• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.4042-4059
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• 2020

The development of new multimedia techniques such as 3D printing is increasingly attracting the public's attention towards 3D objects. An optimized robust and imperceptible watermarking method based on Ant Colony Optimization (ACO) and Weber Law is proposed for 3D polygonal models. The proposed approach partitions the host model into smaller sub meshes and generates a secret watermark from the sub meshes using Weber Law. ACO based optimized strength factor is identified for embedding the watermark. The secret watermark is embedded and extracted on the wavelet domain. The proposed scheme is robust against geometric and photometric attacks that overcomes the synchronization problem and authenticates the secret watermark from the distorted models. The primary characteristic of the proposed system is the flexibility achieved in data embedding capacity due to the optimized strength factor. Extensive simulation results shows enhanced performance of the recommended framework and robustness towards the most common attacks like geometric transformations, noise, cropping, mesh smoothening, and the combination of such attacks.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.2 no.1
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• pp.95-110
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• 1998

Evolutionary Algorithms (EAs) are population-based optimization methods based on the principle of Darwinian natural selection. The representative methodology in EAs is genetic algorithm (GA) proposed by J. H. Holland, and the theoretical foundations of GA are the Schema Theorem and the Building Block Hypothesis. In the meaning of these foundational concepts, simple genetic algorithm (SGA) allocate more trials to the schemata whose average fitness remains above average. Although SGA does well in many applications as an optimization method, still it does not guarantee the convergence of a global optimum in GA-hard problems and deceptive problems. Therefore as an alternative scheme, there is a growing interest in a co-evolutionary system, where two populations constantly interact and co-evolve in contrast with traditional single population evolutionary algorithm. In this paper we show why the co-evolutionary algorithm works better than SGA in terms of an extended schema theorem. And predator-prey co-evolution and symbiotic co-evolution, typical approaching methods to co-evolution, are reviewed, and dynamic fitness landscape associated with co-evolution is explained. And the experimental results show a co-evolutionary algorithm works well in optimization problems even though in deceptive functions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5574-5591
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• 2017

Inspired by the idea of Artificial Immune System, many researches of wireless sensor network (WSN) intrusion detection is based on the artificial intelligent system (AIS). However, a large number of generated detectors, black hole, overlap problem of NSA have impeded further used in WSN. In order to improve the anomaly detection performance for WSN, detector generation mechanism need to be improved. Therefore, in this paper, a Differential Evolution Constraint Multi-objective Optimization Problem based Negative Selection Algorithm (DE-CMOP based NSA) is proposed to optimize the distribution and effectiveness of the detector. By combining the constraint handling and multi-objective optimization technique, the algorithm is able to generate the detector set with maximized coverage of non-self space and minimized overlap among detectors. By employing differential evolution, the algorithm can reduce the black hole effectively. The experiment results show that our proposed scheme provides improved NSA algorithm in-terms, the detectors generated by the DE-CMOP based NSA more uniform with less overlap and minimum black hole, thus effectively improves the intrusion detection performance. At the same time, the new algorithm reduces the number of detectors which reduces the complexity of detection phase. Thus, this makes it suitable for intrusion detection in WSN.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.1A
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• pp.10-17
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• 2000

In this paper, we evaluate the correlation properties and the optimization of PN sequence phase for multi-media DS/CDMA system with variable spreading gain (VSG) scheme. In multi-media multi-rate DS/CDMA systems, the optimization of PN sequence phase is not a tractable problem, since the sequences should be optimized against both sequences of the same length and other sequences with different length. Hence, we verify the correlation properties of PN sequence phase in multi-rate system environment and furthermore, we propose the new phase criterion, MIN-AIP (minimum-average interference parameter), to minimize the bit error rate (BER). As the results of performance evaluations, it is shown that the performance of MIN-AIP criteria gives the best results.

