffer-constrained cost model based on required quality-of-service (QoS) constraints, reconfiguration penalty cost, and buffer gain cost through traffic aggregation. The proposed scheme maximizes the derived expected reward-cost function as well as guarantees the required flow's QoS. Simulation results show that our reconfiguration scheme significantly outperforms the conventional one, while the required physical resources are limited.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.6B
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• pp.233-248
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• 2008

Advances in electronics and wireless communication technologies have enabled the development of large-scale wireless sensor networks (WSNs). There are numerous applications for wireless sensor networks, and security is vital for many of them. However, WSNs suffer from many constraints, including low computation capability, small memory, limited energy resources, susceptibility to physical capture, and the lack of infrastructure, all of which impose unique security challenges and make innovative approaches desirable. In this paper, we present a survey on security issues in wireless sensor networks. We address several network models for security protocols in WSNs, and explore the state of the art in research on the key distribution and management schemes, typical attacks and corresponding countermeasures, entity and message authentication protocols, security data aggregation, and privacy. In addition, we discuss some directions of future work.