• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.4157-4175
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• 2020

Moving target defense, as a 'game-changing' security technique for network warfare, realizes proactive defense by increasing network dynamics, uncertainty and redundancy. How to select the best countermeasure from the candidate countermeasures to maximize defense payoff becomes one of the core issues. In order to improve the dynamic analysis for existing decision-making, a novel approach of selecting the optimal countermeasure using game theory is proposed. Based on the signal game theory, a multi-stage adversary model for dynamic defense is established. Afterwards, the payoffs of candidate attack-defense strategies are quantified from the viewpoint of attack surface transfer. Then the perfect Bayesian equilibrium is calculated. The inference of attacker type is presented through signal reception and recognition. Finally the countermeasure for selecting optimal defense strategy is designed on the tradeoff between defense cost and benefit for dynamic network. A case study of attack-defense confrontation in small-scale LAN shows that the proposed approach is correct and efficient.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.5
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• pp.2081-2101
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• 2016

Successive interference cancellation (SIC) is considered to be a promising technique to mitigate multi-user interference and achieve concurrent uplink transmissions, but the optimal power allocation (PA) issue for SIC users is not well addressed. In this article, we focus on the optimization of the PA ratio of users on an SIC channel and analytically obtain the optimal PA ratio with regard to the signal-to-interference-plus-noise ratio (SINR) threshold for successful demodulation and the sustainable demodulation error rate. Then, we design an efficient resource allocation (RA) scheme using the obtained optimal PA ratio. Finally, we compare the proposal with the near-optimum RA obtained by a simulated annealing search and the RA scheme with random PA. Simulation results show that our proposal achieves a performance close to the near-optimum and much higher performance than the random scheme in terms of total utility and Jain's fairness index. To demonstrate the applicability of our proposal, we also simulate the proposal in various network paradigms, including wireless local area network, body area network, and vehicular ad hoc network.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.14 no.2
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• pp.155-163
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• 1989

For a one link flexible arm control, quadratic optimal control is applied to the dynamic modilling which is derived from an assumed mode method. For the quadratic optimal control technique, the full state feedback must be obtained for closing the control loop, but because some of the states in the flexible system(e.g. the rate of change of the time dependent variables of the mode shapes) can not be directly measured, state estimator is necessary to achieve the practical implementation of the optimal controller. When disturbances and measurement noise occur, stochastic approach must be applied to estimating the states of the system. Kalman Filter is used as a stste estimator. Through the simulation, the flexible system with state estimator is compared with the flexible system assuming that all the states can be measured.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.6
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• pp.768-773
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• 2010

This paper presents the performance verification of the optimal state feedback controller via inverted pendulum systems. The proposed method generates the optimal control inputs satisfying both the constrained input and the performance specification. In addition, it reduces the steady-state error by adopting the integral control technique. In order to verify the performance of the proposed method, we apply both the proposed method and the general state feedback control to an inverted pendulum, CEM-IP-01 in the experiment.

• Journal of the Society of Naval Architects of Korea
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• v.42 no.3
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• pp.284-289
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• 2005

A structural design system is developed for the optimum design of double hull tankers based on the multi-objective function method. As a multi-objective function method, Pareto optimal based random search method is adopted to find the minimum structural weight and fabrication cost. The fabrication cost model is developed by considering the welding technique, welding poses and assembly stages to manage the fabrication man-hour and process. In this study, a new structural design is investigated due to the rapidly increased material cost. Several optimum structural designs on the basis of high material cost are carried out based on the Pareto optimal set obtained by the random search method. The design results are compared with existing ship, which is designed under low material cost.

• Journal of Ocean Engineering and Technology
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• v.2 no.2
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• pp.37-45
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• 1988

A dynamically positioned vessel must be capable of maintaining a specified position and direction by controlling the thruster devices. The motions of a vessel are often assuned to tne sum of low frequency(LF)motions and high frequency(HF)motions. The former is mainly due to wind, current and second order wave forces, while the latter is mainly due to first order wave forces. In order to avoid the high frequency thruser modulation, the control system must include filters to estimate the low frequency motions from the measured motion signals, This paper presents a control system based on Kalman filtering technique and optimal control tyeory. Using the combined kalmam filter, LF motion estimates and HF ones are achieved from the motion measurement of the vessel. The estimated low frequency motions are used as inputs to the dynamic positioning system. The thruster modulation is minimized using the optimal control theory; Linear Quadratic Gaussian(LQG)controller. The performances of the Kalman filter and the dynamic positioned vessel are investigated by computer simulation.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.3
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• pp.232-239
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• 1990