• Journal of Ocean Engineering and Technology
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• v.25 no.5
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• pp.76-81
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• 2011

In the shipbuilding industry, accuracy management is one of the keys for strengthening competitiveness. However, ship block errors are unavoidable in the block erection stage because of the deformation of the blocks. Currently, accuracy managers decide whether or not block corrections are needed, based on measured and designed point data. They adjust the locations of hull blocks so that the blocks are aligned with other assembly blocks based upon the experience of production engineers. This paper proposes an optimization process that can adjust the locations of ship blocks during the erection stage. A genetic algorithm is used for this optimization scheme. Finally, the feasibility of the proposed method is discussed using several case studies. We found that the proposed method can find the optimized re-alignment of erection blocks, as well as improve the productivity of the erection stage.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.5
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• pp.694-700
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• 2010

This paper proposes the intelligent shift algorithm for automatic transmissions and develops the simulator for the its optimization and analysis. It provides the comfortable ride to drivers and improves the driving force efficiency without any loss of the performance. In addition, the developed simulator not only cuts the commercialization cost but provides diverse test conditions. The analysis and optimization of the proposed scheme are verified by the developed simulator. As a simple example, the developed simulator verifies the proposed algorithm and shows the comparative result with the existed automatic transmission shift algorithm.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.11
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• pp.58-67
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• 2014

A grid-connected inverter used for renewable energy resources produces harmonic components in the switching frequency. To effectively reduce switching harmonic components, several types of filter are generally used in the output stage of the grid-connected inverter. Many research works on LCL filter design have been done to maintain the performance with low cost. However, it is not easy to make the filter design be economical and optimal due to the varying characteristic of magnetic core and redundancy design by experience. In this paper, a design method for a LCL filter is presented through the inductor optimization scheme in view of the size and cost when the inductor is manufactured using the magnetic core. The effectiveness is verified through tests using a 3kW grid-connected inverter by simulations and experiments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.9B
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• pp.1407-1415
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• 2010

In recent years, the smart grid technique for maximizing the energy efficiency of power networks has received a great deal of attentions. In particular, the Demand Response is a core technology differentiated from the present power network under the smart grid paradigm. To minimize the electric cost and maximize users' satisfaction, this paper proposes a unique scheduling algorithm derived by using optimization where the characteristics of various home appliances are taken into account. For this goal, we represent mathematical consumption patterns of the electric loads and propose the optimal scheduling scheme based on the importance factor of each device during one day. In the simulation results, we demonstrate the effectiveness of the proposed algorithm in the viewpoint of the minimal electric costs utilizing real statistical figures.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.793-796
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• 1996

This study proposes a new algorithm which performs a production simulation under various constraints and maintains computational efficiency. In order to consider the environmental and operational constraints, the proposed algorithm is based on optimization techniques formulated in LP form In the algorithm, "system characteristic constraints" reflect the system characteristics such as LDC shape, unit loading order and forced outage rate. By using the concept of Energy Invariance Property and two operational rules i.e. Compliance Rule for Emission Constraint, Compliance Rule for Limited Energy of Individual Unit, the number of system characteristic constraints is appreciably reduced. As a solution method of the optimization problem, the author uses Karmarkar's method which performs effectively in solving large scale LP problem. The efficiency of production simulation is meaningful when it is effectively used in power system planning. With the proposed production simulation algorithm, an optimal expansion planning model which can cope with operational constraints, environmental restriction, and various uncertainties is developed. This expansion planning model is applied to the long range planning schemes by WASP, and determines an optimal expansion scheme which considers the effect of supply interruption, load forecasting errors, multistates of unit operation, plural limited energy plants etc.

• Advances in aircraft and spacecraft science
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• v.6 no.5
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• pp.349-369
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• 2019

In the design of flight control systems there are issues that deserve special consideration and attention such as external perturbations or systems failures. A Simple Adaptive Controller (SAC) that does not require a-priori knowledge of the faults is proposed in this paper with the aim of realizing a fault tolerant flight control system capable of leading the pitch motion of an aircraft. The main condition for obtaining a stable adaptive controller is the passivity of the plant; however, since real systems generally do not satisfy such requirement, a properly defined Parallel Feedforward Compensator (PFC) is used to let the augmented system meet the passivity condition. The design approach used in this paper to synthesize the PFC and to tune the invariant gains of the SAC is the Population Decline Swarm Optimization ($P_DSO$). It is a modification of the Particle Swarm Optimization (PSO) technique that takes into account a decline demographic model to speed up the optimization procedure. Tuning and flight mechanics results are presented to show both the effectiveness of the proposed $P_DSO$ and the fault tolerant capability of the proposed scheme to control the aircraft pitch motion even in presence of elevator failures.