A new algorithm is suggested to solve the optimal reactive power and voltage control (optimal VAR control) problem. The model minimizes the real power losses in the system. The constraints include the reactive power limits of the generators, limits on the bus voltages and the operating limits of control variables-the transformer tap positions generator terminal voltages and switchable reactive power sources. The method presented herein, using a newly developed Jacobian decomposition method, employs linearized sensitivity relationships of power systems to establish both the objective function for minimizing the system losses and the system performance sensitivities relating dependent and control variables. The algorithm consists of two modules, i.e. the Q-V module for reactive power-voltage control, and load flow module for computational error adjustments. In particular the acceleration factor technique is introduced to enhance the convergence property in Q-V module. The combined use of the afore-mentioned two modules ensures more effective and efficient solutions for optimal reactive power dispatch problems. Results of the application of the method to a sample system and other worst-case systems demonstrated that the algorithm suggested herein is compared favourably with conventional ones in terms of computation accuracy and convergence characteristics.

• Journal of Electrical Engineering and Technology
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• v.9 no.4
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• pp.1229-1239
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• 2014

Optimal Distributed Generation (DG) output and reconfiguration are among the well accepted approach to reduce power loss in a distribution network. In the past, most of the researchers employed optimal DG output and reconfiguration separately. In this work, a simultaneous DG output and reconfiguration analysis is proposed to maximize power loss reduction. The impact of the separated analysis and simultaneous analysis are investigated. The test result on the 33 bus distribution network with 3 units of DG operated in PV mode showed the simultaneous analysis gave the lowest power loss (global optimal) and faster results compared to other combined methods. All the analyses for optimizing the DG as well as reconfiguration are used the Artificial Bee Colony Optimization technique.

• Journal of Chest Surgery
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• v.53 no.4
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• pp.233-241
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• 2020

Vagal damage and subsequent pyloric denervation inevitably occur during esophagectomy, potentially leading to delayed gastric emptying (DGE). The choice of an optimal pyloric procedure to overcome DGE is important, as such procedures can lead to prolonged surgery, shortening of the conduit, disruption of the blood supply, and gastric dumping/bile reflux. This study investigated various pyloric methods and analyzed comparative studies in order to determine the optimal pyloric procedure. Surgical procedures for the pylorus include pyloromyotomy, pyloroplasty, or digital fracture. Botulinum toxin injection, endoscopic balloon dilatation, and erythromycin are non-surgical procedures. The scope, technique, and effects of these procedures are changing due to advances in minimally invasive surgery and postoperative interventions. Some comparative studies have shown that pyloric procedures are helpful for DGE, while others have argued that it is difficult to reach an objective conclusion because of the variety of definitions of DGE and evaluation methods. In conclusion, recent advances in interventional technology and minimally invasive surgery have led to questions regarding the practice of pyloric procedures. However, many clinicians still perform them and they are at least somewhat effective. To provide guidance on the optimal pyloric procedure, DGE should first be defined clearly, and a large-scale study with an objective evaluation method will then be required.

• Journal of the Society of Naval Architects of Korea
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• v.42 no.2 s.140
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• pp.175-182
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• 2005

It is necessary to develop an efficient optimization technique to optimize the engineering structures which have given design spaces, discrete design values and several design goals. As optimization techniques, direct search method and stochastic search method are widely used in designing of engineering structures. The merit of the direct search method is to search the optimum points rapidly by considering the search direction, step size and convergence limit. And the merit of the stochastic search method is to obtain the global optimum points by spreading point randomly entire the design spaces. In this paper, a Pareto optimal based multi-objective function method (PMOFM) is developed by considering the search direction based on Pareto optimal points, step size, convergence limit and random search generation . The PMOFM can also apply to the single objective function problems, and can consider the discrete design variables such as discrete plate thickness and discrete stiffener spaces. The design results are compared with existing Evolutionary Strategies (ES) method by performing the design of double bottom structures which have discrete plate thickness and discrete stiffener spaces.